Summarize this content to 2000 words in 6 paragraphs in Arabic Unlock the Editor\u2019s Digest for freeRoula Khalaf, Editor of the FT, selects her favourite stories in this weekly newsletter.Nvidia is on the cusp of revolutionising robotics through artificial intelligence, chief executive Jensen Huang said on Monday, as he outlined his vision for the next stage of the company\u2019s staggering growth and predicted a \u201cmultitrillion-dollar\u201d opportunity.Huang announced a range of new products and partnerships in the \u201cphysical AI\u201d space, including AI models for humanoid robots and a major deal with Toyota to use Nvidia\u2019s self-driving car technology, during his keynote speech at the annual Consumer Electronics Show in Las Vegas.Nvidia has flown past a $3tn market capitalisation off the back of demand for its AI chips to become one of the world\u2019s most valuable companies. Huang in turn has become a household name, more than 30 years after he founded Nvidia as a video game graphics chip company.Massive queues had formed outside the Mandalay Bay convention centre long before the keynote started, with some people still lining up when Huang emerged onstage in a sparkly version of his trademark leather jacket, quipping: \u201cI\u2019m in Las Vegas after all.\u201dOutside semiconductors, Nvidia has been building the software that allows companies to train and deploy robots, from those used in smart factories and warehouses to self-driving cars and humanoids, pushing to expand the use cases for AI running on its chips.Cracking the technological challenges involved in deploying robots at scale will pave the way to \u201cthe largest technology industry the world has ever seen\u201d, said Huang.Nvidia said the field of robotics had reached a technological tipping point, as AI accelerates and fine-tunes the process of simulating the physical world and generating the vast amounts of data needed to train robots. In the next two decades, the market for humanoid robots alone is expected to reach $38bn, according to the company.On Monday, Nvidia announced a suite of foundational AI models on its new Cosmos platform, which developers can use for free to generate data and build their own models.Nvidia said the foundation models, which it said were trained on 20mn hours of video data, were as fundamental a technological development as the large language models that underpin apps such as OpenAI\u2019s ChatGPT. It pairs with Nvidia\u2019s Omniverse platform, which is used to run simulations of the physical world.\u201cWhat [those models] are doing for language, we can now do for understanding the physical world,\u201d Rev Lebaredian, Nvidia\u2019s vice-president for Omniverse and simulation technology, told the Financial Times. While data on the physical world is much harder to gather and process than text, Lebaredian said \u201cit\u2019s a necessary part\u201d of the company\u2019s mission.\u201cThe big takeaway [from Huang\u2019s CES speech] is that this moment is going to be a special one,\u201d he added. \u201cI think this year is an inflection point where we\u2019re going to see this acceleration of physical AI and robotics.\u201dThe Omniverse platform and robotics currently represent a small share of the company\u2019s overall revenue. For Nvidia\u2019s quarter to the end of October, \u201cprofessional virtualisation\u201d accounted for $486mn of revenue, while automotive and robotics totalled $449mn.This is a sliver of overall sales, as the company raked in $30.8bn in revenue from selling chips for the data centres that power AI models in the same period.Nvidia\u2019s search for new markets comes as it faces growing pressure from its biggest customers, including Amazon and Microsoft, which are rushing to build their own in-house AI data centre chips.Bank of America analysts said Nvidia\u2019s decision to double down on \u201cphysical AI\u201d was the \u201cnext logical step\u201d. The challenge would be in \u201cmaking the products reliable enough, cheap enough and pervasive enough to spawn credible business models\u201d, they added.At CES, Nvidia also unveiled a collection of foundation models for humanoid robots, called the \u201cGR00T Blueprint\u201d, which it said would \u201csupercharge\u201d the development of robots, as well as new tools for developing and testing fleets of factory and warehousing robots and training autonomous vehicles.Toyota announced it would build its next generation of autonomous vehicles on Nvidia\u2019s hardware and software, known as Drive AGX. Self-driving car group Aurora and automotive parts maker Continental will use Nvidia\u2019s hardware and software to power thousands of driverless trucks under their long-term strategic partnerships with the chipmaker.Nvidia said it expected its automotive business to grow to $6bn in the 2026 fiscal year. Autonomous vehicles \u201cwill be the first multitrillion-dollar robotics industry\u201d, Huang told the CES audience.Separately, Nvidia said it would release a \u201cpersonal AI supercomputer\u201d with its latest and most powerful AI chip, Blackwell, allowing researchers and students to run multibillion-parameter AI models locally rather than through the cloud. It will be available in May at an initial price tag of $3,000.<\/p>\n","protected":false},"excerpt":{"rendered":"
Summarize this content to 2000 words in 6 paragraphs in Arabic Unlock the Editor\u2019s Digest for freeRoula Khalaf, Editor of the FT, selects her favourite stories in this weekly newsletter.Nvidia is on the cusp of revolutionising robotics through artificial intelligence, chief executive Jensen Huang said on Monday, as he outlined his vision for the next<\/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-156011","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\/156011","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=156011"}],"version-history":[{"count":0,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/posts\/156011\/revisions"}],"wp:attachment":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/media?parent=156011"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/categories?post=156011"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/tags?post=156011"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}