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At sufficient scale, the computational complexity of machine learning model training overwhelms general-purpose CPUs. The work will get done; it might just take a long time. Data scientists and machine learning researchers have long used graphics processing units (GPUs) because of their highly parallelized architecture and relatively abundant on-chip memory available.

But as industry and research groups alike seek more efficiency and need to accommodate ever-larger quantities of information, more specialized computing hardware is required for the task.

Headquartered in Bristol, U.K., is in the business of producing silicon purpose-built for munching through machine-learning math at high rates of speed and using less electricity than GPUs. Benchmarks for Graphcore’s (IPU) that it offers notably less latency and higher computational throughput, and uses less power than GPUs.

The company that it raised an additional $150 million in fresh investor capital in an extension of its Series D round. The extension was led by ; new investors and joined in as well. The deal also saw participation from a number of prior investors. The was closed in December 2018, netting the company $200 million.

The Series D extension values Graphcore at $1.95 billion, according to the company. Taken together, the company has raised $460 million, according to Crunchbase data. The company’s shareholders include the likes of , , , various associated with , , and , among .

In a press release provided to Crunchbase News by the company, Graphcore highlighted a number of milestones from 2019. In partnership with strategic investor Dell Technologies, the companies co-developed and launched the DSS8440, a production-ready server built around Graphcore’s IPUs. Alongside Microsoft, another strategic investor, the company launched the Microsoft Azure IPU-Cloud service, as well as the IPU-Bare Metal Cloud service it launched in partnership with . The company’s publicly announced customers include Microsoft, , Carmot Capital, and European search engine company .

The company says the new round brings its cash reserves up to $300 million. Graphcore has plotted for itself an ambitious growth plan. According to its press release, the company has devoted significant resources to research and development efforts. The company doubled headcount in its Bristol headquarters, as well as its engineering center in Oslo, Norway. It says its sales and support office in Palo Alto, California also saw similar up-scaling in 2019. The company also opened a new sales, support and engineering office in Beijing, alongside an engineering center in Cambridge, U.K., and an operations facility in Taiwan.

“Demand for our Intelligence Processor Unit products is increasing at existing and new customers and the outlook for our business in Fiscal 2020 is extremely positive. The major investments that we have made during 2018 and 2019 will help us to meet this strong demand by extending the capabilities of our technology and ecosystem, and will support long-term revenue growth and returns for our investors,” said Graphcore CEO Nigel Toon in a statement.

The company declined to answer questions from Crunchbase News about its revenue and profitability, whether it has its own fabrication facilities, what the company’s future exit prospects might look like and whether it may be affected by Brexit or the emerging SARS-CoV-2 virus situation in Asia.

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The new vehicle, called Q Fund, has already made investments and will deploy capital from , meaning that we know its maximum scale. During a meeting between Q Fund leaders ,��, and a few members of the press, I learned a few more things about the fund worth sharing.

1. Q Fund is happy to invest in companies with long time horizons. With a focus on investing in startups that may solve “foundational problems,” per Tang, the group is comfortable putting money to work in companies that may have extended routes to liquidity.
2. The fund is looking to invest in startups while they are very early. The duo noted that Samsung NEXT’s efforts have focused on the early side of venture work, and Q Fund might deploy capital into even earlier-stage companies.
3. This willingness to invest early—and here I am paraphrasing notes and our conversation—is predicated on the pair’s belief that applied AI (not, to be clear, what is sometimes hand-waved as AI) is not yet market-ready. So there’s a chance to invest in early-stage companies still solving big questions. If one of those manages a breakthrough, Q, its parent NEXT, and Samsung will probably come out in the black.

Q Fund does not intend to invest in academic-style research. Instead, it will invest in companies that land somewhere between academia and traditional early-stage investments.

This is all chat and the like until Q Fund has made more investments.

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Today, , a division working to “transform” the company by “working with entrepreneurs and innovators to build, grow and scale software and services, announced it is running a new fund focused on AI: the .

Samsung NEXT began as the Samsung Global Innovation Center in 2013, hoping to help its parent company discover new technologies and improve its business by investing in emerging startups. Since then, the group has invested in at least 92 startups ranging in category from education to security to health, according to its .

The group has seen 12 exits, according to . Those exits included , a company which develops software for autonomous vehicles. The firm participated in nuTonomy’s in May 2016 before the self-driving car company was sold to in October 2017 for .

In January 2017, Samsung NEXT launched the $150 million to invest in young tech startups working in categories like machine learning and AI, the internet of things, and virtual reality. In May, the group invested in Virtru, a cybersecurity company based in Washington D.C. focused on end-to-end encryption. Its most recent lead investment was a seed round for a San Francisco-based company called , an AI-powered drone startup.

While the company has invested in AI-focused startups in the past, its next fund will focus specifically on companies developing AI-first platforms and technologies. One startup that earned the group’s investment as a “forward thinking” AI company is , a robotics company founded by former OpenAI researchers that uses AI to power complex skill-acquiring robots.

“We prefer novel techniques over solutions that ‘Import AI,’” the group said in its press release.

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