Google’s Demis Hassabis is the man tasked with turning bleeding-edge AI research into profits
Demis Hassabis is a celebrated name in artificial intelligence research. He’s a chess master and a neuroscientist. On Wall Street, he’s less known.
That may not be true for long. Hassabis is emerging as the face of Google’s mammoth AI effort and on Tuesday will take the stage at the annual developer’s conference, Google I/O, for the first time.
For an academic who’s credited with some of the most important breakthroughs in AI over the past decade, Hassabis is extremely clear on his task ahead: bring the latest AI technologies to every corner of the Google universe to serve its billions of users.
“We’re like the engine room of the company,” Hassabis told CNBC, speaking about his newly integrated AI unit within Google.
Last month, Alphabet CEO Sundar Pichai merged Hassabis’ DeepMind with Google Brain, a separate AI team, and selected Hassabis to lead the group. It’s now up to Hassabis to reestablish Google as the leader in generative AI after the company was caught off-guard by the rapid emergence of OpenAI, which is backed by Microsoft.
DeepMind CEO Demis Hassabis at a 2017 event in China.
Source: Alphabet
There may be no more important task at Google, especially as new generative AI services give consumers alternative and more creatives ways to search for information online. The business question is — can a longtime researcher like Hassabis be the person to ship products that consumers love?
Geoffrey Hinton, known as the “Godfather of AI,” says there’s no questioning Hassabis’ will to win.
“I don’t think I’ve ever met anybody more competitive,” said Hinton, who advised Google to buy DeepMind about a decade ago. “Demis is competitive at the level of people who get gold medals in the Olympics.”
He formed that trait at any early age. Hassabis was a child chess prodigy who at one point was the No. 2 rated player in the world. He also competed in the World Series of Poker.
Hassabis says he has consumer experience on his side, too. At just 17 years old, he shipped a hit video game in the 1990s called “Theme Park.” Games at that time had to be fun and easy to navigate in order to succeed, Hassabis said. After Theme Park, he created his own video game company, Elixir Studios.
Hassabis would later go on to co-found DeepMind, which became widely recognized as the world’s leading AI research lab, attracting some of the most prominent experts in deep learning. When Google acquired the lab for a reported $500 million in 2014, DeepMind was given a long leash to operate independently.
Falling behind
Under Hassabis, DeepMind was known for developing its technology through games like Breakout and AlphaGo, an AI program that beat the world’s top Go player.
There was a practical reason for focusing on games. Hassabis told CNBC that “simulations are totally safe, have no consequences, but they can still learn from it.”
During his career at DeepMind and then at Google, Hassabis dominated the field of AI.
Even Tesla CEO Elon Musk would tell OpenAI co-founders in 2018 that they would need billions of dollars to have a chance of competing with Hassabis and Google.
Google, however, would lose that edge as rivals like OpenAI and Microsoft brought headline-making products like ChatGPT and Copilot to market.
A person who has worked with Hassabis but wanted to remain anonymous said that, for a period of time, Hassabis may have been more interested in winning academic accolades than launching products people could use. Nature magazine, one of the most influential scientific journals in the world, has featured Hassabis’ work many times over the past decade.
“Accolades were never the end goal,” DeepMind said in a statement to CNBC. “They simply reflect the importance and impact of the research they recognized.”
One of DeepMind’s most important products, AlphaFold, was a groundbreaking piece of technology that used AI to help scientists predict the structure of proteins, a massive challenges in biology for decades.
DeepMind open sourced AlphaFold, essentially giving it away for free.
In 2017, a team of Google researchers, separate from DeepMind, published a breakthrough study on Transformers, a way for AI models to better process the texts used for training.
Microsoft CEO Satya Nadella (R) speaks as OpenAI CEO Sam Altman (L) looks on during the OpenAI DevDay event in San Francisco on Nov. 6, 2023.
Justin Sullivan | Getty Images
That jumpstarted the wave of AI innovation that followed, notably at OpenAI. Transformers is the “T” in ChatGPT.
Critics have argued that Google was giving away key products and research, and helping its biggest competitors.
“They had the lead and they’ve been very cautious,” Hinton said. “They’ve been very cautious both about generative AI images, and about the large language models. And when OpenAI teamed up with Microsoft and ChatGPT was being used by Microsoft, Google couldn’t afford to be cautious anymore.”
Hassabis and Google went on offense.
The Washington Post reported in May 2023 that Google was internally announcing a big departure from previous policy. Employees had to stop sharing their research with the world, only publishing papers after the research had been turned into products.
AlphaFold became a huge business opportunity, securing commercial partners like Eli Lilly and Novartis for drug discovery.
During a TED talk, Hassabis said the ChatGPT moment demonstrated that the public found value in LLMs and was ready to embrace them.
“When we’re working on these systems, mostly you’re focusing on the flaws and the things they don’t do and hallucinations,” he said. “We wanted to improve those things first before putting them out. But interestingly, it turned out that even with those flaws, many tens of millions of people still find them very useful.”
Hassabis said that it was time to bring these products “beyond the rarefied world of science.”
Now investors are waiting to see if Google can accomplish what they view as the most important feat, and turn that bleeding-edge science into profits.
Technology
Amazon aims to expand advertising business by letting retailers use its ad tools on their stores
BARCELONA, SPAIN – MARCH 2: The Amazon ads logo, the advertising solutions service formerly known as AMD or Amazon Marketing Services, during the Mobile World Congress 2023 on March 2, 2023, in Barcelona, Spain. (Photo by Joan Cros/NurPhoto via Getty Images)
Nurphoto | Nurphoto | Getty Images
Amazon has turned into an online ad juggernaut in recent years, with brands paying big bucks for premium placement on the retailer’s websites. Now, Amazon is letting other sites use its ad technology for their own stores.
The new offering, called Amazon Retail Ad Service, allows companies to show “contextually relevant ads in the right place and at the right time” in search results, product pages and other areas of their site, Amazon said Thursday.
It’s initially available for U.S. retailers, which will pay fees based on usage levels. Prices weren’t disclosed.
Amazon in 2022 began breaking out ad revenue in its quarterly earnings reports, showing that the business had become a significant contributor to the company’s top and bottom lines. Ad revenue in the latest quarter came in at $14.3 billion, third to Alphabet and Meta in digital advertising.
That’s still much less than the sales Amazon generates from online stores and cloud computing, which came to $61.4 billion and $27.4 billion, respectively, in the quarter that ended in October.
The bulk of Amazon’s ad revenue comes from sponsored product advertisements, which are keyword-targeted ads that let brands promote certain items. Amazon has stuffed more of these sponsored items into search results and product pages over time. It also generates some ad revenue through streaming.
With Amazon Retail Ad Service, users will be able to customize the design, placement and number of ads shown across their sites, as well as use Amazon’s ad measurement and reporting tools.
Amazon said the service operates on systems that are separate from its own retail business, and retailers manage their data via AWS accounts.
The service could provide Amazon with valuable data it can use to bolster its ad prediction and recommendation technology. The company said early customers include health and wellness retailer iHerb, Asian grocery startup Weee! and Oriental Trading Co., which sells toys, party and craft supplies.
“We’ve designed this to be a win for retailers, advertisers, and shoppers, and we look forward to seeing how it improves outcomes, drives sales and enhances the shopping experience,” said Paula Despins, vice president of Amazon Ads Measurement, in the press release.
The announcement comes a few days before the National Retail Federation’s annual trade show.
It’s not the first time Amazon has sold its in-house technology and services to third parties.
Amazon Web Services began as cloud infrastructure to support its online retail business. The company launched AWS as a business in 2006. In 2022, the company launched Buy With Prime, which combines Amazon’s payment and fulfillment services for other retailers.
Technology
Cohere co-founder sees big AI opportunity in enterprise, happy to stay out of ChatGPT’s way
Omar Marques | Lightrocket | Getty Images
Cohere co-founder Nick Frosst is surrounded by chatter of artificial general intelligence, or AGI. He’s perfectly happy to stay out of the conversation.
Founded in 2019, by ex-Google AI researchers, Cohere is valued in the billions of dollars and is one of the more high-profile names in the world of generative AI, which has exploded since OpenAI debuted ChatGPT in late 2022.
But it’s not a company that’s well known among consumers, who have swarmed to chatbots and other tools from OpenAI, Google and Perplexity. Rather, Cohere is all about business.
“I’m in meetings with companies in health care, banking and IT all the time,” Frosst told CNBC in an interview this week. “The questions I get are about securely automating tasks like HR, payrolls, research and fraud detection to drive productivity. No one has ever asked me about achieving AGI, let alone ASI.”
The latter is short for artificial superintelligence, or AI that significantly surpasses human intelligence. OpenAI and Anthropic have both made it their goal to achieve it.
In its latest funding round in July, Cohere raised $500 million at a $5.5 billion valuation, more than doubling its valuation from the prior year. Investors in the company include Nvidia, AMD, Salesforce and Oracle.
While that would historically be a huge price tag for a company that’s not even five years old, it’s a fraction of what investors are paying for OpenAI, valued at $157 billion in a round announced in October, and Anthropic, which CNBC confirmed this week is in talks to raise funding at a $60 billion valuation.
Some of Cohere’s chief competitors in the AI arms race offer products for both consumers and businesses. OpenAI, for instance, launched ChatGPT Enterprise in 2023, and Anthropic rolled out Claude Enterprise in September.
Frosst said Cohere’s preference for the enterprise is centered around the idea that large language models are best at automating tedious tasks and “being a co-worker.”
“Really, it’s an automation tool,” Frosst said. “When I think about my personal life, there’s actually not a ton that I want to automate. I don’t want to write text messages to my friends faster. I don’t want to respond to emails more efficiently in my own life. But in my work life, I really, really do want to do that.”
Frosst said, “I want to be free to think creatively and not be bogged down.”
Shortly after closing its funding round in July, Cohere cut about 20 jobs. A company representative said at the time it was an “internal realignment” and that Cohere had a “clear vision for the future.”
That vision includes going all-in on AI agents.
While the term AI agents isn’t neatly defined, it’s generally meant to describe AI services that go a step beyond chatbots. Agents are typically designed for specific business functions, rather than general purpose, and can be customized on the big AI models.
They can perform multistep, complex tasks on a user’s behalf and generate their own to-do lists, so that users don’t have to walk them through the process step-by-step.
Staying capital efficient
On Thursday, Cohere debuted its early access program for its AI agent platform called North, which is focused on allowing users with any level of technical background to “instantly customize and deploy AI agents” and do so “with just a few clicks,” the company said in a press release. Users can search for information across their organizations in multiple languages and in divisions with programs that weren’t previously connected.
That includes summarizing questions and answers in HR, speeding up the amount of time spent on finance reports and automating some core business functions in customer support and IT.
Frosst said that the platform can be used in any industry, but the company plans to target finance and health care, where data privacy and regulation are paramount.
Martin Kon, Cohere’s operating chief, told CNBC in March that by staying focused on enterprise AI, the company is able to run efficiently and keep expen under control even amid a chip shortage, rising costs for Nvidia’s graphics processing units (GPUs) and ever-changing licensing fees for AI models.
Frosst says those dynamics are still at play, allowing Cohere to be “more capital-efficient,” which is increasingly “of interest to investors.” Rivals with popular consumer-facing AI products, he said, use a lot of compute on “consumer applications and science projects.”
Although the sales cycle for enterprise AI can be longer, Frosst said, “the recurring business we’ve been able to create is something that’s really resonating with investors now.”
Competition is stiff and the technology is quickly evolving.
In October, Anthropic said its AI agents had the ability to use a computer like a human would in order to complete complex tasks. The feature, called Computer Use, allows its technology to interpret what’s on a computer screen, select buttons, enter text, navigate websites and execute tasks through any software and real-time internet browsing.
OpenAI reportedly plans to introduce a similar feature soon. And last year, executives from Microsoft, Meta and Google regularly touted their goals to push AI assistants to become increasingly productive.
Even without a consumer business, Cohere has to spend heavily on Nvidia’s costly GPUs, which are in huge demand for companies that are training models and running big workloads. In Cohere’s early days, the company secured a reserve of Google chips to help it pretrain its models. Over the past year, Cohere has moved more toward Nvidia’s H100 GPUs.
“We’ve increased our spend on them, because they’re working really well,” Frosst said.
WATCH: Cohere CEO Aidan Gomez on how his AI models make money for companies
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