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The April 2026 issue of State of AI from Air Street Press. The through-line: frontier AI moved from benchmark progress to operational capability across cyber, coding, agents, and capital formation.Two frontier models cleared the UK AI Security Institute's 32-step end-to-end cyber-attack range in a single month, and AISI now estimates frontier cyber-offence is doubling every four months, down from seven months at the end of last year. We unpack what that means for the public cybersecurity stack.Microsoft and OpenAI reset their 2019 deal to non-exclusive while keeping Microsoft as primary cloud partner. Anthropic stacked another $40B from Google, $5B from Amazon (with $100B of AWS spend), and chip deals with Google and Broadcom reportedly worth hundreds of billions, and is reportedly already raising again at a $900B valuation. Sam Altman's Axios essay sketched a "superintelligence New Deal" in explicit FDR terms.Four Chinese labs (Z.ai, MiniMax, Moonshot, DeepSeek) released open-weights coding models inside a 12-day window, all landing at roughly the same capability ceiling as Claude Opus 4.6 and GPT-5.4 on agentic engineering. NIST's CAISI evaluation puts the aggregate gap closer to eight months. Both are true.Anthropic's Project Deal ran a classified marketplace of 69 Claude agents and reported that stronger agents won, and the losers did not realise it. KellyBench (from Air Street portfolio company General Reasoning) watched every frontier model lose money on a Premier League betting season under non-stationarity. Ramp's procurement agents run 3× faster.Plus eight research papers worth keeping (π0.7, the Ríos-García epistemology paper, ClawBench, the FAIR experience-replay paper, Agent-World, and others), April Investments (Ineffable Intelligence's $1.1B seed, Saronic, Cognition's $25B talks, Cursor's $50B+ talks), and Exits (Skild and Zebra, SpaceX and Cursor, OpenAI and Hiro, Cohere and Aleph Alpha, China blocking Meta's acquisition of Manus).

Profluent just announced a multi-program strategic partnership with Eli Lilly to develop AI-designed recombinases for genetic medicine — worth up to $2.25 billion in milestones, plus tiered royalties on net sales.In this episode, Nathan unpacks why this deal matters far beyond the headline number. CRISPR taught us how to fix typos in the genome. The harder problem — and arguably the larger one — is editing at the kilobase scale: replacing whole paragraphs of DNA at a chosen genomic address. That's the route to therapies for the long tail of genetic disease driven by patient-level mutational heterogeneity, from cystic fibrosis to inherited hearing loss to retinal dystrophy.Recombinases have always been the right class of enzyme for this job. They've also been stuck for decades because their targeting specificity is encoded directly in the protein structure, with no equivalent of CRISPR's modular guide RNA. That makes recombinases a near-perfect problem for foundation-model protein design — and it's exactly the bet Profluent has been building toward since their 2024 work designing novel Cas enzymes from scratch.We cover: why kilobase-scale editing is the next frontier of genetic medicine; why recombinases were intractable until AI; how Profluent's foundation-model platform changes the picture; why Lilly is the right partner; and what the world looks like if you can name a genomic address and get a designed editor back.

Episode DescriptionWelcome back to the State of AI! In this packed Q1 2026 episode, we dive into a quarter defined by unprecedented geopolitical friction, staggering capital concentration, and the rapidly blurring lines between commercial cloud infrastructure and national defense.From a constitutional showdown between Anthropic and the Trump administration to the first-ever kinetic military strike on commercial data centers, the stakes for frontier AI have never been higher. Plus, we break down Anthropic’s explosive $19B ARR sprint, the escalating "distillation wars" with Chinese AI labs, and the historic $1.25 trillion merger between xAI and SpaceX.If you want to understand where the frontier is heading next, you can't miss this one.The Pentagon Standoff: Anthropic's $200M DOD contract, its refusal to drop safety guardrails, and the ensuing White House blacklist and federal lawsuit.Cloud as a Theater of War: Breaking down the unprecedented Iranian drone strikes on AWS data centers in the Middle East.Revenues Go Vertical: How Anthropic surged to a $19B ARR on the back of Claude Cowork, and OpenAI's massive $50B strategic alliance with Amazon.The Model Treadmill: The rapid succession of new model releases, including Claude Sonnet 4.6, Gemini 3.1 Pro, and GPT-5.4.The Distillation Wars: Inside the industrial-scale IP theft by Chinese labs cloning Claude, and the $2.5B NVIDIA GPU smuggling bust.Safety Meets Reality: Sabotage risks, machine-speed SQL injections, and the UK AI Safety Institute's chilling findings on AI-assisted cyber attacks.The Physical Layer & NIMBYism: The pushback against hyper-scale data centers and NVIDIA's complete exit from the China-compliant chip market.Breakthrough Research: From zero-loss cache compression (TurboQuant) to an Australian entrepreneur curing his dog's cancer with AlphaFold.Historic Mega-Deals: OpenAI's record-shattering $110B raise and xAI's trillion-dollar merger into SpaceX.00:00 - Intro, Air Street Capital Epoch 3, & RAAIS 202601:28 - Geopolitics: Anthropic vs. The White House03:12 - The Iran-AWS Conflict & Cloud Warfare04:12 - Financials: Anthropic's $19B ARR & OpenAI's Hyperscaler Strategy08:04 - The Model Treadmill: Claude Sonnet 4.6, Gemini 3.1 Pro, & GPT-5.408:56 - Open Source, IP Warfare, & the $2.5B Smuggling Ring10:44 - AI Safety: Catastrophic Sabotage & The Sabotage Risk Report13:20 - Data Center NIMBYism & The Contested Physical Layer16:00 - Research Highlights: UK AISI, TurboQuant, & World Action Models22:40 - Investments & Exits: OpenAI's $110B Round & The SpaceX/xAI MergerStay Connected:Love hearing what you’re up to! Hit reply to our newsletter or connect with us at the upcoming Air Street AI meetups in SF (April 28) and NYC (May 14). We are also actively recruiting Research Analysts for the State of AI Report—reach out if you live and breathe this space.Produced by the State of AI & Air Street Press.In This Episode, We Cover:Episode Timestamps (Estimated):

Raia Hadsell is VP of Research at Google DeepMind, co-leading the Frontier AI unit. Her work spans Siamese nets and elastic weight consolidation to Gemini 2.5, RoboCat, and a UK AI Ambassador role. A RAAIS 2026 speaker profile from Air Street Press.

Roberta Raileanu leads open-ended learning at Google DeepMind and co-authored Toolformer. From RIDE and AMIGo to Llama 3's tool use and MLGym, her research tackles what it takes for AI agents to keep acquiring skills. A RAAIS 2026 speaker profile from Air Street Press.

Starcloud launched the first NVIDIA H100 GPU in space and trained the first LLM in orbit. CEO Philip Johnston explains why AI's energy bottleneck leads to orbital data centres — with 10x lower energy costs and 5 gigawatts of solar-powered compute on the roadmap. A RAAIS 2026 speaker profile from Air Street Press.

Air Street Capital has raised a third fund of $232M to back AI-first companies from the earliest stages. In this post, founder Nathan Benaich shares the conviction behind the firm - from his first investments in 2013 through to a portfolio that now includes Synthesia, Black Forest Labs, Wayve, Profluent, and poolside - and explains what Fund III enables for the most ambitious AI founders in Europe and North America.Read more: https://press.airstreet.com/p/fund-iii

Sereact's Cortex 2.0 marks a shift in robotics from reactive control to predictive planning. In this episode, we examine how Sereact’s world-model architecture generates and scores imagined futures before acting, improving success rates and eliminating human intervention across complex warehouse tasks. We break down the benchmark results, the planning budget trade-off, and what it means to deploy world models in real industrial environments rather than simulation.

European voters say they support higher defense spending. But when higher taxes or welfare cuts are mentioned, support collapses.In this episode from Munich Security Conference 2026, we explore Europe’s fiscal test: Germany’s industrial flywheel, the reality of attrition warfare in Ukraine, the broken procurement model, and the tension between welfare and warfare.Europe has demonstrated urgency. Now it must prove permanence.

In this episode of the State of AI, we break down the growing disconnect between rapid AI capability gains and collapsing software valuations, with nearly $300B wiped from public markets in weeks. We cover the agent shock triggered by Anthropic and OpenAI’s latest releases, why investors are repricing long-term SaaS revenues, and how AI sovereignty is fracturing across U.S. policy, state-level infrastructure pushback, and China’s accelerating model and talent pipeline. We also look at the security risks of computer-use agents, the infrastructure arms race spanning GPUs, memory, power, and data centers, and the latest research breakthroughs in autonomy, medicine, and reinforcement learning. Plus, a full rundown of the month’s largest AI financings, IPOs, and acquisitions.

AI has progressed fastest where the world can be cleanly digitized, but robotics remains stubbornly hard. In this episode, we examine Sereact’s Cortex 1.6 and what its results reveal about learning from execution rather than sparse task outcomes. We discuss why execution-level learning improves robustness, recovery behavior, and learning efficiency in real-world robotic manipulation, and what this signals for the future of deployment-first robotics.

In this episode, Air Street Capital shares its 2025 year in review. We cover what changed as AI moved into large-scale deployment, from the emergence of reasoning models and agents in production to the economics of frontier AI, energy constraints, and geopolitics.We reflect on the year across our investment portfolio, angel investments, Air Street Press, the State of AI Report, and our global community, and look ahead to what it will take to deploy AI reliably and at scale in the years to come.

Europe sharply increased defense spending in 2025. But money alone does not produce weapons, stockpiles, or readiness.In this episode, we examine why Europe’s defense build-up is running into industrial limits as it enters 2026. From procurement bottlenecks and factory capacity to Germany’s surge in orders and the slow pace of production, the challenge is no longer political will - it is execution.This is a conversation about defense as an industrial system, and why turning budgets into battlefield capability is proving harder than expected.Read more on press.airstreet.com

As 2025 came to a close, conversations about AI swung between excitement and anxiety. Markets debated bubbles, capital cycles, and constraints, while researchers quietly shipped systems that worked.In this audio essay, Nathan Benaich takes stock of what AI actually delivered in 2025 — drawing on recent writing by Tim Dettmers, Dan Fu, and Andrej Karpathy, alongside conversations with Sebastian Borgeaud at Google DeepMind.Rather than speculating about distant futures, this episode focuses on what changed in practice: why AI crossed a usability threshold, how constraints reshaped progress rather than stopping it, and why the shift from models to systems matters more than any single benchmark.The result is a grounded look at AI progress as it enters 2026 — not as hype or prediction, but as an evolving system that continues to compound.Read the full essay at press.airstreet.com

Delfa is an AI-first clinical trials software company. In this episode, we explore how Delfa’s AI-first Participant Relationship Management system transforms clinical trial operations, speeds recruitment, and helps bring medicines to patients faster.

New AI research systems are beginning to contribute verifiable results across mathematics, physics, biology, and materials science. How close are we to AI producing genuinely new scientific knowledge?

A deep dive into world models, VLAMs, planning layers and real deployments from robotics companies Sereact and Wayve - and what comes next for embodied AI.

Today, I’m excited to unveil Air Street’s investment in Black Forest Labs as it announces a landmark funding milestone: a $300M Series B, following a previously unannounced Series A. Together, these rounds represent a big step in scaling the company’s momentum, with Black Forest Labs now capitalised with half a billion dollars and trusted by leading Fortune 500 enterprises.

Welcome to the latest issue of the State of AI, an editorialized newsletter that covers the key developments in AI policy, research, industry, and start-ups over the last month.

Building the first AI-native wealth institution for the mass affluent. Air Street Capital is investing in Clove’s $14M first financing round, backing a new kind of wealth institution built for this generation rather than the last. Clove’s founders, Christian Owens and Alex Loizou, see this gap not as an inevitability but as a result of infrastructure that was never built for the modern consumer. With Clove, they are creating a new kind of financial institution, one designed from the ground up for people who want trustworthy guidance but have been priced out or ignored by traditional services. Their platform brings together regulated human advisors with an AI-first environment that handles the repetitive and compliance heavy processes which dominate advisory work today. By removing friction and expanding advisor capacity, Clove can deliver high quality personalised guidance at a scale that has not been possible before.

Profluent builds frontier AI systems to unlock programmable biology. Now, Profluent has raised $106M led by Bezos Expeditions and Altimeter, with continued support from Spark, Insight, and Air Street. The company is now the largest position in Air Street’s second fund. This new capital accelerates the company’s path toward scaling frontier protein models and, ultimately, delivering the first AI-designed therapeutic to a human patient.

Understanding how protein sequence encodes structure and function remains one of the central challenges in the life sciences. Yet most protein language models still treat each sequence as an isolated datapoint. This forces the entire burden of evolutionary context into model parameters, which leads to blind spots in underrepresented families and amplifies the biases of sequence databases. Profluent’s new E1 family demonstrates that this constraint is no longer necessary. Retrieval augmentation, a technique that transformed natural language processing, is now beginning to reshape protein modeling by allowing models to incorporate evolutionary information at the moment of inference rather than storing it all in weights.

Poolside is building one of the strongest full-stack AI companies in the world: energy, compute, models, and the infrastructure needed to run multi-agent systems for complex enterprise workflows. The Fern team brings a deeply opinionated agentic core - built from first principles and stress-tested on real workloads - into a company with scale, distribution, and compute firepower. Fern’s architecture was built for agent specialization and coordinated long-horizon work - the exact capabilities poolside can scale into a full production environment.

Welcome to the latest issue of the State of AI, an editorialized newsletter formerly known as Guide to AI that covers the key developments in AI policy, research, industry, and start-ups over the last month. First up, a few reminders:Read more on press.airstreet.com

PARIMA, a global leader in cultivated proteins, has become the first European company to secure regulatory approval for cultivated meat, with the Singapore Food Agency granting clearance for its cultivated chicken. It’s a historic moment for Europe’s food-tech sector, but one that’s unfolding thousands of miles away from home.

Building a next-generation food company.

Integrating across compute, power, and intelligence.

The State of AI Report is the most widely read and trusted analysis of key developments in AI. Published annually since 2018, the open-access report aims to spark informed conversation about the state of AI and what it means for the future. Produced by AI investor Nathan Benaich and Air Street Capital. State of AI Report 2025 is reviewed by leading AI practioners in industry and research.

AI is the ultimate force multiplier on technological progress in our digital, data-driven world. Our mission at Air Street Capital has always been to back the most ambitious teams building breakthrough AI products that would have seemed like magic when I started investing over a decade ago. Key to these inflection points is the infrastructure that enables them: NVIDIA computing systems. I have long argued that NVIDIA is the defining company of the AI era, powering breakthroughs in science, industry, and national strategy. This is why I’m excited to share that we are deepening that story together: Air Street Capital is partnering with NVIDIA as part of its new £2B commitment to the UK AI ecosystem.

Clinical trials are the bottleneck of the pharmaceutical industry. They’re slow, expensive, and often fail, not only because the science frequently doesn’t pan out, but because the ops don’t either. That’s why we’re leading the $3.8M Seed round for Delfa. The team is building an AI-native operating system for clinical trials, starting with patient enrolment, the most broken part of the process.

We’re excited to announce Air Street Capital’s lead investment in Studio Atelico’s $5M Seed round, alongside friends including Chris Ré (Stanford), Thomas Wolf (Hugging Face), and Alex Ratner (Snorkel), to back a team on a mission to redefine the role of generative AI in games.

Welcome to the latest issue of your guide to AI, an editorialized newsletter covering the key developments in AI policy, research, industry, and start-ups over the last month.

Gene editing has the potential to solve fundamental challenges in agriculture, biotechnology and human health. CRISPR-based gene editors derived from microorganisms, although powerful, often show notable functional tradeoffs when ported into non-native environments, such as human cells1. Artificial-intelligence-enabled design provides a powerful alternative with the potential to bypass evolutionary constraints and generate editors with optimal properties. Here, using large language models2 trained on biological diversity at scale, we demonstrate successful precision editing of the human genome with a programmable gene editor designed with artificial intelligence. To achieve this goal, we curated a dataset of more than 1 million CRISPR operons through systematic mining of 26 terabases of assembled genomes and metagenomes. We demonstrate the capacity of our models by generating 4.8× the number of protein clusters across CRISPR–Cas families found in nature and tailoring single-guide RNA sequences for Cas9-like effector proteins. Several of the generated gene editors show comparable or improved activity and specificity relative to SpCas9, the prototypical gene editing effector, while being 400 mutations away in sequence. Finally, we demonstrate that an artificial-intelligence-generated gene editor, denoted as OpenCRISPR-1, exhibits compatibility with base editing. We release OpenCRISPR-1 to facilitate broad, ethical use across research and commercial applications.

No one is coming to save Europe. We must build new primes here and now.

At this year’s RAAIS, Max Jaderberg of Isomorphic Labs delivered a talk that felt like the spiritual sequel to AlphaGo, only this time the board isn’t 19×19, it’s the human body. The stakes? The future of drug discovery and human health.Isomorphic Labs, the biotech spinout from DeepMind, has declared a radical mission: solving disease. It's not a metaphor. It’s a systems-level wager that the same kinds of models that cracked Go can crack biology. Not only by digitizing wet labs, but by encoding the dynamics of biomolecules into machine-learnable substrates. If AlphaGo marked the start of AI systems inventing strategies never before seen in human play, Isomorphic wants AI to invent medicines we’d never stumble across in the lab.This is a moonshot, a bet that biology is information science, and machine learning is our best bet at learning its language.

At this year’s RAAIS, I joined Adam Satariano of the New York Times and Dimitrios Kottas, founder of Delian Alliance Industries and formerly Apple's Special Projects Group, for a candid conversation about one of the most taboo, yet increasingly urgent topics in tech: AI and defense.The timing couldn’t be more acute. The war in Ukraine has shown how low-cost drones and software can upend conventional military doctrine. More recently, the escalation of hostilities with Iran has further underscored the volatility of global security and the growing relevance of digital warfare and drone-enabled asymmetric tactics. In the U.S., a second Trump administration has accelerated European defense policy, with Germany, Poland, France, and others pushing military spending to levels unseen since the Cold War. The European Commission plans to deploy €800 billion toward defense by 2029.So: where does that money go? For once, not just to the legacy primes. There’s an opening for new entrants, namely startups building fast, iterating with operational focus, and pushing beyond the traditional defense hardware playbook.

At RAAIS 2025, Andreas Blattmann, co-founder of Black Forest Labs, shared a deep dive into FLUX.1 Kontext, the startup’s newly released generative model for controllable image and video generation. The talk gave a rare look under the hood of one of the most technically ambitious and commercially relevant AI-first companies to emerge in Europe.Andreas is no stranger to the field. He was among the original researchers behind Stable Diffusion and later worked with Stability AI before striking out on his own to build the model he always wanted: a unified, fast, and open infrastructure for pixel generation, whether from text, images, or combinations of the two.

What you need to know in AI across geopolitics, big tech, hardware, research, models, datasets, financings and exits over the last 4 weeks. 

Two years ago, I met Mati Staniszewski in a time before AI voices were good enough to fool anyone. ElevenLabs hadn’t launched yet, but their vision was clear: voice was broken, and they were going to fix it.Today, ElevenLabs is one of the fastest-moving companies in the agentic voice space. Their platform powers narration for authors, dubbing for studios, real-time agents for enterprises, and everything in between. At the 9th Research and Applied AI Summit in London, Mati and I recounted the story of how they got here, and where they're going next, and lessons learned for any founder building in AI.

If 2016 was the year AI shocked the world by mastering Go, 2025 is shaping up to be the year they learn to innovate. This is the thesis of Ed Hughes, long-time researcher at Google DeepMind and one of the few voices charting a credible path toward AI systems capable of doing science.In his closing talk at RAAIS this year, Hughes argued that we’re entering a new phase in the evolution of artificial intelligence: one where open-endedness becomes the central organizing principle. Not just solving problems, but defining them. Not just predicting the next token, but surfacing previously unknown unknowns. If he’s right, the next generation of AI systems won’t just be tools, they’ll be participants in the scientific process itself.

At this year's RAAIS, we convened a panel with Lionel Laurent (Bloomberg), Chris Yiu (Meta), and Benedict Macon-Cooney (Tony Blair Institute) to dissect the uneasy relationship between AI and the state. This conversation, grounded in experience across Whitehall, Big Tech, and Brussels, pulled no punches on where things stand and what still needs to change.

When poolside co-founder and CTO Eiso Kant stepped on stage at RAAIS 2025, he didn’t deliver the kind of slick, pre-baked keynote you might expect from the co-founder of one of the most ambitious AI companies in the world. Instead, Kant opted for a more experimental approach: a candid walkthrough of poolside’s beliefs, software systems, and bets on how to build AGI. The result was one of the most revealing sessions of the summit.Kant’s message was clear: if you want to compete at the frontier of model capabilities, the secret isn’t just scale, it’s iteration speed. And to iterate fast, you need infrastructure that matches the ambition of your research. This is the thesis behind poolside’s “model factory,” a production-grade system for turning ideas into results at industrial speed.

Today, we release v4 of the You'll now find updated counts as of June 2025 for AI research papers using chips from NVIDIA, TPUs, Apple, Huawei, AMD, ASICs, FPGAs, and AI semi startups, as well as updates to A100 H100/200 cluster sizes. We also include new data on the most and least commonly used chips for specific research topic areas. State of AI Report Compute Index in collaboration with Zeta Alpha. 

Across the technology investing world, investors are scaling their bets on a seductive thesis: Generative AI will transform low-margin service businesses into high-margin software companies. Several well-known platform venture firms have committed billions to this strategy and have begun to make their bets. This essay is co-authored by Nathan Benaich and Nikola Mrksic, CEO of PolyAI.

At this year’s RAAIS, Paige Bailey of Google DeepMind delivered her talk on AI research to production with interactive demos and a clear thesis: “I’m going to show you how to automate significant parts of your work.” Generative models are now a co-author, a debugger, a lab assistant, a video editor. And increasingly, models are doing the work behind the curtain while you coach and edit. Here’s her talk and a narrative of the key insights:

A decade is a familiar yardstick for measuring progress. In that time, we tend to expect  steady, incremental change. Historically, meaningful change tends to unfold slowly. In AI, however, the last ten years has been a story of "gradually, then suddenly". The weekly model launches we are now accustomed to feel incremental in the heat of the moment, but a ten-year look back reveals a landscape transformed by something that feels closer to magic.At our 9th Research and Applied AI Summit (RAAIS), we brought together the people building the next decade. Researchers, founders, and policymakers who have gone from writing foundational papers to deploying infrastructure and policies at global scale. And if there’s one thing they agree on, it’s this: ten years in, we are still at the beginning.

On AI factories, sovereign AI and what this means for national AI strategies. This article originally appeared on Fortune.com and can be read here for free.

What you need to know in AI across geopolitics, big tech, hardware, research, models, datasets, financings and exits over the last 4 weeks. 

Our read of the UK's Ministry of Defence Strategic Defence Review 2025.

Bringing you the best of AI today and what’s coming tomorrow.