An AI research team from the University of California, Berkeley, led by Ph.D. candidate Jiayi Pan, claims to have reproduced DeepSeek R1-Zero’s core technologies for just $30, showing how advanced models could be implemented affordably. According to Jiayi Pan on Nitter, their team reproduced DeepSeek R1-Zero in the Countdown game, and the small language model, with its 3 billion parameters, developed self-verification and search abilities through reinforcement learning.
Pan says they started with a base language model, prompt, and a ground-truth reward. From there, the team ran reinforcement learning based on the Countdown game. This game is based on a British game show of the same name, where, in one segment, players are tasked to find a random target number from a group of other numbers assigned to them using basic arithmetic.
