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In an essay a year ago by me and @sayashk, we observed that more capable models don't necessarily mean more useful products, and that real-world usefulness will require training on user data. In retrospect, I'm surprised Anthropic held out for this long. https://t.co/Bd8ySxgHvF https://t.co/8ThNMyVlKQ
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"ext_alt_text": "For example, Google says “we use publicly available information to help train Google’s AI models”. Elsewhere it says that it may use private data such as emails to provide services, maintain and improve services, personalize services, and develop new services. One approach that is consistent with these disclosures is that only public data is used for pre-training of models like Gemini, but private data is used to fine-tune those models to create, say, an email auto-response bot. Anthropic is the one exception we know of. It says: “We do not train our generative models on user-submitted data unless a user gives us explicit permission to do so. To date we have not used any customer or user-submitted data to train our generative models.” This commitment to privacy is admirable, though we predict that it will put the company at a disadvantage if it more fully embraces building products.\n\n",
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