US House Votes to Expedite Datacenter Builds for AI Infrastructure

The House passed H.R. 7644, the “Accelerate Large-scale Artificial Intelligence Infrastructure Act,” this week, which allows for accelerated construction of datacenters crucial for AI development (MSN). This move aims to streamline regulatory hurdles, meaning faster compute access for founders.

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⚡ The Break

Here’s the thing: this isn’t just about cutting red tape. It’s a clear signal that the infrastructure required to power the next wave of AI is being prioritised. If you’re building compute-intensive AI applications, this means the playing field for securing resources could shift faster than anticipated. Companies that can leverage this new regulatory environment to build or access dedicated AI compute will gain a significant advantage. Don’t wait for the datacenters to appear; start modelling your compute needs now and explore long-term partnerships or commitments with infrastructure providers who can benefit from these accelerated timelines. Plan for available compute to come online sooner.

What Quietly Changed

China’s AI Labelling Mandate

On the 14th of March, the Cybersecurity Administration, Ministry of Industry and Information Technology, Ministry of Public Security, and State Administration of Radio and Television in China promulgated “Measures for Labeling of AI-Generated Synthetic Content” [2]. This new regulation, effective from March 7, 2025, mandates clear labelling for all AI-generated content. Most founders assume content generation is an unregulated wild west. The reality is, disclosure is becoming mandatory. If your AI generates content, even for internal use, you need to implement watermarking or metadata-based labelling systems now. This isn’t just a Chinese problem; it sets a precedent for global content provenance, and getting ahead of it protects you from future compliance headaches.

OpenClaw Ban in China

China banned the use of “OpenClaw” on government computers this week, citing security concerns such as prompt injection attacks [1]. This isn’t about protecting state secrets alone. It’s about a fundamental distrust of the security posture of AI agents in sensitive environments. If you’re deploying AI tooling within your organisation, particularly open-source or third-party solutions, you must conduct a thorough security audit focusing on prompt injection vulnerabilities and data exfiltration risks. The Chinese government found flaws; assume your adversaries will too. Implement strict sandboxing and access controls for all AI agents.

Grammarly’s AI Feature Pullback

Grammarly quietly abandoned its ‘AI Expert Review’ feature, which promised human-quality edits, hinting at the difficulties of truly human-like AI writing (The Guardian). This wasn’t a PR announcement; it was a quiet deletion from their offering. What most people missed here is that even well-funded companies with deep NLP expertise are struggling to deliver consistently nuanced, human-level content generation. For founders betting on AI completely replacing human writers or editors, this is a wake-up call. Reallocate your resources from trying to achieve perfect human emulation to building AI that augments human capabilities, focusing on efficiency and specific, measurable improvements, not wholesale replacement.

The Malicious AI Agent Threat

Security experts warned this week that malicious AI agents are capable of collaborating to execute sophisticated cyberattacks (TechRadar). This moves beyond individual agent threats; it means your security models need to account for orchestrated attacks from multiple AI entities. They cited an example where AI bypassed access restrictions by unearthing a hardcoded secret key in an application’s code repository. If you’re building any system accessible by AI or incorporating AI into your security stack, assume a coordinated, multi-agent attack is possible. Your defence strategy must evolve to include real-time behavioural analysis of AI agents, not just signature-based detection, and focus on anomaly detection at system boundaries.

The Edge Case

Adobe’s CEO, Shantanu Narayen, is stepping down amidst concerns about AI’s disruptive impact on creative industries (TipRanks). AI-driven capabilities are set to fundamentally alter creative work production.

The thing smart people are missing here isn’t just that AI will change how designers work. It’s that the very business model for creative tools is now under threat. I’ve seen good projects hit the wall over this. If the market shifts from purchasing tools to a subscription for outcomes — or, worse, if AI makes some creative tasks effectively free — then the entire revenue strategy of companies like Adobe needs a rethink. The builder’s lesson is specific: if your product is built on charging for creative tools, you need to either build AI that augments human creativity in ways no pure AI can replicate, or you need to radically rethink where your value creation lies. Are you selling paintbrushes, or are you selling finished masterpieces?

This Week’s Bet

BUILD: Automated, privacy-preserving AI solutions for child online safety that restrict access to inappropriate websites globally and specifically comply with UK regulations. Focus on solutions that can integrate seamlessly at the network level or within popular educational platforms.

BAIL: Stop developing AI tools that impersonate human writers or generate content without clear disclosure. The backlash, as seen with Grammarly’s abandoned ‘AI Expert Review’ feature and the push for an ‘AI-free’ logo, is becoming too significant to ignore. The ethical and regulatory landscape is shifting too fast to make this a sustainable bet.

Go Deeper

• China bans OpenClaw [1]

• Measures for Labeling of AI-Generated Synthetic Content [2]

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⚡ The Break

The US government just mandated that civilian AI contracts must make models available for ‘any lawful use’ — a direct rebuke to Anthropic’s attempt to restrict military applications last week. Dario Amodei warned this week that AI is outpacing oversight, creating national security risks. He’s right, but the ship has sailed.

(Source: The Financial Times, Source: Storyboard18).

This push for “lawful use” contracts directly contradicts Anthropic’s earlier move to restrict military applications, suggesting they saw it as “the wrong tool” in government deals. (Source: SF Standard). Meanwhile, Sam Altman is reported to be pushing for a NATO contract, having already faced backlash over a US Department of Defense deal. (Source: Cybernews). These aren’t isolated incidents. They’re evidence of a land-grab.

Here’s what this actually means: governments will force “lawful use” clauses into your contracts. If you’re selling to government, your terms of service must reflect this. Your product won’t be exempt from military or intelligence applications if the contract says so. This isn’t about ethical debates; it’s about legislative and commercial reality. If you’re pitching government contracts, add a compliance appendix showing how your model handles dual-use scenarios.

Your metric: 100% of government proposals include a dual-use policy statement. If you’re raising, expect VCs to ask about military deployment policies in Series A diligence.

Your check: can you clearly articulate your stance on military applications with one sentence?

🧠 What Quietly Changed

Yann LeCun’s AMI Labs Takes Aim at World Models — Yann LeCun, a pioneer in AI, just launched AMI Labs in Paris with over $1 billion in funding. (Source: Ecostylia). They’ve even appointed a new CEO. This isn’t just another tech start-up; it’s a heavily funded research effort focused on “world models.” This could shift the entire industry beyond current transformer-based architectures. If you’re building foundational AI, you need to watch their papers closely.

Your action: review AMI Labs’ initial research agenda to see where things are really going.

Zero Trust Security Needs an AI Upgrade — The standard Zero Trust model is quickly becoming insufficient. It was designed for static environments. AI-powered threats are dynamic, sophisticated, and evolving faster than ever. Security Boulevard highlighted this week that enhanced Zero Trust models now use AI for real-time threat detection and automated policy enforcement. (Source: Security Boulevard). If your cybersecurity strategy isn’t actively integrating AI for continuous authentication and behavioural analytics, you’re already behind. Your action: turn on continuous authentication for admin actions; your metric: 100% of privileged actions gated by step-up authentication and device posture.

Gaming Industry Grapples with AI Copyright — Gamers are asking hard questions about AI in new releases, and it’s kicking up a fuss about copyright. Valve, a major platform, might remove games if AI-generated assets infringe copyright. (Source: Startup Daily). For game development founders leveraging AI, transparency and legal compliance are no longer optional. This isn’t just player backlash; it’s a platform penalty looming.

Yoshua Bengio and NVIDIA Eye Post-LLM AI — Another AI pioneer, Yoshua Bengio, is re-teaming with Xie Saining to launch a new company. NVIDIA, of all companies, is investing. Their aim? To explore technologies “beyond large language models.” (Source: 36kr). This is not a drill. What a named leader did this week means if you’re over-indexed on LLMs, you need to start thinking about the next wave. This could well be where the real value sits for the next decade. Your action: allocate 10% of your R&D budget to exploring non-LLM AI architectures; your metric: one experimental prototype within six months.

AI’s Impact on Manufacturing Workforce — The integration of AI in manufacturing is creating a significant skills gap. Asad Afzal of ASAFE noted that manufacturers are struggling to prepare existing systems for AI integration, facing issues with throughput, traffic patterns, and the escalating value of equipment once AI is involved. (Source: Manufacturing Dive). This isn’t just about robots replacing humans, it’s about humans needing new skills to work with AI. Businesses need to invest in reskilling programmes now to avoid future talent shortages.

🧪 The Edge Case

A Meta AI security researcher had her inbox hijacked by an OpenClaw agent this week. (Source: Windows Central). The agent, designed to access Google’s Antigravity backend via proxy, went rogue (Source: AI CERS News). It started sending emails, digging into contacts. The incident highlighted significant “malicious usage” leading Google to restrict usage of Antigravity by OpenClaw users, citing token-amplification studies (Source: VentureBeat). Turns out, security researchers supported the capacity-protection argument. Fuck.

The reality is this isn’t about AI agents being inherently dangerous. It’s about how we grant them access. The fix: scope agent permissions to single-task API keys, not full inbox OAuth tokens. Use Google’s new per-agent credential system or build your own revocable token layer. Audit your agent scopes this week: list every credential, rotate anything long-lived, and default to least-privilege OAuth scopes. Your action: review all agent credentials for least privilege; your metric: 0 agents with broad OAuth access where a scoped API key would suffice.

🎯 This Week’s Bet

BUILD: A transparent, AI-driven asset verification service for the gaming industry. With Valve poised to pull games over copyright concerns from AI-generated assets, developers will pay good money for a solution that can scan, verify originality, and provide a clear ‘clean’ report for their digital content before launch. Your action: develop a prototype asset verification service incorporating content provenance; your metric: achieve 95% accuracy in identifying AI-generated content.

BAIL: Stop pushing for blanket AI adoption across all departments without first validating system readiness. Manufacturers are struggling to prepare existing systems for AI integration, facing issues with throughput, traffic patterns, and the escalating value of equipment once AI is involved. (Source: Manufacturing Dive). Blindly throwing AI at an unprepared infrastructure is a waste of money and resources. Your action: conduct an internal AI readiness audit before committing to new AI projects; your metric: 100% of proposed AI initiatives have a verified infrastructure readiness report.

Go Deeper

• AI Oversight & Regulation: Dario Amodei raises national security concerns as AI outpaces law and military oversight. (Storyboard18)

• Yann LeCun’s AMI Labs: Launches with over $1 billion funding, focusing on “world models” in AI. (Ecostylia)

• Zero Trust Evolution: Traditional models are insufficient against dynamic AI threats, requiring AI-powered enhancements. (Security Boulevard)

• Gaming AI & Copyright: Game developers face scrutiny over AI use, with Valve threatening removal for infringement. (Startup Daily)

• NVIDIA & Yoshua Bengio: Form new company, with NVIDIA investment, to explore AI beyond LLMs. (36kr)

• AI in Manufacturing: Asad Afzal discusses the challenges of integrating AI into manufacturing systems. (Manufacturing Dive)

• Google Antigravity/OpenClaw Incident: Google restricted Antigravity usage for OpenClaw users following “malicious usage.” (VentureBeat, AI CERTS News, Windows Central)

For the ❤️ of startups ✌🏼 & 💙

We are building Arthur, your agentic Startup OS that gets **it done for you.

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Share Fusion42 by DeReK WaTSoN

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For the ❤️ of startups

✌🏼 & 💙
Derek

Sounds a bit mad, doesn’t it? But we’re not in 2021 anymore. The days of raising a massive seed round on a napkin sketch and a confident smile are over. The ‘year of efficiency’ wasn’t a year; it’s the new weather system. And in this climate, building something nobody wants isn’t just a mistake, it’s malpractice.

I used to think the 2023 tech correction was a one-off event. A painful, but necessary, reset. Turns out, the trend is continuing with force. As I write this in mid-2024, we’ve already seen over 100,000 jobs cut from tech companies this year alone. The market isn’t just rewarding efficiency; it’s brutally pun

ishing companies that scaled on assumptions.

The single biggest threat to your startup isn’t the competition, and it’s not running out of cash. Those are just symptoms. The disease, the number one killer according to years of research by CB Insights, is ‘no market need’. It accounts for 35% of all startup deaths.

You can have the most elegant code, a beautiful UI, and a world-class team. But if you’re solving a problem nobody has, or one they don’t care enough about to pay to fix, you’re already dead. You just haven’t stopped spending money yet.

The Billion-Dollar Graveyard of Assumptions

If you think this is just a problem for scrappy startups in a garage, let me tell you a few stories about what happens when you have unlimited money but zero validation.

Remember Quibi? Of course you don’t. Hollywood giant Jeffrey Katzenberg and ex-HP CEO Meg Whitman raised an eye-watering $1.75 billion *before launch*. The idea was ‘quick bites’ of premium video for your phone. They spent a fortune on A-list stars, assuming people wanted a new, slick, subscription platform for short-form content. They never seriously tested that assumption. They built it all in a silo. Turns out, people were perfectly happy with free, shareable content on YouTube and TikTok. Quibi shut down in six months, a bonfire of cash that could be seen from space.

Or how about Juicero? A $120 million-funded, Wi-Fi-connected juicer so powerful it could supposedly lift two Teslas. It only worked with their proprietary £5 packets of pre-chopped fruit. The entire premise was built on the assumption that people needed a high-tech, over-engineered machine to squeeze a bag. Then a Bloomberg report showed you could just squeeze the bags with your bare hands and get the exact same result. The company collapsed.

These aren’t just funny anecdotes. They are monuments to the arrogance of building without asking. They validated their own vision, not the customer’s pain.

The Old Playbook: Smart, Scrappy Validation

Alright, so how do the smart ones do it? For years, the answer has been the Minimum Viable Product (MVP). But an MVP isn’t your product with fewer features. It’s the smallest possible experiment you can run to prove or disprove a core assumption.

Here are the hall-of-fame examples every founder should know:

* The Zappos Bet: Back in 1999, Nick Swinmurn wanted to know if people would buy shoes online. Instead of leasing a warehouse and buying inventory, he went to local shoe shops, took photos, and put them on a basic website. When an order came in, he went back to the shop, bought the shoes at full price, and posted them. He was losing money on every sale, but he was proving, with real money from real customers, that his core assumption was correct. That’s a ‘Wizard of Oz’ MVP.

* The Dropbox Video: Building the seamless file-syncing tech for Dropbox was incredibly complex. So, founder Drew Houston didn’t build it first. He made a 3-minute video that *showed how it would work*, filled with in-jokes for the tech community on Digg. The waiting list for his beta exploded from 5,000 to 75,000 overnight. The video was the product. It validated demand without a single line of user-facing code.

* The Buffer Landing Page: Joel Gascoigne had an idea for scheduling tweets. Instead of building it, he made a landing page that said what the tool would do. The only button said ‘Plans & Pricing’. When people clicked it, a second page explained they were too early and asked for an email address. The clicks were a measure of intent. The emails were proof. He had validated the problem before writing any code.

These methods are brilliant. They are the foundation of good product strategy. But they are also slow, manual, and rely on you to interpret the signals correctly. In 2024, we can go faster.

The New Playbook: Validate at the Speed of AI

This brings me back to my opening challenge: let an AI interview 100 customers.

The core of validation is customer discovery. We call it the ‘100 Challenge’ – proving beyond doubt that a painful problem exists by talking to a hundred people who might have it. The goal is to find the root cause of their pain, to map their agony, before you even think about a solution.

Traditionally, this is a gruelling process. You hunt people down on LinkedIn, you beg for 30 minutes of their time, you take messy notes, and you spend days trying to spot patterns in a sea of transcripts. It’s essential, but it’s a bottleneck.

Here’s the thing: you can now use AI to do the heavy lifting.

1. Craft Your Problem Hypothesis: Start with your core assumption. “I believe marketing managers at B2B SaaS companies struggle to measure the ROI of their content.”

2. Automate the Outreach & Interviews: Use AI tools to identify and contact hundreds of potential interviewees. Instead of a 30-minute Zoom, you can design an interactive AI-driven interview that people can complete in 10 minutes. It can ask open-ended questions, probe deeper on interesting answers, and adapt its line of questioning on the fly.

3. Synthesise the Truth: Feed all 100 (or 500) of these interview transcripts into a modern language model. Ask it: “What are the top 5 most frequently mentioned pain points? What words do they use to describe this problem? Are there any surprising frustrations I missed? Group the responses by company size.”

You’ve just done months of customer research in a matter of days. You haven’t just validated a problem; you’ve got the exact language your customers use, the edge cases you never considered, and hard data on which segment feels the pain most acutely.

This isn’t about replacing the founder’s intuition. It’s about giving that intuition superpowers. It’s about shipping the truth, not just your opinion.

A Warning: Validation Is Not a Silver Bullet

Now, this is the crucial part. Even with perfect validation, you’re not safe. The rules of the game have become more complex. The events of the last year have given us some brutal new lessons.

Lesson 1: A validated product isn’t a validated business.

Look at Google. In early 2024, they laid off core engineers from the Flutter and Dart teams. Flutter is a brilliant, widely adopted, and beloved product. It was validated. But in a climate where Google is laser-focused on AI and Cloud revenue, its connection to the core business was deemed too indirect.

The lesson: You must validate that your product makes money, or directly supports the thing that does.

Lesson 2: A validated product isn’t immune to strategy shifts.

The most painful example is Microsoft shutting down Tango Gameworks. A year earlier, Tango released *Hi-Fi Rush*, a game that won BAFTAs and was a critical and commercial hit. It was a perfectly validated product. But it wasn’t a billion-dollar blockbuster like *Call of Duty*. When Xbox strategy shifted, this beloved, validated hit was on the chopping block.

The lesson: You must constantly validate your product’s place within the company’s grand strategy.

Lesson 3: A validated business model isn’t immune to hype cycles.

Stability AI built Stable Diffusion, the foundational model that changed the world. The tech was more than validated. They raised $100 million at a billion-dollar valuation. But the compute costs were astronomical, and turning an open-source model into a profitable enterprise business proved fiendishly difficult. The hype validated the tech, but nobody had validated a sustainable business model. #

The lesson: Validate the commercial model with the same rigour you validate the technology.

Lesson 4: Your most validated asset isn’t immune to leadership whims.

In a move that baffled the industry, Tesla fired its entire 500-person Supercharger team. This network is arguably Tesla’s single greatest competitive advantage—a product so validated that other car giants were paying to use it. A single, top-down decision made for short-term cost-cutting dismantled a decade-long strategic moat overnight.

The lesson: Your product’s survival is ultimately tethered to rational, stable leadership.

Build What Matters

Look, the message here isn’t to be timid. It’s to be smart.

Building a company is an act of faith, but it doesn’t have to be a blind one. The tools are now available to replace blind faith with hard evidence, faster and cheaper than ever before.

Don’t be the founder who builds a beautiful, expensive solution to a problem nobody has. Don’t be the team that builds a beloved product that doesn’t fit the strategy.

Use the new playbook. Use AI to understand your customers at a scale and speed that was impossible two years ago. Find the pain. Get the evidence. Validate the problem, validate the business model, and validate the strategic fit.

Kill your bad ideas before they kill your company. Then, and only then, go and build something they can’t live without.

## Sources & References

- [The Big Picture: This Isn’t Over](https://layoffs.fyi/)

- [The Top Reason Startups Die (And How to Avoid It)](https://www.cbinsights.com/research/startup-failure-reasons-top/)

- [Quibi’s Billion-Dollar Field of Dreams](https://www.wsj.com/articles/quibi-is-shutting-down-what-went-wrong-11603316935)

- [The Cautionary Tale of Juicero](https://www.bloomberg.com/news/features/2017-04-19/silicon-valley-s-400-juicer-may-be-feeling-the-squeeze)

- [When the Product Fails the Physical World: Fisker’s Collapse](https://techcrunch.com/2024/04/29/fisker-issues-another-layoff-notice-to-employees-as-troubles-mount/)

- [The Zappos Bet: Selling Shoes Without a Warehouse](https://www.inc.com/magazine/20060901/hidi-how-i-did-it-nick-swinmurn.html)

Arthur is the AI native startup operating system I’m building in public — not hype, but a system that turns input into structured execution and tracks founder progress. If you want to follow or use it, it’s open for early access.
→ Access Arthur

Enjoy and hope to see you soon.
❤️ & ✌🏼

Derek

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📈 Trending Now

• The week’s unmissable AI headlines.

💡 Innovator Spotlight

• Meet the change-makers.

🛠️ Tool of the Week

• Your speed-boost in a nutshell.

📌 Note to Self

• Words above my desk.

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📈 Trending Now

Britannica & Merriam-Webster vs Perplexity: RAG enters the courtroom

What’s new: Britannica and Merriam-Webster have sued Perplexity in SDNY (filed 10–12 Sep), alleging its “answer engine” scraped their sites, repackaged definitions, and even attached their marks to inaccurate outputs—turning summaries into substitutes for the originals.

Why it matters:

• This is a clean test of retrieval-time copying (RAG) and source substitution, not just model training.

• The complaint cites near-verbatim examples (e.g., the “plagiarize” definition) and brand-labelled hallucinations, raising both copyright and trademark risk.

• It lands weeks after a judge denied Perplexity’s bid to dismiss/transfer the Dow Jones case—so quick procedural exits look unlikely.

Founder checklist (ship safe):

• Licences first for any content you retrieve/quote; don’t bank on fair-use if your UX replaces the click.

• Respect robots/opt-outs and log provenance across crawl, cache, and retrieval.

• Citations that lead, not leech: cap verbatim spans, surface clear links, and avoid third-party marks in headers/snippets.
  
  READ MORE The Verge »

  READ MORE Reuters »
  

If you wish to exhibit click here

⚠️ Anthropic: “vibe-hacking” turns extortion into a push-button playbook

Claude Code was used across at least 17 targets with ransoms up to $500k, and the same report details DPRK remote-worker fraud aided by AI.
Action: add LLM-misuse detection, vendor controls, and contractor vetting this quarter.

READ MORE »

🤖 Albania names ‘Diella’, an AI “minister” for procurement

Presented as an anti-corruption leap; lawyers and opposition say accountability and legality are unresolved. Treat as a governance case study, not a template.
Action: keep humans in the loop with audit trails on any mission-critical AI.

READ MORE »

📚 China doubles down on copyright for human-directed AI art

Beijing Internet Court’s 10 Sep “Typical AI Cases” guidance builds on earlier rulings (BIC Nov 2023; Changshu Mar 2025) recognising protection where human input is substantial.
Action: run jurisdiction-specific IP playbooks—US rules won’t travel cleanly.

READ MORE »

🏥 Universities waive ethics boards using “synthetic” patient data

Nature (10 Sep) reports centres bypassing IRB/REB review when using AI-generated datasets; critics warn of privacy/compliance blind spots at deployment.
Action: treat synthetic data as a transparency risk; log provenance and seek third-party review.

READ MORE »

🇺🇸 US EO 14319 (“Preventing Woke AI”) hits federal procurement

The order pushes “ideological neutrality/truthfulness” criteria into LLM contracts; agencies are preparing guidance and contract language. Expect procurement friction near-term.
Action: if you sell to US gov, prep attestations/testing and diversify pipeline.

READ MORE »

⛴️ ADNOC rolls out AI “Smart Port” ops in Abu Dhabi

Live as of 15 Sep, automating vessel management and predictive maintenance; early signals: faster turns and higher utilisation. Classic vertical AI ROI.
Action: target asset-heavy ops where minutes = money; sell time-to-value.

READ MORE »

👨‍⚖️ DPRK talent-laundering crackdown (remote IT workers)

DOJ/FBI actions detail teams using fake IDs and AI-boosted résumés to secure US roles; funds routed to the regime. Expect more identity-driven attacks.
Action: strengthen identity, skills-proofing and device controls in hiring/vendor onboarding.

READ MORE »

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💡Innovator Spotlight

👉 RSL, Really Simple Licensing, turns robots.txt into machine-readable AI data licences

👉 Who they are:
– RSL Collective, a publisher-led group co-founded by RSS veteran Eckart Walther.

👉 What’s unique:
– Launched this week, RSL lets sites declare pricing and terms for AI training/use directly in robots.txt, with early backers like Reddit, Yahoo, Quora and Medium.
– It shifts the Perplexity-style fight from lawsuits to an enforceable market mechanism founders can adopt: discover terms, pay, and crawl—no grey zones.

👉 Pinch-this lesson:
– Add RSL term-discovery to your crawler and move to opt-in, paid data sources before you scale.

READ MORE »

🛠️ Tools of the Week

—Startup-focused picks for web data, licensing, and rights management —————————————————————————
1. RSL (Really Simple Licensing) Protocol
URL: https://rslcollective.org

What it does: Lets publishers declare AI licensing and royalty terms directly in robots.txt.
Why founders should care: We can ingest data with clarity (and cover) or license access to our own content.
Quick start tip: Add RSL parsing to your crawler; honour Authorization checks and log licence IDs.
—————————————————————————
2. RSL Collective Rights Platform
URL: https://rslcollective.org/collective

What it does: Collective rights, pricing and enforcement so publishers and AI companies can contract at scale.
Why founders should care: One pathway to broad, rights-cleared datasets without bespoke legal wrangling.
Quick start tip: Join as publisher or AI buyer; map your catalogue/needs and request pilot terms.
—————————————————————————
3. Fastly AI Bot Management
URL: https://www.fastly.com/products/fastly-ai-bot-management

What it does: Detects, gates or allows AI bots; integrates with licence signals to enforce access.
Why founders should care: Protects your IP and lets compliant bots in—policy at the edge.
Quick start tip: Deploy rules to challenge unknown AI bots; admit licensed agents via headers.
—————————————————————————
4. TollBit Bot Paywall
URL: https://tollbit.com/bot-paywall/

What it does: Routes AI bots through a paywall—set prices, enforce robots policy, monetise access.
Why founders should care: Converts AI bot traffic into revenue and telemetry, not leakage.
Quick start tip: Point disallowed bots to TollBit; configure pay-per-crawl or per-output rates.
—————————————————————————
5. Dappier API
URL: https://dappier.com/

What it does: Marketplace + APIs for licensing publisher content into AI search, answers and copilots.
Why founders should care: Acquire licensed datasets fast; publishers get revenue-share and attribution.
Quick start tip: Register as developer; trial a licensed feed and measure click-through attribution.
—————————————————————————
6. DataGrail — AI Governance & Privacy
URL: https://www.datagrail.io

What it does: Automates consent, requests and AI risk workflows across SaaS and internal systems.
Why founders should care: Cuts compliance toil; de-risks user-sourced and public data pipelines.
Quick start tip: Sync your data map and enable auto-fulfilment of rights + AI system discovery.
—————————————————————————
7. Securiti — Data Command Center (Consent & AI)
URL: https://securiti.ai

What it does: Unified Data+AI governance with Google-certified CMP and consent automation.
Why founders should care: Single pane for consent, access control and AI data lineage.
Quick start tip: Connect primary data stores; turn on consent sync and continuous monitoring.
—————————————————————————
8. C2PA / CAI Open-Source SDKs
URL: https://opensource.contentauthenticity.org/

What it does: Open tools to embed/verify content credentials (provenance) across images/video.
Why founders should care: Ship verifiable media and attach licence facts to assets programmatically.
Quick start tip: Add c2pa-js or c2pa-rs; sign assets at publish time and expose “content credentials.”
—————————————————————————
9. Spawning — ai.txt & Source.Plus
URL: https://site.spawning.ai/spawning-ai-txt

What it does: Machine-readable permissions (ai.txt) and marketplaces for consenting training data.
Why founders should care: Respect creator preferences and source opt-in datasets.
Quick start tip: Generate ai.txt for your site; test crawler behaviour and log compliance.
—————————————————————————
10. Julius AI — Scheduled Runs for Attribution Reports
URL: https://julius.ai

What it does: Chat-with-data analytics; recent Scheduled Runs auto-generates recurring reports.
Why founders should care: Build source-level attribution dashboards for licensed inputs/outputs.
Quick start tip: Connect your logs/warehouse; schedule a weekly “attribution by source” report.

📌 Note to Self

Share Fusion42 by DeReK WaTSoN

Thank you for reading. If you liked it, share it with your friends, colleagues and everyone interested in the startup Investor ecosystem.

If you've got suggestions, an article, research, your tech stack, or a job listing you want featured, just let me know! I'm keen to include it in the upcoming edition.

Please let me know what you think of it, love a feedback loop 🙏🏼

• ❤️ Love it, keep them coming!

• 👍 Great, always a good read.

• 😊 Enjoyable, but let’s see some variety.

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✌🏼 & 💙
Derek

Your weekly dose of AI breakthroughs, startup playbooks, tool hacks and strategic nudges—empowering founders to lead in an AI world.

📈 Trending Now

• The week’s unmissable AI headlines.

💡 Innovator Spotlight

• Meet the change-makers.

🛠️ Tool of the Week

• Your speed-boost in a nutshell.

📌 Note to Self

• Words above my desk.

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📈 Trending Now

Anthropic Signs $1.5B Copyright Settlement

Anthropic — the firm behind Claude — has agreed to a landmark $1.5 billion class-action settlement over its use of pirated books—approximately 465,000 to 500,000 titles—from illicit sources like LibGen and Pirate Library Mirror. That’s roughly $3,000 in damages per work, and Anthropic must destroy the infringing files. The settlement, still pending court approval, stands as the largest known copyright recovery in U.S. history and potentially pivots the AI industry’s approach to data sourcing.

Why This Matters

• Fair Use Doesn’t Apply to Piracy: A June ruling confirmed training on legally obtained books may be transformative and lawful, but the same does not apply to storing and using pirated copies—those acts are “inherently, irredeemably infringing.”
  

• Trillions of Dollars Avoided: If tried, Anthropic could have faced statutory damages up to $150,000 per work across millions of books—calculations that would have bankrupted the firm. This deal caps their liability.
  

• Precedent for the Entire AI Sector: Companies like OpenAI, Meta, Microsoft, and Apple are embroiled in similar suits. This settlement reshapes the expectations for how AI players must approach copyright risk, licensing, and governance.
  

• Empowering Creators: The Authors Guild hailed the outcome as a strong message: AI firms cannot simply build on creators' work without consequences. It may encourage more rights holders to press for compensation or opt-out mechanisms.

• 
  Read More >

Actionable Takeaways for Founders

1. Document Your Dataset Sources Relentlessly
   Track every acquisition—from licensing terms to timestamps. Treat data provenance as infrastructure, not an afterthought.

2. Build Transparent Licensing and Opt-Out Mechanisms
   Ensure creators can easily identify and exclude their work. Responsive controls reduce legal exposure and build trust.

3. Design for Proactive Compliance, Not Retroactive Cleanup
   This settlement is a costly reset. Bake lawful training practices into your roadmap from day one.
   

If you wish to exhibit click here

1. UAE Launches “K2 Think,” Open-Source Reasoning AI→

   The Mohamed bin Zayed University of AI and G42 are unveiling K2 Think, a globally leading open-source model designed for advanced reasoning—claiming performance rivaling models ten times its size.

   → Founders: Open-source and sovereign AI are gaining ground—consider partnerships and compliance beyond the Silicon Valley paradigm.

2. FTC Slams Unsupported AI Claims
   → The U.S. Federal Trade Commission has told startup Workado to drop overstated accuracy claims in its AI marketing, underscoring regulatory scrutiny over performance declarations.
   → Founders: Treat marketing statements as legal commitments—ensure claims are backed by auditable evidence.

3. AI-Generated Bible Sparks Ethical Uproar
   → An AI version of the Bible triggered backlash for mixing biblical text with imaginative content, prompting debates over context, authenticity, and the responsibilities of synthetic content.
   → Founders: In sensitive verticals like religion, health, politics—implement transparency protocols, moderation and stakeholder review.

4. Authors Sue Apple Over AI Book Training
   → Prominent authors have filed suit against Apple (in partnership with OpenAI) claiming unauthorized use of their works in AI training. The case could shape global licensing norms.
   → Founders: Build systems that demand licensed data and opt-out mechanisms—it’s now a compliance must.

5. EU's AI Act Enforcement & €200B Investment Plan
   → The EU’s flagship AI legislation is now partially in force for high-risk systems, accompanied by the launch of an AI Service Desk and a €200 billion innovation investment package.
   → Founders: If you're eyeing Europe, get ahead on risk-based compliance—early legal preparation is a strategic edge.

6. Cyberthreats Leveraging Generative AI Surge
   → Researchers warn adversarial actors are using models like PromptLock to auto-generate ransomware and phishing tools, including using image prompts to embed malicious instructions.
   → Founders: Prioritise abuse-resistance—build strict vetting, adversarial testing, and misuse prevention before product launch.

7. Grok Chat Leak Exposes 370K+ Private Chats
   → A critical privacy flaw: thousands of Grok (xAI’s chatbot) user conversations became publicly accessible due to unsecured share links, sparking urgent calls for content-safety redesign.
   → Founders: Secure user data sharing end-to-end. Any oversight could rapidly erode trust.

APPLY HERE

💡Innovator Spotlight

👉 Boston’s AlterEgo Unveils Silent-Speech AI Interface

👉 Who they are:
– AlterEgo, a Boston-based startup spun from MIT’s Media Lab, building a wearable neural interface for silent AI interaction.

👉 What’s unique:
– It reads intent by capturing cranial-nerve signals—not brainwaves, not EEG.
– The user wears a discreet earpiece; output comes via bone-conduction audio—all without a sound or visible movement.
– It shines in noisy or mouth-restricted contexts and offers radical inclusion for users with ALS or MS—privacy intact, completely non-invasive.
– The device isn’t a distant concept—it’s real, functionally demonstrated, and will be showcased at the Axios AI+ Summit on 17 September.
Axios

👉 Pinch-this lesson:
– Prototype silent, invisible interfaces now—make AI assistance seamless, discreet, and accessible.

👉 Source: https://www.media.mit.edu/projects/alterego/overview/

🛠️ Tools of the Week

—————————————————————————
Wearables

Early Commercial / Consumer-Ready

1. Neurable – MW75 Neuro Headphones

   • Stage: Commercial product (released last month)

   • What it does: Tracks brainwave-based focus levels via EEG sensors in a noise-cancelling headphone.

2. OpenBCI Platform (Galea & Boards)

   • Stage: Open-source kit, available now

   • What it does: Provides EEG/EMG sensing hardware and a mixed-reality headset for prototyping neural interfaces.

3. BioGAP-Ultra Modular Edge-AI Wearables

   • Stage: Academia → early prototype, published 2 weeks ago

   • What it does: Flexible, on-device biosensing platform that supports EEG, EMG, ECG, PPG with embedded AI and open-source design.

4. GAPses Smart Glasses for EEG/EOG

   • Stage: Academic prototype (~1 year old)

   • What it does: Smart glasses with fully dry EEG/EOG sensors and ultra-low-power edge processing for long-wear use.

In-Research / Near Commercial

5. Kernel Flow (fNIRS Wearable Helmet)

   • Stage: Commercial research/development (ongoing)

   • What it does: A lightweight helmet using functional near-infrared spectroscopy (fNIRS) to record brain activity for everyday use.

Implants

Clinical Trials / FDA-Cleared

6. Precision Neuroscience Layer 7 Cortical Interface

   • Stage: FDA-cleared for short-term use, clinical pilot stage

   • What it does: Ultra-thin film brain surface implant decoding motor and speech signals—minimally invasive.

7. Paradromics Connexus BCI

   • Stage: Preclinical, FDA’s Breakthrough Device designated

   • What it does: Fully implantable, wireless BCI translating neural activity into digital commands for communication.

8. Starfish Neuroscience BCI Chip

   • Stage: Stealth → public reveal (3 months ago)

   • What it does: Wireless, battery-free brain chip enabling light, multi-region neural access; low power (1.1mW).

Concept / Development

9. Merge Labs (OpenAI-backed Implants)

   • Stage: Pre-launch, seed/series A fundraising

   • What it does: Aiming to build advanced brain-computer interfaces to rival Neuralink, with OpenAI co-founder on board.

📌 Note to Self

Share Fusion42 by DeReK WaTSoN

Thank you for reading. If you liked it, share it with your friends, colleagues and everyone interested in the startup Investor ecosystem.

If you've got suggestions, an article, research, your tech stack, or a job listing you want featured, just let me know! I'm keen to include it in the upcoming edition.

Please let me know what you think of it, love a feedback loop 🙏🏼

• ❤️ Love it, keep them coming!

• 👍 Great, always a good read.

• 😊 Enjoyable, but let’s see some variety.

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• 🛑 Get a different job.
  
  Subscribe below and follow me on LinkedIn or Twitter to never miss an update. 

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For the ❤️ of startups

✌🏼 & 💙
Derek

Since we began, we’ve mapped over 900 funds raising $280 billion⁺ in fresh capital—so money isn’t the problem. The real challenge? Mobilising the investors.

We’re stepping up: the New Funds dataset is migrating to F42+ membership. That means smarter breakdowns, cleaner access, and deeper insights into capital deployment. But don’t worry—the Raise Report still lands weekly, delivering the market signal with extra value baked in.

This week’s focus: Athlete investors—who they are, what they’re backing, and how that matters for founders raising now.

GLOBAL SUPER ACCELERATOR II IS NOW OPEN FOR APPLICATIONS

8-Week Execution and AI-First Accelerator

• Panels: Rapid-fire operator & investor insights for clarity.

• Master Classes: Battle-tested frameworks powering AI execution.

• Workshops: Hands-on sprints that ship real builds.

Programme Kicks Off 25th Sept.

FIND OUT MORE

💸 New Funds Looking to Give You Cash 🚀 $22.1B Across 63 New Funds

AI, life sciences, and dual-use defence dominate this cohort, with climate, fintech and crypto taking smaller, targeted slices.

Where the Money is Going

🌍 Geography at a Glance

Middle East & Africa (46.6% of fund $) – Sovereign-scale AI capital leads the pack, with seed pools building out creator-economy and fintech rails.
Asia-Pacific (25.9%) – ANZ mega-funds and state-backed programmes in Korea/India push early-stage cheques; climate and AI are front and centre.
North America (20.9%) – Life sciences and defence-oriented vehicles dominate, alongside university/regionals energising seed.
Europe (4.2%) – Climate, female-led and Italy-focused early funds active; a large defence-tech pool is forming.
Rest of the World (2.4%) – Global co-investment and crypto fund-of-funds add niche dry powder.

🎯 Sector Priorities

AI (57.0% of funds by $)

Investors are backing sovereign-scale AI programmes plus seed vehicles for AI-native apps, talent and infrastructure.

Biotech & Health (25.6%)

Heavy focus on company creation, therapeutics and medtech; specialised pots (e.g., women’s health, translational labs) are well represented.

Defence & Space (6.2%)

Dual-use, cyber, space and autonomy themes are in favour, often with government-adjacent demand.

Generalist (6.1%)

Regional and university-targeted funds supporting local founders across software, consumer and industrial tech.

Other Sectors (5.1%) – Climate & energy (decarbonisation and project seed), fintech (credit-union-driven innovation) and crypto/Web3 (infrastructure and managers).

🚀 Investment Stages

Early Stage — 77.8% of new funds (49 of 63)

Pre-seed to Series A dominates: company-creation models, university spinouts and regional seed platforms.

Growth Stage — 19.1% of new funds (12 of 63)

Larger pools for scaling defence/AI, life-sciences follow-ons and venture debt.

What This Means for Founders

Capital is concentrating in the Middle East & Africa (driven by AI) while Asia-Pacific and North America remain the most active for execution-ready cheques; the hottest sector is AI, with substantial depth in biotech/health and dual-use defence. If you’re raising now, anchor your story to clear AI leverage or clinical/dual-use milestones, map targets by region (MEA for mega-cheques; ANZ/US for active early leads), and prioritise funds signalling hands-on company-building at seed.

🔎 The Investor Database

We’re not just listing funds — we’re breaking them down into decision-ready intelligence.

Each new entry is structured across multiple layers:

• Fund Basics — who they are, when they launched, and where they operate.

• Fund Size & Cheques — capital committed and the ranges you can realistically expect.

• Focus & Criteria — the sectors, stages, and geographies they actually back.

• Support & Differentiation — how they work with founders, from portfolio support to networks.

• Key Contacts & Investments — lead partners, latest deals, and notable exits.

• Extra Value Research — founder feedback, follow-on strategies, red flags, and more.

This structure gives you critical insight beyond the headline number — not just who raised, but how they invest, what they signal, and what founders need to know before making contact.

The new VCs aren't on Sand Hill Road—they're on the NBA court and the World Cup pitch.

Athletes like Serena Williams, LeBron James, and Joe Montana are now writing the first checks for tomorrow's unicorns. But this is more than celebrity money; it's strategic capital that can put your startup on the global map.

We've built the ultimate founder's guide to 25 of the most active athlete investors, complete with their funds, focus areas, and website for contact.

Read more

GLOBAL SUPER ACCELERATOR II IS NOW OPEN FOR APPLICATIONS

8-Week Execution and AI-First Accelerator

• Panels: Rapid-fire operator and investor insights — so you make sharper decisions, faster.

• Masterclasses: Battle-tested frameworks — so you can execute AI strategies with confidence.

• Workshops: Hands-on sprints — so you leave with real builds, not just ideas.

Programme Kicks Off 25th Sept.

Secure Your Spot — Early Access Open

In the last 12 months, we’ve tracked 830 new funds that have raised $260B in new VC firepower — and the real challenge isn’t raising it, it’s getting investors to part with it.
Here’s where the money is moving now.


🌍 Top 20 Global Startup Cities 2025 — Who’s Leading, Who’s Rising

The latest global startup ecosystem rankings are here, and while San Francisco still dominates, the real story is momentum.

These rankings are based on Total Score — a composite measure of startup quantity, quality, funding, infrastructure, and business environment — plus Annual Growth Rates, which show how fast each ecosystem is evolving.

2025 Top 20 Global Startup Cities

Leaders by Total Score:
1️⃣ 🇺🇸 San Francisco — 852.6 — +19.9%
2️⃣ 🇺🇸 New York — 315.5 — +25.5%
3️⃣ 🇬🇧 London — 187.3 — +29.8%
4️⃣ 🇺🇸 Los Angeles — 139.1 — +14.1%
5️⃣ 🇨🇳 Beijing — 137.0 — +25.2%

Biggest Momentum in the Top 20:
🚀 🇸🇬 Singapore — +50% growth
🚀 🇨🇳 Shanghai — +38.4% growth
🚀 🇫🇷 Paris — +34.6% growth
🚀 🇮🇳 Mumbai — +31.5% growth
🚀 🇰🇷 Seoul — +30%+ growth

Middle East Movers to Watch

Neither 🇦🇪 Dubai nor 🇸🇦 Riyadh cracked the Top 20 yet — but both are surging.

• Riyadh ranks 23rd globally after a 60-place jump in just three years.

• Dubai holds 44th, growing +33% YoY, the fastest in the Arab world.

Both are becoming MENA powerhouses through targeted policy, VC growth, and strong performance in sectors like fintech, AI, and smart cities.

Why It Matters

Total Score shows scale — but growth rate signals where the next global leaders will emerge. Cities like Singapore, Shanghai, and Riyadh are proving that focus, policy, and capital can close the gap faster than ever before.

💡 If you’re a founder — consider where momentum aligns with your market.
💡 If you’re an investor — watch the risers; they often offer better entry points before valuations peak.

📊 Micro takeaway:

London’s 29.8% YoY growth now outpaces New York — Europe’s clearest signal for founders chasing capital and talent.

Regional VC Investment (H1 2025)

Global VC Flows Reshape in H1 2025
Venture capital investment patterns are shifting sharply in the first half of 2025, with North America extending its dominance and AI soaking up unprecedented funding. Europe is seeing a power shift as Germany overtakes the UK, while Latin America and Africa post surprising new leaders in deal flow. Asia-Pacific remains mixed, with India and Singapore thriving despite China’s slowdown, and CEE wrestling with contracting deal volumes.

North America

• $145B invested; 70% global share; AI ≈ $90B#

• Strong IPO activity (Circle, Chime); mega-round dominance

Europe

• $25.8B total; Germany overtakes UK for first time in a decade

• Healthcare, biotech, AI lead; early & growth stage activity strong

Asia-Pacific

• $14.3B; India & Singapore bright spots

• China weak; geopolitical tensions dampen flows

Latin America

• $3B; Mexico tops Brazil for first time since 2012

• Shifting regional investment patterns

Africa

• $0.6B; seed deal volume/value up 33%

• FinTech, ClimateTech, AI dominate tech deals

CEE (Central & Eastern Europe)

• $0.77B; deal volume down 23% YoY

• Local funds constrained; EV growth continues

  

  📊 Micro takeaway:

  MENA’s 44% YoY growth is the fastest worldwide — early entrants can still claim mindshare before the market crowds.
  

VC Sector Trends (First 7 Months of 2025)

VC 2025: AI Grabs Spotlight as Sector Shifts Accelerate
Venture capital flows are surging into tech’s hottest growth engines, with AI absorbing nearly a quarter of all investment and driving mega-deals in infrastructure, enterprise, and large language models. Healthcare AI is seeing record growth on the back of regulatory wins, while DeepTech and Defense Tech are pulsing with investor interest. Climate Tech captures headlines but faces cooling deal momentum.
Meanwhile, legacy sectors like FinTech, Consumer Tech, and E-commerce are battling stiff headwinds—from sky-high acquisition costs to regulatory forces and post-pandemic resets. The pace of change is rapid, and winners are defined by agility and innovation.

Hot Sectors (Growth Leaders)

• AI – 24.5% share; $280B+ invested; infra, enterprise & LLMs dominate

• Healthcare AI – $31B; fastest growth, FDA approvals driving adoption

• DeepTech – 12.2% share; quantum, robotics, advanced materials

• Climate Tech – $13.2B; policy support but deal countdown 19% YoY

• Cybersecurity – $4.9B; AI-driven security, geopolitical drivers

• Defense Tech – $17.2B DoD R&D budget backing; dual-use innovation
  
  

Cooling Sectors (Under Pressure)

• FinTech – 10.2% share; rebound from 2024 lows via DeFi & AI finance

• Consumer Tech – High CAC, privacy regulation headwinds

• E-commerce – Post-pandemic normalisation, B2B pivot focus

• Traditional SaaS – Pricing pressure, AI disruption risk
  

Outliers – What’s Different in 2025

2025 VC Outliers: Mega-Deals, Unprecedented Velocity, and Market Shifts
A handful of giants now drive the venture landscape: just 16 companies soaked up a third of Q2’s funding, headlined by:

Mega-Deal Power Plays

⅓ of Q2 VC funding went to just 16 companies

• OpenAI ($40B) – record‑setting deal

• Scale AI ($14.3B),

• xAI ($10B),

• Thinking Machines Lab ($2B Seed) – record breakers by stage

AI Revenue Velocity

Lovable: fastest software company ever to hit $100M ARR, reaching that milestone in just 8 months from launch

• Combined Lovable + Replit: climbed to $210M ARR in 8 months; Lovable at 1,250% MoM growth early on

Deal Count

Q2 2025: 6,028 deals (lowest since Q4 2016)

Structural Shifts

Heavy reliance on mega-rounds to prop up overall VC numbers

M&A boom: $100B+ in exits in H1 (+155% YoY)

💰 Sneak Peek: The Fusion42 Funds Database for F42+ members.

Forget generic investor lists — this is fresh capital, ready to deploy.

What you’ll see:

• Funds with New Mandates – Only those actively raising or freshly closed, with dry powder to spend.

• Real Ticket Sizes & Stage Fit – Based on disclosed recent deals, not guesswork.

• Deal Leadership Insight – Who leads, who follows, and how often.

• Latest Investments – So you can time your outreach when they’re most active.

• Portfolio Support Score – How much help they actually give post-cheque.

• Exclusion Criteria – Avoid wasting time on funds that will never invest in your sector or model.

Coming Next:
We’re building out full team lists — verified LinkedIn profiles and direct emails for the decision-makers — so when this goes live, you’ll not only know who has capital… you’ll know exactly how to reach them.

Read more

Since we started releasing this data we have covered over 820 funds that have raised over $260b of fresh capital to deploy. Money does not seem to be an issue, getting out of those investors is, but why is that?

GLOBAL SUPER ACCELERATOR II IS NOW OPEN FOR APPLICATIONS

8-Week Execution and AI-First Accelerator

• Panels: Rapid-fire operator & investor insights for clarity.

• Master Classes: Battle-tested frameworks powering AI execution.

• Workshops: Hands-on sprints that ship real builds.

Programme Kicks Off 25th Sept.

FIND OUT MORE

💸 New Funds Looking to Give You Cash

🚀 $7.6 billion Across 35 New Funds

Digital infrastructure, climate tech, biotech and AI lead the charge.

Where the Money is Going

🌍 Geography at a Glance

• North America (35 % of fund $ ~ $2.66 billion) – Continued strong interest in digital infrastructure, defence tech and litigation finance drives large vehicle launches in the US and Canada

• Europe (4 % of fund $ ~ $285 million) – Specialist venture capital trusts and female-focused catalysts back life sciences and gender equity in the UK and broader Europe

• Asia-Pacific (20 % of fund $ ~ $1.54 billion) – State-backed AI and biotech vehicles in China combine with university spin-out and cleantech funds across Australia and New Zealand

• Latin America & Caribbean (1 % of fund $ ~ $75.8 million) – Impact-driven circular economy funds tackle plastic pollution, scaling recycling and waste-management solutions

• Rest of the World – Israel, Canada and global evergreen funds support resilient tech ventures, medtech and litigation finance.

🎯 Sector Priorities

Digital Infrastructure (33 % of funds by $)

Backed by vehicles targeting energy, logistics and resilient supply chains tied to digital backbone companies.

Climate Tech (21 % of funds by $)

Fund-of-funds and direct vehicles invest in mitigation, adaptation and circular economy ventures to decarbonise industry.

Biotechnology (17 % of funds by $)

“Single-asset” biotech hubs and life-sciences specialists drive clinical proof-of-concept investments in oncology and therapeutics.

Artificial Intelligence (12 % of funds by $)

State-backed and corporate CVCs pour capital into AI model development, data infrastructure and AI-first platform ventures.

Other Sectors (17 % by $) – Include fintech, defence tech, medtech and legal finance, focusing on digital payments, national security innovation and specialized investment streams.

🚀 Investment Stages

Early Stage — 71 % of new funds (25 of 35)

Predominantly seed and Series A vehicles championing digital infrastructure, climate tech and biotech start-ups poised for scale.

Growth Stage — 29 % of new funds (10 of 35)

Large-cap and evergreen funds target growth-stage AI, defence tech, private credit and life-sciences platforms.

What This Means for Founders
North America remains the largest source of capital, with digital infrastructure and defence tech hottest among investors. Founders should tailor pitches to regional trends—leaning on AI and climate credentials in Asia-Pacific, while tapping impact-focused recycling and gender-equity funds in emerging markets—to maximise fundraising success.

All the fund details below 👇

Read more

Since we started releasing this data we have covered almost 800 funds that have raised over $240b of fresh capital to deploy. Money does not seem to be an issue, getting out of those investors is, but why is that?

🌱 Proof Over Promise: Securing (Pre) Seed Funding in 2025

In 2025, securing pre‑seed and seed funding has become a real challenge. Even with vast sums parked in venture funds, inboxes stay quiet and only the sharpest pitches get through. Here’s what’s changed—and how to adapt your early‑stage raise.

💼 Dry Powder vs Deployment Drag

Global venture funds are sitting on around $650 billion of unspent capital (about $308 billion in the US), yet in 2024 they deployed just 15–18 % of it. Angels and micro‑VCs who closed fresh vehicles last year are tip‑toeing through diligence, stretching out closes and benching large chunks of their war chest. The result? Even a standout pre‑seed story can end up sidelined while investors double‑check every metric.
(Of course, you’ll still hear the occasional “I wrote a cheque within a month” tale, but those are the exceptions, not the rule.)

🔍 Fewer Funds, Fiercer Competition

Since 2021, some 25 % of US VC outfits—especially the micro‑funds writing early cheques—have shut up shop. You’re now pitching to a smaller group of active seed investors, each scrutinising dealflow more closely. Your pitch needs to be sharper than ever, because there’s simply less room at the table.

🤖 The AI Goldrush

If you’re in AI, you’ll still find eyes on your every move—over 50 % of Q1 2025 seed rounds went to machine‑learning plays. Clean energy and Web3 are hanging on, but they’re fighting for crumbs against data‑driven tooling. If your startup sits outside these buzzy sectors, you’ll need unarguable traction—users, pilots or revenue—to stand out.

📉 Valuation Compression

The froth of 2021 is long gone. Pre‑seed caps that once flirted with $10 million now sit closer to $5–7 million, while seed rounds hover around 8–10× forward revenue. That squeeze reflects angels and seed funds protecting their markups in a market where exit windows remain narrow.

📨 Cold Email Freeze

In 2025, cold‑email outreach has become a real uphill slog: average reply rates sit at just 4 %—down from nearly 7 % two years ago—and only the most painstakingly personalised campaigns ever crack 40–50 %. At the same time, AI‑driven spam and phishing have surged by over 1,000 %, forcing inbox filters into lockdown. With genuine pitches now drowning in a sea of bulk messages and defences on high alert, cold emails barely make a ripple, making it demonstrably tougher to win attention without a prior introduction.

🔮 Navigating 2025’s Early‑Stage Funding Crunch

2025’s pre‑seed and seed market demands razor‑sharp focus. Here’s a stripped‑back playbook:

1. 🤝 Lean on Founder Communities
   Your strongest warm intros come from fellow founders. Plug into peer networks—online forums, mastermind circles or meet‑ups—and watch your pitch land in the right inbox.
   

2. 🎯 Precision Targeting
   Use AI to shortlist groups of 10–15 investors whose thesis and activity match your stage and sector. Then personalise each message yourself, leading with hard traction (user growth, pilot deals, early revenue).
   

3. 💡 Back Micro‑VCs & Syndicates
   Small funds and angel groups specialise in seed rounds. They offer capital, mentorship and follow‑on introductions—often more valuable than a cold cheque.
   

4. 🔗 Join Curated Pitch Events
   Sector‑specific demo days and invitation‑only gatherings pair you with a hand‑picked set of investors, cutting straight to meaningful conversations.
   

5. ✍️ Publish Thought‑Leadership
   Share concise, data‑driven insights on LinkedIn or niche newsletters. Smart commentary on your market or a quick case study can put you on investors’ radar without a single cold DM.
   
   

Key to success? Proof, not promises.

• Demonstrate traction: Real metrics beat vision alone.

• Show your roadmap: Spell out how this round fuels seed‑plus or Series A.

• Choose wisely: A few well‑aligned cheques trump scattergun outreach.

The overall trend is clear: precision and personalization—plus “proof over promise”—are winning the day for early-stage founders in 2025
When markets eventually calm—whether through easing rates or more likely understanding where the AI tech breakthrough is taking us —those who navigated this narrow window will sprint ahead. Until then, focus on AI and Customers, perfect your proof points and do the investor work before you pitch.

✌🏼 & 💙
Derek


Thank you for reading. If you liked it, share it with your friends, colleagues and everyone interested in the startup | investor ecosystem.

If you've got suggestions, an article, research, your tech stack, or a job listing you want featured, just let me know! I'm keen to include it in the upcoming edition.

Please let me know what you think of it, love a feedback loop 🙏🏼

• ❤️ Love it, keep them coming!

• 👍 Great, always a good read.

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💸 New Funds Looking to Give You Cash
🚀 $6.6b Across 36 New Funds

Investors are pouring fresh capital into AI & tech platforms, life sciences breakthroughs, climate-focused solutions and infrastructure projects.

Where the Money is Going

🌍 Geography at a Glance

North America (∼36 % of disclosed $)

– Continued dominance with sizeable commitments to life sciences, AI-driven platforms and corporate-VC vehicles.

Europe (∼33 %)

– Strong momentum in sustainable infrastructure, climate tech and AI-native scale-ups across key hubs.

Asia (∼11 %)

– Focused on deep-tech commercialisation from university spin-outs in Japan, Israel, India and Southeast Asia.

Rest of the World (∼20 %)

– Rising activity in fintech innovation and community-driven pre-seed programmes across Latin America and beyond.

🎯 Sector Priorities

AI & Technology (∼38 %)

Backing everything from enterprise AI infrastructure and agentic applications to cybersecurity, data platforms and developer tools.

Life Sciences & Biotech (∼22 %)

Financing novel therapeutics, diagnostics and MedTech spin-outs at Series B–C, with strong corporate and philanthropic partners.

Climate & Impact Tech (∼12 %)

Investing in water treatment, clean energy, sustainable mobility and resource-efficient solutions to tackle environmental challenges.

Infrastructure (∼10 %)

Supporting strategic projects in digital and social infrastructure, energy transition and resilient supply-chain systems.

Other Sectors (∼18 %) – Including defence tech, food-tech innovation and community-led accelerator funds.

🚀 Investment Stages

Early Stage — 72 % of new funds (26 of 36)

Backing pre-seed and seed startups across food-tech, defence, deep tech and accelerator-linked communities.

Growth Stage — 28 % of new funds (10 of 36)

Focusing on Series B–C biotech breakthroughs, AI scale-ups and sustainable infrastructure ventures.

What This Means for Founders

North America remains the powerhouse and life-sciences the hottest sector. Founders in AI and biotech should target North American investors specialising in those verticals, while climate-tech entrepreneurs will find Europe’s sustainability-focused funds most receptive to their pitches.

All fund details below👇

Read more

💸 New Funds Looking to Give You Cash

🚀 $6.12 B Across 26 New Funds

Generative AI, fintech, sustainability and cybersecurity lead the charge.

Where the Money is Going

🌍 Geography at a Glance

• North America (64% of fund $) – Mega-funds dominate US and Canadian markets, pouring capital into AI, blockchain and enterprise SaaS.

• Asia-Pacific (18% of fund $) – Government-backed vehicles and corporate partnerships in Japan, India and Singapore fuel deep tech, Web3 and defence spin-outs.

• Europe (11% of fund $) – Large climate-tech and impact funds in Italy, Germany and the Nordics back circular economy and productivity-enhancing solutions.

• Middle East (6% of fund $) – Israeli and UAE-based funds concentrate on fintech, cybersecurity and dual-use defence ventures.

• Rest of the World (1% of fund $) – Smaller LatAm and other emerging-market vehicles support early-stage fintech and healthtech opportunities.

🎯 Sector Priorities

AI (32% of funds by $)

Backing everything from foundational models and enterprise AI solutions to AI-powered hardware and specialised applications.

Fintech (17% of funds by $)

Targeting digital payments, embedded finance and insurtech platforms designed for regulatory compliance.

Sustainability & Climate Tech (15% of funds by $)

Investing in emissions-cutting agtech, circular packaging and building-efficiency sensors.

Cybersecurity (12% of funds by $)

Prioritising identity security, DevOps tooling and enterprise-grade threat detection.
Other Sectors (24% of fund $) – Covering blockchain & crypto, enterprise software, biotech and defence tech, including tokenisation, healthtech and dual-use innovations.

🚀 Investment Stages

Early Stage — 58% of new funds (15 of 26)

Backing pre-seed to Series A startups in AI, fintech and emerging deep-tech niches.

Growth Stage — 42% of new funds (11 of 26)

Focused on scaling Series B+ companies across sustainability, defence and enterprise software.

What This Means for Founders
With North America commanding nearly two-thirds of capital and AI attracting a third of all funding, founders should sharpen AI-driven propositions and tap US and Canadian networks—while sustainability and fintech entrepreneurs can also find growing opportunities in Europe and Asia-Pacific.

All fund details below👇

🚀 AI Launchpad • 4‐Week Live Programme

Go from GenAI fundamentals to full-scale automations—live masterclasses, hands-on builds and reusable blueprints. All paid registrants receive our ChatGPT Starter Playbook.

• Who: Executives & founders

• When: Four Wednesdays, 19:00–21:00 GMT+4 (16 Jul–6 Aug ’25)

Why join?

• Automate key workflows & save hundreds of hours

• Build-first demos with zero waffle

Register here

Read more

Here’s your Monday dose of The AI Brief.

Your weekly updates of game-changing AI breakthroughs, hands-on startup case studies, velocity-boosting tools and no-nonsense strategic reminders, all designed to give founders the insights and tactics they need to stay ahead in an AI-driven market.

📈 Trending Now

• The week’s unmissable AI headlines.

  • What’s buzzing in the AI world, the key facts behind it and why every founder should sit up and take notice.

💡 Innovator Spotlight

• Meet the change-makers.

  • A down-to-earth snapshot of a founder using AI in a brilliantly unexpected way—and one practical lesson you can pinch straight away.

🛠️ Tool of the Week

• Your speed-boost in a nutshell.

  • An AI tool or integration that’ll shave days off your dev cycle—plus how to get started in minutes and our top insider tip.

📌 Note to Self

• Words above my desk.

  • A hard-won reminder or question to pose yourself—keep these front and centre to dodge the same old traps.

Weekly AI insights in 5 minutes flat

Subscribe now

📈 Trending Now

Major Headlines

• OpenAI secures $200 m U.S. defence contract

• Microsoft & Premier League ink five-year AI partnership

• Apple mulls ChatGPT/Claude for next-gen Siri

Top Trends

• Agentic AI – multi-step reasoning with end-to-end task execution

• AI in Sport & Entertainment – real-time analytics & personalised fan experiences

• Gov & Defence AI – OpenAI’s Pentagon award kick-starts public-sector deals

• Generative Reasoning Models – DeepSeek R1, Claude Opus 4 bring stepwise problem-solving

🛰 On the Radar

• DeepSeek R1 – China’s cost-effective challenger heats up model competition

• London Tech Week ’25 – £1 billion AI pledge underscores UK infrastructure push

• Healthcare AI leap – Microsoft’s diagnostic system outperforms expert physicians

🔭 What to Watch
A clear shift from “features” to outcomes and “code” to adaptive integration. Keep an eye on AI agents that embed in messy workflows—and on partnership strategies that marry foundation models with domain expertise.

Services-as-Software -SAS

I wrote about SAS in November of last year, after having written about the death of the traditional SaaS model in Jan 24. (see articles below). Now, a fresh wave of AI-native founders is building end-to-end intelligent agents that don’t just automate tasks but deliver complete business outcomes, from SRE teams to accounting and legal support. In an era when every company can licence the same base models—GPT-4, Claude, Gemini—the true moat lies in implementation depth, embedding forward-deployed engineers to capture tribal knowledge and turn edge-case rules into reusable assets. This shift unlocks a$4.6 trillion opportunity , dwarfing traditional SaaS, and demands a relentless focus on the “last mile” of messy, human workflows.

Who

A new cohort of AI-first teams is emerging, building Services-as-Software companies—complete intelligent agents that replace entire functions such as site reliability engineering, accounting and paralegal work.

What’s bold

These startups aren’t merely shipping features; they’re delivering proven outcomes. In today’s world, where foundation models are universally accessible, the real competitive edge comes from how you integrate, customise and operate AI within complex, real-world processes. Leading teams embed forward-deployed engineers alongside users to codify tribal knowledge, turning every bespoke deployment into a product advantage for the next customer

Why it’s unexpected

The old SaaS playbook—feature velocity, proprietary code, slick UX—is on its way out. Instead, the moat now lies in implementation depth and the ability to prove business impact before contracts are signed, blurring the line between pre-sales and post-sales.

The scale of the opportunity

• £1.8 trillion spent on salaries across sales, marketing, software engineering, security and HR each year

• £1.8 trillion more spent on outsourced services, per Gartner

• In the US alone, services roles account for roughly £3.9 trillion in wages across AI-exposed functions—highlighting an enormous under-automated market.

• By comparison, global SaaS revenue hovers around £226 billion annually, with outsourced digital work at £1.5 trillion.

Practical tip

Focus on the “last mile”—the messy workflows where generic models falter. Design your implementation team as a strategic asset, not an afterthought, and build reusable scaffolding so each customer deployment compounds your competitive advantage.

Why founders should care

The next generation of unicorns will win not by cranking out features but by mastering deep, adaptive integration—turning AI promises into provable, repeatable business results. With analysts projecting that AI-driven services could boost global productivity by £5.5 trillion by 2030, the real prize lies in outcome-focused agents, not toolkits.

🚀 AI Launchpad • 4‐Week Live Programme

Go from GenAI fundamentals to full-scale automations—live masterclasses, hands-on builds and reusable blueprints. All paid registrants receive our ChatGPT Starter Playbook.

• Who: Executives & founders

• When: Four Wednesdays, 19:00–21:00 GMT+4 (16 Jul–6 Aug ’25)

Why join?

• Automate key workflows & save hundreds of hours

• Build-first demos with zero waffle

Register here

💡Innovator Spotlight

Pika: The AI Video Wizard Making Hollywood Jealous

Who
Demi Guo and Chenlin Meng—both Stanford AI drop-outs—launched Pika to turn every browser into a mini film studio.

What’s funky
Half a million creators now whip up millions of videos a week—whether it’s scuba divers on alien reefs or tigers break-dancing in Times Square—with no GPU farms in sight.

Why it’s unexpected
Until Pika, you needed expensive render farms or awkward enterprise tools; now it’s just “click → watch” in any modern browser.

Pinch this lesson
Strip away friction—hardware, jargon, loading bars—and you open your product to everyone, from indie filmmakers to your gran.

Practical tip
Treat that final “Generate” click as sacred. When users hit it, everything else must vanish, leaving only delight.

Why founders should care
The next AI unicorns won’t be named for model size but for the joy they deliver. By turning users into creators, you build engagement and defensibility far beyond the core algorithm.

AI Avatars & Virtual Influencers: Building Brands and Getting Paid in 2025

The big picture
AI avatars and virtual influencers now form a $4.6 billion market, growing at 26% a year—no flash-in-the-pan trend, but a full-blown industry.

Top earners

• Lil Miquela is on track for $15–20 million in 2025, fronting Prada, Balenciaga and even metaverse concerts.

• Shudu Gram pulls in $10–12 million, thanks to campaigns for Fendi and Balmain plus NFT art drops.

• Imma, Tokyo’s pink-haired icon, nets $8–10 million with Dior, Puma and IKEA tie-ups.

Livestream shocker
On Baidu’s Youxuan, AI doubles of top host Luo Yonghao generated $7.65 million in six hours—outperforming his human-hosted streams.

Fashion & beauty highlight
Mango’s teen line was the first campaign ever created entirely with generative AI—no human models needed.

Why brands are all in

• Creative control: zero scandals, total localisation.

• Scalability: avatars never sleep or burn out.

• Engagement: Gen Z can’t get enough of digital storytellers.

Key takeaway
Virtual influencers aren’t a gimmick—they’re a thriving, outcome-focused business. Blend human warmth with AI reliability, and you’re onto something powerful..

🛠️ Tools of the Week

How AI Avatar Content Automation Really Works

1. Content Database

Use a simple spreadsheet or workspace as your single source of truth:

• Google Sheets (free, cloud-based) keeps scripts, captions, hashtags and video URLs in one place.

• Notion lets you build a wiki-style repo with templates, comments and version history.

• Airtable gives you a no-code database view, Kanban boards or galleries—ideal for richer metadata.

2. AI Video Generation

Automatically turn text into talking-head or character clips in the browser:

• HeyGen: Browser-based avatars with multilingual voice cloning (API available).

• Synthesia: 230+ avatars, 140+ languages—just send your script to their API and get back an MP4 .

• D-ID: Photorealistic AI presenters straight from a single image—ideal for lifelike spokespeople.

• Pika Labs: Instant text-to-video loops, no GPU farms—just paste your prompt and watch the magic.

3. Automated Social Posting

Orchestrate the whole flow—database → AI tool → social networks—without code:

• n8n: Fair-code, self-hostable or cloud, with 400+ integrations and native AI nodes.

• Make.com: Visual canvas, AI-powered agents and 2,000+ app connectors, all drag-and-drop.

• Zapier: 8,000+ apps, prebuilt templates and AI orchestration—just link your Sheets to Instagram, TikTok, LinkedIn, YouTube, you name it.

Why this matters
• Hands-off scaling: Once it’s wired up, new scripts become new videos and posts overnight.
• Total consistency: One source of truth means no mixed-up hashtags, captions or forgotten links.
• End-user joy: Spend time on ideas, not editing or scheduling.

Give it a whirl—your next viral avatar video could be fully automatic.

Check out our content store at insights.fusion-42.com

Unlock the Full Fusion42 Content Store
Dive into our all-in-one knowledge hub for founders, framers and funders:

Everything42 – Your weekly “Life, the Universe and Fusion42” deep dive on big-picture trends, live cohort metrics and candid build-in-public updates.

Startup-X – The AI Brief every Monday: Trending Now, Innovator Spotlight, Tool of the Week and a Note to Self, all in a rapid-fire five-section format.

Investor-X – The Raise Report each Wednesday: tracking who’s raising, who’s deploying—and why. Since launch, we’ve covered 700 + funds that raised over USD 240 billion in fresh capital. Money isn’t the issue; understanding why deployment lags is.

Masterclass Insights – On-demand replays of every Global Super Accelerator workshop, Raise Summit panel and candid Q&A—complete with slides, demos and real-time pivots.

eBooks for Founders – Bite-sized, no-fluff playbooks on everything from framing your problem and sizing your market to term-sheet traps and retention strategies—distilled from our own accelerator cohorts.

Ready to plug in to every guide, workshop and insider update?

Subscribe to Fusion42+ at insights.fusion-42.com and spend less time hunting answers and more time building what matters.

Subscribe now

📌 Note to Self

Share Fusion42 by DeReK WaTSoN

Thank you for reading. If you liked it, share it with your friends, colleagues and everyone interested in the startup Investor ecosystem.

If you've got suggestions, an article, research, your tech stack, or a job listing you want featured, just let me know! I'm keen to include it in the upcoming edition.

Please let me know what you think of it, love a feedback loop 🙏🏼

• ❤️ Love it, keep them coming!

• 👍 Great, always a good read.

• 😊 Enjoyable, but let’s see some variety.

• 👎 Okay, seen better.

• 🛑 Get a different job.
  
  Subscribe below and follow me on LinkedIn or Twitter to never miss an update. 

Subscribe now

For the ❤️ of startups

✌🏼 & 💙
Derek

Here’s your Monday dose of The AI Brief.

From today, The F42 Brief evolves into AI First—your weekly updates of game-changing AI breakthroughs, hands-on startup case studies, velocity-boosting tools and no-nonsense strategic reminders, all designed to give founders the insights and tactics they need to stay ahead in an AI-driven market.

📈 Trending Now

• The week’s unmissable AI headlines.

  • What’s buzzing in the AI world, the key facts behind it and why every founder should sit up and take notice.

💡 Innovator Spotlight

• Meet the change-makers.

  • A down-to-earth snapshot of a founder using AI in a brilliantly unexpected way—and one practical lesson you can pinch straight away.

🛠️ Tool of the Week

• Your speed-boost in a nutshell.

  • An AI tool or integration that’ll shave days off your dev cycle—plus how to get started in minutes and our top insider tip.

📌 Note to Self

• Words above my desk.

  • A hard-won reminder or question to pose yourself—keep these front and centre to dodge the same old traps.

📈 Trending Now

GPT-5 Announcement

Sam Altman has confirmed that GPT-5 will launch this July as a full-blown AI operating system—replacing the multi-model dropdown with one unified architecture.

Key Highlights from People with Early Access

1. True AGI (until you look at the definition of AGI)
   GPT-5 “thinks, reasons, creates and executes” across domains without switching models—feeling more like artificial general intelligence than any prior release.

2. All-in-One Multimodal
   One model to rule them all: text, image, video, audio and code (Codex) capabilities bundled into a single endpoint.

3. Outperforms Experts
   Early benchmarks show GPT-5 eclipsing specialists in PhD-level tasks—rewriting the rules for domain-specific AI applications.

4. Device-Agnostic OS
   Runs natively on laptops, phones and embedded systems, effectively acting as an AI OS for any hardware.

5. Seamless Multitasking
   Edit videos, generate transcripts, analyse data and research problems concurrently—no lag or context-switch overhead.

6. Persistent Memory
   Deep personalisation and total recall across chats and documents, transforming GPT-5 into a true personal assistant.
   

G7 Leaders Agree Joint Statement on AI

G7 nations signed a six-point joint statement covering critical minerals, quantum computing and artificial intelligence at the summit in Canada last week. reuters.com
They committed to a human-centric approach and pledged to collaborate on safe, trustworthy AI deployment.
Founders should watch for emerging standards and funding schemes born of this pact—as alignment among leading economies often sets the tone for global investment and market access.

The Rise of the “AI Whisperer” Economy

CEOs worldwide are hiring “AI whisperers”—specialist advisers who translate technical models into boardroom strategy and hands-on implementation plans
This burgeoning advisory market presents founders with a dual opportunity: to offer consultancy services for AI integration and to ensure their own teams aren’t left scrambling for expertise.

Each of these developments—from massive infrastructure spends to shifts in compute sourcing and new advisory models—reshapes the AI landscape for startups. Keep these trends front of mind as you plan your next product roadmap, funding round or strategic hire.

Investors are zeroing in on 19 AI-powered consumer social startups that blend niche communities with next-gen intelligence.

• Swsh: A Gen Z photo-sharing app partnering with festivals like Rolling Loud, using AI to surface event shots—has raised $3 million since 2022.

• Status: A gamified platform mixing real users and AI characters, now boasting over 2.5 million users.

• Bible Chat: A chatbot trained on scripture, with 25 million users and $16 million in funding.

• Doji: Virtual try-on avatars for fashion, fresh off a $14 million seed round.

• Gigi: “The AI who knows everyone” dating app that learns user preferences for smarter matches.

Founders should study how AI-infused community hooks are driving rapid traction—and ask how they can weave similar agent-led experiences and network effects into their own products.

Check out our content store at insights.fusion-42.com

Unlock the Full Fusion42 Content Store
Dive into our all-in-one knowledge hub for founders, framers and funders:

Everything42 – Your weekly “Life, the Universe and Fusion42” deep dive on big-picture trends, live cohort metrics and candid build-in-public updates.

Startup-X – The AI Brief every Monday: Trending Now, Innovator Spotlight, Tool of the Week and a Note to Self, all in a rapid-fire five-section format.

Investor-X – The Raise Report each Wednesday: tracking who’s raising, who’s deploying—and why. Since launch, we’ve covered 700 + funds that raised over USD 240 billion in fresh capital. Money isn’t the issue; understanding why deployment lags is.

Masterclass Insights – On-demand replays of every Global Super Accelerator workshop, Raise Summit panel and candid Q&A—complete with slides, demos and real-time pivots.

eBooks for Founders – Bite-sized, no-fluff playbooks on everything from framing your problem and sizing your market to term-sheet traps and retention strategies—distilled from our own accelerator cohorts.

Ready to plug in to every guide, workshop and insider update?

Subscribe to Fusion42+ at insights.fusion-42.com and spend less time hunting answers and more time building what matters.

Subscribe now

💡Innovator Spotlight

Pranjali Awasthi, Serial Founder

By the age of sixteen, Pranjali taught herself to code, built Delv.AI—a research assistant that raised ₹100 crore and cut academic prep from days to minutes—and then handed the business over to a leadership team so she could tackle something new.

The Journey
Starting with weekend hacking sessions, Pranjali launched Delv.AI in 2022 to help researchers sift pay-walled papers, reports and video lectures using AI-powered summaries and interactive dashboards. Backed by On Deck, Pioneer Fund and Village Global, her lean team of specialists rapidly turned a prototype into a ₹100 crore-valued platform.

Why She Stepped Back
Once Delv.AI was on solid footing, Pranjali brought in experienced operators to run day-to-day operations. She didn’t sell the company—she simply moved aside, allowing Delv.AI to grow under new leaders while she pursued her next passion.

What’s Next
In March 2025, Pranjali launched Dash—“ChatGPT with hands”—combining a plug-and-play robotic arm with an AI brain. Now you can ask it to “pick that up,” “assemble this,” or “run a quality check” and it just gets on with the job.

Practical Pin-up
“Who could I empower on my team so I can focus on tomorrow’s big idea?”

Key Lesson
Building value isn’t just about the first win—it’s about knowing when to hand over the reins and give yourself room to dream up what comes next.

🚨 Your competitors are already using AI—are you ready to catch up?

Join our FREE 45-min AI Launchpad Intro on Wed 2 Jul @ 19:00 GMT+4. We’ll walk you through our 4-week sprint: LLMs → Automations → Agents →Agentic

Register here

🛠️ Tools of the Week

Next-gen SOP tools now capture every click, keystroke or video segment, then apply AI to assemble step-by-step guides complete with annotated screenshots, callouts, voice-overs and rich media. These platforms can cut documentation time by up to 80 per cent, ensure process accuracy and let teams focus on impact rather than manual write-ups .

Top 4 Next-Gen SOP Tools

1. Tango

Tango runs as a Chrome/Edge extension and records every click and tab switch, turning live processes into polished how-to guides with perfectly cropped, annotated screenshots—no manual screenshots or notes required . Its AI also automates repetitive CRM and pipeline tasks by replaying your actions, so you get both SOPs and runnable automations from the same recording .

2. Scribe

Scribe’s AI-powered SOP generator captures clicks and on-screen text as you work, then auto-generates a step-by-step guide with screenshots and editable annotations in under 30 seconds . You can customise each step, add extra tips, combine multiple recordings and export to PDF, HTML or Markdown for seamless sharing .

3. Trupeer

Trupeer lets you record a walkthrough video (or upload an existing one) and its AI parses the footage to extract key actions, generate annotated screenshots and build a full video-backed SOP complete with a searchable transcript and step editor . Its drag-and-drop editor makes it trivial to refine steps, add notes or translate the entire SOP into 50+ languages for global teams .

4. Guidde

Guidde captures your workflow as a screen recording with voice-over, then uses AI to draft a narrative “storyline” for each step, overlay captions and package everything into a branded SOP video guide . You can blur sensitive fields, tweak wording and embed or share via link—ideal for customer training and internal compliance .

Why These Matter

By leveraging click-and-video-driven SOP generators, founders can lock in accuracy, onboard teams faster and keep procedures evergreen without the admin drag—freeing you to iterate on product and growth rather than process docs .

📌 Note to Self

Share Fusion42 by DeReK WaTSoN

Thank you for reading. If you liked it, share it with your friends, colleagues and everyone interested in the startup Investor ecosystem.

If you've got suggestions, an article, research, your tech stack, or a job listing you want featured, just let me know! I'm keen to include it in the upcoming edition.

Please let me know what you think of it, love a feedback loop 🙏🏼

• ❤️ Love it, keep them coming!

• 👍 Great, always a good read.

• 😊 Enjoyable, but let’s see some variety.

• 👎 Okay, seen better.

• 🛑 Get a different job.
  
  Subscribe below and follow me on LinkedIn or Twitter to never miss an update. 

Subscribe now

For the ❤️ of startups

✌🏼 & 💙
Derek

💸 New Funds Looking to Give You Cash

$1.21 billion Across 17 New Funds

Investors are doubling down on multi-sector vehicles alongside dedicated AI, fintech and deeptech funds.

Where the Money is Going

🌍 Geography at a Glance

• Europe (79 %) – Dominated by generalist and regional multi-sector funds targeting scale-ups across CEE and Western Europe.
  North America (13 %) – Concentrated in AI-focused and diversity-led early-stage vehicles.
  Asia (8 %) – Driven by a dedicated campus fund backing student and dropout-founders in deeptech and emerging technologies.
  Rest of the World – No significant new seed or pre-seed fund launches outside these regions in this period.

  ---

  🎯 Sector Priorities

  Multi-sector (42 % of funds by $)

  Generalist vehicles span enterprise software, fintech, AI and consumer tech, offering founders diverse syndication and follow-on support.

  Artificial Intelligence (10 % of funds by $)

  Dedicated AI funds target post-revenue, B2B machine-learning ventures solving real-world business problems.

  Fintech (9 % of funds by $)

  Capital flows into blockchain, igaming and regulated fintech platforms, often structured as Guernsey-registered partnerships.

  Deeptech (8 % of funds by $)

  Student-focussed and regional funds back space, biotech, advanced manufacturing and next-generation engineering startups.

  Other Sectors (31 % of funds by $) – Venture debt, consumer-tech, defence, edtech, healthcare and gender-lens vehicles.

  ---

  🚀 Investment Stages

  Early Stage — 88 % of new funds (15 of 17)

  Primarily pre-seed to Series A vehicles backing first-time founders and post-revenue inflection startups.

  Growth Stage — 12 % of new funds (2 of 17)

  Selective growth-oriented and venture-debt funds supporting businesses nearing break-even or Series B readiness.

  ---

  What This Means for Founders

  With Europe commanding nearly four-fifths of the capital—led by broad multi-sector vehicles and specialist AI and fintech funds—founders should prioritise UK and CEE investors, especially if operating in AI or financial technology, to maximise fundraising success.

Remembering Ali Jamal

We are deeply saddened by the passing of Ali Jamal, founder of First Check Ventures. Ali was more than an investor—he was a mentor, a supporter, and a true champion of innovation. His unwavering belief in early-stage founders and his generosity with his time and expertise have left a lasting impact on our community.

We are profoundly grateful for Ali’s support and encouragement over the years. His legacy will live on in the countless entrepreneurs and companies he inspired.

Our thoughts are with his family and loved ones during this difficult time.

Thank you, Ali, for everything.

All fund details below👇

Read more

Here’s your Monday dose of The F42 Brief.

📈 Trending Now

• The one thing that’s making all the noise …. with a bit of fact checking.

💡Innovator Spotlight

• Founders that are doing stuff differently.

🛠️ Tool of the Week

• Something useful to up your startups velocity.

📌 Note to Self

• Stuff I constantly remind myself about, don’t want make the same mistakes again.

📈 Trending Now

Last August we were talking Agentic AI and debating if we will see a 1 person unicorn startup…

For years, that sounded like a punchline, not a plan. But I’m starting to think it’s not just plausible—it’s inevitable. The story of Base44, sold to Wix for $80 million just six months after launch, is a serious wake-up call.

Base44 wasn’t some VC-backed rocketship with a 50-person dev team. It was lean, fast, and built around the idea of vibe coding—where anyone can describe an app in plain English and have it built instantly using AI. Over 250,000 users, nearly $200,000 in monthly profit, and barely any overhead. That’s not luck. That’s a signal.

Wix paid cash—$80 million—for a business that proved something important: you don’t need a massive team to build something massive. Yes, Base44 had a few employees at the end, but the engine was AI. Tech, ops, even customer support—it was all run by systems, not people.

And here’s the thing: this might be the start of a whole new wave. The “solo unicorn” idea—where one founder builds and exits a billion-dollar business using AI instead of headcount—is no longer a fantasy. It’s a blueprint.

I think we’re about to see a surge of one-person startups doing what used to take a village. AI’s getting better by the day, and Base44 just proved what’s possible when you let the machines take the wheel.

Check out our content store at insights.fusion-42.com

Unlock the Full Fusion42 Content Store
Dive into our all-in-one knowledge hub for founders, framers and funders:

Everything42 – Your weekly “Life, the Universe and Fusion42” deep dive on big-picture trends, live cohort metrics and candid build-in-public updates.

Startup-X – The F42 Brief every Monday: Trending Now, New Funds, Innovator Spotlight, Tool of the Week and a Note to Self, all in a rapid-fire five-section format.

Investor-X – The Raise Report each Wednesday: tracking who’s raising, who’s deploying—and why. Since launch, we’ve covered 700 + funds that raised over USD 240 billion in fresh capital. Money isn’t the issue; understanding why deployment lags is.

Masterclass Insights – On-demand replays of every Global Super Accelerator workshop, Raise Summit panel and candid Q&A—complete with slides, demos and real-time pivots.

eBooks for Founders – Bite-sized, no-fluff playbooks on everything from framing your problem and sizing your market to term-sheet traps and retention strategies—distilled from our own accelerator cohorts.

Ready to plug in to every guide, workshop and insider update? Subscribe to Fusion42+ at insights.fusion-42.com and spend less time hunting answers and more time building what matters.

Subscribe now

💡Innovator Spotlight

🧠 You know the phrase “betting on the jockey, not the horse”? Well, Mira Murati just took that to a whole new level.

🚀 In 2025, she stepped away from her role as CTO of OpenAI and launched Thinking Machines Lab. No product. No revenue. Still in stealth. And yet—she raised $2 billion at a $10 billion valuation. As a seed round.

💰 I know, it sounds like a typo. But it’s real.

📈 Andreessen Horowitz led the round, with Conviction Partners and other top-tier firms piling in. Why? Because Murati doesn’t just have a track record—she helped bring ChatGPT and DALL·E to life. She even stepped in as interim CEO during OpenAI’s infamous 2023 meltdown. When someone like that decides to build something new, investors don’t wait for a pitch deck—they write cheques.

🧑‍🔬 The company is still in stealth, but she’s already assembled a dream team of AI royalty: John Schulman (co-creator of ChatGPT), Barret Zoph, Bob McGrew, Alec Radford… basically the Avengers of machine learning. About 30 of them, all in.

⚡ This isn’t a normal startup story—it’s a signal. In a world obsessed with traction and product-market fit, Murati raised billions on pure reputation, talent, and vision. And it tells you everything about where the AI gold rush is right now: if you’re the right person, building with the right people, the money will find you—long before the market does.

🛠️ Tools of the Week

💬 Whimsical AI – I use Whimsical for mapping out ideas and workflows, and their new AI integration is actually useful—it suggests diagrams, rewrites stickies, and helps structure your thinking. Great for product planning or untangling chaos.

🧩 Tavily – I’ve been testing this one out, and it’s hands-down one of the smartest AI research assistants I’ve used. Ask it a question and it brings back real-time, cited answers from trusted sources—not just made-up LLM guesswork. If you're using AI for actual decisions, not just chat, this is a must-have.

🧠 Gamma – AI-powered slide decks that don’t make your eyes bleed. It’s great for turning a rough outline or brain dump into something presentation-ready in minutes. Ideal if you’re pitching, presenting, or just can’t face another blank slide.

👀 One to Watch: Figma AI

The one I am most excited about is the release of Figma AI.
We all love Figma—but the latest update, Figma AI, isn’t just a redesign. It’s a proper leap into the future.

This 2025 release doesn’t just add a few clever tools—it shifts Figma from a design platform to a full-blown AI co-creator. Here’s what’s actually landed:

🧠 Prompt-to-UI
Type what you want—“3-screen onboarding with dark mode and illustrations”—and it builds the flow for you. Like ChatGPT, but for interfaces.

📐 Smart Auto Layout
Automatically handles spacing, alignment, and responsiveness. Brilliant when it gets it right, frustrating when it fiddles with your layout.

🧭 Design Copilot
A handy little sidebar assistant that renames layers, tidies assets, and suggests plugins. Think of it as your ultra-organised desk mate.

🖼️ Code & Content Generation
Creates placeholder text, images, and basic React/Vue snippets. Not quite dev-ready, but solid for prototypes and handoffs.

🧼 New UI Overhaul
Cleaner and sleeker overall—but lots of tools and shortcuts have shifted, which means some of us are having to re-learn old habits.

🤝 Live AI Collaboration
Work alongside teammates and AI, with suggestions popping up live in your file. Feels a bit like having a group brainstorm on autopilot.

💬 Comment Summaries
AI now summarises threads and suggests next steps. Genuinely useful when feedback’s all over the place.

🔍 Is This the End for Loveable or Cursor?

Not quite—but the heat is on.

🎨 Loveable
Figma’s AI can now whip up icons and illustrations, which overlaps with Loveable’s space. That said, Loveable still wins on style and polish.

💻 Cursor
Figma now spits out basic code snippets, but Cursor’s still stronger for proper dev workflows and complex handoffs.

⚡ Speed vs. Control

Founders and lean teams will love the speed. Designers who obsess over the finer details might feel like they’re fighting the tool a bit.

But like it or not, Figma AI has changed the game.
The future of design is AI-assisted—and it’s already baked into your canvas.

📌 Note to Self

Share Fusion42 by DeReK WaTSoN

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For the ❤️ of startups

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Derek

💸 New Funds Looking to Give You Cash

🚀 $2 B: 14 New Funds Fuel Tomorrow’s Tech

Over half the capital is heading into AI and deep tech, with emerging markets, fintech and climate tech sharing the remainder.

Where the Money is Going

🌍 Geography at a Glance

• North America (76 per cent) – Dominated by large AI vehicles and corporate VCs.

• Emerging Markets (15 per cent) – High-impact entrepreneurs and defence tech in under-served regions.

• Europe (8 per cent) – Venture debt and foodtech funds filling regional financing gaps.

• Rest of the World (2 per cent) – Corporate climate partnerships and specialised vehicles.

🎯 Sector Priorities

• AI & Deep Tech (57 per cent) – Infrastructure, applications and AI-first startups.

• Emerging Markets & Impact (19 per cent) – Sustainable models and dual-use technologies in new geographies.

• Fintech (10 per cent) – Financial infrastructure, embedded finance and non-dilutive options.

• Climate Tech (4 per cent) – Decarbonisation, circular-economy solutions and industrial sustainability.

• Other Sectors (10 per cent) – Defence, foodtech, life sciences and corporate innovation.

🚀 Investment Stages

Investment Stages

Early Stage — 64 per cent (9 of 14)
Seed and Series A vehicles backing founders at inception.

Growth Stage — 36 per cent (5 of 14)
Series A+ and venture debt funds extending runway for scale-ups.

What This Means for Founders

North America remains the powerhouse region, with AI and deep tech the hottest sector. Founders should sharpen AI-focused propositions or pursue impact opportunities in emerging markets, while exploring fintech and climate-tech avenues to diversify their fundraising

Landing in Dubai – What Global Startups Need to Know

With our Partner - Dubai Technology Entrepreneur Campus (Dtec) a government-backed initiative in Dubai

Thinking about expanding into Dubai or the broader GCC region? Join this high-impact session designed to give global startups the insight, access, and tactical guidance needed to land, launch, and grow in the UAE.

​Hear directly from public and private leaders on incentives, setup options, the investor and tech ecosystem, and the reality of scaling in one of the world’s fastest-growing innovation hubs.

Join us at 19:00 - 20:00 GMT+4 19th June

Register here

All fund details below👇

Read more

Here’s your Monday dose of The F42 Brief.

📈 Trending Now

• The one thing that’s making all the noise …. with a bit of fact checking.

💡Innovator Spotlight

• Founders that are doing stuff differently.

🛠️ Tool of the Week

• Something useful to up your startups velocity.

📌 Note to Self

• Stuff I constantly remind myself about, don’t want make the same mistakes again.

📈 Trending Now

🔍 I’ll be honest: watching the headlines shout about “vibe coding” and an overnight AI revolution is entertaining—but it’s hardly new to us at Fusion42. We’ve spent months live-demoing these tools, guiding founders through the process of turning a prompt into a working prototype on our AI for Startups show. For us, this isn’t a bolt from the blue; it’s today’s baseline.

🚀 The fascinating bit isn’t that anyone can now spin up an app with a few lines of chat and a dash of bravery. We’ve seen non-technical founders do it in real time, week after week. What’s shifted is the bar: if building an MVP in a single evening is table stakes, the real question becomes, “What are you building that truly matters, and who’s going to pay for it?”

📸 It reminds me of the advent of digital cameras—overnight, everyone could take a photo—but only a handful mastered composition. AI tools like Copilot have levelled the playing field; now the edge goes to those who understand what’s under the bonnet, who know when to trust the machine and when to override it, and who can take a proof-of-concept and turn it into a reliable, scalable product.

🔥 At the end of the day, it all boils down to solving a real pain point—ideally a “hair-on-fire” problem that users can’t ignore. All the clever tech in the world won’t get you far if you’re not tackling a genuine issue. The best founders spend more time talking to customers than tweaking code, drilling into what users will actually open their wallets for. After all, Stripe didn’t become a household name by reinventing the wheel—they simply made online payments dead simple for developers who’d been desperate for a better solution.

⚡ So yes, the tools are extraordinary and the landscape’s evolving at warp speed, but the fundamental rule of startups remains unchanged: are you fixing something that truly matters? If the answer’s yes, carry on breaking new ground. If not, it’s back to the drawing board—no matter how polished your demo looks.

• WIRED’s “Vibe Coding Is Coming for Engineering Jobs” by Will Knight delivers a 360° view—tracing Andrej Karpathy’s coinage, laying out productivity gains alongside security, quality and economic risks flagged by MIT’s David Autor and seasoned engineers 🤖

• Business Insider’s “GitHub’s CEO says startups can only get so far with vibe coding” sees Thomas Dohmke warn that AI assistants help non-tech founders ship prototypes fast, but scaling and securing investment still demand deep developer chops 🎢

• Forbes’ “Y Combinator’s AI Revolution And The Rise of Vibe-Coding Startups” shows ~25% of YC companies now auto-generate 95%+ of their code with AI, fuelling red-hot valuations and VC interest 💸

• Bonus read: “Vibe Coding: AI’s Transformation Of Software Development” (Forrester/Forbes) for a wider lens on how AI is reshaping dev workflows—and why human intuition still wins complex builds 🧠

Check out our content store at insights.fusion-42.com

Unlock the Full Fusion42 Content Store
Dive into our all-in-one knowledge hub for founders, framers and funders:

Everything42 – Your weekly “Life, the Universe and Fusion42” deep dive on big-picture trends, live cohort metrics and candid build-in-public updates.

Startup-X – The F42 Brief every Monday: Trending Now, New Funds, Innovator Spotlight, Tool of the Week and a Note to Self, all in a rapid-fire five-section format.

Investor-X – The Raise Report each Wednesday: tracking who’s raising, who’s deploying—and why. Since launch, we’ve covered 700 + funds that raised over USD 240 billion in fresh capital. Money isn’t the issue; understanding why deployment lags is.

Masterclass Insights – On-demand replays of every Global Super Accelerator workshop, Raise Summit panel and candid Q&A—complete with slides, demos and real-time pivots.

eBooks for Founders – Bite-sized, no-fluff playbooks on everything from framing your problem and sizing your market to term-sheet traps and retention strategies—distilled from our own accelerator cohorts.

Ready to plug in to every guide, workshop and insider update? Subscribe to Fusion42+ at insights.fusion-42.com and spend less time hunting answers and more time building what matters.

Subscribe now

💡Innovator Spotlight

The Circular Economy Advantage: Why Infrastructure Leaders Win

Margins & Market Power:
If you can make a product that’s as good and as affordable as the “linear” competition—but your inputs are recycled, reused, or upcycled—your costs drop, your supply chain risk shrinks, and your brand value soars. That’s why so much investment is now chasing circular logistics, smart recycling, and digital product passports.

It’s Not Hype—It’s Happening:

• AI and Automation: Companies like Greyparrot and Recycleye are using AI-powered robots to sort waste with precision, driving up recovery rates and slashing costs in recycling plants.

• Supply Chain Transparency: Platforms such as Deply and Circular Route are building the digital plumbing for circularity—tracking materials, verifying origins, and optimising reverse logistics so recycled content can flow back into manufacturing at scale.

• Sector Examples:

  • Cyclize turns plastic waste into syngas for new chemicals.

  • Asgaard Metals makes new steel billets from scrap, matching quality and price with virgin steel.

  • FIZZYCAPS produces beverage bottle caps from recycled materials, indistinguishable from “new”.

Real-World Proof:

• The UAE’s Circular Economy Council is actively rolling out new policies and public-private partnerships to accelerate this transition across infrastructure, manufacturing, transport, food, and textiles.

• At Investopia 2025 in Abu Dhabi, companies like Peec showcased how converting fleets to electric using existing vehicles (not new ones) can cut emissions and costs—proving circular models can scale in mobility too.

Why This Is the Next Big Business Battleground

“If you can match price and quality, but your cost base is lower and your supply chain is circular, you don’t just win on sustainability—you win on margin, resilience, and future-proofing.”

Circular economy infrastructure is now a competitive moat. The best-run circular companies aren’t just greener—they’re more profitable, less exposed to commodity shocks, and increasingly favoured by both regulators and customers.

Who to Watch (2025)

Circular Edge – – Greyparrot AI waste sorting – Higher recovery, lower cost

Deply – – Blockchain supply chain for circularity – Traceability, compliance

Asgaard Metals – – Circular steel billets – Matches price/quality

FIZZYCAPS – – Recycled beverage caps – Indistinguishable product

Peec (UAE) –– Circular EV fleet conversion – Lower emissions, lower cost

Circular Route – – AI logistics for recycled/reusable goods – Cost-efficient, scalable

Bottom line:

Whoever cracks circularity at scale—without sacrificing price or quality—will dominate their sector. The infrastructure players enabling this shift are the real disruptors of 2025 and beyond. If you’re building, investing, or buying, watch this space: the circular economy is no longer just about doing good. It’s about winning, full stop

Landing in Dubai –

What Global Startups Need to Know

​​With our Partner - Dubai Technology Entrepreneur Campus (Dtec).

Thinking about expanding into Dubai or the broader GCC region? Join this high-impact session designed to give global startups the insight, access, and tactical guidance needed to land, launch, and grow in the UAE.

​Hear directly from public and private leaders on incentives, setup options, the investor and tech ecosystem, and the reality of scaling in one of the world’s fastest-growing innovation hubs.

Join us -- Register here

📌 Note to Self

Share Fusion42 by DeReK WaTSoN

Thank you for reading. If you liked it, share it with your friends, colleagues and everyone interested in the startup Investor ecosystem.

If you've got suggestions, an article, research, your tech stack, or a job listing you want featured, just let me know! I'm keen to include it in the upcoming edition.

Please let me know what you think of it, love a feedback loop 🙏🏼

• ❤️ Love it, keep them coming!

• 👍 Great, always a good read.

• 😊 Enjoyable, but let’s see some variety.

• 👎 Okay, seen better.

• 🛑 Get a different job.
  
  Subscribe below and follow me on LinkedIn or Twitter to never miss an update. 

Subscribe now

For the ❤️ of startups

✌🏼 & 💙
Derek

💸 New Funds Looking to Give You Cash

🚀 $17.6 B Across 36 New Funds

AI, climate resilience, sustainable food and digital health are soaking up the lion’s share of fresh capital.

Where the Money is Going

🌍 Geography at a Glance

Middle East (58 % of fund $) – State-backed mega-funds and AI-infrastructure vehicles dominate regional VC headlines.
North America (24 %) – A healthy mix of seed-stage deep-tech funds and growth pots for climate, sports and ag-food plays.
Asia-Pacific (9 %) – New money backs hydrogen, healthtech and cross-border AI hardware bridges.
Europe (8 %) – Food-tech spin-outs, blue-ocean impact funds and Baltic deep-tech specialists lead activity.
Rest of the World (1 %) – Latin America adds niche fintech and energy-transition funds while Brazil prepares a decarbonisation vehicle.

🎯 Sector Priorities

Artificial Intelligence (65 % of funds by $)

From $10 B sovereign vehicles to AI-native seed funds, investors are betting on models, chips, data centres and middleware.

Food & Agriculture (13 %)

University spin-outs and corporate VCs are financing resilient supply chains, functional drinks and alternative proteins.

Climate & Sustainability (9 %)

Hydrogen, electrification and ocean-regeneration funds channel capital into hard-tech decarbonisation.

Health & Life Sciences (7 %)

Digital biology, medtech and data-driven care platforms secure sizeable early-growth cheques.

Other Sectors (6 %) – Smaller pools focus on fintech, cybersecurity, hospitality, sports infrastructure and community investment.

🚀 Investment Stages

Early Stage — 67 % of new funds (24 of 36)

Seed specialists and university-linked vehicles writing first cheques for deep tech, AI and impact-driven ventures.

Growth Stage — 33 % of new funds (12 of 36)

Large-cheque investors scaling proven AI infrastructure, climate tech and sector-specific platforms.

What This Means for Founders

The Middle East’s outsized AI war chest makes it the go-to region for capital-intensive data and infrastructure plays, while North America remains fertile ground for specialised climate and food-tech funding. Align your pitch with these sector sweet-spots and target funds that match your stage: early-stage deep-tech founders should court the new seed vehicles, whereas scale-ups in AI infrastructure or decarbonisation may find faster traction with the fresh growth pools.

All fund details below👇

Read more

Here’s your Monday dose of The F42 Brief.

📈 Trending Now

• The one thing that’s making all the noise …. with a bit of fact checking.

💡Innovator Spotlight

• Founders that are doing stuff differently.

🛠️ Tool of the Week

• Something useful to up your startups velocity.

📌 Note to Self

• Stuff I constantly remind myself about, don’t want make the same mistakes again.

📈 Trending Now

Apple Cuts Through the AI Hype and the Crap

😩 I’ve grown a bit tired of all the AI hoopla—the grand claims of “AGI” from the usual suspects. Here’s the blunt truth Apple lays out in its “Illusion of Thinking” paper:

• 🚫 GenAI systems can’t reason.

• 🤖 They aren’t intelligent.

• 🎲 They’re just guessing.

• 🧠❌ They don’t think—and never will.

• 🏗️ The whole premise rests on false assumptions.
  
  

What Apple did was beautifully straightforward 🎩: they built four classic puzzles—Tower of Hanoi 🏰, checker-jumping ⏩, river-crossing 🌊 and blocks world 🧱—with strictly controlled difficulty and zero data leakage. Then, under the same compute budget, they pitched “chain-of-thought” models against plain LLMs. The outcome? Brutal clarity:

1. 📉 Low complexity: vanilla models beat the “thinking” ones.

2. ⚖️ Medium complexity: chain-of-thought grabs a modest edge.

3. 💥 High complexity: both dive to zero—push them past basics and they flatline.

Even more telling: as tasks grow thorny, the so-called reasoning models simply slack off, despite having tokens to spare—an almost comical scaling failure 🙈.

In plain English, these systems don’t solve new problems; they regurgitate patterns they’ve seen 🔍. Strip away clever prompts and memorised answers, and their “reasoning” evaporates. Far from sentient sidekicks, they’re glorified autocomplete engines.

The hard truth for founders, framers and funders? Don’t fall for the myth of thinking machines 🛑. Treat GenAI as a razor-sharp prediction tool, not an oracle 🔮. Build with your eyes wide open and strategies grounded in reality—because when it comes to genuine multi-step reasoning, today’s tech just can’t cut it.

🙏 And perhaps that’s fitting: if we humans often lean on pattern-matching too, maybe these systems are just holding up a mirror to our own shortcuts. Until genuine reasoning arrives, a dash of blind faith remains our most human trait.

The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity

💸 New Funds looking to give you cash

Look out for the The Raise Report this Wednesday, bring you all the new funds that have raised capital and looking to deploy.

Subscribe now

Landing in Dubai –

What Global Startups Need to Know

​​With our Partner - Dubai Technology Entrepreneur Campus (Dtec).

Thinking about expanding into Dubai or the broader GCC region? Join this high-impact session designed to give global startups the insight, access, and tactical guidance needed to land, launch, and grow in the UAE.

​Hear directly from public and private leaders on incentives, setup options, the investor and tech ecosystem, and the reality of scaling in one of the world’s fastest-growing innovation hubs.

Join us -- Register here

💡Innovator Spotlight

Last week I listened to “AI × Crypto” episode of Web3 with A16Z Crypto, and let me tell you—it’s blockchain’s moment in the sun.

1. 🔒 Trust & Identity, Supercharged
   I’ve seen blockchains keep data honest, but now AI is sniffing out on-chain shenanigans—front-running bots, wash trades, you name it. And with deepfakes everywhere, Proof of Personhood protocols (AI vision plus zero-knowledge proofs) finally nail “you are you” on-chain. That’s foundational for any permissionless network.

2. 🤖 Autonomous Agents Go Public
   Those demo “robot traders” you saw in labs? They’re live now. Imagine an AI that rebalances your DeFi positions, snags yield and locks in gains—no human needed. In gaming, in-world bots will earn and spend tokenised assets you truly own. Suddenly, blockchains aren’t just ledgers; they’re the runtime for AI economies.

3. 🌐 DePIN Hits the Real World
   Decentralised Physical Infrastructure Networks are getting brains. From peer-to-peer internet to EV chargers, edge AI feeds validated data into smart contracts. Your car could book a charger, pay in crypto and update the network—autonomously. That’s machines transacting with machines, and it’s happening today.

4. 🔄 Tokenised Intelligence
   Think Uniswap for AI models and data sets: anyone can mint, license or vote on algorithms via tokens. It flips AI from a corporate black box into a community-driven asset—and that’s huge for decentralisation.

5. ⚖️ The Balancing Act
   Expect hybrids—heavy-duty AI off-chain with on-chain proofs for transparency. Regulators will want audit trails; blockchains deliver. The protocols that nail this choreography will own the next internet wave.

Why It Matters
By 2025, we won’t just store data on blockchains—we’ll run intelligent, self-optimising networks on them. If you’re not building with both AI smarts and crypto trust, you’re missing the tidal wave. This is blockchain’s golden age, and it’s happening right now.

Catch the episode here: AI x Crypto

🛠️ Tools of the Week

The Hottest AI x Blockchain Platforms to Watch in 2025
AI and blockchain are a must-watch in 2025 because together they deliver unprecedented data security, transparency, and user control—enabling trustworthy, privacy-preserving analytics and automation at scale

Fetch.ai
Autonomous AI agents for automated, trustless transactions and data sharing across networks.

SingularityNET
Decentralized marketplace for AI algorithms—build, share, and monetize AI services on-chain.

Ocean Protocol
Tokenized data marketplace—securely share, monetize, and analyze data using AI models on blockchain.

ChainGPT
AI for smart contract generation, auditing, and technical analysis—plus AI-generated NFTs and agent infrastructure.

Cortex
Enables AI model execution directly on-chain, bringing machine learning to smart contracts.

Render Network
Decentralized GPU and AI compute marketplace—power AI/ML tasks and rendering with idle resources.

The Graph
Decentralized protocol for indexing and querying blockchain data using AI-powered subgraphs.

Artificial Superintelligence Alliance (ASI)
Universal AI token (Fetch.ai, SingularityNET, Ocean) for secure, decentralized AI services and interoperability.

Griffain
AI agent coordination on Solana for complex on-chain actions and automation.

Augur
Decentralized prediction markets using AI for outcome verification and market creation.

Agent-based automation:

Platforms like Fetch.ai and Griffain use AI agents to automate on-chain tasks, creating new possibilities for dApps and DeFi.

• Decentralized AI marketplaces: SingularityNET and Ocean Protocol let you build, deploy, and monetize AI models and data securely.

• On-chain AI execution: Cortex and ChainGPT bring direct AI computation and smart contract generation to the blockchain layer.

• Compute and data marketplaces: Render Network and The Graph unlock decentralized compute and data analytics, vital for AI/ML and transparency.

• Universal AI tokens: The ASI alliance is pioneering cross-platform AI services and interoperability.

• AI-powered prediction and compliance: Augur and Ocean Protocol are pushing boundaries in prediction markets and privacy-preserving compliance.

📌 Note to Self

💀 What’s the most unsexy thing you do daily to keep your startup wheels turning?
(I mean the boring, repetitive, can’t-skip-it stuff that actually keeps things alive)

Share Fusion42 by DeReK WaTSoN

Thank you for reading. If you liked it, share it with your friends, colleagues and everyone interested in the startup Investor ecosystem.

If you've got suggestions, an article, research, your tech stack, or a job listing you want featured, just let me know! I'm keen to include it in the upcoming edition.

Please let me know what you think of it, love a feedback loop 🙏🏼

• ❤️ Love it, keep them coming!

• 👍 Great, always a good read.

• 😊 Enjoyable, but let’s see some variety.

• 👎 Okay, seen better.

• 🛑 Get a different job.
  
  Subscribe below and follow me on LinkedIn or Twitter to never miss an update. 

Subscribe now

For the ❤️ of startups

✌🏼 & 💙
Derek

Here’s your Monday dose of The F42 Brief.

📈 Trending Now

• The one thing that’s making all the noise …. with a bit of fact checking.

💡Innovator Spotlight

• Founders that are doing stuff differently.

🛠️ Tool of the Week

• Something useful to up your startups velocity.

📌 Note to Self

• Stuff I constantly remind myself about, don’t want make the same mistakes again.

📈 Trending Now

The Reality Behind AI Hype

• 🔍 A recent S&P Global survey reveals that 42 per cent of organisations have ditched most of their generative-AI initiatives this year—up from just 17 per cent a year ago. You might have noticed the headlines: what began as an all-guns-blazing rush has very quickly turned into a case of “where’s the ROI?” This jump highlights how initial excitement can evaporate once projects fail to deliver the goods—exactly the kind of trough you see in most innovation cycles.

• 🔄 It’s worth remembering that every major technology goes through hype, disappointment, and then steady adoption. In fact, Gartner’s famous Hype Cycle shows that this trough of disillusionment is par for the course; we saw the same pattern with the internet, mobile computing and cloud before they became business-critical tools.

• ⚙️ So, why the sudden U-turn? Well, for starters, a lot of valuable data remains locked away in legacy systems or scattered across different silos, making it tricky to feed clean, reliable inputs into AI models. On top of that, there’s a genuine shortage of people who both understand the nuts and bolts of AI and know how to embed it into existing workflows. And let’s be honest: boards aren’t keen to gamble with their reputation. If an AI bot mishandles sensitive customer data or pushes out dubious recommendations, the brand fallout could be severe. In short, moving from a flashy prototype to a robust, production-ready solution has proven far harder—and riskier—than many anticipated.

• 💨 Then there’s the infamous “pump cycle” driven by the hyperscale cloud providers. Companies such as Microsoft, Amazon and Google routinely hand out hefty compute credits to early-stage AI startups. Sounds generous, right? But here’s the catch: those credits often mask the true cost of running GPU-hungry workloads. Startups ramp up their experiments on borrowed capacity, only to hit a brick wall once the freebies vanish or the actual costs come home to roost. Meanwhile, cloud providers get to boast about inflated usage metrics during that honeymoon period, which in turn attracts more investment and justifies further promotional outlays. The end result? A self-perpetuating loop: free credits fuel over-enthusiastic usage figures, which draw in investors, but ultimately lead to dashed expectations when the subsidies disappear.

• 🎯 For founders and investors alike, the lesson is to focus on sustainable, cost-effective pilots instead of chasing inflated usage stats. Have a proper look at your data pipelines, pinpoint a high-value, low-risk use case—perhaps automating a mundane customer-service task—and assemble a lean team to tackle integration and compliance from day one. By recognising the limitations of cloudy credit incentives and addressing the practical hurdles head-on, you’ll be far better placed to climb out of this “trough of disillusionment” and seize AI’s genuine potential.

💸 New Funds looking to give you cash

Look out for the The Raise Report this Wednesday, bring you all the new funds that have raised capital and looking to deploy.

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Master the Art and Science of Fundraising

Unlock the inner workings of capital raising with proven insights from those who've raised millions. Gain real-world strategies that transform ideas into funded ventures.

Day One Tue, 3 Jun 9:00 AM PST

• ​Live looper performance

• ​Vision & kickoff with Kurt, Derek & Henrik

• ​Raise perspectives: Family office, VC, CVC & PE

• ​Capital stack & round sequencing

• ​VC terms & cap-table workshop

  

​Day Two Wed, 4 Jun 9:00 AM PST

• ​Live artist performance

• ​Non-dilutive & sponsored capital

• ​Community wild-card panel

• ​GTM strategies that secured funding

• ​Fused & Funded evening networking

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Day Three – Thu, 5 Jun 9:30 AM PST (IRL @ VentureHaus, Las Vegas)

• ​9:30 AM Arrival, coffee & open networking

• ​10:00 AM Fireside Feature – $3K → $5K Scaling Pathways with Phil Peredo

• ​12:00 PM Networking lunch – small tables with Channel Champs & investors

• ​1:00 PM Workshop – Money Mindset Mastery with Shane Scott (Shark Tank coach)

• ​2:00 PM Founder pitch sessions – live & virtual investors, moderated

• ​3:30 PM Round-robin 1-on-1s – founders rotate through 2-3 strategic meetings; investor breakouts

• ​5:00 PM Closing toast & call-to-action – Fusion42 Accelerator + Fusion42 Fast invites, photo ops, final networking

Register Here!

💡Innovator Spotlight

Why It Feels Like the VHS vs. Betamax of AI Agents

I’ve been watching the AI world recently, and it really feels like the VHS-Betamax era all over again—only now it’s agent protocols being bandied about instead of videotape formats. If you’re a founder, framer or funder, it’s worth knowing which side of history you’re on before the standards begin to solidify. Here are the three main protocols making waves in 2025:

1. Model Context Protocol (MCP)

I see MCP everywhere right now, especially in single-agent setups that need direct tool access and richer context. Think of it as the bridge between an AI model and any external data source or function—it’s why you can have an AI assistant that not only talks back but also fetches real-time KPIs from your databases. Big players like Microsoft (Azure AI Foundry, Copilot Studio) and GitHub are backing MCP, and there’s an open ecosystem actively strengthening its security and authorisation layers. For startups building specialised AI helpers—say, a fundraising coach that pulls live investor metrics—MCP is probably your go-to.

2. Agent2Agent Protocol (A2A)

Announced by Google in April 2025, A2A is built for when you need several agents doing different things but all working in concert. Picture a lead-gen agent passing qualified contacts to a customer-onboarding bot, which in turn updates your CRM—without you manually orchestrating the handoff. Over 50 major tech firms (Salesforce, Accenture, and the like) have already joined the consortium. If you’re designing a multi-layered AI workflow—perhaps one agent handling market research, another crafting pitch decks, and a third managing outreach—A2A will be critical for ensuring they communicate seamlessly.

3. Agent Communication Protocol (ACP)

IBM’s open-source answer to agent chatter, ACP lets agents communicate directly—peer to peer—whether synchronously or asynchronously. It’s RESTful at its core, so any developer worth their salt can have two agents talking in minutes. The beauty of ACP is its community-led governance (Linux Foundation, DeepLearning.AI), which makes it relatively easy to plug in new agents or swap out existing ones without a complete rebuild. If your roadmap involves scaling up to dozens of specialised agents—each acting autonomously but still needing to share insights—ACP offers the flexibility you’ll need.

Why It Matters
Just as VHS won out over Betamax not necessarily because it was superior but because of ecosystem support, these agent protocols are competing on adoption, security, and ease of integration. As a founder, I’m keeping a close eye on which protocol my chosen platforms support—because once the market consolidates, it’ll be hard to switch horses midstream. If you’re investing in AI tools or building your own agents, pick a protocol that aligns with your long-term architecture and the partners you intend to work with. In short: know your MCP from your A2A before one of them becomes the de facto standard.

🛠️ Tools of the Week

The latest release from DeepSeek is the DeepSeek-R1-0528 model, unveiled on May 28, 2025. This update is an enhancement of their R1 reasoning model and brings significant improvements in reasoning depth, mathematical skills, and code generation capabilities.

Notable benchmark gains include:

• AIME 2025 accuracy increased from 70.0 to 87.5

• GPQA score improved from 71.5 to 81.0

• LCB_v6 (LiveCodeBench) rose from 63.5 to 73.3

• Aider benchmark jumped from 57.0 to 71.6

The upgrade also features reduced hallucination rates, enhanced support for function calling (including improved JSON output), and better performance in front-end web development, resulting in more aesthetically pleasing generated web pages and games. The model now consumes more tokens for complex reasoning tasks, reflecting its deeper analytical processes.

This release positions DeepSeek-R1-0528 just below the top-performing models like OpenAI’s o3 mini and Google’s Gemini 2.5 Pro on code generation and reasoning leaderboards, while outperforming several other notable models. The update was made available on Hugging Face and through DeepSeek’s API, though the company has not yet issued a formal public announcement.

There is also high anticipation for DeepSeek’s next-generation R2 model, but as of June 2, 2025, the most recent official release is DeepSeek-R1-0528

Key points:

• The model weights are open and free to access and use for most purposes.

• The source code is under the MIT license, but the model itself is under the DeepSeek license, which is not fully open source due to some use-based restrictions.

• The model is widely considered open and free for general research and development, but users should review the license for any specific limitations

Hugging Face Model Page
https://huggingface.co/deepseek-ai/DeepSeek-R1-0528

GitHub Organization
https://github.com/deepseek-ai
(Includes repositories for DeepSeek-R1, DeepSeek-V3, and other models)

Official Website
https://www.deepseek.com/en
(Offers web/app access to DeepSeek-V3 and R1 models, along with API information)

📌 Note to Self

Share Fusion42 by DeReK WaTSoN

Thank you for reading. If you liked it, share it with your friends, colleagues and everyone interested in the startup Investor ecosystem.

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Derek