Summarize this content to 2000 words in 6 paragraphs in Arabic OpenAI chief executive Sam Altman said he would fast-track product releases and \u201cdeliver much better models\u201d after advances by Chinese start-up DeepSeek undermined Silicon Valley\u2019s lead in a global artificial intelligence arms race.DeepSeek\u2019s generative AI chatbot, a direct rival to ChatGPT, is able to perform some tasks at the same level as recently released models from OpenAI, Anthropic and Meta, despite claims it cost a fraction of the money and time to develop. The release of DeepSeek\u2019s R1 model last week and its rise to the top of Apple\u2019s App Store has triggered a tech stock sell-off. Asian tech shares fell on Tuesday in the wake of a Wall Street rout overnight. The Nasdaq fell 3 per cent and US chipmaker Nvidia, which produces the chips used to train large AI models, slumped 17 per cent, losing $600bn in market capitalisation.On Monday evening, Altman wrote on X that DeepSeek\u2019s model was \u201cimpressive, particularly around what they\u2019re able to deliver for the price\u201d. He added: \u201cWe will obviously deliver much better models and also it\u2019s legit invigorating to have a new competitor!\u201dAltman, who last week announced that investors including SoftBank would spend up to $500bn to build a network of data centres to power its AI models, added that computing resources were \u201cmore important now than ever before\u201d. Microsoft, Meta, Alphabet, Amazon and Oracle have earmarked $310bn in 2025 for capital expenditure, which includes AI infrastructure, according to data compiled by Visible Alpha. Such estimates have been based on the premise that huge amounts of computing power will be needed to advance AI capabilities. But DeepSeek\u2019s ability to compete on a fraction of the budget of OpenAI \u2014 which was recently valued at $157bn \u2014 and rivals Anthropic, Google and Meta, has raised questions about the vast sums being poured into training systems. \u201cThe winners won\u2019t be the ones burning the most cash,\u201d said Aidan Gomez, founder of Toronto-based Cohere, which builds large language models for enterprises. Instead, he said, they would be those \u201cfinding efficient solutions\u201d.The advances by DeepSeek have also exposed risks for venture capitalists who put almost $100bn into US AI start-ups last year. \u201cThere\u2019s now an open weight model floating around the internet which you can use to bootstrap any other sufficiently powerful base model into being an AI reasoner,\u201d said Jack Clark, co-founder of Anthropic, in a blog on Monday. \u201cAI capabilities worldwide just took a one-way ratchet forward,\u201d he added. \u201cKudos to DeepSeek for being so bold as to bring such a change into the world!\u201dDeepSeek\u2019s success has complicated the argument that massive cash piles create an unassailable advantage, which has helped leading Silicon Valley labs raise tens of billions of dollars over the past year.\u201cIf you\u2019re Anthropic or OpenAI, attempting to be at the forefront, and someone can serve what you can at a tenth of the cost, that\u2019s problematic,\u201d said Mike Volpi, who led Index Ventures\u2019 investment into Cohere.The sudden release of DeepSeek\u2019s latest model surprised some at Meta. \u201cThe main frustration is, \u2018Why didn\u2019t we come up with this first?\u2019 when we have thousands of the brightest minds working on this,\u201d said one Meta employee.Chief executive Mark Zuckerberg \u2014 who last week said he expected to allocate up to $65bn in capital spending to expand AI teams and build a new data centre \u2014 has advocated for open source, positioning Meta at its forefront in the US.\u201cWe want the US to set the global AI standard, not China,\u201d the company said in response to DeepSeek. Meta\u2019s chief AI scientist Yann LeCun said \u201crunning AI assistant services for billions\u201d would still require large levels of computing power.Rival company insiders and investors have expressed scepticism about the low costs cited by DeepSeek in developing its models. In December, the company said its V3 model, which its app\u2019s chatbot runs on, cost just $5.6mn to train.However, it added that this figure was only for the final training run, not the complete cycle, and excluded \u201cthe costs associated with prior research and\u2009.\u2009.\u2009.\u2009experiments on architectures, algorithms, or data\u201d.DeepSeek has attributed its success \u2014 despite using inferior chips to its US competitors \u2014 to methods that allow the AI model to selectively focus on specific parts of input data as a way of reducing the costs of running the model. For its latest R1 model, it used a reinforcement learning technique, a relatively new approach to AI in which models teach themselves how to improve without human supervision. The company also used open-source models, including Alibaba\u2019s Qwen and Meta\u2019s Llama, to fine tune its R1 reasoning model.The technical advances and investor interest in DeepSeek\u2019s progress could light a fire under AI companies. \u201cIn general, we expect the bias to be on improved capability, sprinting faster towards artificial general intelligence, more than reduced spending,\u201d said research firm Rosenblatt on Monday.Researchers and investors, including Marc Andreessen, have drawn parallels between the race between the US and China on artificial general intelligence and its competition with the Soviet Union during the cold war, both in space exploration and nuclear weapons development.Stuart Russell, professor of computer science at the University of California, Berkeley, said the race to AGI was \u201cworse\u201d.\u201cEven the CEOs who are engaging in the race have stated that whoever wins has a significant probability of causing human extinction in the process, because we have no idea how to control systems more intelligent than ourselves,\u201d he said. \u201cIn other words, the AGI race is a race towards the edge of a cliff.\u201dAdditional reporting by Michael Acton and Rafe Uddin in San Francisco and Melissa Heikkil\u00e4 in LondonVideo: AI and the potential for a revolution in healthcare<\/p>\n","protected":false},"excerpt":{"rendered":"
Summarize this content to 2000 words in 6 paragraphs in Arabic OpenAI chief executive Sam Altman said he would fast-track product releases and \u201cdeliver much better models\u201d after advances by Chinese start-up DeepSeek undermined Silicon Valley\u2019s lead in a global artificial intelligence arms race.DeepSeek\u2019s generative AI chatbot, a direct rival to ChatGPT, is able to<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[63],"tags":[],"class_list":{"0":"post-183530","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-tech"},"_links":{"self":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/posts\/183530","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/comments?post=183530"}],"version-history":[{"count":0,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/posts\/183530\/revisions"}],"wp:attachment":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/media?parent=183530"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/categories?post=183530"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/tags?post=183530"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}