
Professor @Wharton studying AI. New book, Co-Existence, is out now: https://xitter.twitterapi.xyz/t.co/hsDYf1xU9K My Substack: https://xitter.twitterapi.xyz/t.co/UIBhxu4bgq
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Another weird AI game project: I gave Claude Fable 5.2 a vague paragraph asking for a fantasy transport sim with heart. Then I left it to a bunch of agents arguing about art, lore and jokes. Now here is Dread & District, where good logistics defeats evil. dread-and-district.netlify.a…
One of the most significant things about Gemini 4 Carbon is that it is showing that Google is back in the race of frontier models, rapid releases and rapid improvement.
Had early access to Gemini 4 Carbon, it is a very good model that improves on Argon. It is useful to have an AI that thinks differently than Claude/GPT & is still highly capable, but has its own strengths & weakness
One fun demo: I gave Carbon a video clip & it reproduced in 3js
Looks like Fable 5.2 is above the already steep trendline on three of the most informative unsaturated benchmarks (ECI is a composite of other benchmarks, Remote Labor measures the ability to do end-to-end freelance jobs, RoboDojo involves controlling robotics).
In my post, I talk about how the agents involved began to build a bureaucracy over time, which eventually slowed development to a crawl. An example of jaggedness at scale: oneusefulthing.org/p/fable-5…
In one of my favorite experiments, I told Fable 5.2 to build an endless, hands-off journey through 3D worlds linked by portals.
25,000 agents created over 450 worlds inspired by books, art, places, all in code.
Play: portals-endless-worlds.netli…
Github: github.com/emollick/ai-porta…
In addition to more serious examples I shared in my post, I had Fable 5.2 build a parody reverse Scooby Doo game where you have to scare away meddling kids. Here is the trailer it made (including the music and sounds) and the game (which is fun) is here: i-would-have-gotten-away-wit…
A favorite optimistic view of the future of AI is from a pessimistic book that not about AI: "Rise and Fall of American Growth," which argues that we had a one-time explosion in living standards from 1870 and 1920 (& later outside the US).
In 1870: no toilets, no city plumbing, lamp light, no central heating, little public health, horses for local travel, etc. In 50 years, all of this was solved & the nation was electrified. In the next fifty modern medicine, air travel and telecommunication happened.
The book then points out that we have had no changes in lifestyle of similar scale since the 1970s. Written in 2016, it argued that we would likely never experience another boom like the "Special Century." The positive view of AI should make us ask "But what if we do?" and "How do we make it all go right?"
Nice DeepSWE score! Does it survive a lowercase filename?
Introducing MaxxBench: 89 DeepSWE tasks with small changes to the instructions or starting code. Same engineering problem, slightly different requirement.
Models clustered around 74% on DeepSWE end up 23 pp apart.
Good at coding, or good at DeepSWE? 🧵
I think there is way too much concern expressed about verification of AI output in everyday work due to a risk of factual errors.
It used to be true, but data on more recent models suggest they beat human experts, including PhD specialists, in finding facts and checking claims.














