Artificial intelligence technology holds a huge amount of promise for enterprises \u2014 as a tool to process and understand their data more efficiently; as a way to leapfrog into new kinds of services and products; and as a critical stepping stone into whatever the future might hold for their businesses. But the problem for many enterprises is that they are not tech businesses at their core, so bringing on and using AI will typically involve a lot of heavy lifting. Today, one of the startups building AI services is announcing a big round of funding to help bridge that gap.<\/p>\n
SambaNova<\/a> \u2014 a startup building AI hardware and integrated systems that run on it that only officially came out of three years in stealth last December \u2014 is announcing a huge round of funding today to take its business out into the world. The company has closed on $676 million in financing, a Series D that co-founder and CEO Rodrigo Liang has confirmed values the company at $5.1 billion.<\/p>\n The round is being led by SoftBank, which is making the investment via Vision Fund 2. Temasek and the government of Singapore Investment Corp. (GIC), both new investors, are also participating, along with previous backers<\/a> BlackRock, Intel Capital, GV (formerly Google Ventures), Walden International and WRVI, among other unnamed investors. (Sidenote: BlackRock and Temasek separately kicked off an investment partnership yesterday<\/a>, although it\u2019s not clear if this falls into that remit.)<\/p>\n Co-founded by two Stanford professors, Kunle Olukotun and Chris R\u00e9, and Liang, who had been an engineering executive at Oracle, SambaNova has been around since 2017 and has raised more than $1 billion to date \u2014 both to build out its AI-focused hardware, which it calls DataScale<\/a>, and to build out the system that runs on it. (The \u201cSamba\u201d in the name is a reference to Liang\u2019s Brazilian heritage, he said, but also the Latino music and dance that speaks of constant movement and shifting, not unlike the journey AI data regularly needs to take that makes it too complicated and too intensive to run on more traditional systems.)<\/p>\n SambaNova on one level competes for enterprise business against companies like Nvidia, Cerebras Systems and Graphcore \u2014 another startup in the space which earlier this year also raised a significant round<\/a>. However, SambaNova has also taken a slightly different approach to the AI challenge.<\/p>\n Green shoots for software companies<\/a><\/p>\n<\/blockquote>\n\n In December<\/a>, the startup launched Dataflow-as-a-Service<\/a> as an on-demand, subscription-based way for enterprises to tap into SambaNova\u2019s AI system, with the focus just on the applications that run on it, without needing to focus on maintaining those systems themselves. It\u2019s the latter that SambaNova will be focusing on selling and delivering with this latest tranche of funding, Liang said.<\/p>\n SambaNova\u2019s opportunity, Liang believes, lies in selling software-based AI systems to enterprises that are keen to adopt more AI into their business, but might lack the talent and other resources to do so if it requires running and maintaining large systems.<\/p>\n \u201cThe market right now has a lot of interest in AI. They are finding they have to transition to this way of competing, and it\u2019s no longer acceptable not to be considering it,\u201d said Liang in an interview.<\/p>\n The problem, he said, is that most AI companies \u201cwant to talk chips,\u201d yet many would-be customers will lack the teams and appetite to essentially become technology companies to run those services. \u201cRather than you coming in and thinking about how to hire scientists and hire and then deploy an AI service, you can now subscribe, and bring in that technology overnight. We\u2019re very proud that our technology is pushing the envelope on cases in the industry.\u201d<\/p>\n To be clear, a company will\u00a0still<\/em> need data scientists, just not the same number, and specifically not the same number dedicating their time to maintaining systems, updating code and other more incremental work that comes managing an end-to-end process.<\/p>\n SambaNova has not disclosed many customers so far in the work that it has done \u2014 the two reference names it provided to me are both research labs, the Argonne National Laboratory<\/a> and the Lawrence Livermore National Laboratory<\/a> \u2014\u00a0but Liang noted some typical use cases.<\/p>\n One was in imaging, such as in the healthcare industry, where the company\u2019s technology is being used to help train systems based on high-resolution imagery, along with other healthcare-related work. The coincidentally-named Corona supercomputer at the Livermore Lab (it was named after the 2014 lunar eclipse, not the dark cloud of a pandemic that we\u2019re currently living through) is using SambaNova\u2019s technology to help run calculations related to some COVID-19 therapeutic and antiviral compound research, Marshall Choy, the company\u2019s VP of product, told me.<\/p>\n Another set of applications involves building systems around custom language models, for example in specific industries like finance, to process data quicker. And a third is in recommendation algorithms, something that appears in most digital services and frankly could always do to work a little better than it does today. I\u2019m guessing that in the coming months it will release more information about where and who is using its technology.<\/p>\n\n
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