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NVIDIA surges 3X on AI, but no word on Altman’s ghar waapsi as Microsoft readies office with Macs

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Contenuto fornito da One Thing Today in Tech. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da One Thing Today in Tech o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

NVIDIA, which has a near monopoly on computer chips for AI applications, reported its fiscal third-quarter numbers yesterday that beat street expectations.

The semiconductor company’s Q3 revenues of $18.12 billion is a 206 percent year-on-year jump, reflecting the extent to which big tech companies are ramping up AI investments. Sales to the data centre segment, which accounted for 80 percent of the company’s Q3 revenues, was even more impressive, rising 279 percent.

Sales rose 34 percent sequentially over Q2, and data centre sales, 41 percent. NVIDIA expects this scorching growth to continue. Q4 revenues are expected to touch $20 billion, plus or minus 2 percent, representing a 231 percent increase year on year.

“Our strong growth reflects the broad industry platform transition from general-purpose to accelerated computing and generative AI,” Jensen Huang, founder and CEO of NVIDIA, said in the company’s Q3 earnings press release.

“Large language model startups, consumer internet companies and global cloud service providers were the first movers, and the next waves are starting to build,” Huang said.

Nations and regional communications services providers are investing in AI clouds to meet local demand, enterprise software companies are adding AI co-pilots and assistants to their platforms, and enterprises are creating custom AI to automate the world’s largest industries, he said.

“NVIDIA GPUs, CPUs, networking, AI foundry services and NVIDIA AI Enterprise software are all growth engines in full throttle. The era of generative AI is taking off,” he said.

Meanwhile, at the very company that made generative AI mainstream with its ChatGPT bot, we await the final word on whether Sam Altman will return to the company he co-founded, or make his rift with the it permanent.

Altman was abruptly fired from the company on Nov. 17 and two days later, Microsoft CEO Satya Nadella announced Altman was joining Microsoft to lead a new advanced AI research unit.

Microsoft, expecting to welcome any of the 770 OpenAI researchers who leave to join it, is said to be readying workspaces at its LinkedIn office, complete with Macbook laptops, Axios reported earlier today. About 95 percent of OpenAI staff have threatened to leave and follow Altman if the board of OpenAI doesn’t resign, making way for his return.

What’s happened “highlights the growing rift between the proponents of a more measured rollout of the technology, that emphasizes safety guardrails above commercialization and monetization of solutions. This could have deep-reaching implications for the market,” Beatriz Valle, Senior Technology Analyst at the UK based consultancy GlobalData, said in an email yesterday.

The events also shine a light on the legal structure of OpenAI, which was founded in 2015 as a non-profit company and adopted a new structure in 2019, following Microsoft’s involvement, Valle writes.

The company’s founding charter still allowed the four-person board to fire Altman.

OpenAI is controlled by its non-profit board, which has no fiduciary obligations towards stakeholders or investors, she points out.

“This was a very immature board with members who had never built companies, never moved from ideology to commercialization, nor had any pragmatic board experience,” Ray Wang, principal analyst at Constellation Research in San Francisco, writes in a blog post.

The board's big worries included ownership of training data, impact of untested models and detection of unwanted bias, Wang writes.

OpenAI's biggest challenge is making the economics work, and Altman’s move to accelerate commercialization was the right thing, he says.

  continue reading

474 episodi

Artwork
iconCondividi
 
Manage episode 385074084 series 3372928
Contenuto fornito da One Thing Today in Tech. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da One Thing Today in Tech o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

NVIDIA, which has a near monopoly on computer chips for AI applications, reported its fiscal third-quarter numbers yesterday that beat street expectations.

The semiconductor company’s Q3 revenues of $18.12 billion is a 206 percent year-on-year jump, reflecting the extent to which big tech companies are ramping up AI investments. Sales to the data centre segment, which accounted for 80 percent of the company’s Q3 revenues, was even more impressive, rising 279 percent.

Sales rose 34 percent sequentially over Q2, and data centre sales, 41 percent. NVIDIA expects this scorching growth to continue. Q4 revenues are expected to touch $20 billion, plus or minus 2 percent, representing a 231 percent increase year on year.

“Our strong growth reflects the broad industry platform transition from general-purpose to accelerated computing and generative AI,” Jensen Huang, founder and CEO of NVIDIA, said in the company’s Q3 earnings press release.

“Large language model startups, consumer internet companies and global cloud service providers were the first movers, and the next waves are starting to build,” Huang said.

Nations and regional communications services providers are investing in AI clouds to meet local demand, enterprise software companies are adding AI co-pilots and assistants to their platforms, and enterprises are creating custom AI to automate the world’s largest industries, he said.

“NVIDIA GPUs, CPUs, networking, AI foundry services and NVIDIA AI Enterprise software are all growth engines in full throttle. The era of generative AI is taking off,” he said.

Meanwhile, at the very company that made generative AI mainstream with its ChatGPT bot, we await the final word on whether Sam Altman will return to the company he co-founded, or make his rift with the it permanent.

Altman was abruptly fired from the company on Nov. 17 and two days later, Microsoft CEO Satya Nadella announced Altman was joining Microsoft to lead a new advanced AI research unit.

Microsoft, expecting to welcome any of the 770 OpenAI researchers who leave to join it, is said to be readying workspaces at its LinkedIn office, complete with Macbook laptops, Axios reported earlier today. About 95 percent of OpenAI staff have threatened to leave and follow Altman if the board of OpenAI doesn’t resign, making way for his return.

What’s happened “highlights the growing rift between the proponents of a more measured rollout of the technology, that emphasizes safety guardrails above commercialization and monetization of solutions. This could have deep-reaching implications for the market,” Beatriz Valle, Senior Technology Analyst at the UK based consultancy GlobalData, said in an email yesterday.

The events also shine a light on the legal structure of OpenAI, which was founded in 2015 as a non-profit company and adopted a new structure in 2019, following Microsoft’s involvement, Valle writes.

The company’s founding charter still allowed the four-person board to fire Altman.

OpenAI is controlled by its non-profit board, which has no fiduciary obligations towards stakeholders or investors, she points out.

“This was a very immature board with members who had never built companies, never moved from ideology to commercialization, nor had any pragmatic board experience,” Ray Wang, principal analyst at Constellation Research in San Francisco, writes in a blog post.

The board's big worries included ownership of training data, impact of untested models and detection of unwanted bias, Wang writes.

OpenAI's biggest challenge is making the economics work, and Altman’s move to accelerate commercialization was the right thing, he says.

  continue reading

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