A Berkeley PhD candidate claims his team recreated core functions of DeepSeek's R1-Zero AI model for a mere $30, using a smaller language model trained with reinforcement learning. This breakthrough, dubbed 'TinyZero,' challenges the prevailing paradigm of expensive, data-center-heavy AI development and sparks debate about the accessibility and future of AI research.
Jiayi Pan, a PhD candidate at the University of California, Berkeley, claims that he and his AI research team have recreated core functions of DeepSeek's R1-Zero for just $30 — a comically more limited budget than DeepSeek, whichTake it with a grain of salt until other experts weigh in and test it for themselves.
Pan's crew is currently working to produce a paper, but their model, preciously dubbed "TinyZero," is available onon pie-in-the-sky artificial general intelligence ventures led by the likes of Meta, Google, OpenAI, and Microsoft, sending stocks associated with American AI into aAnd if reproducing a model like TinyZero can be done with less than $30 and only a few days of work, then what do big tech conglomerates needOpenAI Hit With Wave of Mockery for Crying That Someone Stole Its...
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