In the last two weeks, NVIDIA, the enabler and chief beneficiary of the AI craze, has bought into quantum computing. \u201cI’m a little surprised they haven’t done it before,\u201d says Richard Shannon, an investment analyst at Craig Hallum. <\/p>\n
The investments from NVIDIA\u2019s venture capital arm and other investors\u2014which collectively value quantum computing startups Quantinuum<\/a>, QuEra<\/a> and PsiQuantum<\/a> at over $17 billion\u2014represent a shift in tone for NVIDIA\u2019s CEO, Jensen Huang. In January, Huang said<\/a> that useful quantum computers were 15 to 20 years away, sending publicly-listed quantum computing firms tumbling. He walked this back in March<\/a>, saying<\/a> in June that quantum computing had reached an \u201cinflection point\u201d and could \u201csolve some interesting problems in the coming years\u201d. A NVIDIA spokesperson declined to comment.<\/p>\n By positioning itself at the center of the hardware that AI companies need to run their models, NVIDIA has become the world\u2019s most valuable company, valued at $4 trillion. NVIDIA designs GPUs (the chips specialized for running AI algorithms), develops CUDA (which allows the chips to talk to each other), and packages it all into supercomputers the size of fridges\u2014which AI companies are falling over each other to put into their data centers.<\/p>\n Quantum computing is unlikely to help NVIDIA\u2019s AI customers. \u201cQuantum computing and AI are sort of diametrically opposed,\u201d said Pete Shadbolt, chief science officer at PsiQuantum, one of the startups that NVIDIA invested in. AI systems are powerful because they learn patterns from vast quantities of data. Quantum computers, by contrast, \u201chate data, and they love precision,\u201d said Shadbolt.<\/p>\n Proponents believe that quantum computing could usher in a new computing paradigm. Rather than performing numerous simple calculations in parallel, as NVIDIA\u2019s GPUs do, quantum computers could solve a few, extremely valuable equations. Quantinuum does this using ions (charged atoms), PsiQuantum uses photons (light particles), and QuEra uses neutral atoms. These tiny particles obey the strange laws of quantum mechanics: they can be in multiple states at the same time, allowing quantum computers to explore multiple paths of a complex calculation simultaneously, arriving at solutions that current \u201cclassical\u201d computers cannot reach in any reasonable length of time. This includes shortening the millions of years that it would take classical computers to break the encryption schemes that underlie much of the digital economy to hours<\/a>, which has sent<\/a> banks scrambling for \u201cquantum-resistant\u201d cryptography.<\/p>\n There are beneficial applications, too. Quantum computers can simulate quantum mechanical systems, which can\u2019t be done using classical computers, said Hsin-Yuan Huang, a senior research scientist at Google Quantum AI. Quantum mechanics is our most fundamental description of the physical world, and the ability to simulate it could help design new drugs, materials, and chemical processes. \u201cThat’s not going to be solvable with just many GPUs. It’s just inherently too hard,\u201d said Hsin-Yuan Huang.<\/p>\n For example, quantum computing may unlock<\/a> greener ways of producing ammonia, which currently accounts for 2 percent of global energy consumption. PsiQuantum has partnered with Mercedes-Benz to understand how quantum computers could simulate lithium-ion battery electrolytes\u2014which might accelerate electric vehicle battery design\u2014and is working with Boehringer Ingelheim, a pharmaceutical company, to understand an enzyme that is involved in the human body\u2019s metabolism of drugs.<\/p>\n But without large enough quantum computers to put these ideas into practice, the concrete utility of quantum computers has yet to be demonstrated, said Jan Ole Ernst, a Ph.D. researcher in quantum information and computation at the University of Oxford. It\u2019s possible that this will change when larger quantum computers are available for application development. \u201cBut I think that’s also kind of far-fetched, because there’s so much research going into applications, and we haven’t really found anything really clear-cut, apart from factorizing large numbers.\u201d<\/p>\n It\u2019s unclear how long it will take for quantum computers to work on the scale where these questions can be answered definitively. Timelines in quantum computing, as in many technically challenging fields, have a habit of stretching. PsiQuantum says that it has started work on sites in Australia and Illinois, and is testing the equipment that will cool their chips to operating temperatures. The company says it will be running a quantum computer large enough to be useful by 2027, two years later than it thought<\/a> in 2021.<\/p>\n If and when quantum computers do start running, NVIDIA is likely to be in the center of the action. \u201cYou’ll never be able to run a quantum computer without a ton of classical processing,\u201d said Ernst. Classical computers are needed to control quantum computers, perform error correction and analyze their readouts. PsiQuantum uses NVIDIA\u2019s hardware to prepare their quantum computation and process its outputs. In 2022, the company launched<\/a> CUDA-Q, which would allow quantum computers to talk to classical computers. This year, it announced<\/a> the NVIDIA Accelerated Quantum Computing Research Center in Boston, \u201cdedicated to shortening the timeline to useful quantum computing.\u201d\u00a0<\/p>\n \u201cI think it’s fair to say that they’re doing everything but the quantum computer,\u201d said Shadbolt.\u00a0<\/p>\n That could change. NVIDIA\u2019s recent investments will give the company \u201cadvance notice about which platforms are scaling better,\u201d said Shannon. \u201cI believe, given enough time, it’s a virtual certainty that NVIDIA buys one or more quantum companies.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"In the last two weeks, NVIDIA, the enabler and chief beneficiary of the AI craze, has bought into…\n","protected":false},"author":2,"featured_media":163661,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[21],"tags":[256,64,63,257,105],"class_list":{"0":"post-163660","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-computing","8":"tag-ai","9":"tag-au","10":"tag-australia","11":"tag-computing","12":"tag-technology"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts\/163660","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/comments?post=163660"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts\/163660\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/media\/163661"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/media?parent=163660"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/categories?post=163660"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/tags?post=163660"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}