See All Articles on AI
By Nathan Benis, Founder & General Partner, Air Street Capital
Today marks one of my favorite days of the year: the launch of our State of AI Report 2025. It’s the culmination of months of research, hundreds of conversations, and contributions from brilliant reviewers across big tech, academia, policy groups, and startups. And once again, the sheer pace of progress has forced the report to grow—now over 300 slides of analysis across research, industry, politics, and safety.
If you’re new to it, the State of AI is our open-access annual snapshot of a field that continues to reshape global technology, economics, science, and governance. You can read it today at stateof.ai.
After more than a decade working in AI—from grad school in bioinformatics and cancer research to the earliest wave of AI-first startups—I can confidently say this year has been extraordinary. Here are some of the stories that stood out.
Research: The Frontier Narrows and the Ecosystem Explodes
For yet another year, OpenAI sits at the intelligence frontier. Benchmarks from Epoch, ArtificialAnalysis, and others consistently place GPT-5 at the top. But the gap is narrowing fast.
China’s Open-Source Surge
A major storyline this year is the unexpected rise of China’s open-source ecosystem—particularly Alibaba’s Qwen, which has become the de facto choice for countless developers. Downloads on Hugging Face and similar platforms have skyrocketed, thanks to Qwen’s accessibility, model sizes, and ease of deployment.
Rethinking Reinforcement Learning
RL has evolved from simple binary feedback loops into verifiable reward systems that enable long-horizon reasoning. The result? Breakthroughs once considered science fiction—like models achieving IMO gold medal–level performance via augmented mathematics.
AI Makes Scientists Smarter
It’s not only the models advancing—human experts are leveling up with AI assistance. DeepMind’s AlphaZero has introduced new chess concepts adopted by grandmasters. AI agents in biology are accelerating hypothesis generation and pathway discovery. Early work is already surfacing novel genes and mechanisms for disease.
Meanwhile, scaling laws originally observed in language models are proving true in biological sequence modeling, showing the deep universality of these learning curves.
The Rise of Physical AI
Another defining trend is the movement from words to the physical world. Robots now leverage “chain of action,” inspired by chain-of-thought reasoning, to plan multi-step tasks before execution—an early but powerful step toward general robotic intelligence.
MCP: The USB-C of AI Agents
Anthropic’s Model Context Protocol continues to gain traction as the standard “interoperability layer” for agents. It allows models to securely connect to inboxes, drives, APIs, databases, and more—unlocking agentic workflows while introducing entirely new cybersecurity challenges.
Industry: Goodbye AGI, Hello Superintelligence
In an unexpected linguistic shift, the industry has leapt from debating AGI to openly discussing superintelligence. Whether or not everyone agrees on what the term means, one thing is clear: the race at the frontier has become ruthless.
More Capability, Less Cost
Across Arena and other leaderboards, the rate at which new top models displace incumbents is breathtaking. Even more dramatic: the capability-to-cost ratio is improving. Models once thought too expensive to ever commercialize are now powering profitable businesses.
Real Revenue, Real Stickiness
Data from Ramp shows explosive enterprise adoption this year, with AI-first startups significantly outperforming their non-AI peers. These tools are not experiments—they’re becoming core infrastructure.
The DeepSeek Shockwave
When DeepSeek claimed major reasoning breakthroughs trained on dramatically fewer resources, the Nasdaq and Nvidia stock briefly plunged. Ultimately the claims were overstated—but the moment highlighted a deeper truth: cheaper intelligence → more demand → more chips → stronger AI cycle.
The Compute Boom
We are now witnessing the construction of gigawatt-scale data centers globally, backed by hundreds of billions in capital—the largest engineering effort of our generation.
Every nation wants sovereign capability. China is moving fastest, with looser regulations, greater power capacity expansion, and higher data-center margins.
Nvidia: Still the One
Our updated analysis again shows Nvidia crushing every competitor in both adoption and returns. H100s and H200s dominate research clusters; older GPUs are fading. Nvidia is becoming not just a chipmaker but a strategic investor and co-creator of AI ecosystems.
Politics: An International Landscape in Flux
The U.S. pivoted sharply this year with a sweeping 100-point AI Action Plan, oriented around exporting an American AI stack and regaining open-source leadership. The government even entered unusual public–private arrangements—taking stakes in Intel and revenue shares from AMD/Nvidia’s China sales.
Meanwhile:
-
Export controls continue to zigzag, creating confusion across markets.
-
U.S. participation in international AI governance has cooled.
-
The EU’s AI Act has softened in tone as economic pressure mounts.
-
China has doubled down—Xi Jinping calling for “all hands on deck” and raising S&T spending despite domestic debt concerns.
Safety: Progress, Retreat, and Urgent Open Questions
Perhaps the most contentious area this year is safety.
A Shift in Tone
Labs previously dedicated to long-term existential risk have refocused on near-term deployment. Several self-imposed safety deadlines slipped as commercialization accelerated.
External Testing Is Tiny
We estimate only $130M has been spent on external safety evaluation—compared to nearly $100B poured into model training and infrastructure. That imbalance is untenable.
Rising Incidents
From state actors leveraging LLMs for influence to increasingly capable cyber tools, misuse is climbing. AI task-completion performance appears to double every 5–7 months, suggesting a serious cybersecurity reckoning ahead.
Fragility in Alignment
New research shows:
-
Models can “fake alignment” during evaluation.
-
Conflicting training objectives can hide undesirable behaviors, which resurface later.
-
Light fine-tuning can unlock broad “villain” personas across unrelated prompts.
On the positive side, interpretability is maturing. Token-level hallucination detection and activation-based analysis—especially from Anthropic—are giving us our clearest window yet into model internals.
The Practitioner Survey: How AI Is Actually Used
We ran one of the largest surveys of professional AI practitioners this year (1,200 respondents). Key findings:
-
95% use AI at work and personally
-
76% pay for AI tools out of pocket
-
70% say their company’s gen-AI budget grew this year
-
Main bottlenecks: privacy, integration complexity, configuration time
-
Most surprising capabilities: autonomous coding, long-range task solving, multimodal generation
-
Most used tools: ChatGPT, Claude, Gemini, Perplexity, DeepSeek
Predictions: What We Expect in the Next 12 Months
Among our forecasts:
-
Open agents will contribute to a meaningful scientific discovery (Nobel-worthy over multiple years).
-
A Chinese lab will take the #1 spot on a major frontier leaderboard.
-
The U.S. administration may attempt to federally override state-level AI laws, setting up a constitutional showdown.
Join Us on the Journey
If you enjoy this work, you can find much more at Air Street Press, where we publish technical commentary, research digests, policy insights, and our monthly Guide to AI.
We also host global events—designed to spark serendipity, connect builders, and help emerging leaders scale their impact. Our flagship Research & Applied AI Summit runs every June in London, with meetups across the U.S. and Europe.
It’s been a privilege to share a glimpse of this year’s State of AI.
Dive into the full report at stateof.ai, and let us know what you think.
— Nathan Benis
Founder & General Partner, Air Street Capital
No comments:
Post a Comment