• AMD CEO Lisa Su and Nvidia CEO Jensen Huang are first cousins once removed, a researcher said.
• Su told Bloomberg they did not grow up together and were "really distant."
• "No family dinners," she said. "It is an interesting coincidence."

AMD CEO Lisa Su said in a recent interview that she never met Nvidia CEO Jensen Huang, her competitor and distant relative, until later in their careers.

"We were really distant, so we didn't grow up together," Su said in an interview with Bloomberg's Emily Chang published Thursday. "We actually met at an industry event. So it wasn't until we were well into our careers."

Former journalist and genealogist Jean Wu said last year that Su and Huang, both Taiwanese chief executives of global chip powerhouses, are first cousins, once removed. Huang, 61, is the older cousin to Su, 55. Huang's mother is a sister to Su's grandfather, a condensed family tree Wu published on her Facebook account showed.

Su confirmed the familial relationship with her competitor in 2020, saying that the two are "distant relatives, so some complex second cousin type of thing."

An Nvidia spokesperson confirmed to CNN last year that Su is Huang's distant cousin through his mother's side.

An Nvidia spokesperson declined to comment on this story, and an AMD spokesperson did not immediately respond to a request for comment.

Huang and Su have eerily similar career paths but different upbringings.

Su was born in Tainan, whereas Huang was born in Taiwan's capital, Taipei.

The AMD CEO later moved to the US, where she grew up in New York and studied at the Massachusetts Institute of Technology.

Huang lived in Washington and Kentucky before settling in Oregon. He later attended Oregon State University.

Su said in the Bloomberg interview that she has a large family she visits when she travels back to Taiwan.

"My dad had like nine siblings, and my mom had like six, so it was like a big family," she said. "So there are lots and lots of cousins and aunts and uncles."

Despite their familial ties, Su and Huang never crossed paths at those family gatherings.

"No family dinners," she said. "It is an interesting coincidence."

• Brian Chesky and Nvidia's Jensen Huang avoid one-on-one meetings with subordinates.
• "You become like their therapist," Chesky told Fortune.
• Yet one person who studies meetings said making an employee feel heard can have "amazing" outcomes.

Meetings are the main way Airbnb's Brian Chesky gets work done. Yet he says the one-on-one format with a direct report is fundamentally flawed.

"Almost no great CEO in history has ever done them," the Airbnb chief said in a recent interview.

That's because when an employee "owns the agenda," they bring up subjects managers don't want to discuss — and "you become like their therapist," Chesky said. Topics can also arise that would benefit other people at the company to hear, but instead, they're sequestered in a one-on-one.

Of course, there are certain times when a one-on-one makes sense, Chesky told Fortune in the interview — such as when an employee is having a difficult time personally and needs to confide to a boss privately.

But generally, he said, they're just not productive on a regular basis.

Chesky isn't alone. Although he has many direct reports, Nvidia CEO Jensen Huang also prefers to skip one-on-one meetings.

"I don't really believe there's any information that I operate on that somehow only one or two people should hear about," Huang said at Stripe Sessions earlier this year.

Making employees feel heard can have 'amazing' outcomes

While some leaders are cracking down, one expert previously told Business Insider that, when conducted correctly, one-on-ones can boost employee engagement, productivity, and overall happiness.

"The outcomes associated with effective one-on-ones are amazing," said Steven G. Rogelberg, an organizational psychologist who's also a professor at the University of North Carolina at Charlotte and the author of "Glad We Met: The Art and Science of 1:1 Meetings."

Rogelberg previously told BI that one-on-ones are more successful when the worker leads the conversation. He said managers should dedicate roughly 25 minutes a week and focus on the personal needs of employees as well as the practical aspects of the job.

Many managers avoid that first component, Rogelberg said, because it takes more effort.

But at the same time, workers need to do their due diligence, he said — showing up prepared to talk more than half the time. Some fruitful topics include: challenges, how a manager can better support a worker, and what's going well and what could be improved.

'Nitpicking sessions'

Chesky isn't the only boss who's over the one-on-one. In May, Aditya Agarwal, a former Facebook director, wrote in a post on X that after more than a decade of conducting such meetings with those who report to him, he determined they did more harm than good.

"They condition people to do spot checks on happiness and constantly be critical about things that aren't ideal. In practice, 1:1s descend into nitpicking sessions," Agarwal wrote as part of a thread.

Agarwal added that bosses should give feedback every three to six months rather than weekly. That approach, he said, could drive managers to pick up on patterns and give "holistic" guidance rather than weekly spot checks.

• Nvidia's gaming past and mastering of the GPU made it well-positioned for the AI boom.
• Its next market to corner is advanced robotics that could give way to humanoids.
• Technical hurdles could be a reality check for Jensen Huang's robotics future.

Wearing his signature black leather jacket, Jensen Huang outstretched both arms, gesturing at the humanoid robots flanking him, and the audience applauded. "About my size," he joked from the stage at Computex 2024 in Taipei, Taiwan, in June.

"Robotics is here. Physical AI is here. This is not science fiction," he said. The robots, though, were flat, generated on a massive screen. What came onto the stage were wheeled machines resembling delivery robots.

Robots are a big part of Huang's vision of the future, which is shared by other tech luminaries, including Elon Musk. In addition to the Computex display, humanoid robots have come up on Nvidia's latest two earnings calls.

Most analysts agree that Nvidia's fate is all but sealed for a few years. Demand for graphics processing units has fueled it to a $3 trillion market capitalization — some days. But the semiconductor industry is cruel. Investment in data centers, which make up 87% of Nvidia's revenue, comes in booms and busts. Nvidia needs another big market.

At Computex, Huang said there would be two "high-volume" robotic products in the future. The first is self-driving cars, and the second is likely to be humanoid robots. Thanks to machine learning, the technologies are converging.

Both machines require humanlike perception of fast-changing surroundings and instantaneous reactions with little room for error. They also both require immense amounts of what Huang sells: AI computing power. But robotics is a tiny portion of Nvidia's revenue today. And growing it isn't just a matter of time.

If Nvidia's place in the tech stratosphere is to be permanent, Huang needs the market for robotics to be big. While the story of Nvidia's past few years has been one of incredible engineering, foresight, and timing, the challenge to make robots real may be even tougher.

How can Nvidia bring on the robots?

Artificial intelligence presents a massive unlock for robotics. But scaling the field means making the engineering and building more accessible.

"Robotic AI is the most complicated because a large language model is software, but robots are a mechanical-engineering problem, a software problem, and a physics problem. It's much more complicated," Raul Martynek, the CEO of the data-center landlord DataBank, said.

Most of the people working on robotics are experts with doctoral degrees in robotics because they have to be. The same was true of language-based AI 10 years ago. Now that foundation models and the computing to support them are widely available, it doesn't take a doctorate to build AI applications.

Layers of software and vast language and image libraries are intended to make users stickier and lower the barrier to entry so that almost anyone can build with AI.

Nvidia's robotics stack needs to do the same, but since using AI in physical spaces is harder, making it work for laypeople is also harder.

The Nvidia robotics stack takes some navigating. It's a sea of platforms, libraries, and names.

Omniverse is a simulation platform. It offers a virtual world that developers can customize and use to test simulations of robots. Isaac is what Nvidia calls a "gym" built on top of Omniverse. It's how you put your robot into an environment and practice tasks.

Jetson Thor is Nvidia's chip for powering robots. Project Groot, which the company refers to as a "moonshot" initiative, is a foundation model for humanoid robots. In July, the company launched a synthetic-data-generation service and Osmo, a software layer that ties it all together.

Huang often says that humanoids are easier to build because the world is already made for humans.

"The easiest robot to adapt in the world are humanoid robots because we built the world for us," he said at Computex, adding: "There's more data to train these robots because we have the same physique."

Gathering data on how we move still takes time, effort, and money. Tesla, for example, is paying people $48 an hour to perform tasks in a special suit to train its humanoid, Optimus.

"That's been the biggest problem in robotics — how much data is needed to give those foundational models an understanding of the world and adjust for it," Sophia Velastegui, an AI expert who's worked for Apple, Google, and Microsoft, said.

But analysts see the potential. The research firm William Blair's analysts recently wrote, "Nvidia's capabilities in robotics and digital twins (with Omniverse) have the potential to scale into massive businesses themselves." The analysts said they expected Nvidia's automotive business to grow 20% annually through 2027.

Nvidia has announced that BMW uses Isaac and Omniverse to train factory robots. Boston Dynamics, BYD Electronics, Figure, Intrinsic, Siemens, and Teradyne Robotics use Nvidia's stack to build robot arms, humanoids, and other robots.

But three robotics experts told Business Insider that so far, Nvidia has failed to lower the barrier to entry for wannabe robot builders like it has in language- and image-based AI. Competitors are coming in to try to open up the ideal stack for robotics before Nvidia can dominate that, too.

"We recognize that developing AI that can interact with the physical world is extremely challenging," an Nvidia spokesperson told BI via email. "That's why we developed an entire platform to help companies train and deploy robots."

In July, the company launched a humanoid-robot developer program. After submitting a successful application, developers can access all these tools.

Nvidia can't do it alone

Ashish Kapoor is acutely aware of all the progress the field has yet to make. For 17 years, he was a leader in Microsoft's robotics-research department. There, he helped to develop AirSim, a computer-vision simulation platform launched in 2017 that was sunsetted last year.

Kapoor left with the shutdown to make his own platform. Last year, he founded Scaled Foundations and launched Grid, a robotics-development platform designed for aspiring robot builders.

No one company can solve the tough problems of robotics alone, he said.

"The way I've seen it happen in AI, the actual solution came from the community when they worked on something together," Kapoor said. "That's when the magic started to happen, and this needs to happen in robotics right now."

It feels like every player aiming for humanoid robots is in it for themselves, Kapoor said. But there's a robotics-startup graveyard for a reason. The robots get into real-world scenarios, and they're simply not good enough. Customers give up on them before they can get better.

"The running joke is that every robot has a team of 10 people trying to run it," Kapoor said.

Grid offers a free tier or a managed service that offers more help. Scaled Foundations is building its own foundation model for robotics but encourages users to develop one, too.

Some elements of Nvidia's robotics stack are open source. And Huang often says that Nvidia is working with every robotics and AI company on the planet, but some developers fear the juggernaut will protect its own success first and support the ecosystem second.

"They're doing the Apple effect. To me, they're trying to lock you in as much as they can into their ecosystem," said Jonathan Stephens, the chief developer advocate at the computer-vision firm EveryPoint.

An Nvidia spokesperson told BI that this perception was inaccurate. The company "collaborates with the majority of the leading players in the robotics and humanoid developer ecosystem" to help them deploy robots faster. "Our success comes from the ecosystem," they said.

Scaled Foundations and Nvidia aren't the only ones working on a foundation model for robotics. Skild AI raised $300 million in July to build its version.

What makes a humanoid?

Simulators are an essential stop on the path to humanoid robots, but they don't necessarily lead to humanlike perception.

When describing a robotic arm at Computex, Huang said that Nvidia supplied "the computer, the acceleration layers, and the pretrained AI models" needed to put an AI robot into an AI factory. The goal of using robotic arms in factories at scale has been around for decades. Robotic arms have been building cars since 1961. But Huang was talking about an AI robot — an intelligent robot.

The arms that build cars are largely unintelligent. They're programmed to perform repetitive tasks and often "see" with sensors instead of cameras.

An AI-enabled robotic arm would be able to handle varied tasks — picking up diverse items and putting them down in diverse places without breaking them, maybe while on the move. They need to be able to perceive objects and guardrails and then make moves in a coherent order. But a humanoid robot is a world away from even the most useful nonhumanoid. Some roboticists doubt that it's the right target to aim for.

"I'm very skeptical," said a former Nvidia robotics expert with more than 15 years in the field who was granted anonymity to protect industry relationships. "The cost to make a humanoid robot and to make it versatile is going to be higher than if you make a robot that doesn't look like a human and can only do a single task but does the task well and faster."

But Huang is all in.

"I think Jensen has an obsession with robots because, ultimately, what he's trying to do is create the future," Martynek said.

Autonomous cars and robotics are a big part of Nvidia's future. The company told BI it expected everything to be autonomous eventually, starting with robotic arms and vehicles and leading to buildings and even cities.

"I was at Apple when we developed iPad inspired by 'Star Trek' and other future worlds in movies," Velastegui said, adding that Robotics taps into our imagination.

• TSMC founder Morris Chang asked Nvidia founder Jensen Huang to take over as CEO in 2013.
• In a new memoir, Chang reveals he set out his vision for TSMC for 10 minutes before Huang declined.
• Huang said, "I already have a job," Chang recalled.

The founder of Taiwanese chip giant TSMC has revealed he once asked Jensen Huang if he would succeed him as the company's CEO.

But Huang, the founder and CEO of AI chipmaker Nvidia, turned the role down in less than 10 minutes and said "I already have a job," Morris Chang wrote in his memoir, published Friday.

In the memoir, Chang writes he was looking for a successor to lead TSMC in 2013. He said that Huang's character, professional background, and deep knowledge of the semiconductor space made him an ideal frontrunner for the role.

Huang listened intently as Chang spent 10 minutes explaining his ambitions for TSMC, but said he was determined to keep his focus on Nvidia, Chang writes.

Nvidia has since become one of the world's most valuable companies, fuelled by the AI boom. Huang has been CEO and president since founding it in 1993.

Huang and Chang have shared an amiable relationship that spans their professional endeavors.

In the early years after its launch, Nvidia exclusively partnered with TSMC to produce its chips. In 1998, TSMC helped supply Nvidia with production workers when it was short-staffed.

Nvidia now works with various chipmakers but remains one of TSMC's biggest customers, along with Apple.

Having founded TSMC in 1987, Chang, 93, stood down as CEO in 2018 and was replaced by C C. Wei, the current CEO. According to Forbes, Chang has a personal wealth of $4.1 billion.

The latest memoir, his second volume of autobiography, details his life from 1964 to 2018.

• Jensen Huang is becoming more of a household name as Nvidia's value skyrockets amid the AI boom.
• The CEO has some unusual management practices, including having 60 direct reports and no 1-on-1s.
• Here are some of Huang's most notable tips when it comes to business leadership and management.

Nvidia overtook Apple and Microsoft separately earlier this month to briefly become the world's most valuable company.

With the AI chip company's stock skyrocketing, Huang has also seen his fame — and fortune — grow, and there are plenty of eyes on him to see how he runs one of the world's biggest companies.

Here is some of Huang's most notable advice for leading teams and managing a business.

Manage a lot of people

Huang believes a CEO should have more direct reports than anyone else in an organization. He, in fact, has 60 direct reports, considered an unusually high number for any manager.

"The more direct reports the CEO has, the less layers are in the company," Huang said in an interview at The New York Times DealBook Summit in 2023. "It allows us to keep information fluid, allows us to make sure that everyone is empowered by information."

Management exists "in service of all the other people that work at the company," he said in a separate interview with Stanford's Graduate School of Business earlier this year.

"I don't believe in a culture, in an environment, where the information you possess is the reason why you have power," he said.

Be transparent with decision-making

Asked how he manages 60 direct reports, Huang told an audience at Hong Kong University Of Science & Technology that it boils down to one thing.

"Transparency," he said.

"I reason in front of everybody what we need to do. We work together to come up with a strategy," he said. "Whatever strategy it is, everybody hears it at the same time because they were hearing all of us work through the strategy at the same time."

His job is then to make sure everyone comes away from the process with the same takeaway.

"I'm usually the last person to talk, to describe, based on everything that we've done, 'This is the direction, and these are the priorities,'" he added. "And to make sure that, if there's any ambiguity, I've taken out the ambiguity. Now once we're all aligned and we understand what the strategies are, I count on the fact that everyone is an adult."

"Nobody loses alone," he said. "Nobody fails alone."

Skip the 1:1 meetings

Huang has said he doesn't have one-on-one meetings with his many direct reports.

"Almost everything that I say, I say to everybody all at the same time," he said at Stripe Sessions 2024. "I don't really believe there's any information that I operate on that somehow only one or two people should hear about."

Give feedback publicly

In the same vein, Huang also believes in giving someone feedback in front of their peers.

"The problem I have with one-on-ones and taking feedback aside is you deprive a whole bunch of people that same learning," he said at Stripe Sessions. "Feedback is learning. For what reason are you the only person who should learn this?"

He added that learning from other people's mistakes is "the best way to learn.

"Why learn from your own mistakes? Why learn from your own embarrassment? You've got to learn from other people's embarrassment," he said.

Communicate briefly and often

Nvidia employees can expect to receive a lot of emails from their chief executive. Huang sends his staff hundreds of emails a day, many of which are only a few words long, The New Yorker reported last year.

He expects employees to keep their email communications just as concise.

One former Nvidia worker told Business Insider's Jyoti Mann that "you'd get in trouble for sending a super-long email to him."

"The idea was to nail down what you have to say, send it, and if he, or others, need more information, then it's a conversation, not another email," the former Nvidian said.

Show your work

Huang believes showing others how you reason through a problem is "empowering."

"I show people how to reason through things all the time — strategy things, how to forecast something, how to break a problem down, and you're just empowering people all over the place," he said in the Stanford Graduate School of Business interview.

He continued: "If you send me something and you want my input on it and I can be of service to you and in my review of it, share with you how I reasoned through it, I've made a contribution to you. I've made it possible to see how I reason through something."

That can lead to a lightbulb moment.

"You go, 'Oh my gosh. That's how you reason through something like this. It's not as complicated as it seems.'"

• Nvidia's workforce has grown nearly 20-fold since 2003.
• The company's stock price surge and low turnover have enriched many long-term employees.
• Nvidia's median salary now surpasses Microsoft's and other Silicon Valley peers.

Nvidia was largely unknown just a few years ago.

In 2022, google searches for Jensen Huang, the company's charismatic CEO, were almost nonexistent. And Nvidia employees were not nearly the source of fascination and interest they are today.

Nvidia recruiters are now swamped at conferences, and platforms like Reddit and Blind are full of eager posters wondering how to land a job or at least get an interview at the company, which has around 30,000 employees.

They want to know how many Nvidians are millionaires — likely quite a few.

The skyrocketing stock price has made that the case, but so has the longevity of its employees. Twenty-year-plus tenures are not uncommon, and even now when AI talent has never been more prized, staff turnover has been falling in recent years. In January, the company reported a turnover rate of 2.7%. Tech industry turnover below 20% is notable, an HR firm told Business Insider earlier this year.

The data behind the evolution of Nvidia's workforce tells the story of the company's meteoric rise just as well, if not better than the revenue or stock price. Until the early 2000s, the chip design company, which was founded in 1993, was relatively under the radar. Here is Nvidia's story in four charts.

Nvidia's workforce has grown nearly 20-fold since 2003

Beyond Nvidia's historic rise in market value, the company has a lot to offer employees. It maintains a permissive remote work policy even as tech giants like Amazon mandate a return to the office. It has also built an appropriately futuristic new Santa Clara, California, headquarters which robotics leader Rev Lebaredian described to Business Insider as so tech-infused it is a "type of robot."

But the culture isn't for everyone.

Public feedback, for example, is a very intentional part of the workplace culture. Huang famously has dozens of direct reports and eschews one-on-one meetings, preferring to call out mistakes in public rather than saving harsh feedback for private conversation, so that everyone can learn.

Nvidia has become one of the best-paying firms in Silicon Valley

Four years ago, Nvidians' median salary wasn't at the top of the market. In 2019, Microsoft's median employee salary was nearly $20,000 higher than an Nvidia worker. But as of January 2024, Nvidia's median salary (excluding the CEO) surpassed Microsoft and has left other tech giants in the dust.

Yet, this chart only reports on base compensation.

Years of stock-based compensation and "special Jensen grants," along with four-digit growth in the stock price within the last decade, have led to wealthy employees and, at times, internal tension surrounding rich Nvidia employees not pulling their weight.

Certainly, not all Nvidians are millionaires and the compensation the company is required to report to shareholders every Spring isn't quite the full picture. Still, Huang has repeatedly said that despite Nvidia's AI dominance, he wakes up worrying about staying on top.

Nvidia's revenue per employee has recovered after years of investment

Divide the company's revenue by its employee headcount and its financial strategy shows through.

Beginning in 2006, long before using graphics processing units to run AI models was commonplace, Nvidia invested in building a programming software layer called compute unified device architecture (CUDA).

Nvidia's GPUs are capable of immense computing capacity at nearly unprecedented speed because they perform calculations simultaneously rather than one at a time. Instructing these powerful chips required a new software paradigm.

CUDA is that paradigm and building it took years and cost Nvidia dearly. In hindsight, the benefit of this investment period is undeniable. CUDA is the main element that keeps AI builders from easily or willingly switching to competing hardware like AMD's MI325 and Amazon's Trainium chips.

It's not a literal translation of every employee's contribution, but looking at the revenue-to-headcount ratio can show trends in efficiency, investment, and return.

Nvidia's revenue-to-headcount ratio showed a downward trend from 2003 until 2014, and then steady upward progress until the AI boom in 2023. During that year, this ratio doubled.

CUDA is likely not the only factor affecting this data point, but it may help explain why investors questioned CUDA expenditures for years — and why they no longer do.

But the company isn't as far ahead in other areas.

Nvidia has less than one in five women employees — but it has pay parity

Despite the dizzying progress of Nvidia's technological achievements, gender representation in the company's workforce and the semiconductor industry as a whole has remained relatively unchanged in the last decade. As of January 2024, Nvidia's global workforce was 19.7% female.

Nvidia's stats are in line with the industry totals for female representation, but ahead of the pack when it comes to women in technical and management positions.

According to a 2023 Accenture analysis, the median representation of women in the semiconductor industry is between 20% and 29%, up from between 20% and 25% in 2022. Over half of the companies in the sample reported less than 10% representation of women in technical director roles and less than 5% in technical executive leadership roles.

In January Nvidia reported that women at the company make 99.5% of what men make in terms of baseline compensation. For the last two years, the turnover rate for women at the company has been slightly lower than that for men.

Nvidia declined to comment on this dynamic when BI reported on it in September.

Do you work at Nvidia? Have a tip or an insight to share? Contact Emma at [email protected] or use the secure messaging app Signal: 443-333-9088

• Nvidia CEO Jensen Huang uses AI chatbots for learning by questioning their reasoning.
• Huang's method involves asking AI to explain answers and apply reasoning to new contexts.
• Companies like Google and Khan Academy are developing AI tools for educational purposes.

Jensen Huang's method of learning from AI probably sounds more like an interrogation.

During an interview at Hong Kong University, the Nvidia CEO encouraged people to "get an AI as a tutor," revealing that he often talks to his chatbot in order to learn more.

"I use my AI," he said, "and I torture my AI to teach me."

Huang's form of "torture" involves asking the AI a question and then five follow-up queries. First, he asks why it gave its answer. Then, he prompts the AI to break it down to him "step by step." Next, he has it explain its reasoning in different ways.

He then asks the chatbot to "apply this reasoning to something else" and finally requests some analogies.

While Huang's preferred learning process is drilling chatbots with questions, companies are developing more specialized tools for teaching users. In November, Google launched "Learn About," a new AI tool that acts as a conversational learning guide for users exploring educational topics.

In March, education platform Khan Academy introduced its chatbot, Khamingo, designed to help students with various subjects such as math, writing, and programming. Powered by OpenAI's GPT-4, the chatbot doesn't provide answers outright but guides users on how to solve problems.

Founder Sal Khan said in a TED Talk that he predicts each student will eventually have an "artificially intelligent, but amazing, personal tutor." Some teachers are already incorporating AI into their curriculum for more personalized teaching assistance with each student.

• The world's 10 biggest wealth gainers have grown $790 billion richer in 2024.
• Elon Musk leads the list with a $257 billion gain that has boosted his net worth to $486 billion.
• Mark Zuckerberg, Jeff Bezos, Larry Ellison, and Jensen Huang are all up more than $70 billion.

Ten people have grown their personal fortunes by a combined $790 billion this year — a figure larger than the market value of Walmart ($767 billion).

The biggest wealth gainers of 2024 include Tesla CEO Elon Musk, Meta CEO Mark Zuckerberg, Amazon chairman Jeff Bezos, Oracle chairman Larry Ellison, and Nvidia CEO Jensen Huang, according to the Bloomberg Billionaires Index.

The buzz around artificial intelligence, a solid outlook for the US economy, and market expectations about Donald Trump's second term in office have boosted their companies' stock prices, benefiting them as major shareholders.

Here are the 10 greatest wealth builders this year as of the market close on Tuesday, December 17.

1. Elon Musk

Year-to-date wealth gain: $257 billion

Net worth: $486 billion

Source of wealth gain: Tesla and SpaceX stock

Elon Musk is the CEO of automaker Tesla and spacecraft manufacturer SpaceX. He's also the owner of X, the social network previously known as Twitter, along with Neuralink, xAI, and The Boring Company.

Musk's $257 billion wealth gain this year exceeds the total net worth of Jeff Bezos, the second-richest person on the planet. The serial entrepreneur could soon become the first individual to amass a $500 billion fortune.

2. Mark Zuckerberg

Year-to-date wealth gain: $90.9 billion

Net worth: $219 billion

Source of wealth gain: Meta stock

Mark Zuckerberg is the cofounder and CEO of Meta, the parent company of Facebook, Instagram, WhatsApp, and Threads.

Meta stock has soared 75% this year as investors wager Zuckerberg's big bets on AI and the metaverse will pay off in the years ahead. Zuckerberg has added about $90 billion to his net worth as a result, propelling him into third place on Bloomberg's rich list.

3. Jeff Bezos

Year-to-date wealth gain: $72.9 billion

Net worth: $250 billion

Source of wealth gain: Amazon stock

Jeff Bezos is Amazon's founder, executive chairman, and former CEO.

Amazon shares have leaped 52% this year as investors bet the online retailer can harness AI to supercharge its sales and leverage Amazon Web Services to become a key provider of cloud infrastructure to AI companies.

4. Larry Ellison

Year-to-date wealth gain: $70.4 billion

Net worth: $193 billion

Source of wealth gain: Oracle and Tesla stock

Larry Ellison is the cofounder, executive chairman, and chief technology officer of Oracle, one of the largest enterprise software companies.

Oracle stock has jumped 61% this year as the company has emerged as a key provider of cloud data centers for AI businesses, fueling a $70 billion increase in Ellison's net worth.

Ellison purchased more than 1.5% of Tesla prior to joining its board in December 2018, making him the electric-vehicle maker's second-largest individual shareholder after Musk. He's believed to have retained his stake, now worth upward of $20 billion, since resigning as a director in 2022.

5. Jensen Huang

Year-to-date wealth gain: $70 billion

Net worth: $114 billion

Source of wealth gain: Nvidia stock

Jensen Huang is the founder and CEO of Nvidia, the graphics chip maker that has emerged as a critical seller of "picks and shovels" to the AI gold rush.

Nvidia's stock has surged 163% this year, making it one of the world's most valuable companies with a $3.2 trillion market value and lifting Huang's net worth by $70 billion.

6. Michael Dell

Year-to-date wealth gain: $48.9 billion

Net worth: $127 billion

Source of wealth gain: Dell Technologies stock

Michael Dell is the founder and CEO of Dell Technologies, the maker of PCs, printers, and other computing equipment.

Dell shares have soared 55% this year as the company has shifted its focus toward AI-powered devices and servers.

7. Larry Page

Year-to-date wealth gain: $47.4 billion

Net worth: $174 billion

Source of wealth gain: Alphabet stock

Larry Page cofounded Google in 1998 and was the company's CEO until 2001 and again between 2011 and 2015 after Google was restructured as a subsidiary of Alphabet.

Alphabet shares have surged 40% this year as investors wager the search-and-advertising titan can dominate AI. The stock jump has fueled a $47 billion rise in Page's net worth.

8. Jim Walton

Year-to-date wealth gain: $45.1 billion

Net worth: $118 billion

Source of wealth gain: Walmart stock

Jim Walton is the youngest son of Walmart founder Sam Walton and, like his siblings, one of the retailer's largest shareholders with an 11%-plus stake.

Walmart stock has climbed 82% this year, fueled by resilient consumer spending in the face of historic inflation and soaring interest rates in recent years. The surge led to Walton amassing a $100 billion fortune for the first time in September.

9. Alice Walton

Year-to-date wealth gain: $44.4 billion

Net worth: $114 billion

Source of wealth gain: Walmart stock

Alice Walton is the only daughter of Walmart founder Sam Walton.

She overtook L'Oréal heiress Françoise Bettencourt Meyers in August to become the world's richest woman.

10. Rob Walton

Year-to-date wealth gain: $43.8 billion

Net worth: $115 billion

Source of wealth gain: Walmart stock

Rob Walton is the eldest son of Sam Walton and an heir to the Walmart fortune.

He and his siblings owe a big chunk of their wealth to their father, who handed them each a 20% stake in the family business over 70 years ago instead of having them inherit his fortune upon his death, in turn avoiding paying billions of dollars in estate taxes.

• Nvidia CEO Jensen Huang met his wife Lori Huang at Oregon State University.
• In a recent interview, he said that he tried to use homework as an excuse to spend time with her.
• Huang said he promised her he'd be CEO by 30 to ensure she'd marry him.

When Jensen Huang met his wife in college, the odds weren't in his favor.

He was 17 years old, and she was 19. "I was the youngest kid in school, in class. There were 250 students and 3 girls," he said in an interview at Hong Kong University of Science and Technology last week after receiving an honorary degree. He was also the only student who "looked like a child," he said.

Huang used his youthful appearance to approach his future wife, hoping she'd assume he was smart. "I walked up to her and I said, 'do you want to see my homework?'" Then he made a deal with her. "If you do homework with me every Sunday, I promise you, you will get straight As."

From that point on, he said he had a date every Sunday. And just to ensure that she would eventually marry him, he told her that by 30, he'd be a CEO.

Huang married Lori Mills five years after they first met at Oregon State University, according to his biography on OSU College of Engineering's website. The couple has two children, Madison, a director of marketing at Nvidia, and Spencer, a senior product manager at the company.

After graduating from OSU in 1984, Huang worked at chip companies LSI Logic and Advanced Micro Devices, according to his bio on Nvidia's website. He then pursued a master's degree in electrical engineering at Stanford University in 1992, a year before he founded Nvidia, which has grown into a $3.48 trillion company thanks to the artificial intelligence boom.

Huang was 30 years old when he founded Nvidia.

The CEO often shares the lore about Nvidia's origin: He conceived the idea for a graphics company while dining at Denny's, a US diner chain, with his friends. Huang said in a 2010 New York Times interview that he also waited tables at Denny's while he was a student.

Huang's net worth is now estimated to be $124 billion.

The CEO also credits his wife and daughter with establishing his signature style: the black leather jacket.

In an interview last year on HP's online show, "The Moment," host Ryan Patel asked Huang how he feels to become a style icon.

"Now, at Denny's I'm sure you weren't thinking you were gonna be the style star of the future, but now you are," Patel said. "What do you think? How do you feel?"

"Don't give me that," Huang replied. "I'm happy that my wife and my daughter dresses me."

A spokesperson for Nvidia did not respond to a request for comment.

• Nvidia CEO Jensen Huang said in a recent interview that today's AI doesn't provide the best answers.
• "We have to get to a point where the answer that you get, you largely trust," he said.
• The CEO said we're still "several years away" and that companies will need more computational power.

Nvidia CEO Jensen Huang said today's artificial intelligence doesn't provide the best answers and that the world is still "several years away" from an AI we can "largely trust."

"Today, the answers that we have aren't the best that we can provide," Huang said Saturday in an interview at Hong Kong University of Science & Technology.

The CEO said people shouldn't have to second-guess an AI's answer, wondering if it's "hallucinated or not hallucinated" or "sensible or not sensible."

"We have to get to a point where the answer that you get — you largely trust — you largely trust," he said, "and so I think that we're several years away from being able to do that and, in the meantime, we have to keep increasing our computation."

Large language models, such as ChatGPT, have advanced exponentially in the past few years in their ability to answer complex questions, but they still have limitations.

Hallucination, or providing false or fictitious answers, is one persistent problem with AI chatbots.

OpenAI, widely viewed as the leader of the AI race, was sued last year by a radio host after ChatGPT created a fake legal complaint about him.

A spokesperson for OpenAI did not respond to a request for comment.

Some AI companies are also facing the quandary over how to advance LLMs without solely having to rely on getting their hands on large amounts of data — an already finite resource.

During the Saturday interview, Huang said that pre-training or training a model on a large, diverse dataset before it's developed to perform a certain task will not be enough.

"Pre-training — just taking all of the data in the world and discovering knowledge from it automatically — pre-training is not enough," he said. "Just as going to college and graduating from college is a very important milestone, but it's not enough."

An Nvidia spokesperson declined to comment.

• Nvidia has a lot riding on Blackwell, its new flagship AI chip.
• Investors had a tepid response to earnings despite reporting $35.1 billion in third-quarter revenue.
• To deliver with Blackwell, Nvidia must juggle performance expectations and complex supply chains.

Nvidia looks set to end the year as confidently as it started. How next year plays out will significantly depend on the performance of Blackwell, its next-generation AI chip.

The Santa Clara-based chip giant reminded everyone why it has grown more than 200% this year to become the world's most valuable company. On Wednesday, it reported another blowout earnings. Revenue hit $35.1 billion in its third quarter, up 94% from a year ago.

But despite the strong earnings, which Wedbush analyst Dan Ives said "should be framed and hung in the Louvre," investors remained cautious as they focused their attention on the highwire act Nvidia must pull off with Blackwell.

The new chip, known as a GPU, was first unveiled by CEO Jensen Huang at the company's GTC conference in March. It was revealed as a successor to the Hopper GPU that companies across Silicon Valley and beyond have used to build powerful AI models.

While Nvidia confirmed on Wednesday that Blackwell is now "in full production," with 13,000 samples shipped to customers last quarter, signs emerged to suggest that Nvidia faces a difficult path ahead as it prepares to scale up its new-era GPUs.

Nvidia must navigate complex supply chains

First, Blackwell is what Nvidia CFO Colette Kress called a "full-stack" system.

That makes it a beast of machinery that needs to be fit for an incredibly wide range of specific needs from a variety of customers. As she told investors on the earnings call on Wednesday, Blackwell is built with "customizable configurations" to address "a diverse and growing AI market." That includes everything from "x86 to Arm, training to inferencing GPUs, InfiniBand to Ethernet switches," Kress said.

Nvidia will also need incredible precision in its execution to satisfy its customers. As Kress said on the earnings call, the line for Blackwell is "staggering," with the company "racing to scale supply to meet the incredible demand customers are placing on us."

To achieve this, it'll need to focus on two areas. First, meeting demand for Blackwell will mean efficiently orchestrating an incredibly complex and widespread supply chain. In response to a question from Goldman Sachs analyst Toshiya Hari, Huang reeled off a near-endless list of suppliers contributing to Blackwell production.

There were Far East semiconductor firms TSMC, SK Hynix, and SPIL; Taiwanese electronics giant Foxconn; Amphenol, a producer of fiber optic connectors in Connecticut; cloud and data center specialists like Wiwynn and Vertiv, and several others.

"I'm sure I've missed partners that are involved in the ramping up of Blackwell, which I really appreciate," Huang said. He'll need each and every one of them to be in sync to help meet next quarter's guidance of $37.5 billion in revenue. There had been some recent suggestions that cooling issues were plaguing Blackwell, but Huang seemed to suggest they had been addressed.

Kress acknowledged that the costs of the Blackwell ramp-up will lead to gross margins dropping by a few percentage points but expects them to recover to their current level of roughly 75% once "fully ramped."

All eyes are on Blackwell's performance

The second area Nvidia will need to execute with absolute precision is performance. AI companies racing to build smarter models to keep their own backers on board will depend on Huang's promise that Blackwell is far superior in its capabilities to Hopper.

Reports so far suggest Blackwell is on track to deliver next-generation capabilities. Kress reassured investors on this, citing results from Blackwell's debut last week on the MLPerf Training benchmark, an industry test that measures "how fast systems can train models to a target quality metric." The Nvidia CFO said Blackwell delivered a "2.2 times leap in performance over Hopper" on the test.

Collectively, these performance leaps and supply-side pressures matter to Nvidia for a longer-term reason, too. Huang committed the company to a "one-year rhythm" of new chip releases earlier this year, a move that effectively requires the tech giant to showcase a vastly more powerful variety of GPUs each year while convincing customers that it can dole them out.

While performance gains seem to be showing real improvements, reports this year have suggested that pain points have emerged in production that have added delays to the rollout of Blackwell.

Nvidia remains ahead of rivals like AMD

For now, investors appear to be taking a wait-and-see approach to Blackwell, with Nvidia's share price down less than a percentage point in pre-market trading. Hamish Low, research analyst at Enders Analysis, told BI that "the reality is that Nvidia will dominate the AI accelerator market for the foreseeable future," particularly as "the wave of AI capex" expected from tech firms in 2025 will ensure it remains "the big winner" in the absence of strong competition.

"AMD is a ways behind and none of the hyperscaler chips are going to be matching that kind of volume, which gives Nvidia some breathing room in terms of market share," Low said.

As Low notes, however, there's another reality Nvidia must reckon with. "The challenge is the sheer weight of investor expectations due to the scale and premium that Nvidia has reached, where anything less than continually flying past every expectation is a disappointment," he said.

If Blackwell misses those expectations in any way, Nvidia may need to brace for a fall.

• Nvidia beat forecasts again in its third-quarter results on Wednesday.
• CEO Jensen Huang said more Blackwell chips will be delivered this quarter than previously estimated.
• One analyst says some investors are concerned about a possible slowdown in future growth.

Nvidia delivered another strong set of quarterly results after the bell on Wednesday, beating estimates. Here's what analysts are saying about the world's most valuable company.

Wedbush analysts, including Dan Ives, issued another typically bullish note on Thursday:

"In another earnings performance for the ages Nvidia delivered a $2 billion top-line beat with $35 billion of sales showing a $5 billion sequential increase driven by flagship data center sales. We would characterize results as another earnings press release from Nvidia that should be framed and hung in the Louvre given these eye popping results and unprecedented growth from the Godfather of AI Jensen and Nvidia.

"The LeBron of chip releases, next generation Blackwell appears to ramping even faster than expected with NO overheating issues and appears to be on a massive demand trajectory ahead of the Street that our Wedbush Global Tech Team is tracking very closely throughout the Asia supply chain."

Konstantin Oldenburger at CMC Markets said Nvidia had exceeded forecasts again, but some question marks remained.

"What stuck in people's minds was the possibility of a slowdown in future growth. The gross margin, which previously only knew one direction — up — to a whopping 75% of revenue, is expected to fall to 'only' 73% in the current quarter.

"Even if the competition can only dream of such figures, investors, who have been accustomed to success, now fear an end to Nvidia's growth story. Whether the fear is justified will become clear when the new chip generation Blackwell is delivered in the coming months," he wrote.

Deutsche Bank analysts said the results drew a "tepid reaction" because its guidance "failed to match some of the loftiest expectations."

They wrote in a note that third-quarter sales came in at $35.1 billion, above the $33.2 billion estimate. However, the fourth-quarter sales guidance was $37.5 billion "was 'only' a touch above the average analyst estimate of $37.1 billion."

"Overall it was deemed to be a slightly underwhelming outcome," they added.

Dan Coatsworth at AJ Bell said Nvidia had again posted blockbuster growth. "What's troubled investors this time was a quarter-on-quarter decline in gross margins, with guidance for them to fall further in the coming quarter, and weaker than expected forward guidance for revenue.

"Investors have enjoyed stellar share price gains from Nvidia over the past two years and that's made them think it is invincible. In reality, a small decline in margins is not a reason to panic, particularly when they are still over 70% which many companies could only dream of. Nvidia is confident margins will rebound as production volumes ramp up for its Blackwell chips."

HSBC analysts wrote in a note that they expect "significant" earnings upside for the 2026 financial year despite gross margin pressure.

Stephen Yiu, who manages the $1.4 billion London-based Blue Whale growth fund, invested 10% of the fund — the limit for any one stock. He told Bloomberg TV he wished he could have bought more Nvidia stock because he's so bullish on AI infrastructure.

"We need to believe in how AI is going to change the world in terms of our day-to-day," he said. "Nvidia remains the center of that AI transformation."