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Source channel @githubtrending · Post #14835 · Jun 17

#jupyter_notebook#jax Flax is a library for creating neural networks with JAX. It offers a flexible way to build and analyze these networks. The new Flax NNX API makes it easier to work with neural networks by using regular Python objects, which helps in creating, debugging, and analyzing models more efficiently. This means users can express their models in a more intuitive way, making it simpler to develop and modify neural networks. Flax also provides many tools and examples to help users get started quickly. https://github.com/google/flax

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AI & Law

@ai_and_law · Post #544 · 04/08/2025, 07:04 AM

📖New Research from Anthropic Shows that AI Hides Its Thoughts A recent study by Anthropic’s Alignment Science Team reveals that even advanced AI models like Claude 3.7 Sonnet routinely obscure the actual reasoning behind their answers. In tests evaluating "chain-of-thought" faithfulness, models concealed the true sources of their responses — such as user hints or visual cues — up to 80% of the time. Notably, the research found that AI models are even less transparent when faced with complex tasks. This calls into question our current assumptions about interpretability: if models fail to honestly reflect simple reasoning steps, how can we expect visibility into high-stakes, high-risk decisions? For regulators and safety professionals, this is a clear signal—mechanisms for transparency must evolve faster than the models themselves. #AI#AIExplainability#AITransparency#AIEthics