3 years, 8 months ago

Need to Fit Billions of Transistors on a Chip? Let AI Do It

Artificial intelligence is now helping to design computer chips—including the very ones needed to run the most powerful AI code. At Nvidia, principal research scientist Haoxing “Mark” Ren is testing how an AI concept known as reinforcement learning can help arrange components on a chip and how to wire them together. “You can design chips more efficiently.” Haoxing “Mark” Ren, principal research scientist, Nvidia The AI tools Ren is testing explore different chip designs in simulation, training a large artificial neural network to recognize which decisions ultimately produce a high-performing chip. “Also, it gives you the opportunity to explore more design space, which means you can make better chips.” Nvidia started out making graphics cards for gamers but quickly saw the potential of the same chips for running powerful machine-learning algorithms, and it is now a leading maker of high-end AI chips. In the more distant future, he says, “you will probably see a major part of the chips that are designed with AI.” Reinforcement learning was used most famously to train computers to play complex games, including the board game Go, with superhuman skill, without any explicit instruction regarding a game’s rules or principles of good play.

Wired
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Nvidia's AI-Based Chip Design Could Help In Better Placement Of Transistors, Reduce Cost
2 years ago

Nvidia's AI-Based Chip Design Could Help In Better Placement Of Transistors, Reduce Cost

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Nvidia shows new research on using AI to improve chip designs
2 years ago

Nvidia shows new research on using AI to improve chip designs

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5 years, 7 months ago

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