Kevin Minott retweeted
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.
Judging by my tl there is a growing gap in understanding of AI capability.
The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code.
But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along.
So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions.
TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
Kevin Minott retweeted
AI is a big W for 40-somethings. Old enough to have learned how to do things the right way, young enough to learn some new tricks.
😭 @ChatGPT down - Unexpected status 401 unauthorized: Incorrect API key provided
Kevin Minott retweeted
Jev gave me $5 of API credit when i signed up
when i die, i will pass what's left of it to my son
Kevin Minott retweeted
DuckTales premiered 39 years ago today.
I loved that show. Not for the gold. For the idea that adventure meant going somewhere wild with people you love.
It was Indiana Jones for kids.
Nobody's making the movie, so I made the trailer. Sound on. 🦆
🤖 Made with AI
Kevin Minott retweeted
After working on multiple games with this woman, I truly WISH you guys could see her casting audition videos compared to her competition. It's like watching 1996 Michael Jordan turn up to a high school basketball game.
Kevin Minott retweeted
Today, we’re releasing Kalypta, the first app to block AI notetakers in your meetings.
Granola? Wisprflow? Cluely? No more.
With Kalypta, you become inaudible to AI.
Your call continues normally.
Kevin Minott retweeted
Build with GPT-6 Astra. Launch on Product Hunt on September 18.
We've teamed up with @OpenAIDevs for the GPT-6 Astra Challenge. The top five launches each win $10K in OpenAI API credits and a year of ChatGPT Pro for up to two team members.
If you’re already building with Astra, this is a chance to share what you’ve made and put it in front of a wider audience. You can schedule your launch for Friday, September 18.
Kevin Minott retweeted
I fed GPT-6 Astra 9 crappy photos of my studio and it was able to understand the spatial arrangement, stitch them together and create a fully interactive 3D model of the space.
Absurd. I'll link it below so you can check it out for yourself:
Kevin Minott retweeted
🇨🇺 There is a town in the middle of Cuba where the older people speak English, play cricket and dance around a maypole.
Jamaicans went to Cuba in their thousands from the early 1900s. They cut cane on American owned estates and worked at Guantanamo Bay. Many never came home. They settled in the sugar towns of the east and the centre. One of them is Baragua. It still has a quarter everybody calls the Jamaican Quarter. 🏘️
What they built there was more than housing. They put up lodges, churches and schools. They taught their children in English. Barbadians, Grenadians, Antiguans, Vincentians and Nevisians settled alongside them. The quarter is West Indian rather than only Jamaican.
About five thousand descendants remain. Almost none of the first generation are left. But young men still play cricket in a country that plays baseball, and the maypole still goes up. That is what a community does when it decides not to disappear. 🇯🇲
Do you have relatives who went somewhere and never came back?
Kevin Minott retweeted
Once you start working on water rendering, you are cursed with never seeing the world the same.
I was at a resort with the fam this weekend and noticed this little stream out back.
I couldn't have asked for a better reference for understanding water/foam transport in flowing water!
Super helpful as I work on the rivers add-on for Water Pro.
Luckily my wife is very understanding of my insanity and patiently waited while I captured video of the entire thing 😂
Kevin Minott retweeted
The Tupac murder trial. Very niche post.
Tupac's murder trial is going on. There were rumors for years that Orlando Anderson (Pac beat him up hours before the shooting, but he's now dead) did it along with his uncle Keffe D.
Well last year we had Ben Horowitz on. He's a Pac fan and was involved in Vegas (he lives there, Pac was killed there). So, he told us a story on how he organized a dinner with the Las Vegas PD.
At the end of dinner he told the police chief he ought to reopen the case. Next day the answer came back: if Ben wants the case opened, we're opening the case. They reopened it.
Also, years ago we had on Harry O aka Michael Harris. Michael was in prison (drug charges) but his sentence was commuted. Michael was the co-founder of Death Row records along with Suge Knight. Michael was the funder (did it while in prison).
Michael said of Pac that he was prolific, had all those albums before age 25, and that everyone who worked with him described a professional.
But also on Pac: "you have to guard the people that surround you as as much as you guard the food that you digest."
So if you're one of the few people in the center of the venn diagram that's interested in MFM and Pac's case, look up the episode with Michael Harris and Ben. They're very interesting.
























