The New Yorker writes: In the race to accelerate A.I., the Silicon Valley company Cerebras has landed on an unusual strategy: go big.
Andrew Feldman, Cerebras’s co-founder, began his slide deck with a cover slide, then a team slide, catching Vishria’s attention: the talent was impressive. Then Feldman compared two kinds of computer chips. First, he looked at graphics-processing units, or G.P.U.s—chips designed for creating 3-D images. For a variety of reasons, today’s machine-learning systems depend on these graphics chips. Next, he looked at central processing units, or C.P.U.s—the general-purpose chips that do most of the work on a typical computer. “Slide 3 was something along the lines of, ‘G.P.U.s actually suck for deep learning—they just happen to be a hundred times better than C.P.U.s,’ ” Vishria recalled. “And, as soon as he said it, I was, like, facepalm. Of course! Of course!” Cerebras was proposing a new kind of chip—one built not for graphics but for A.I. specifically.
Cerebras’s approach is unique. Instead of making chips in the usual way—by printing dozens of them onto a large wafer of silicon, cutting them out of the wafer, and then wiring them to one another—the company has made one giant “wafer-scale” chip. A typical computer chip is the size of a fingernail. Cerebras’s is the size of a dinner plate. It is the largest computer chip in the world.
Read about this amazing chip and what it can do with real world problems in the article here.
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