Democratizing LLMs needs a revolution in AI hardware

There’s growing concern that artificial intelligence—namely deep learning—is becoming centralized within a few very wealthy companies. This shift does not apply to all areas of AI, but it is certainly the case for large language models, deep learning systems composed of billions of parameters and trained on terabytes of text data.

Accordingly, there has been growing interest in democratizing LLMs and making them available to a broader audience. However, while there have been impressive initiatives in open-sourcing models, the hardware barriers of large language models have gone mostly unaddressed.

This is one of the problems that Cerebras, a startup that specializes in AI hardware, aims to solve with its Wafer Scale processor. In an interview with TechTalks, Cerebras CEO Andrew Feldman discussed the hardware challenges of LLMs and his company’s vision to reduce the costs and complexity of training and running large neural networks.

Read the interview on TechTalks.

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