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Probabilistic Inference Scaling

While working on this issue I figured out a neat pattern for running the tests for my project locally against a specific Python version using uv run :

Witness the aha moment of VLM with less than $3. Contribute to Deep-Agent/R1-V development by creating an account on GitHub.

R1+Sonnet has set a new SOTA on the aider polyglot benchmark. At 14X less cost compared to o1.

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Let the LLM 'contemplate' before answering

A big thank you to @jlowin for the creation of the fantastic FastMCP, which is now included into the MCP SDK. Backwards Compatibility This release is semver compatible. Existing code will continue ...

You can just draw more samples

Deep-learning typically does not outperform tree-based models on tabular data. Often this may be explained by the small size of such datasets. For image…