Tech

Cerebras to Release Wafer Scale Engine Chip to Help AI Machines

To address the demand for advanced AI machines, top-caliber computer systems company, Cerebras revealed the biggest computer chip in the world so far.

Dubbed as the Wafer Scale Engine, this chip has 400,000 interconnected cores that are capable of accomplishing complex digital tasks in no time.

According to Cerebras chairman Andrew Feldman, with the superb processing speed of this huge chip, it can efficiently handle any AI tasks such as speech recognition, fingerprint decoding, translation, robotics, and the like. Feldman said that this revolutionized computer chip is a result of their sacrifices and hard labor for years. He stressed that their primary goal in creating the Wafer Scale Engine is to help people save time. In fact, he shared that a month-long task would be accomplished in just a few minutes using this chip.

When asked on the cost of this powerful chip, Cerebras has yet to provide a definite answer. However, it admitted that it already shipped this ‘giant’ computer chip to some exclusive clients.

Why ‘Giant’ Chip is Beneficial in the Digital Age

Computers do process signals and feed using the binary language. In other words, before you can get an output from the input that you feed into the system of the computer, it must be translated first. Now, if you want a quicker translation and response from your computer, you must install processors or chips with higher processing capacity or speed. For AI machines, no doubt that they need higher specs to run. You cannot just input complicated instructions or features to AI-run devices, and yet you are using a dual-core CPU. The recent production from Cerebras will surely help AI machines to operate seamlessly and without any glitch at all. Before the release of this gigantic chip, the most powerful GPU got 5,000 total of cores. But with the development of this chip, we are talking none less than 400,000 cores doing the job of translating signals and digital commands at the same time.

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