2023年5月5日

公司合作提供了一个替代Nvidia Corp .)、占据市场AI-capable芯片称为图形处理单元,人们说,他不愿透露姓名,因为是私人的问题。微软支持AMD的扩张到人工智能芯片微软(Microsoft corp .)和高级微设备公司工作芯片制造商的扩张到人工智能处理器,根据知情人士的情况下,多管齐下的策略来获得更多的令人垂涎的组件。公司合作提供了一个替代Nvidia Corp .)、占据市场AI-capable芯片称为图形处理单元,人们说,他不愿透露姓名,因为是私人的问题。这个软件巨头提供支持支持AMD的努力,和使用国产的芯片制造商微软处理器对于人工智能工作负载,代号为雅典娜。AMD股价周四跳涨逾6.5%,而微软上涨约1%。这两家公司的代表拒绝置评。Nvidia的股票下跌了1.9%。这种安排的一部分急于增加人工智能处理能力,这是需求量很大的爆炸后聊天机器人就像ChatGPT基于技术和其他服务。微软是一个顶级的云计算服务提供商和人工授精技术的驱动力。公司注入100亿美元ChatGPT OpenAI制造商,并发誓要将这些特性添加到它的整个软件产品线。 The move also reflects Microsoft’s deepening involvement in the chip industry. The company has been building up a silicon division over the past several years under former Intel Corp. executive Rani Borkar, and the group now has a staff of almost 1,000 employees. The Information last month reported on Microsoft’s development of the Athena artificial-intelligence chip. Related stories Several hundred of those employees are working on the Athena project, and Microsoft has spent about $2 billion on its chip efforts, according to one of the people. But the undertaking doesn’t portend a split with Nvidia. Microsoft intends to keep working closely with that company, whose chips are the workhorses for training and running AI systems. It’s also trying to find ways to get more Nvidia’s processors, underscoring the urgent shortage Microsoft and others are facing. Microsoft’s relationship with OpenAI — and its own slate of newly introduced AI services — are requiring computing power at a level beyond what the company expected when it ordered chips and set up data centers. OpenAI’s ChatGPT service has drawn interest from businesses that want to use it as part of their own products or corporate applications, and Microsoft has introduced a chat-based version of Bing and new AI-enhanced Office tools. It’s also updating older products like GitHub’s code-generating tool. All of those AI programs run in Microsoft’s Azure cloud and require the pricey and powerful processors Nvidia provides. The area is also a key priority for AMD. “We are very excited about our opportunity in AI — this is our No. 1 strategic priority,” Chief Executive Officer Lisa Su said during the chipmaker’s earnings call Tuesday. “We are in the very early stages of the AI computing era, and the rate of adoption and growth is faster than any other technology in recent history.” Su also said that AMD has an opportunity to make partly customized chips for its biggest customers to use in their AI data centers. Borkar’s team at Microsoft, which has also worked on chips for servers and Surface computers, is now prioritizing the Athena project. It’s developing a graphics processing unit that can be used for training and running AI models. The product is already being tested internally and could be more widely available as soon as next year, said one of the people. Even if the project makes that timeline, a first version is just a starting point, the people said. It takes years to build a good chip, and Nvidia has a substantial head start. Nvidia is the chip supplier of choice for many providers of tools for generative AI, including Amazon.com Inc.’s AWS and Google cloud, and Elon Musk has secured thousands of its processors for his fledgling AI business, according to reports. Creating an alternative to Nvidia’s lineup will be a challenging task. That company offers a package of software and hardware that works together — including chips, a programming language, networking equipment and servers — letting customers rapidly upgrade their capabilities. That’s one of the reasons Nvidia has become so dominant. But Microsoft isn’t alone in trying to develop in-house AI processors. Cloud rival Amazon acquired Annapurna Labs in 2016 and has developed two different AI processors. Alphabet Inc.’s Google also has a training chip of its own.