Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.

Resharing this and urging everyone to read it for several reasons. 1. Everything Cindy writes is fantastic and serious engineering discourse 2. The examples here are concrete and clear and most importantly production services with real world consequences

We’re publishing another update to OpenAI Problem #130#: computing the exact discrete Fourier transform below n log n. Our paper now incorporates the all-length bound: T(n) = O(n(log n)^(1−δ)), with δ = 0.0007547360. That’s 10.34 times the exponent saving of δ = 7.3×10⁻⁵ in our previous announcement. The stronger Fourier result comes from Jacob Sussman’s five-stage framework and Chafik Boukhalfa’s improved construction, building on @OpenAI, @0xdoug, @RohanArun, @SJ_Swapnil_Jain and the wider community.

Amazon banning agents is the first opportunity I've seen since Amazon was founded for a startup to create an Amazon competitor. People will want agents to buy stuff for them. It will be one of the main use cases. And they won't want to use some Amazon-supplied agent to do it.

literal hardest role to hire for rn and every ai startup wants someone. - chronically online but can still make eye contact with ppl irl - knows current trends and can do frontier shitpoasting - abg or abg vibes spiritually - has good taste, high aura and high motion - technical and understands ai (can RL post-train 1T param models, rawdogs flash attention 4 in 15 minutes) - can shill for our company's product non stop in interesting ways - good with people and conducting events - available sf/nyc onsite

i feel like swe interviews could probably collapse into just 2 technical rounds: • system design (how well can you articulate your ideas, do you actually know how to engineer something) • onsite project to build a real thing with agents (can you translate your intent into high quality outcomes) everything else we used to ask is no longer necessary

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