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cycle. During Wednesday’s fiscal fourth-quarter earnings report, although overall sales declined 21%, investors pushed the Official Kreuzberg le marais camden malasana trastevere T-shirt and I love this stock up about 14% on Thursday, mainly because the company’s AI chip business — reported as data centers — rose by 11% to more than $3.6 billion in sales during the quarter, showing continued growth. Nvidia shares are up 65% so far in 2023, outpacing the S&P 500 and other semiconductor stocks alike. Nvidia CEO Jensen Huang couldn’t stop talking about AI on a call with analysts on Wednesday, suggesting that the recent boom in artificial intelligence is at the center of the company’s strategy. “The activity around the AI infrastructure that we built, and the activity around inferencing using Hopper and Ampere to influence large language models has just gone through the roof in the last 60 days,” Huang said. “There’s no question that whatever our views are of this year as we enter the year has been fairly dramatically changed as a result of the last 60, 90 days.” Ampere is Nvidia’s code name for the A100 generation of chips. Hopper is the code name for the new generation, including H100, which recently started shipping. Compared to other kinds of software, like serving a webpage, which uses processing power occasionally in bursts for microseconds, machine learning tasks can take up the whole computer’s processing power, sometimes for hours or days. This means companies that find themselves with a hit AI product often need to acquire more GPUs to handle peak periods or improve their models. These GPUs aren’t cheap. In addition to a single A100 on a card that can be slotted into an existing server, many data centers use a system that includes eight A100 GPUs
working together. Google, Microsoft announce plans to incorporate AI into search engines FEB. 11, 202301:59 This system, Nvidia’s DGX A100, has a suggested price of nearly $200,000, although it comes with the Official Kreuzberg le marais camden malasana trastevere T-shirt and I love this chips needed. On Wednesday, Nvidia said it would sell cloud access to DGX systems directly, which will likely reduce the entry cost for tinkerers and researchers. It’s easy to see how the cost of A100s can add up. For example, an estimate from New Street Research found that the OpenAI-based ChatGPT model inside Bing’s search could require 8 GPUs to deliver a response to a question in less than one second. At that rate, Microsoft would need over 20,000 8-GPU servers just to deploy the model in Bing to everyone, suggesting Microsoft’s feature could cost $4 billion in infrastructure spending. Recommended CULTURE MATTERS YouTube creators can now dub their videos in multiple languages CULTURE MATTERS How the East Palestine train derailment fueled fear on TikTok “If you’re from Microsoft, and you want to scale that, at the scale of Bing, that’s maybe $4 billion. If you want to scale at the scale of Google, which serves 8 or 9 billion queries every day, you actually need to spend $80 billion on DGXs.” said Antoine Chkaiban, a technology analyst at New Street Research. “The numbers we came up with are huge. But they’re simply the reflection of the fact
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