{"id":5612,"date":"2025-02-12T10:16:10","date_gmt":"2025-02-12T10:16:10","guid":{"rendered":"https:\/\/site.itshrt.com\/worldnews\/how-did-deepseek-build-its-a-i-with-less-money\/"},"modified":"2025-02-12T10:16:10","modified_gmt":"2025-02-12T10:16:10","slug":"how-did-deepseek-build-its-a-i-with-less-money","status":"publish","type":"post","link":"https:\/\/site.itshrt.com\/worldnews\/how-did-deepseek-build-its-a-i-with-less-money\/","title":{"rendered":"How Did DeepSeek Build Its A.I. With Less Money?"},"content":{"rendered":"<p> <script async src=\"https:\/\/pagead2.googlesyndication.com\/pagead\/js\/adsbygoogle.js?client=ca-pub-6606220950177433\"\r\n     crossorigin=\"anonymous\"><\/script>\r\n<!-- ItShrt World News -->\r\n<ins class=\"adsbygoogle\"\r\n     style=\"display:block\"\r\n     data-ad-client=\"ca-pub-6606220950177433\"\r\n     data-ad-slot=\"1882483372\"\r\n     data-ad-format=\"auto\"\r\n     data-full-width-responsive=\"true\"><\/ins>\r\n<script>\r\n     (adsbygoogle = window.adsbygoogle || []).push({});\r\n<\/script>\r\n<br \/>\n<\/p>\n<div data-testid=\"companionColumn-0\">\n<div class=\"css-53u6y8\">\n<p class=\"css-at9mc1 evys1bk0\">Last month, <a class=\"css-yywogo\" href=\"https:\/\/www.nytimes.com\/2025\/01\/27\/business\/us-stock-market-deepseek-ai-sp500-nvidia.html\" title=\"\">U.S. financial markets tumbled<\/a> after a Chinese start-up called DeepSeek said it had <a class=\"css-yywogo\" href=\"https:\/\/www.nytimes.com\/2025\/01\/23\/technology\/deepseek-china-ai-chips.html\" title=\"\">built one of the world\u2019s most powerful artificial intelligence systems<\/a> using <a class=\"css-yywogo\" href=\"https:\/\/www.nytimes.com\/2025\/01\/27\/technology\/what-is-deepseek-china-ai.html\" title=\"\">far fewer computer chips than many experts thought possible<\/a>.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">A.I. companies typically train their chatbots using supercomputers packed with 16,000 specialized chips or more. But DeepSeek said it needed only about 2,000.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">As DeepSeek engineers detailed in a <a class=\"css-yywogo\" href=\"https:\/\/arxiv.org\/html\/2412.19437v1\" title=\"\" rel=\"noopener noreferrer\" target=\"_blank\">research paper<\/a> published just after Christmas, the start-up used several technological tricks to significantly reduce the cost of building its system. Its engineers needed only about $6 million in raw computing power, roughly one-tenth of what Meta spent in building its latest A.I. technology.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">What exactly did DeepSeek do? Here is a guide.<\/p>\n<h2 class=\"css-13o6u42 eoo0vm40\" id=\"link-318acc00\">How are A.I. technologies built?<\/h2>\n<p class=\"css-at9mc1 evys1bk0\">The leading A.I. technologies are based on what scientists call <a class=\"css-yywogo\" href=\"https:\/\/www.nytimes.com\/2018\/03\/06\/technology\/google-artificial-intelligence.html\" title=\"\">neural networks<\/a>, mathematical systems that learn their skills by analyzing enormous amounts of data.<\/p>\n<\/div>\n<aside class=\"css-ew4tgv\" aria-label=\"companion column\"\/><\/div>\n<div data-testid=\"companionColumn-1\">\n<div class=\"css-53u6y8\">\n<p class=\"css-at9mc1 evys1bk0\">The most powerful systems spend months <a class=\"css-yywogo\" href=\"https:\/\/www.nytimes.com\/2024\/04\/06\/technology\/tech-giants-harvest-data-artificial-intelligence.html\" title=\"\">analyzing just about all the English text on the internet<\/a> as well as many images, sounds and other multimedia. That requires enormous amounts of computing power.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">About 15 years ago, A.I. researchers realized that specialized computer chips called graphics processing units, or GPUs, were an effective way of doing this kind of data analysis. Companies like the Silicon Valley chipmaker Nvidia originally designed these chips to render graphics for computer video games. But GPUs also had a knack for running the math that powered neural networks.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">As companies packed more GPUs into their computer data centers, their A.I. systems could analyze more data.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">But the best GPUs cost around $40,000, and they need huge amounts of electricity. Sending the data between chips can use more electrical power than running the chips themselves.<\/p>\n<h2 class=\"css-13o6u42 eoo0vm40\" id=\"link-17ff1666\">How was DeepSeek able to reduce costs?<\/h2>\n<p class=\"css-at9mc1 evys1bk0\">It did many things. Most notably, it embraced a method called \u201cmixture of experts.\u201d<\/p>\n<p class=\"css-at9mc1 evys1bk0\">Companies usually created a single neural network that learned all the patterns in all the data on the internet. This was expensive, because it required enormous amounts of data to travel between GPU chips.<\/p>\n<\/div>\n<aside class=\"css-ew4tgv\" aria-label=\"companion column\"\/><\/div>\n<div data-testid=\"companionColumn-2\">\n<div class=\"css-53u6y8\">\n<p class=\"css-at9mc1 evys1bk0\">If one chip was learning how to write a poem and another was learning how to write a computer program, they still needed to talk to each other, just in case there was some overlap between poetry and programming.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">With the mixture of experts method, researchers tried to solve this problem by splitting the system into many neural networks: one for poetry, one for computer programming, one for biology, one for physics and so on. There might be 100 of these smaller \u201cexpert\u201d systems. Each expert could concentrate on its particular field.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">Many companies have struggled with this method, but DeepSeek was able to do it well. Its trick was to pair those smaller \u201cexpert\u201d systems with a \u201cgeneralist\u201d system.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">The experts still needed to trade some information with one another, and the generalist \u2014 which had a decent but not detailed understanding of each subject \u2014 could help coordinate interactions between the experts.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">It is a bit like an editor\u2019s overseeing a newsroom filled with specialist reporters.<\/p>\n<h2 class=\"css-13o6u42 eoo0vm40\" id=\"link-4b656185\">And that is more efficient?<\/h2>\n<p class=\"css-at9mc1 evys1bk0\">Much more. But that is not the only thing DeepSeek did. It also mastered a simple trick involving decimals that anyone who remembers his or her elementary school math class can understand.<\/p>\n<\/div>\n<aside class=\"css-ew4tgv\" aria-label=\"companion column\"\/><\/div>\n<div data-testid=\"companionColumn-3\">\n<div class=\"css-53u6y8\">\n<h2 class=\"css-13o6u42 eoo0vm40\" id=\"link-1a376114\">There is math involved in this?<\/h2>\n<p class=\"css-at9mc1 evys1bk0\">Remember your math teacher explaining the concept of pi. Pi, also denoted as \u03c0, is a number that never ends: 3.14159265358979 \u2026<\/p>\n<p class=\"css-at9mc1 evys1bk0\">You can use \u03c0 to do useful calculations, like determining the circumference of a circle. When you do those calculations, you shorten \u03c0 to just a few decimals: 3.14. If you use this simpler number, you get a pretty good estimation of a circle\u2019s circumference.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">DeepSeek did something similar \u2014 but on a much larger scale \u2014 in training its A.I. technology.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">The math that allows a neural network to identify patterns in text is really just multiplication \u2014 lots and lots and lots of multiplication. We\u2019re talking months of multiplication across thousands of computer chips.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">Typically, chips multiply numbers that fit into 16 bits of memory. But DeepSeek squeezed each number into only 8 bits of memory \u2014 half the space. In essence, it lopped several decimals from each number.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">This meant that each calculation was less accurate. But that didn\u2019t matter. The calculations were accurate enough to produce a really powerful neural network.<\/p>\n<\/div>\n<aside class=\"css-ew4tgv\" aria-label=\"companion column\"\/><\/div>\n<div data-testid=\"companionColumn-4\">\n<div class=\"css-53u6y8\">\n<h2 class=\"css-13o6u42 eoo0vm40\" id=\"link-48fa9f9d\">That\u2019s it?<\/h2>\n<p class=\"css-at9mc1 evys1bk0\">Well, they added another trick.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">After squeezing each number into 8 bits of memory, DeepSeek took a different route when multiplying those numbers together. When determining the answer to each multiplication problem \u2014 making a key calculation that would help decide how the neural network would operate \u2014 it stretched the answer across 32 bits of memory. In other words, it kept many more decimals. It made the answer more precise.<\/p>\n<h2 class=\"css-13o6u42 eoo0vm40\" id=\"link-95b359f\">So any high school student could have done this?<\/h2>\n<p class=\"css-at9mc1 evys1bk0\">Well, no. The DeepSeek engineers showed in their paper that they were also very good at writing the very complicated computer code that tells GPUs what to do. They knew how to squeeze even more efficiency out of these chips.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">Few people have that kind of skill. But serious A.I. labs have the talented engineers needed to match what DeepSeek has done.<\/p>\n<h2 class=\"css-13o6u42 eoo0vm40\" id=\"link-5a2c16a7\">Then why didn\u2019t they do this already?<\/h2>\n<p class=\"css-at9mc1 evys1bk0\">Some A.I. labs may be using at least some of the same tricks already. Companies like OpenAI do not always reveal what they are doing behind closed doors.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">But others were clearly surprised by DeepSeek\u2019s work. Doing what the start-up did is not easy. The experimentation needed to find a breakthrough like this involves millions of dollars \u2014 if not billions \u2014 in electrical power.<\/p>\n<\/div>\n<aside class=\"css-ew4tgv\" aria-label=\"companion column\"\/><\/div>\n<div data-testid=\"companionColumn-5\">\n<div class=\"css-53u6y8\">\n<p class=\"css-at9mc1 evys1bk0\">In other words, it requires enormous amounts of risk.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">\u201cYou have to put a lot of money on the line to try new things \u2014 and often, they fail,\u201d said Tim Dettmers, a researcher at the Allen Institute for Artificial Intelligence in Seattle who specializes in building efficient A.I. systems and previously worked as an A.I. researcher at Meta.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">\u201cThat is why we don\u2019t see much innovation: People are afraid to lose many millions just to try something that doesn\u2019t work,\u201d he added.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">Many pundits pointed out that DeepSeek\u2019s $6 million covered only what the start-up spent when training the final version of the system. In their paper, the DeepSeek engineers said they had spent additional funds on research and experimentation before the final training run. But the same is true of any cutting-edge A.I. project.<\/p>\n<p class=\"css-at9mc1 evys1bk0\">DeepSeek experimented, and it paid off. Now, because the Chinese start-up has shared its methods with other A.I. researchers, its technological tricks are poised to significantly reduce the cost of building A.I.<\/p>\n<\/div>\n<aside class=\"css-ew4tgv\" aria-label=\"companion column\"\/><\/div>\n<p><script async src=\"https:\/\/pagead2.googlesyndication.com\/pagead\/js\/adsbygoogle.js?client=ca-pub-6606220950177433\"\r\n     crossorigin=\"anonymous\"><\/script>\r\n<!-- ItShrt World News -->\r\n<ins class=\"adsbygoogle\"\r\n     style=\"display:block\"\r\n     data-ad-client=\"ca-pub-6606220950177433\"\r\n     data-ad-slot=\"1882483372\"\r\n     data-ad-format=\"auto\"\r\n     data-full-width-responsive=\"true\"><\/ins>\r\n<script>\r\n     (adsbygoogle = window.adsbygoogle || []).push({});\r\n<\/script>\r\n<br \/>\n<br \/><a href=\"https:\/\/www.nytimes.com\/2025\/02\/12\/technology\/deepseek-ai-chip-costs.html\">Source link <\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Last month, U.S. financial markets tumbled after a Chinese start-up called DeepSeek said it had built one of the world\u2019s<\/p>\n","protected":false},"author":1,"featured_media":5613,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[39],"tags":[213,770,123,771,772,268],"class_list":["post-5612","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology","tag-artificial-intelligence","tag-computer-chips","tag-computers-and-the-internet","tag-deepseek-artificial-intelligence-co-ltd","tag-nvidia-corporation","tag-research"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>How Did DeepSeek Build Its A.I. 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