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Democratizing LLMs Needs a Revolution in AI Hardware


Integrated circuit.

Credit: 123RF

Andrew Feldman is CEO of Cerebras, a startup that specializes in AI hardware.

There is growing concern that artificial intelligence (AI)—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 (LLMs). 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 LLMs have gone mostly unaddressed.

In an interview, Feldman discusses the hardware challenges of LLMs and his company's vision to reduce the costs and complexity of training and running large neural networks. "The way you get more democracy with the technology, the way you get more users, the way you get it out of a very narrow group of super-large technology companies is to drive down the costs and make it simpler to use," Feldman said.

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