A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.
To feed the endless appetite of generative artificial intelligence (gen AI) for data, researchers have in recent years increasingly tried to create "synthetic" data, which is similar to the ...
LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.
A new partnership between metaverse startup VLGE and data firm Protege leverages natural human behavioral data from virtual ...
Internal reports have emerged that learning data workers hired to make AI (artificial intelligence) smarter are using AI ...
Google’s Search history update stores media uploads from your interactions, like images used in reverse image searches, for ...
The next generation of AI models are meant to be trained by people paid to have conversations with them, but several of these ...
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After a model’s initial training on a large corpus of mostly Internet-derived data, Anthropic follows a post-training process intended to nudge the final model toward being “helpful, honest, and ...