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Technology Stocks : Meta Platforms, Inc. (Facebook) -- Ignore unavailable to you. Want to Upgrade?

To: Doren who wrote (3710)	5/6/2023 5:53:03 PM
From: Doren	1 Recommendation Recommended By Glenn Petersen Respond to of 3790

Inside Meta's scramble to catch up on AI This is pretty interesting to me. It looks like UltraGeek Zuck finally realized that VR wasn't going to be the killer app HIS DEMOGRAPHIC thought it would be NINE MONTHS AGO. I have a friend from college, same demographic, who's really into VR creation... the ONLY person I know. His stuff is pretty crude but interesting. I was into 3D software in college, really good at it. Glad I didn't get into the business because it looks to me, ironically, that AI will make 3D/VR much much easier. Thousands of jobs at effects houses gone... poof! So combined with their surprise profit, Instagram looking up and Zuck's admission and plunge into AI Meta is looking interesting again. Profit despite, what looks like a considerable increase in AI CapEx. Its very encouraging that Zuck could swallow his pride, capitulate and press forward big time. It also seems to mean fired the right people and he's now listening to people who knew better. The recruiting fight for AI talent must be red hot. Partial copy/paste: ============== A key source of the trouble, those five sources said, can be traced back to Meta's belated embrace of the graphics processing unit, or GPU, for AI work. GPU chips are uniquely well-suited to artificial intelligence processing because they can perform large numbers of tasks simultaneously, reducing the time needed to churn through billions of pieces of data. However, GPUs are also more expensive than other chips, with chipmaker Nvidia Corp (NVDA.O) controlling 80% of the market and maintaining a commanding lead on accompanying software, the sources said. Nvidia did not respond to a request for comment for this story. Instead, until last year, Meta largely ran AI workloads using the company's fleet of commodity central processing units (CPUs), the workhorse chip of the computing world, which has filled data centers for decades but performs AI work poorly. According to two of those sources, the company also started using its own custom chip it had designed in-house for inference, an AI process in which algorithms trained on huge amounts of data make judgments and generate responses to prompts. By 2021, that two-pronged approach proved slower and less efficient than one built around GPUs, which were also more flexible in running different types of models than Meta's chip, the two people said. Meta declined comment on its AI chip's performance. As Zuckerberg pivoted the company toward the metaverse - a set of digital worlds enabled by augmented and virtual reality - its capacity crunch was slowing its ability to deploy AI to respond to threats, like the rise of social media rival TikTok and Apple-led ad privacy changes, said four of the sources. The stumbles caught the attention of former Meta board member Peter Thiel, who resigned in early 2022, without explanation. At a board meeting before he left, Thiel told Zuckerberg and his executives they were complacent about Meta's core social media business while focusing too much on the metaverse, which he said left the company vulnerable to the challenge from TikTok, according to two sources familiar with the exchange. Meta declined to comment on the conversation. CATCH-UPAfter pulling the plug on a large-scale rollout of Meta's own custom inference chip, which was planned for 2022, executives instead reversed course and placed orders that year for billions of dollars worth of Nvidia GPUs, one source said. Meta declined to comment on the order. By then, Meta was already several steps behind peers like Google, which had begun deploying its own custom-built version of GPUs, called the TPU, in 2015. Executives also that spring set about reorganizing Meta's AI units, naming two new heads of engineering in the process, including Janardhan, the author of the September memo. More than a dozen executives left Meta during the months-long upheaval, according to their LinkedIn profiles and a source familiar with the departures, a near-wholesale change of AI infrastructure leadership. Meta next started retooling its data centers to accommodate the incoming GPUs, which draw more power and produce more heat than CPUs, and which must be clustered closely together with specialized networking between them.