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action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home4/scienrds/scienceandnerds/wp-includes/functions.php on line 6114Source:https:\/\/techcrunch.com\/2023\/06\/28\/celestial-ai-raises-100m-to-transfer-data-using-light-based-interconnects\/<\/a><\/br> David Lazovsky and Preet Virk, technologists with backgrounds in semiconductor engineering and photonics, came to the joint realization several years ago that AI<\/span> and machine learning workloads would quickly encounter a \u201cdata movement\u201d problem. Increasingly, they predicted, it would become challenging to move data to and from compute hardware as AI models scaled past what could be kept on the die of any one memory chip.<\/p>\n Their solution \u2014 architected by Phil Winterbottom, previously a researcher at the distinguished Bell Labs \u2014 was an optical interconnect technology for compute-to-compute, compute-to-memory and on-chip data transmission. Along with Winterbottom, Lazovsky and Virk founded a startup, Celestial AI<\/a>, to commercialize the tech. And now that startup is attracting big backers.<\/p>\n Celestial AI today announced that it raised $100 million in a Series B round led by IAG Capital Partners, Koch Disruptive Technologies and Temasek\u2019s Xora Innovation fund. The tranche, which brings Celestial AI\u2019s total raised to more than $165 million, will be used to support the production of Celestial\u2019s photonics platform by expanding the company\u2019s engineering, sales and technical marketing departments, according to CEO Lazovsky.<\/p>\n Celestial has around 100 employees at present \u2014 a number that Lazovsky expects will grow to 130 by the end of the year.<\/p>\n \u201cToday, compute and memory are closely coupled. The only way to add more high bandwidth memory is to add more compute, whether the additional compute is required or not,\u201d Lazovsky told TechCrunch via email. \u201cCelestial\u2019s tech enables memory disaggregation.\u201d<\/p>\n In a data center, memory is often one of the most expensive<\/a> resources \u2014 in part because it\u2019s not always used efficiently. Because memory is tied to compute, it\u2019s challenging \u2014 and sometimes impossible, due to bandwidth constraints and sky-high latency \u2014 for operators to \u201cdisaggregate\u201d and pool the memory across hardware within the data center.<\/p>\n According to an internal<\/a> Microsoft study, up to 25% of memory in Azure is \u201cstranded,\u201d or left over, after the servers\u2019 cores have been rented to virtual machines. Reducing this stranded memory could cut data center costs by 4% to 5%, the company estimated<\/a> \u2014 potentially significant savings in the context of a multibillion-dollar operation.<\/p>\n Celestial \u2014 which began as a portfolio company of The Engine, the VC firm spun out of MIT in 2016 \u2014 developed an ostensible solution in its photonics-based architecture, which scales across multiple-chip systems. Using light to transfer data, Celestial\u2019s tech can beam information within chips and chip-to-chip, making both memory and compute available for AI \u2014 and other \u2014 workloads.<\/p>\n
\nCelestial AI raises $100M to transfer data using light-based interconnects<\/br>
\n2023-06-29 22:27:02<\/br><\/p>\n