"This is a closed-source only capability, but we wanted to bring this capability to the most popular ecosystem, which is Llama," said James Wang, head of Cerebras's product marketing effort, in an interview with ZDNET.
"Essentially, we're now beating Llama 3.1 405B, a model that's some seven times larger, just by thinking more at inference time," said Wang.
Chain of thought can enable models using less training time, data, and computing power, to equal or surpass a large model's performance.
The idea behind chain-of-thought processing is for the AI model to detail the sequence of calculations performed in pursuit of the final answer, to achieve "explainable" AI.
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