descriptionLong TextJev doesn’t write essays or code. Why everyone is talking about it?!
I got early access to TypeSafe’s new System One Model, explored the playground, and tested it alongside Codex.
Behind Jev is Diogo Almeida, an InstructGPT coauthor whose work helped make ChatGPT possible. Now he’s betting on AI built for software to use.
Is it a breakthrough or just a classifier? We explain RLCD, look at Vercel and OpenCode examples, and discuss what Jev might mean for the future.
The question: can better small decisions help AI finish bigger jobs?
Watch the demo, then decide: useful classifier, bigger shift, or both?
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Attention Span is here to show you AI isn’t magic. This time, we look at what happens when a model gives up conversation and focuses on decisions.
Links
Introducing Jev and System One Models: https://typesafe.ai/blog/introducing-system-one-models-and-jev
TypeSafe console: https://console.typesafe.ai/home
System One documentation: https://docs.typesafe.ai/concepts/system-one
RLCD and calibrated decisions: https://docs.typesafe.ai/introduction/machine-learning-primer
TypeSafe agent skill: https://docs.typesafe.ai/agent-skill
InstructGPT paper: https://arxiv.org/abs/2203.02155
Neural-network calibration research: https://arxiv.org/abs/1706.04599
Earlier zero-shot text classification research: https://arxiv.org/abs/1909.00161
Guillermo Rauch on Vercel’s Jev test: https://x.com/rauchg/status/2100307962262872105
Dax’s Jev + OpenCode browser-use preview: https://x.com/thdxr/status/2100288951978164647
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