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AI chatbots are becoming popular alternatives to therapy. But they may worsen mental health crises, experts warn

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    B
    MC and VISA are the networks. They allow communication between banks, and the entire operation is packaged up by payment processors like Stripe, Square or PayPal. So you have processors, the banks on either end (perhaps two separate ones), the network operator, and additionally any extra companies that might offer additional services for the transaction, like for fraud prevention or financing.
  • Huawei shows off AI computing system to rival Nvidia's top product

    Technology technology
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    C
    Huawei was uniquely, specifically, forced out of the US market around the time they were completing for 5G Tower standards.
  • Navigating the Skies: Growth and Challenges in the UTM Market

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    Niemand hat geantwortet
  • WhatsApp rolls out AI-generated summaries for private messages

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    W
    So I think, but I'm not sure, this is for group chats. Group chats are only encrypted to/from the server because the server broadcasts the message to each recipient. As the messages are unencrypted on the server, they can feed them to LLMs. This is different to Signal. On Signal it's your phone encrypting each copy of the message before sending to each recipient individually.
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    toastedravioli@midwest.socialT
    ChatGPT is not a doctor. But models trained on imaging can actually be a very useful tool for them to utilize. Even years ago, just before the AI “boom”, they were asking doctors for details on how they examine patient images and then training models on that. They found that the AI was “better” than doctors specifically because it followed the doctor’s advice 100% of the time; thereby eliminating any kind of bias from the doctor that might interfere with following their own training. Of course, the splashy headline “AI better than doctors” was ridiculous. But it does show the benefit of having a neutral tool for doctors to utilize, especially when looking at images for people who are outside of the typical demographics that much medical training is based on. (As in mostly just white men. For example, everything they train doctors on regarding knee imagining comes from images of the knees of coal miners in the UK some decades ago)
  • How the Rubin Observatory Will Reinvent Astronomy

    Technology technology
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    M
    Giant twice-reflecting mirror of low-expansion borrosilicate covered in pure silver and a giant digital camera with filters.
  • Why doesn't Nvidia have more competition?

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    B
    It’s funny how the article asks the question, but completely fails to answer it. About 15 years ago, Nvidia discovered there was a demand for compute in datacenters that could be met with powerful GPU’s, and they were quick to respond to it, and they had the resources to focus on it strongly, because of their huge success and high profitability in the GPU market. AMD also saw the market, and wanted to pursue it, but just over a decade ago where it began to clearly show the high potential for profitability, AMD was near bankrupt, and was very hard pressed to finance developments on GPU and compute in datacenters. AMD really tried the best they could, and was moderately successful from a technology perspective, but Nvidia already had a head start, and the proprietary development system CUDA was already an established standard that was very hard to penetrate. Intel simply fumbled the ball from start to finish. After a decade of trying to push ARM down from having the mobile crown by far, investing billions or actually the equivalent of ARM’s total revenue. They never managed to catch up to ARM despite they had the better production process at the time. This was the main focus of Intel, and Intel believed that GPU would never be more than a niche product. So when intel tried to compete on compute for datacenters, they tried to do it with X86 chips, One of their most bold efforts was to build a monstrosity of a cluster of Celeron chips, which of course performed laughably bad compared to Nvidia! Because as it turns out, the way forward at least for now, is indeed the massively parralel compute capability of a GPU, which Nvidia has refined for decades, only with (inferior) competition from AMD. But despite the lack of competition, Nvidia did not slow down, in fact with increased profits, they only grew bolder in their efforts. Making it even harder to catch up. Now AMD has had more money to compete for a while, and they do have some decent compute units, but Nvidia remains ahead and the CUDA problem is still there, so for AMD to really compete with Nvidia, they have to be better to attract customers. That’s a very tall order against Nvidia that simply seems to never stop progressing. So the only other option for AMD is to sell a bit cheaper. Which I suppose they have to. AMD and Intel were the obvious competitors, everybody else is coming from even further behind. But if I had to make a bet, it would be on Huawei. Huawei has some crazy good developers, and Trump is basically forcing them to figure it out themselves, because he is blocking Huawei and China in general from using both AMD and Nvidia AI chips. And the chips will probably be made by Chinese SMIC, because they are also prevented from using advanced production in the west, most notably TSMC. China will prevail, because it’s become a national project, of both prestige and necessity, and they have a massive talent mass and resources, so nothing can stop it now. IMO USA would clearly have been better off allowing China to use American chips. Now China will soon compete directly on both production and design too.
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    J
    I deleted the snapchat now.