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| | | Whichever AI segment you follow most closely, be it healthcare or any other, you had to pause to absorb this week’s financial report from Nvidia. Wednesday the chipmaker reported a 101% blast in second-quarter revenues versus the same period last year. The dollar figure, $13.5 billion, also represents a jump of 88% over the first quarter. And the company netted income of $6.18 billion—nine times what it made in Q2 2022. What primed the pump for the extraordinary performance? What else? The race to adopt generative AI. With that has come pedal-to-the-metal demand for high-end, AI-ready GPUs of the kind Nvidia makes. “A new computing era has begun,” Nvidia founder and CEO Jensen Huang told the press Aug. 23, two months after his company became the seventh in the U.S. to hit $1 trillion in market capitalization. “Leading enterprise IT system and software providers have announced partnerships to bring Nvidia AI to every industry.” Notably, the boffo success owes much to chip sales at data centers, where algorithm training takes place. Q2 revenues from that part of the company’s business soared 141% from the previous quarter and 171% from a year ago, to $10.3 billion. Technology market watchers have met the development with almost as much giddiness as investors themselves. Here’s a taste. - Nvidia is now a bellwether for the AI boom, and an ecosystem has emerged in which a win for Nvidia can come in tandem with wins for some additional companies—as well as questions for others.—Yahoo! Finance
- Nvidia CEO Jensen Huang went out of his way to talk about [preferred customer] VMware when answering AI questions from analysts. He didn’t have to do this, but he did.—Insider
- Competition doesn’t look like an immediate concern. Nvidia executives emphasized the move toward GPUs to power AI tools and away from general-purpose processors. Nvidia is estimated to have around a 90% market share for AI-related GPUs currently.—Barron’s
- Until recently, Nvidia got the biggest share of its revenue from sales of GPUs for rendering images in video games. But AI researchers started using those chips in 2012 for tasks such as machine learning, a trend that Nvidia exploited over the years by adding enhancements to its GPUs and many pieces of software to reduce labor for AI programmers.—The New York Times
- Demand for GPUs in AI applications is huge … Huang’s move to buy back [$25 billion in] stock when it is more expensive than ever is risky, but it shows his confidence in Nvidia’s continued success.—Ars Technica
Lots more coverage here. |
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| | | Buzzworthy developments of the past few days. - Some fear AI will hasten the end of humankind. Others believe such thinking is exactly upside-down. Take Thomas Fuchs, DSc, dean for AI and human health at the Icahn School of Medicine in New York City. “Today patients are dying not because of AI but because of the lack of it,” Fuchs told attendees of a recent symposium on the “new wave” of AI in healthcare. Fuchs was one of a handful of subject matter experts who addressed the gathering. The event was co-hosted by the New York Academy of Sciences, which was founded when James and Dolley Madison would have been living in the White House had the British not burned it down. (Sorry, love historical trivia.) The academy has posted a summary of the proceedings.
- Microsoft and Epic are doing a mind meld over AI. Together they’ll work to outbrain all sorts of issues nagging U.S. healthcare. Epic will ask healthcare-specific questions. Microsoft will ramp up AI and cloud computing to come up with answers. The output will be “dozens of copilot solutions” to help provider orgs find qualified staffing, ease financial pain and expand patient access. Microsoft AI veep Eric Boyd gives some details.
- During World War II, England’s Bletchley Park hosted the use of early AI technology to help defeat the Nazis. (If you saw 2014’s The Imitation Game, you know the story.) In early November the site will welcome AI experts from around the world. This time the focus will be on marshaling the will of nations to prioritize safety in AI development and deployment. Details.
- Half of digital healthcare marketers admit to using unethical means of boosting search engine optimization. Well, what goes around comes around: Some 65% of those who went “black hat”—paying for links, stuffing keywords, hiding text, et cetera—experienced negative repercussions. Fear of losing a job to AI may help explain the widespread willingness to play dirty, as 1 in 5 of these digital marketers worries about just that. On the other hand, more than 60% believe large language models will make healthcare SEO a better gig. The findings are from a survey conducted by Tebra as reported in The Intake. See the rest of the findings.
- In China, suppliers of healthcare chatbots and large language AI models must “adhere to core socialist values” when designing their systems. Such adherence is to be demonstrated by refusing to create content that “incites subversion of state power and the overthrow of the socialist system, endangers national security and interests, damages the image of the country, incites secession from the country, undermines national unity and social stability, promotes terrorism, extremism, national hatred and ethnic discrimination, violence, obscenity and pornography.” To be fair, right now the rules, 41 in number, are in the proposal phase. Then again, they were drafted by the influential Beijing Municipal Health Commission. The more things change …
- In Pennsylvania, control over AI isn’t so draconian. In fact, more than a few people want more of it. Among them are state representatives miffed by the idea of algorithms declining health insurance claims with no human oversight. Pittsburgh’s NPR affiliate has the story.
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