This week in AI had the strange texture of a market that is simultaneously becoming more scientific, more productized, and more speculative. The headlines looked disconnected at first: Anthropic published a fascinating interpretability paper, OpenAI released new voice models, SubQ made a controversial 12 million-token context claim, DeepSeek and Moonshot attracted enormous valuation attention, and Sierra raised at a level that would have sounded absurd for an AI customer service company only a few years ago. But underneath all of it is the same story: AI is moving from a model race into an infrastructure race. Anthropic's Natural Language Autoencoders paper was the most intellectually interesting development of the week. The idea is almost poetic: take the hidden activations inside a neural network and compress them into natural language, then try to reconstruct those activations from the explanation itself. In other words, language becomes a microscope for the model's internal...
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