trying to remember what it was like to code before codex
LLMS
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Confusion over GPT model naming conventions
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Though I will continue to insist that the path we were on would have been much clearer if o3 had been called GPT-5 and GPT-5 had been called GPT-5.5 and GPT-5.2 had been called GPT-6.
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Models progressing from basic math to solving hard problems
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Its funny how much the whole "strawberry" thing, which turned out to be o1-preview, was dismissed as overhyped at launch when it is clear in retrospect that it was way underhyped. A direct line from models unable to do basic math to solving unresolved math problems in 18 months.
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Model control enables labs to monopolize AI products
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And it is the model that makes it so it is the labs, as opposed to every other software vendor, can ultimately be the sole provider of products. Their post-training and their harnesses and their control over access means that they can build products that no one else can touch.
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Gemini 3.5 Flash Shows Major Progress and Competitiveness
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Gemini 3.5 Flash has made huge progress from 3.1 Pro on GDPval, Flash is competing at the frontier, post training going strong 🙂
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Models as the prime mover behind AI products
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I would push back a little: because the models are so good & improving, they don't have to be the product. But it is the model that is the prime mover. If they weren't so generally capable, the harnesses & apps the labs build around them would be hard to build and wouldn't work.
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Disappearance of instant, thinking, pro and effort levels
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You had instant, thinking, pro, etc and then each had the ability to specify their effort levels (4 levels) All of that is gone lol
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User angry at OpenAI for enforcing router model selection on paid subscription
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OpenAI, what the fuck is this? Give me back the ability to specify WHICH MODEL I am using + their effort levels EXPLICITLY I don't want this router crap you're enforcing on my $200 paid subscription I DID NOT AGREE TO THIS SHIT
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AI models can be persuaded to accept falsehoods study
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You can persuade #AI models to accept falsehoods as truth, study shows
by Ashique KhudaBukhsh @_TCglobal Learn more: https://
bit.ly/4dPA5ao #LLM #GenerativeAI #ArtificialIntelligence #MachineLearning -
AI Agents Memory Solutions: Offline Dreaming vs Embedding
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Hive: This project is supported by the @Evermind community, it's really great, highly recommended. CLI agent: Everyone is racing to develop their own memory solutions. Claude Code goes with offline "dreaming" batch processing, Hermes goes with on-site embedding, but they all