Can confirm

Whoa!!! That’s awesome!!!!!

GPT-5.4 Pro just solved Erdős Problem #1196, a 60-year-old conjecture from Erdős, Sárközy, and Szemerédi on primitive sets. One shot. ~80 minutes of reasoning. What makes this different from other AI math results (from what I understand): The world's top expert on this problem, Jared Lichtman (who proved the original Erdős Primitive Set Conjecture during his PhD), worked on #1196 for 7 years alongside Fields Medal-level collaborators; this was not attention-starved. The AI rejected the standard approach every mathematician had used since Erdős' 1935 paper, a switch from analysis to probability, and instead stayed purely analytic using von Mangoldt weights. Human aesthetic convention had made that path invisible. Lichtman's analogy: like AI discovering a new chess opening that grandmasters overlooked because of convention. Terry Tao suspects the trick could simplify the broader theory of prime factorization anatomy, not just solve one conjecture. Lichtman calls it possibly the first AI "Book proof" for an Erdős problem. GPT-5.4 pro is the math goat.

I wrote this early this morning and I wasn't sure if I would actually publish it, but here it is: blog.samaltman.com/2279512

So true. Many non-technical people I know have tried AI (usually ChatGPT) 1 - 1.5 years ago, it didn't went really well, and since then they dismiss it (with the occasional not-so-important query about something). And the true power of the current crop of models is unleashed in certain domains only.

Working on a new project and for one day I did more than normally possible for 3 weeks. Using agents for coding literally feels like unlocking God mode.

GPT-5.4 at the moment is No1 for agentic coding. By far.

it is insane what i am now capable doing with a computer

🚨 CRITICAL: Active supply chain attack on axios -- one of npm's most depended-on packages. The latest axios@1.14.1 now pulls in plain-crypto-js@4.2.1, a package that did not exist before today. This is a live compromise. This is textbook supply chain installer malware. axios has 100M weekly downloads. Every npm install pulling the latest version is potentially compromised right now. Socket AI analysis confirms this is malware. plain-crypto-js is an obfuscated dropper/loader that: • Deobfuscates embedded payloads and operational strings at runtime • Dynamically loads fs, os, and execSync to evade static analysis • Executes decoded shell commands • Stages and copies payload files into OS temp and Windows ProgramData directories • Deletes and renames artifacts post-execution to destroy forensic evidence If you use axios, pin your version immediately and audit your lockfiles. Do not upgrade.

Three weeks ago there were rumors that one of the labs had completed its largest ever successful training run, and that the model that emerged from it performed far above both internal expectations and what people assumed the scaling laws would predict. At the time these were only rumors, and no lab was attached to them. But in light of what we now know about Mythos, they look more credible, and the lab was probably Anthropic. Around the same time there were also rumors that one of the frontier labs had made an architectural breakthrough. If you are in enough group chats, you hear claims like this constantly, and most turn out to be nothing. But if Anthropic found that training above a certain scale, or in a certain way at that scale, produces capabilities that sit far above the prior trendline, then that is an architectural breakthrough. I think the leaked blog post was real, but still a draft. Mythos and Capybara were both candidate names for the new tier, though Mythos may now have enough mindshare that they end up keeping it. The specific rumor in early March was that the run produced a model roughly twice as performant as expected. That remains unconfirmed. What is confirmed is that Anthropic told Fortune the new model is a 'step change,' a sudden 2x would certainly fit the definition. We will find out in April how much of this is true. My own view is that the broad shape of this is correct even if some of the numbers are wrong. And if it is substantially accurate, then it also casts OpenAI's recent restructuring in a new light. If very large training runs are about to become essential to staying in the game, then a lot of their recent decisions, like dropping Sora, make even more sense strategically. For the public, this would mean the best models in the world are about to become much more expensive to serve, and therefore much more expensive to use. That will put pressure on rate limits, pricing, and subscription plans that are already subsidized to some unknown degree. Instead of becoming too cheap to meter, frontier intelligence may be about to become too expensive for most of humanity to afford. Second-order effects; compute, memory, and energy are about to become much more important than they already are. In the blog they describe the new model as not just an improvement, but having 'dramatically higher scores' than Opus 4.6 in coding and reasoning, and as being 'far ahead' of any other current models. If this is the new reality, then scale is about to become king in a whole new way. It would also mean, as usual, that Jensen wins again.

Mythos is a new tier, bigger than Opus, and more capable. It will be beyond the current state of the art by a wide margin, a dramatic jump in intelligence. Things have been accelerating under the surface since December. Capabilities are increasing faster, the time between model releases is getting shorter. I think OpenAI's recent decisions and refocus have been driven by the fact that it is increasingly obvious to some people working in the industry that we are beginning to take off. I think there have been multiple unannounced breakthroughs over the last few months, in more than one lab. I think there have been advances in capabilities, in alignment, and in architecture. The loop that started in December has begun to bear fruit. This model will be huge, very expensive to serve, and incredibly powerful. It has already finished training, and is in early rollout to some enterprise partners so they can prepare for what's about to arrive. Once we get benchmarks I think it will become clearer where we are; we are already inside the singularity.

"AI is not doing end-to-end science yet. But this project proves that I could create a set of prompts that can get Claude to do frontier science. This wasn’t true three months ago." anthropic.com/research/vibe-…

this is easily the best thing you’ll read this year. you’ll never have to to hear the words skill issue or code mogged ever again. bookmark it. re read it. tell your agents to read it. enjoy generational wealth. wave bye bye permanent underclass.

Interesting observation: In KuorumAI we built a notes system via MCP with clear instructions to actively update a short-term scratchpad on every conversation. Both Claude 4.6 and GPT-5.4 fail to follow it reliably. The only model that does it consistently is @grok 4.2 beta.

“If it can’t be exposed through a CLI or MCP server, you’re at a disadvantage.”

“A company might spend $10K a year for QuickBooks and $120K on an accountant to close the books.” sequoiacap.com/article/servi… via @sequoia

i’ll be honest, with all this anthropic chatter that >their models are conscious >they have the recipe for super intelligence this year >the models know they’re being tested and can game benchmarks. imma little concerned…

Working with GPT-5.4 in the API? We’ve updated our prompting guide with patterns for reliable agents covering tool use, structured outputs, verification loops, and long-running workflows. developers.openai.com/api/do…

Not only are there no walls, but AI capabilities are advancing exponentially! GPT-5.4 is another step change in this progress! Any cynics left will be forced to realize this the hard way soon!

Dario at MS TMT Conference today: On defense / DOW:"We really believe in defending America." Anthropic has been working with the national security community for 2 years. "We are the most lean forward." On AI acceleration:"We do not see hitting a wall. This year will have a radical acceleration that surprises everyone." Exponentials catch people off guard. "We are at the precipice of something incredible. We need to manage it the right way." On where markets are wrong:"It's already big and it will get 1 million times bigger." The underestimation of exponential growth is the key thing people need to understand. On revenue scale:Anthropic was at ~$100M run rate 2 years ago. Now at $19B run rate. On culture — Dario says he spends 40% of his time on it:"Anyone who is CEO of a growing firm needs to realize they are chief culture officer. My job is to make sure everyone is on same page and believes in what we are doing. That's the most important thing." He does a vision quest with the whole company every couple weeks. "I want them to hear it directly from me. If I tell the CTO, who tells the VP Eng, who tells the manager — that's too long of a game of telephone." "Politics and infighting are a cancer to companies as they grow." On talent retention vs Meta:"We lost 2 people to Meta. They lost several dozen. Normalized by size, they lost 10-20x more people vs us." Attributes this to unified culture generating "super linear returns — by working together vs working against each other." On code as the breakout use case:Code has "exceeded our high expectations." Why? Devs adopt fast, code is verifiable, and gains compound — you build software to build software. "Didn't realize it would go so fast even at traditional enterprises." Frustration is around regulated industries where legal/compliance slow things down. "That's how fast everything could be going if not for non-AI barriers." On Anthropic's own AI usage:Top internal use cases: 1) writing code, 2) the process around writing code (SWE), 3) managing servers and controlling clusters. "If we were paying ourselves for our usage, we'd be one of our largest customers." On Claude Code:"You can supervise an army of 100 Claudes. It's closely analogous to a management skill." The people who are best at it keep the big picture in their head. Higher return to finding people who can handle more complex tasks. On platform vs apps:"We are primarily a platform, but there are places where we have expertise to make something directly useful." Claude Code emerged as a tool they built for themselves — thousands of internal users before shipping it externally. "Code is a prelude for what we will see in everything else." On societal implications:"Human history — lots of muddling through. We found ourselves in this comedy of errors and figured it out eventually. It's happening so fast that we need to do better than that this time." The market will deliver positive benefits — "I see that as priced in." What's not priced in: the choices we make around externalities. Jobs, national security, ensuring the benefits reach everyone. On chips & compute:Anthropic uses multiple chip suppliers. "We find that actually using different chips is useful to us. Chips aren't just a speed number — we gain benefits from heterogeneity." Also standard business logic of having more than one supplier.