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Tag: Alexandr Wang

  • How Twelve Labs Teaches A.I. to ‘See’ and Transform Video Understanding: Interview

    Soyoung Lee, co-founder and head of GTM at Twelve Labs, pictured at Web Summit Vancouver 2025. Photo by Vaughn Ridley/Web Summit via Sportsfile via Getty Images

    Sure, the score of a football game is important. But sporting events can also foster cultural moments that slip under the radar—such as Travis Kelce signing a heart to Taylor Swift in the stands. While such footage could be social-media gold, it’s easily missed by traditional content tagging systems. That’s where Twelve Labs comes in.

    “Every sports team or sports league has decades of footage that they’ve captured in-game, around the stadium, about players,” Soyoung Lee, co-founder and head of GTM at Twelve Labs, told Observer. However, these archives are often underutilized due to inconsistent and outdated content management. “To date, most of the processes for tagging content have been manual.”

    Twelve Labs, a San Francisco-based startup specializing in video-understanding A.I., wants to unlock the value of video content by offering models that can search vast archives, generate text summaries and create short-form clips from long-form footage. Its work extends far beyond sports, touching industries from entertainment and advertising to security.

    “Large language models can read and write really well,” said Lee. “But we want to move on to create a world in which A.I. can also see.”

    Is Twelve Labs related to Eleven Labs?

    Founded in 2021, Twelve Labs isn’t to be confused with ElevenLabs, an A.I. startup that specializes in audio. “We started a year earlier,” Lee joked, adding that Twelve Labs—which named itself after the initial size of its founding team—often partners with ElevenLabs for hackathons, including one dubbed “23Labs.”

    The startup’s ambitious vision has drawn interest from deep-pocketed backers. It has raised more than $100 million from investors such as Nvidia, Intel, and Firstman Studio, the studio of Squid Game creator Hwang Dong-hyuk. Its advisory bench is equally star-studded, featuring Fei-Fei Li, Jeffrey Katzenberg and Alexandr Wang.

    Twelve Labs counts thousands of developers and hundreds of enterprise customers. Demand is highest in entertainment and media, spanning Hollywood studios, sports leagues, social media influencers and advertising firms that rely on Twelve Labs tools to automate clip generation, assist with scene selection or enable contextual ad placements.

    Government agencies also use the startup’s technology for video search and event retrieval. Beyond its work with the U.S. and other nations, Lee said that Twelve Labs has a deployment in South Korea’s Sejong City to help CCTV operators monitor thousands of camera feeds and locate specific incidents. To reduce security risks, the company has removed capabilities for facial and biometric recognition, she added.

    Will video-native A.I. come for human jobs?

    Many of the industries Twelve Labs serves are already debating whether A.I. threatens humans jobs—a concern Lee argues is only partly warranted. “I don’t know if jobs will be lost, per se, but jobs will have to transition,” she said, comparing the shift to how tools like Photoshop reshaped creative roles.

    If anything, Lee believes systems like Twelve Labs’ will democratize creative work traditionally limited to companies with big budgets. “You are now able to do things with less, which means you have more stories that can be created from independent creatives who do not have that same capital,” she said. “It actually allows for the scaling of content creation and personalizing distribution.”

    Twelve Labs is not the only A.I. player eyeing video, but the company insists it serves a different need than its much larger competitors. “We’re excited that video is now starting to get more attention, but the way we’re seeing it is a lot of innovation in large language models, a lot of innovation in video generation models and image generation models like Sora—but not in video understanding,” said Lee, referencing OpenAI’s text-to-video A.I. model and app.

    For now, Twelve Labs offers video search, video analysis and video-to-text capabilities. The company plans to expand into agentic platforms that can not only understand video but also build narratives from it. Such models could be useful beyond creative fields, Lee said, pointing to examples like retailers identifying peak foot-traffic hours or security clients mapping the sequence of events surrounding an accident.

    While A.I. might help a Hollywood director assemble a movie, Lee believes it won’t ever be the director. Even if the technology can provide narrative options, humans still decide which story is most compelling, identify gaps and supply the footage. “At the end of the day, I think there’s nothing that can replace human creative intent.”

    How Twelve Labs Teaches A.I. to ‘See’ and Transform Video Understanding: Interview

    Alexandra Tremayne-Pengelly

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  • The Rise of the Chief A.I. Officer: A New Power Player in Corporate C-Suite

    More companies are naming chief A.I. officers as A.I. becomes central to strategy, reshaping corporate power and leadership structures. Unsplash

    When A.I. moved from academia to corporate America, it didn’t just change how companies operate—it reshaped what leadership looks like. A title that barely existed a few years ago is now spreading fast: the chief A.I. officer (CAIO). The role signals how deeply A.I. has become embedded in corporate strategy and identity.

    According to IBM’s 2025 survey, 26 percent of global enterprises now have a chief A.I. officer, up from 11 percent two years ago. More than half (57 percent) were promoted internally, and two-thirds of executives predict that nearly every major company will have one within the next two years.

    The title first appeared in the early 2010s, as deep learning began to take off, but it truly gained momentum after 2023 with the rise of generative A.I. The U.S. government cemented its importance in 2024 through Executive Order 14110, which required every federal agency to appoint a CAIO to oversee A.I. governance and accountability.

    The private sector quickly followed suit. A.I. strategists began moving into the C-suite, marking a new kind of leadership role for the algorithmic age.

    “A.I. was often a specialist function living under the CTO. Organizations realized A.I. was too strategic to be managed as a side project,” Baris Gultekin, software giant Snowflake’s vice president of A.I., told Observer. “In addition to CAIOs, we often hear that Snowflake customers now also have large internal A.I. councils made up of individuals across departments to strategically and effectively facilitate enterprise-wide A.I. adoption.” Gultekin reports through Snowflake’s product leadership to the CEO.

    Some of the most influential chief A.I. officers are already reshaping Big Tech. At Meta, Alexandr Wang, former Scale AI CEO, took on the role in mid-2025, co-leading Meta Superintelligence Labs alongside Nat Friedman, former GitHub CEO. Microsoft’s Mustafa Suleyman, DeepMind co-founder and former Inflection AI CEO, now heads Microsoft AI, overseeing the company’s long-term infrastructure push. At Apple, veteran A.I. leader John Giannandrea, continues to guide the company’s A.I. direction, reporting directly to CEO Tim Cook.

    Companies beyond tech are also joining the trend. Lululemon appointed Ranju Das as its first chief A.I. and technology officer in September to boost personalization and innovation. Consulting giant PwC recently appointed Dan Priest, former VP and CIO at Toyota Financial Services, as its first CAIO for the U.S. market. Even universities, such as UCLA and the University of Utah, have added CAIOs to coordinate campuswide A.I. strategy.

    From CIO to CDO to CAIO

    In the 1980s, chief information officers (CIOs) led the IT revolution; in the 2010s, chief data officers (CDOs) rose with big data; now, CAIOs embody the institutionalization of A.I.

    “CAIOs are responsible for exploring what parts of the business can be safely delegated to A.I. agents, how teams can properly govern A.I. decisions, the types of infrastructure needed to serve context-rich data to A.I. systems, and much more,” Sean Falconer, head of A.I. at data streaming platform Confluent, told Observer. “CDOs ensure the data is clean, while CIOs ensure it’s accessible. CAIOs ensure data becomes actionable and capable of reasoning, predicting and taking autonomous steps on behalf of the business.”

    In industries like banking, health care and retail, CAIOs often act as translators, turning complex A.I. potential into practical results. “They navigate complex legacy processes and cultural resistance, making upskilling and securing organizational willingness to change as critical as building the models themselves,” Snowflake’s Gultekin said.

    The rise of the chief A.I. officer also parallels the growing influence of data engineers. A study by Snowflake and MIT Technology Review Insights found that 72 percent of global executives now view data engineers as essential to business success. More than half said data engineers play a major role in shaping A.I. deployment and determining which use cases are feasible.

    “Businesses will always require a CIO, which has also evolved over the years into providing strategic guidance to the business rather than just simply an IT function. Where we see overlap (with CAIOs) are areas that are critical to a company, like governance, tech enablement and strategic alignment,” Bhaskar Roy, chief of A.I. & product solutions at business automation platform Workato, told Observer. “The mandate for CAIOs is clear: continuously push the boundaries of what’s possible with A.I., and ensure the organization remains at the forefront of technological change, all while listening to customers’ needs and concerns.”

    The Rise of the Chief A.I. Officer: A New Power Player in Corporate C-Suite

    Victor Dey

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  • Elon Musk’s xAI Is Redefining Data Annotation—an Unglamorous But Vital Job in A.I.

    Elon Musk’s A.I. firm is scaling back on “generalist A.I. tutors.” Allison Robbert/POOL/AFP via Getty Images

    Data annotation may not be the most glamorous job in Silicon Valley, but it’s indispensable for A.I. developers and has made companies like Scale AI multibillion-dollar ventures overnight. Training large language models requires armies of humans to label text, images and video so A.I. systems can learn from them. Now, Elon Musk’s xAI is reshaping how that work is done by shifting away from general contractors and toward experts in specialized fields it calls “A.I. tutors.”

    In that vein, xAI recently laid off at least 500 generalist annotators, as reported by Business Insider. The cuts affected about one-third of the company’s 1,500-person annotation team. In emails cited by the outlet, executives described a “strategic pivot” toward hiring domain experts as specialist A.I. tutors.

    “Specialist A.I. tutors at xAI are adding huge value,” said xAI in a Sep. 12 post on X that declared the company will “immediately surge” its specialist A.I. team by tenfold. The company did not respond to requests for comment from Observer.

    What data annotation is and why it matters

    Human annotators play a crucial role in fine-tuning raw data, ensuring it can be used effectively to train models. But the work has long been fraught. Firms that outsource this work, like Scale AI, have faced lawsuits from contractors alleging wage theft, misclassification and exposure to disturbing content without safeguards.

    Unlike rivals that rely heavily on third parties, xAI employs a large in-house annotation team. Other A.I. leaders—including OpenAI and Google—have worked with Scale in the past, though both distanced themselves from the firm after Meta took a 49 percent stake and hired its CEO, Alexandr Wang, to lead its new superintelligence division. Today, many also contract with competitor Surge AI, which counts Anthropic and Microsoft among its clients.

    xAI itself has previously tapped third-party annotators, but is now doubling down on its own staff. The company has posted openings for more than a dozen specialist tutor roles spanning A.I. safety, data science, STEM, finance, Japanese and even “memes and headline commentary.” The latter position involves improving Grok’s ability to “recognize and analyze memes, trolling and virality mechanisms,” according to the listing.

    Qualifications for these roles are steep. For STEM specialists, candidates must hold a master’s or Ph.D. in a relevant field—or have earned medals in competitions like the International Mathematical Olympiad. xAI says tutors can work part-time or full-time and earn between $45 and $100 per hour.

    The changes come as xAI faces wider turnover beyond its annotation team. In July, the company’s head of infrastructure, Uday Ruddarraju, left for rival OpenAI. Co-founder Igor Babushkin departed the following month to launch a venture capital firm. And in September, Mike Liberatore resigned after just three months as chief financial officer.

    Elon Musk’s xAI Is Redefining Data Annotation—an Unglamorous But Vital Job in A.I.

    Alexandra Tremayne-Pengelly

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  • Cracks are forming in Meta’s partnership with Scale AI | TechCrunch

    It’s only been since June that Meta invested $14.3 billion in the data vendor Scale AI, bringing on CEO Alexandr Wang and several of the startup’s top executives to run Meta Superintelligence Labs (MSL). However, the relationship between the two companies is already showing signs of fraying.

    At least one of the executives Wang brought over to help run MSL — Scale AI’s former Senior Vice President of GenAI Product and Operations, Ruben Mayer — has departed Meta after just two months with the company, two people familiar with the matter told TechCrunch. 

    Mayer spent roughly five years with Scale AI across two stints. In his short time at Meta, Mayer oversaw AI data operations teams and reported to Wang, but wasn’t tapped to join the company’s TBD labs — the core unit tasked with building AI superintelligence, where top AI researchers from OpenAI have landed. 

    Mayer did not respond to two separate requests for comment from TechCrunch. 

    Further, TBD Labs is working with third-party data vendors other than Scale AI to train its upcoming AI models, according to five people familiar with the matter. Those third-party vendors include Mercor and Surge, two of Scale AI’s largest competitors, the people said. 

    While AI labs commonly work with several data vendors – Meta has been working with Mercor and Surge since before TBD Labs was spun up –  it’s rare for an AI lab to invest so heavily in one data vendor. That makes this situation especially notable: even with Meta’s multi-billion-dollar investment, several sources said that researchers in TBD Labs see Scale AI’s data as low quality and have expressed a preference to work with Surge and Mercor.

    Scale AI initially built its business on a crowdsourcing model that used a large, low-cost workforce to handle simple data annotation tasks. But as AI models have grown more sophisticated, they now require highly-skilled domain experts—such as doctors, lawyers, and scientists—to generate and refine the high-quality data needed to improve their performance.

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    Although Scale AI has moved to attract these subject matter experts with its Outlier platform, competitors like Surge and Mercor have been growing quickly because their business models were built on a foundation of high-paid talent from the outset.

    A Meta spokesperson disputed the fact that there are quality issues with Scale AI’s product. Surge and Mercor declined to comment. Asked about Meta’s deepening reliance on competing data providers, a Scale AI spokesperson directed TechCrunch to its initial announcement of Meta’s investment in the startup, which cites an expansion of the companies’ commercial relationship. 

    Meta’s deals with third-party data vendors likely mean the company is not putting all its eggs in Scale AI, even after investing billions in the startup. The same can’t be said for Scale AI, however. Shortly after Meta announced its massive investment with Scale AI, OpenAI and Google said they would stop working with the data provider.

    Shortly after losing those customers, Scale AI laid off 200 employees in its data labeling business in July, with the company’s new CEO, Jason Droege, blaming the changes in part on “shifts in market demand.” Droege said Scale AI would staff up in other parts of the business, including government sales — the company just landed a $99 million contract with the U.S. Army.

    Some speculated initially that Meta’s investment in Scale AI was really to lure Wang, a founder who has operated in the AI space since Scale AI was founded in 2016 and who appears to be helping Meta to attract top AI talent. 

    Aside from Wang, there’s an open question around how valuable Scale is to Meta. 

    One current MSL employee says that several of the Scale executives brought over to Meta are not working on the core TBD Labs team, as with Mayer. Further, Meta isn’t exclusively relying on Scale AI for data labeling work.

    Meanwhile, Meta’s AI unit has become increasingly chaotic since bringing on Wang and a wave of top researchers, according to two former employees and one current MSL employee. New talent from OpenAI and Scale AI have expressed frustration with navigating the bureaucracy of a big company, while Meta’s previous GenAI team has seen its scope limited, they said.

    The tensions indicate that Meta’s largest AI investment to date may be off to a rocky start, despite that it was supposed to address the company’s AI development challenges. After the lackluster launch of Llama 4 in April, Meta CEO Mark Zuckerberg grew frustrated with the company’s AI team, one current and one former employee told TechCrunch. 

    In an effort to turn things around and catch up with OpenAI and Google, Zuckerberg rushed to strike deals and launched an aggressive campaign to recruit top AI talent.

    Beyond Wang, Zuckerberg has managed to pull in top AI researchers from OpenAI, Google DeepMind, and Anthropic. Meta has also acquired AI voice startups including Play AI and WaveForms AI, and announced a partnership with the AI image generation startup, Midjourney.

    To power its AI ambitions, Meta recently announced several massive data center buildouts across the U.S. One of the largest is a $50 billion data center in Louisiana called Hyperion, named after a titan in Greek mythology that fathered the God of Sun.

    Wang, who’s not an AI researcher by background, was viewed as a somewhat unconventional choice to lead an AI lab. Zuckerberg reportedly held talks to bring in more traditional candidates to lead the effort, such as OpenAI’s chief research officer, Mark Chen, and tried to acquire the startups of Ilya Sutskever and Mira Murati. All of them declined.

    Some of the new AI researchers recently brought in from OpenAI have already left Meta, Wired previously reported. Meanwhile, many longtime members of Meta’s GenAI unit have departed in light of the changes. 

    MSL AI researcher Rishabh Agarwal is among the latest, posting on X this week that he’d be leaving the company.

    “The pitch from Mark and @alexandr_wang to build in the Superintelligence team was incredibly compelling,” said Agarwal. “But I ultimately choose to follow Mark’s own advice: ‘In a world that’s changing so fast, the biggest risk you can take is not taking any risk’.”

    Asked afterward about his time at Meta and what drove his decision to leave, Agarwal declined to comment.

    Director of product management for generative AI, Chaya Nayak, and research engineer, Rohan Varma, have also announced their departure from Meta in recent weeks. The question now is whether Meta can stabilize its AI operations and retain the talent it needs for its future success.

    MSL has already started working on its next generation AI model. According to reports from Business Insider, it’s aiming to launch it by the end of this year.

    Maxwell Zeff, Marina Temkin

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  • 30-Year-Old Billionaire Says She’s Frugal, Shops Uber Deals | Entrepreneur

    Lucy Guo, 30, saw her net worth reach $1.3 billion in April. But the entrepreneur, who is now the world’s youngest female billionaire, is committed to finding the best deals — even if she can afford to pay full price.

    Guo told CNBC on Wednesday that she remains “frugal,” admitting that she has done things like reserve flights at the airport and cancel them later so she could have a meal for free in the Amex lounge. She also rides UberX, the budget-friendly, low-cost version of Uber, and compares prices for food before buying something to eat. Her closet consists mainly of $10 pieces from stores like Shein.

    “I’m frugal at some things, and I spend more on other things,” Guo told CNBC.

    Lucy Guo. Photo by Gonzalo Marroquin/Getty Images for Passes

    Guo’s fortune was built via Scale AI, the AI data labeling startup she co-founded with Alexandr Wang in 2016. Meta made a $14.3 billion investment in Scale AI in June, acquiring 49% of the startup and allowing the company to achieve a $29 billion valuation.

    Related: These Are the AI Skills You Should Learn Right Now, According to the World’s Youngest Self-Made Billionaire

    Though Guo left Scale AI in 2018, she has held onto a nearly 5% stake in the company, which has grown to be worth $1.25 billion. Despite her billionaire status, Guo says that her life has remained the same.

    “My life pre-money and post-money, it hasn’t really changed that much,” Guo told CNBC Make It earlier this month.

    While Guo may be frugal when it comes to her closet, her food, and her rides to work, she still has the means to spend lavishly in key areas without thinking about the cost.

    For example, when it comes to homes, Guo bought a newly constructed mansion in L.A.’s Hollywood Hills for $29.5 million earlier this year. She got it at a discount: The 5-bedroom, 13,500-square-foot mansion was first listed for $43 million in January 2024.

    Related: Sam Altman’s Mansion Was Once the Most Expensive Home Listing in San Francisco. A New Lawsuit Says It’s a ‘Lemon.’

    Guo is also the owner of a $6.7 million condo in Florida, which she purchased in 2021, as well as another L.A. home, which she bought for $4.2 million last year.

    Guo additionally owns a Ferrari in a vintage rose color, which she admits was a “splurge.” A Ferrari can cost upwards of $230,950. When it comes to transportation, she also sometimes flies via private jet to skip the lines at the airport.

    Guo is a college dropout who studied computer science and human-computer interactions for two years at Carnegie Mellon University, per her LinkedIn. She left to pursue a Thiel Fellowship, which rewards young entrepreneurs for following non-traditional paths and choosing to build a business over going to college. Thiel Fellows receive a $200,000 grant and access to a network of founders to grow their companies.

    Related: ‘We Don’t Believe in Work-Life Balance’: A Newly Acquired Startup Just Offered Its 200-Person Team a Choice — Work Weekends or Take a Buyout

    Guo still puts in long hours at her startup, the creator commerce and monetization platform Passes, which she founded in 2022. Passes has raised a total of $66 million across three funding rounds. She says that the normal working day for her stretches twelve hours, from 9 a.m. to 9 p.m.

    “9 a.m. to 9 p.m., to me, that’s still work-life balance,” Guo told CNBC.

    Lucy Guo, 30, saw her net worth reach $1.3 billion in April. But the entrepreneur, who is now the world’s youngest female billionaire, is committed to finding the best deals — even if she can afford to pay full price.

    Guo told CNBC on Wednesday that she remains “frugal,” admitting that she has done things like reserve flights at the airport and cancel them later so she could have a meal for free in the Amex lounge. She also rides UberX, the budget-friendly, low-cost version of Uber, and compares prices for food before buying something to eat. Her closet consists mainly of $10 pieces from stores like Shein.

    “I’m frugal at some things, and I spend more on other things,” Guo told CNBC.

    The rest of this article is locked.

    Join Entrepreneur+ today for access.

    Sherin Shibu

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  • Meta is licensing Midjourney’s AI image and video tech

    Meta has signed a partnership with Midjourney, an AI service that can generate images and videos from text prompts. According to Alexandr Wang, Meta’s Chief AI Officer, Meta is licensing Midjourney’s “aesthetic technology” for its future models and products. “To ensure Meta is able to deliver the best possible products for people it will require taking an all-of-the-above approach. This means world-class talent, ambitious compute roadmap, and working with the best players across the industry,” Wang added.

    The company previously launched its own AI image generator and AI video editor, but Midjourney’s technology could help Meta offer services that can actually compete with rivals’, such as OpenAI’s Sora and Google’s Veo. Midjourney made V7 its default model for image generation back in June. It described V7 as an “entirely new” AI image generation model that’s much smarter at processing text prompts than its predecessors. It also released its V1 video model, which allows users to turn the images they generate into a short animated video, at the same time. “We are incredibly impressed by Midjourney. They have accomplished true feats of technical and aesthetic excellence, and we are thrilled to be working more closely with them,” Wang said on X.

    This partnership is but Meta’s latest move in its quest to form a Superintelligence laboratory and become a major player in the AI sphere. Mark Zuckerberg went on a hiring spreed and managed to convince several key players from rivals to join his company instead by offering them massive salaries and signing bonuses. Wang himself became the company’s Chief AI office after Meta invested $14.8 billion in Scale AI, the company he founded.

    Mariella Moon

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  • Nvidia’s Billion-Dollar A.I. Pitch: How the Chip Giant Ramps Up Startup Bets

    Nvidia’s Billion-Dollar A.I. Pitch: How the Chip Giant Ramps Up Startup Bets

    Jensen Huang prepares to throw out the ceremonial first pitch before the game between the San Francisco Giants and the Arizona Diamondbacks at Oracle Park on Sept. 03, 2024 in San Francisco. Lachlan Cunningham/Getty Images

    There’s no question that Nvidia (NVDA) is one of the biggest winners of the A.I. boom so far. Funneled by an insatiable demand for its graphics processing units (GPUs), the chipmaker’s stock has skyrocketed by more than 450 percent since early 2023. As Nvidia’s market cap and revenue soar, so does the pace of its investing in A.I. startups. More than half of the company’s startup investments since 2005 took place in the past two years.

    The value of the company’s startup investments reportedly totaled more than $1.5 billion at the beginning of 2024, a significant jump from the $300 million a year prior. The chipmaker has participated in more than ten $100 million-plus funding rounds for A.I. startups in 2024 alone, according to data from Crunchbase, and has backed more than 50 startups since 2023. That’s not to mention a flurry of activity from the company’s venture capital arm NVentures, which separately made 26 investments in 2023 and 2024.

    Nvidia’s seemingly unflappable upward trajectory took a hit yesterday (Sept. 3) after reports surfaced that it had received a subpoena from the U.S. Department of Justice as part of an antitrust probe. The company’s stock dropped nearly 10 percent, shaving $279 billion off its market cap, which currently stands at $2.6 trillion.

    But its falling stock price doesn’t mean the company is slowing down in its startup department. In addition to eyeing an investment in an upcoming funding round in ChatGPT-maker OpenAI, Nvidia yesterday unveiled its participation in a more than $100 million funding round for the Tokyo-based Sakana AI, a company that specializes in accessible A.I. models trained on small datasets.

    “We invest in these companies because they’re incredible at what they do,” Nvidia founder and CEO Jensen Huang told Wired earlier this year. “These are some of the best minds in the world.”

    From companies specializing in humanoid robots to autonomous vehicles, here’s a look at some of Nvidia’s most significant startup investments:

    Perplexity AI

    Huang hasn’t been shy about his love for Perplexity AI, the A.I.-powered search engine positioned as a competitor to the likes of Google. The Nvidia CEO uses the startup’s tool nearly every day for research, according to Huang’s interview with Wired.

    He has also put his money where his mouth is, with Nvidia partaking in a $62.7 million funding round for Perplexity AI in April that valued the startup at $1 billion. Led by investor Daniel Gross, the round included participants like Amazon (AMZN)’s Jeff Bezos. It wasn’t the first time Nvidia has backed the company—the chipmaker also invested in Perplexity AI during another funding round in January that valued the startup at $73.6 million.

    Hugging Face

    Hugging Face, a startup providing open-source A.I. developer platforms, has long had close ties to Nvidia. The chipmaker participated in a $235 million funding round in Hugging Face in August 2023 that valued the company at $4.5 billion. Other corporate investors participating in the round included Google, Amazon, Intel, AMD and Salesforce.

    Hugging Face has previously included Nvidia hardware among its shared resources. In May, it launched a new program that donated $10 million worth of free, shared Nvidia GPUs to be used by A.I. developers.

    Adept AI

    Unlike more well-known A.I. assistants from companies such as OpenAI and Anthropic, Adept AI’s primary product doesn’t center around text or image generation. Instead, the startup is focused on building an assistant that can complete tasks on a computer, such as generating a report or navigating the web, and is able to use software tools. Nvidia is on board, having participated in a $350 million funding round in March 2023.

    Databricks

    After receiving a giant valuation of $43 billion last fall, Databricks became one of the world’s most valuable A.I. companies. The data analytics software provider unsurprisingly uses Nvidia’s GPUs and has been backed by the chipmaker alongside other investors like Andreessen Horowitz and Capital One Ventures, all of whom participated in a $500 million funding round in September 2023. “Databricks is doing incredible work with Nvidia technology to accelerate data processing and generative A.I. models,” said Huang in a statement at the time.

    Cohere

    A formidable opponent to OpenAI and Anthropic, the Canadian startup Cohere specializes in A.I. models for enterprises. The company’s growth over the past five years has attracted backers such as Nvidia, Salesforce and Cisco, which funded Cohere during a round held in July. Nvidia also took part in a May 2023 funding round that brought in some $270 million for the startup.

    Mistral AI

    Mistral AI is a French startup focusing on developing open-source A.I. models. It was founded by former Google DeepMind and Meta employees in April 2023. Nvidia has participated in two of the startup’s fundraising rounds, a $518 million round in June and a $426 million round in December 2023. The collaboration between the two companies doesn’t end there—in July, Nvidia and Mistral AI jointly released a small and accessible language model for developers.

    Figure

    Huang has long reiterated his belief that A.I.-powered robots able to work among humans will constitute the next wave of technology. It is, therefore, no surprise that Nvidia is a backer of Figure, a startup developing humanoid robots for use in warehouses, transportation and retail. Nvidia reportedly funneled $50 million towards the company during a February funding round that raised a total of $675 million and included participants like Bezos and Microsoft.

    Scale AI

    To properly train A.I. tools like OpenAI’s ChatGPT, tech companies need vast amounts of data. This is where A.I. startups like Scale AI, which provides troves of accurately labeled data and is headed by billionaire Alexandr Wang, come in. Nvidia participated in a $1 billion funding round for the company in May alongside Big Tech players like Amazon and Meta.

    Wayve

    Autonomous driving is another area of interest for A.I. leaders across the tech world. Huang himself said that “every single car, someday, will have to have autonomous capability” in a recent interview with Yahoo Finance. One of the startups at the forefront of this wave is the U.K.-based Wayve. Nvidia participated in a $1 billion funding round in the startup in May.

    Inflection AI

    Out of the 92 startups Nvidia has backed throughout the decades, Huang’s company has only been a lead investor in 20 rounds. One of these occurred in June 2023, when Nvidia led a staggering $1.3 billion round for Inflection AI. The chipmaker co-led the round alongside Microsoft, Bill Gates and former Google CEO Eric Schmidt.

    The A.I. startup, which was co-founded by LinkedIn (LNKD) co-founder Reid Hoffman and Google DeepMind co-founder Mustafa Suleyman and most recently valued at $4 billion, produces a chatbot known as Pi. Much of the round’s funding went towards bolstering Inflection A.I.’s computing cluster of 22,000 Nvidia H100 GPUs.

    Nvidia’s Billion-Dollar A.I. Pitch: How the Chip Giant Ramps Up Startup Bets

    Alexandra Tremayne-Pengelly

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