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Someone should create a benchmark.
Giving models with different reasoning levels a task.
And instead of measuring success rate. We measure how much total tokens for the model to finish the task.
And each time the task isn't finished or successfully solved. The model will be prompted again with the error it made letting it continue.
This way we'll figure which reasoning effort actually costs the least.
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I'm going to build my first open source project.
Called Open Token.
It would be a better version of AI token analytics than any other you can find.
Just getting started, would be active building it. Right now is just a useless demo, so I don't recommend forking it now.
https://t.co/Y5KqiexZa6
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I'm going to build my first open source project.
Called Open Token.
It would be a better version of AI token analytics than any other you can find.
Just getting started, would be active building it. Right now is just a useless demo, so I don't recommend forking it now.
https://t.co/Y5KqiexZa6
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Replx is now live 🔥
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@AnthropicAI as a non us citizen, I'm really scared about whether I can keep building things in the future with models that is actually good
us government is bullying foreign by restricting that is created by a company but not the government