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About DeepMind

DeepMind is an artificial intelligence company. It combines the techniques of machine learning and systems neuroscience and builds general-purpose learning algorithms. The company was founded in 2010 and is based in London, United Kingdom. In January 2014, DeepMind was acquired by Google.

Headquarters Location

5 New Street Square

London, England, EC4A 3TW,

United Kingdom



Research containing DeepMind

Get data-driven expert analysis from the CB Insights Intelligence Unit.

CB Insights Intelligence Analysts have mentioned DeepMind in 4 CB Insights research briefs, most recently on Oct 18, 2023.

Expert Collections containing DeepMind

Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.

DeepMind is included in 1 Expert Collection, including Artificial Intelligence.


Artificial Intelligence

10,987 items

Companies developing artificial intelligence solutions, including cross-industry applications, industry-specific products, and AI infrastructure solutions.

DeepMind Patents

DeepMind has filed 364 patents.

The 3 most popular patent topics include:

  • artificial neural networks
  • machine learning
  • artificial intelligence
patents chart

Application Date

Grant Date


Related Topics




Artificial neural networks, Block ciphers, Rotating disc computer storage media, Computational neuroscience, Classification algorithms


Application Date


Grant Date



Related Topics

Artificial neural networks, Block ciphers, Rotating disc computer storage media, Computational neuroscience, Classification algorithms



Latest DeepMind News

Ego, fear and money: How the AI fuse was lit

Dec 4, 2023

Updated SAN FRANCISCO – Elon Musk celebrated his 44th birthday in July 2015 at a three-day party thrown by his wife at a California wine country resort dotted with cabins. It was family and friends only, with children racing around the upscale property in Napa Valley. This was years before Twitter became X, and Tesla had a profitable year. Musk and his wife, Talulah Riley, were a year from throwing in the towel on their second marriage. Larry Page, a party guest, was still CEO of Google. And artificial intelligence had pierced the public consciousness only a few years before, when it was used to identify cats on YouTube – with 16 per cent accuracy. AI was the big topic of conversation when Musk and Page sat down near a fire pit beside a swimming pool after dinner the first night. The two billionaires had been friends for more than a decade. But the tone that clear night soon turned contentious as the two debated whether AI would ultimately elevate humanity or destroy it. As the discussion stretched into the chilly hours, it grew intense, and some of the more than 30 partygoers gathered closer to listen. Page, hampered for more than a decade by an unusual ailment in his vocal cords, described his vision of a digital utopia in a whisper. Humans would eventually merge with artificially intelligent machines, he said. One day, there would be many kinds of intelligence competing for resources, and the best would win. If that happens, Musk said, we’re doomed. The machines will destroy humanity. With a rasp of frustration, Page insisted his utopia should be pursued. Finally, he called Musk a “specieist,” a person who favours humans over the digital life-forms of the future. That insult, Musk said later, was “the last straw.” Eight years later, the argument between the two men seems prescient. The question of whether AI will elevate the world or destroy it – or at least inflict grave damage – has framed an ongoing debate among Silicon Valley founders, chatbot users, academics, legislators and regulators about whether the technology should be controlled or set free. That debate has pitted some of the world’s richest men against one another: Musk, Page, Mark Zuckerberg of Meta, tech investor Peter Thiel, Satya Nadella of Microsoft and Sam Altman of OpenAI. All have fought for a piece of the business and the power to shape it. At the heart of this competition is a brain-stretching paradox. The people who say they are most worried about AI are among the most determined to create it and enjoy its riches. They have justified their ambition with their strong belief that they alone can keep AI from endangering Earth. Musk and Page stopped speaking soon after the party that summer. A few weeks later, Musk dined with Sam Altman, who was then running a tech incubator, and several researchers in a private room at the Rosewood hotel in Menlo Park, California. That dinner led to the creation of a startup called OpenAI later in the year. Backed by hundreds of millions of dollars from Musk and other funders, the lab promised to protect the world from Page’s vision. Thanks to its ChatGPT chatbot, OpenAI has fundamentally changed the technology industry and has introduced the world to the risks and potential of artificial intelligence. OpenAI is valued at more than $80 billion, according to two people familiar with the company’s latest funding round, although Musk and Altman’s partnership didn’t make it. The two have since stopped speaking. “There is disagreement, mistrust, egos,” Altman said. “The closer people are to being pointed in the same direction, the more contentious the disagreements are. You see this in sects and religious orders. There are bitter fights between the closest people.” Last month, that infighting came to OpenAI’s boardroom. Rebel board members tried to force out Altman because, they believed, they could no longer trust him to build AI that would benefit humanity. Over five chaotic days, OpenAI looked as if it were going to fall apart, until the board – pressured by giant investors and employees who threatened to follow Altman out the door – backed down. The drama inside OpenAI gave the world its first glimpse of the bitter feuds among those who will determine the future of AI. But years before OpenAI’s near meltdown, there was a little-publicized but ferocious competition in Silicon Valley for control of the technology that is now quickly reshaping the world. The New York Times spoke with more than 80 executives, scientists and entrepreneurs, including two people who attended Musk’s birthday party in 2015, to tell that story of ambition, fear and money. The birth of DeepMind Five years before the Napa Valley party and two before the cat breakthrough on YouTube, Demis Hassabis, a 34-year-old neuroscientist, walked into a cocktail party at Peter Thiel’s San Francisco town house and realized he had hit pay dirt. There in Thiel’s living room was a chessboard. Hassabis had once been the second-best player in the world in the under-14 category. “I was preparing for that meeting for a year,” Hassabis said. “I thought that would be my unique hook in: I knew that he loved chess.” In 2010, Hassabis and two colleagues, who all lived in Britain, were looking for money to start building “artificial general intelligence,” or AGI, a machine that could do anything the brain could do. At the time, few people were interested in AI. Still, some scientists and thinkers had become fixated on the downsides of AI. Many, including the three young men from Britain, had a connection to Eliezer Yudkowsky, an internet philosopher and self-taught AI researcher. Yudkowsky was a leader in a community of people who called themselves Rationalists or, in later years, effective altruists. Thiel had become enormously wealthy through an early investment in Facebook and through his work with Musk in the early days of PayPal. He had developed a fascination with the singularity, a trope of science fiction that describes the moment when intelligent technology can no longer be controlled by humanity. With funding from Thiel, Yudkowsky had expanded his AI lab and created an annual conference on the singularity. Years before, one of Hassabis’ two colleagues had met Yudkowsky, and he snagged them speaking spots at the conference, ensuring they’d be invited to Thiel’s party. Yudkowsky introduced Hassabis to Thiel. Charmed, Thiel invited the group back the next day. The three made their pitch, and soon Thiel and his venture capital firm agreed to put 1.4 million British pounds (S$2.37 million) into their startup. He was their first major investor. They named their company DeepMind, a nod to “deep learning,” a way for AI systems to learn skills by analysing large amounts of data; to neuroscience; and to the Deep Thought supercomputer from the sci-fi novel “The Hitchhiker’s Guide to the Galaxy.” By the fall of 2010, they were building their dream machine. They wholeheartedly believed that because they understood the risks, they were uniquely positioned to protect the world. “I don’t see this as a contradictory position,” said Mustafa Suleyman, one of the three DeepMind founders. “There are huge benefits to come from these technologies. The goal is not to eliminate them or pause their development. The goal is to mitigate the downsides.” Having won over Thiel, Hassabis worked his way into Musk’s orbit. About two years later, they met at a conference organized by Thiel’s investment fund, which had also put money into Musk’s company SpaceX. Hassabis secured a tour of SpaceX headquarters. Afterward, the two men lunched in the cafeteria and talked. Musk explained that his plan was to colonize Mars to escape overpopulation and other dangers on Earth. Hassabis replied that the plan would work – so long as superintelligent machines didn’t follow and destroy humanity on Mars, too. Musk was speechless. He hadn’t thought about that particular danger. Musk soon invested in DeepMind alongside Thiel. Flush with cash, DeepMind hired researchers who specialized in neural networks, complex algorithms created in the image of the human brain. A neural network is essentially a giant mathematical system that spends days, weeks or even months identifying patterns in large amounts of digital data. First developed in the 1950s, these systems could learn to handle tasks on their own. After analysing names and addresses scribbled on hundreds of envelopes, for instance, they could read handwritten text. DeepMind took the concept further. It built a system that could learn to play classic Atari games to illustrate what was possible. This got the attention of another Silicon Valley powerhouse, Google, and specifically Page. The Talent Auction In the fall of 2012, Geoffrey Hinton, a 64-year-old professor at the University of Toronto, and two graduate students published a research paper that showed the world what AI could do. They trained a neural network to recognize common objects such as flowers, dogs and cars. Scientists were surprised by the accuracy of the technology built by Hinton and his students. One who took particular notice was Yu Kai, an AI researcher who had met Hinton at a research conference and had recently started working for Baidu, a giant Chinese internet company. Baidu offered Hinton and his students $12 million to join the company in Beijing, according to three people familiar with the offer. Hinton turned Baidu down, but the money got his attention. “We did not know how much we were worth,” Hinton said. He consulted lawyers and experts on acquisitions and came up with a plan: “We would organize an auction, and we would sell ourselves.” The auction would take place during an annual AI conference at the Harrah’s hotel and casino on Lake Tahoe. Google made an offer. So did Microsoft. DeepMind quickly bowed out. The industry giants pushed the bids to US$20 million and then US$25 million. As the price passed US$30 million, Microsoft quit, but it rejoined the bidding at US$37 million. Then Microsoft dropped out a second time. Only Baidu and Google were left, and they pushed the bidding to US$42 million, US$43 million. Finally, at US$44 million, Hinton and his students stopped the auction. The bids were still climbing, but they wanted to work for Google. And the money was staggering. It was an unmistakable sign that deep-pocketed companies were determined to buy the most talented AI researchers – which was not lost on Hassabis at DeepMind. He had always told his employees that DeepMind would remain an independent company. That was, he believed, the best way to ensure its technology didn’t turn into something dangerous. But as Big Tech entered the talent race, he decided he had no choice: It was time to sell. By the end of 2012, Google and Facebook were angling to acquire the London lab, according to three people familiar with the matter. Hassabis and his co-founders insisted on two conditions: No DeepMind technology could be used for military purposes, and its AGI technology must be overseen by an independent board of technologists and ethicists. Google offered $650 million. Mark Zuckerberg of Facebook offered a bigger payout to DeepMind’s founders but would not agree to the conditions. DeepMind sold to Google. The Lost Ethics Board When Musk invested in DeepMind, he broke his own informal rule – that he would not invest in any company he didn’t run himself. The downsides of his decision were already apparent when, only a month or so after his birthday spat with Page, he again found himself face to face with his former friend and fellow billionaire. The occasion was the first meeting of DeepMind’s ethics board, on Aug 14, 2015. The board had been set up at the insistence of the startup’s founders to ensure that their technology did no harm after the sale. The members convened in a conference room just outside Musk’s office at SpaceX, according to three people familiar with the meeting. But that’s where Musk’s control ended. When Google bought DeepMind, it bought the whole thing. Musk was out. Three Google executives now firmly in control of DeepMind were there: Page; Sergey Brin, a Google co-founder and Tesla investor; and Eric Schmidt, Google’s chair. Among the other attendees were Reid Hoffman, another PayPal founder; and Toby Ord, an Australian philosopher studying “existential risk.” The DeepMind founders reported that they were pushing ahead with their work but that they were aware the technology carried serious risks. Eight months later, DeepMind had a breakthrough that stunned the AI community and the world. A DeepMind machine called AlphaGo beat one of the world’s best players at the ancient game of Go. The game, streamed over the internet, was watched by 200 million people across the globe. Most researchers had assumed that AI needed another 10 years to muster the ingenuity to do that. The Breakup Convinced that Page’s optimistic view of AI was dead wrong, and angry at his loss of DeepMind, Musk built his own lab. OpenAI was founded in late 2015. In late 2017, he hatched a plan to wrest control of the lab from Altman and the other founders and transform it into a commercial operation that would join forces with Tesla and rely on supercomputers the car company was developing, according to four people familiar with the matter. When Altman and others pushed back, Musk quit and said he would focus on his own AI work at Tesla. In February 2018, he announced his departure to OpenAI’s staff on the top floor of the startup’s offices in a converted truck factory, three people who attended the meeting said. OpenAI suddenly needed new financing in a hurry. Altman flew to Sun Valley for a conference and ran into Satya Nadella, Microsoft’s CEO. A tie-up seemed natural. The deal closed in 2019. Altman and OpenAI had formed a for-profit company under the original nonprofit, they had $1 billion in fresh capital, and Microsoft had a new way to build AI into its vast cloud computing service. The Reveal After OpenAI received another $2 billion from Microsoft, Altman and another senior executive, Greg Brockman, visited Bill Gates at his sprawling mansion on the shores of Lake Washington, outside Seattle. Over dinner, Gates told them he doubted that large language models could work. He would stay sceptical, he said, until the technology performed a task that required critical thinking – passing an Advanced Placement biology test, for instance. Five months later, on Aug 24, 2022, Altman and Brockman returned and brought along an OpenAI researcher named Chelsea Voss. Voss had been a medalist in an international biology Olympiad as a highschooler. On a huge digital display on a stand outside Gates’ living room, the OpenAI crew presented a technology called GPT-4. Brockman gave the system a multiple-choice advanced biology test, and Voss graded the answers. There were 60 questions. GPT-4 got only one answer wrong. Gates sat up in his chair, his eyes opened wide. In 1980, he had a similar reaction when researchers showed him the graphical user interface that became the basis for the modern personal computer. He thought GPT was that revolutionary. By that October, Microsoft was adding the technology across its online services, including its Bing search engine. And two months later, OpenAI released its ChatGPT chatbot, which is now used by 100 million people every week. OpenAI had beat the effective altruists at Anthropic. Page’s optimists at Google scurried to release their own chatbot, Bard, but were widely perceived to have lost the race to OpenAI. Three months after ChatGPT’s release, Google stock was down 11%. Musk was nowhere to be found. But it was just the beginning. NYTimes More On This Topic

DeepMind Frequently Asked Questions (FAQ)

  • When was DeepMind founded?

    DeepMind was founded in 2010.

  • Where is DeepMind's headquarters?

    DeepMind's headquarters is located at 5 New Street Square, London.

  • What is DeepMind's latest funding round?

    DeepMind's latest funding round is Acquired.

  • Who are the investors of DeepMind?

    Investors of DeepMind include Google, Horizons Ventures, Elon Musk, Jaan Tallinn and Founders Fund.

  • Who are DeepMind's competitors?

    Competitors of DeepMind include Aleph Alpha, Irreverent Labs, MindsDB, Inflection, InstaDeep and 7 more.


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