Some fun examples, I just gave basic prompts and the AI executed:
Balatro, but for coin flipping (all the design and ideas was Fable): https://
play-flipside.netlify.app
The best self-aware snake game: https://
snake-stable-build.netlify.app An isochronic map using real data: https://
isochronic-passage-chart.netlify.app/#syd
@emollick
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AI creates coin-flipping Balatro, self-aware snake, isochronic map
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Fable’s jump in capability: works 9+ hours on 15-page design
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I've had access to Fable for a bit. A genuine jump in capability, I could feed it a 15 page design document for a project and it would work for 9+ hours and deliver terrific results. But working with it is weird & weirder is coming Lots of examples:
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NYT roundtable on AI’s future and workplace winners
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The New York Times published a roundtable discussion between @DAcemogluMIT
, @deanwball
, @clarashih & myself about the future of AI & who wins at work. I think it is a really nice overview of the core debates on the topic, and has some fun examples. -
Anthropic and OpenAI suggest coordinated global slowdown of AI development
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Both Anthropic and OpenAI mention the possibilities of slowing AI development in their latest "what comes next" in AI posts, but say they need to be an action coordinated across the entire world using as-yet-unidentified methods.
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Humans as dice: LLMs lack human variation
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The Matrix idea of keeping humans as batteries is obviously weird… we would be more useful as dice. LLMs default to very similar kinds of arguments & structure, and even different LLMs seem to collapse to similar concepts. Humans provide a lot more variation in their own work.
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Apple’s Siri AI: Local model limited without cloud capabilities
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Last time around Apple released a lot of information about how their AI version of Siri worked between local and cloud models, not so much this time It is nice to have a Gemma-like model on device, but it is extremely limited unless it can call a smarter cloud model when needed.
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AI writing quality issues in software menus
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One reason you want AIs to be better writers is that there is a lot of writing even in software, and it is incredibly painful to hit a menu which is filled with Claudisms or ChatGPTish phrases. A report is not "what leaves the room" & analyses are not "every number makes a mark"
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Gemini Pro models lag behind Claude and GPT in iteration speed
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The Gemini Pro models do not seem to be iterating anywhere near as quickly as Claude or GPT (last release was 3.1 Pro in February). Its causing a growing performance gap between Google and the other two labs, and the Gemini 3.5 Flash model, good as it is, doesn't close it much.
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Anthropic chart on Agent Teams, Workflows, and AI decisions
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This chart from Anthropic is useful, since Agent Teams and Workflows are both very new and very powerful (and token hungry). On the other hand, maybe it doesn't matter as a lot of the decisions about which approach to use is from the AI itself & it often uses them in combination
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Chinese labs might stop open weights as costs rise
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Also, a lot depends on Chinese labs continuing to ship open weights models. If they stop, the frontier falls further and further behind to those who want to use local/fine-tuned models. I think this is possible because open weights may not be a good business model as costs rise.