Meet Mark Zuckerberg's AI dream team powering Meta's next big leap

Time of India

a day ago

Brains over data. That's Meta's game plan as it races to dominate artificial intelligence. While other tech titans throw compute power and training data at the problem, Mark Zuckerberg is doing something far more personal.
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He's handpicking minds.
And he's not subtle about it. According to The Wall Street Journal, Zuckerberg has been personally calling OpenAI researchers, offering eye-popping compensation packages—some reportedly as high as $100 million—to woo them away. Even Sam Altman, OpenAI's CEO, admitted in a recent podcast that Meta's offers were staggering.
It's all part of Meta's newly revealed Superintelligence Lab, and Zuckerberg has already released the first 11 names on what insiders call 'The List.'
These aren't just brilliant AI engineers. They are scientists, founders, problem solvers—and in many cases, immigrants or first-generation Americans whose work helped define the most powerful AI models in existence today.
Before we dive in, one thing is clear: this isn't just a hiring spree. It's the making of a brain trust that could shape how AI reasons, speaks, listens, and even dreams.
Let's meet the team.
Alexandr Wang
Source: X
The wunderkind leading Meta's new lab has already made a name for himself in Silicon Valley.
As the founder of Scale AI, Wang built a company that quietly powered the data-hungry ambitions of tech's biggest players. What fewer people know is that his story begins far from boardrooms—in New Mexico, where he was born to Chinese immigrant parents who worked as physicists for the U.S. military.
Wang grew up surrounded by science and structure, but also by discipline. He competed in national math Olympiads as early as sixth grade, taught himself how to code, and played violin with the same intensity he brought to algorithms.
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After enrolling at MIT to study mathematics and computer science, he dropped out to pursue Scale. By 28, he wasn't just building tools for AI—he was redefining how AI learns.
Meta reportedly invested $14 billion into Scale as part of the deal to bring Wang onboard.
Nat Friedman
Source: LinkedIn
In contrast to Wang's youth, Nat Friedman brings gravitas. A seasoned technologist and venture investor. Friedman is known for scaling ideas into institutions.
As the former CEO of GitHub, he steered the platform through its $7.5 billion acquisition by Microsoft and was known for his understated but razor-sharp leadership style.
Born in Charlottesville, Virginia, Friedman fell in love with online communities at the age of 14 and later called them his 'actual hometown.' That early sense of connection shaped his future—first at MIT, then through his work co-founding Xamarin, a developer tools company that attracted Fortune 500 clients like Coca-Cola and JetBlue.
Today, Friedman is deeply embedded in the AI startup ecosystem, backing companies like Perplexity and Stripe.
Trapit Bansal
Source: X
Born and raised in India, Trapit Bansal is a quiet architect behind some of OpenAI's most sophisticated reasoning models. With dual degrees in mathematics and statistics from IIT Kanpur and a PhD from the University of Massachusetts Amherst, Bansal's academic journey has always straddled theory and application.
At OpenAI, he played a crucial role in the development of the o-series, particularly the o1 model—widely regarded as a turning point in AI's ability to 'think' before responding. Bansal's specialty is meta-learning.
Jiahui Yu
Source: LinkedIn
A rising star in the world of multimodal AI, Jiahui Yu has already left his mark on two of the most powerful labs in the world—Google and OpenAI. At OpenAI, he led the perception team, working on how machines interpret images, audio, and language as a seamless whole.
At Google's DeepMind, he helped develop Gemini's multimodal capabilities.
Yu's educational path began at the prestigious School of the Gifted Young in China, followed by a PhD in computer science from the University of Illinois Urbana-Champaign.
Shuchao Bi
Source: X
Shuchao Bi is one of the few people who can claim co-founder status on a cultural juggernaut—YouTube Shorts. During his 11 years at Google, he helped create and refine its short-form video platform and later led its algorithm team.
But Bi's heart has always belonged to research.
At OpenAI, he focused on multimodal AI and helped launch GPT-4o's voice mode—essentially giving chatbots the power to talk back. Educated at Zhejiang University and later at UC Berkeley, Bi blends statistical elegance with creative application. His role at Meta? To make machines not just responsive, but expressive.
Huiwen Chang
Source: LinkedIn
Known for her expertise in image generation and style transfer, Huiwen Chang was instrumental in OpenAI's visual interface work for GPT-4o.
But her roots are in rigorous academia. She graduated from the Yao Class at Tsinghua University—a training ground for China's best minds in computer science—and then earned her PhD from Princeton.
Chang's work is where art meets architecture. She understands how to train machines to not just see an image, but to manipulate it, interpret it, and even mimic human aesthetic judgment. Before OpenAI, she cut her teeth at Adobe and Google.
Ji Lin
Source: LinkedIn
Another Tsinghua-to-MIT story, Ji Lin blends engineering finesse with frontier thinking. He worked on several of OpenAI's most powerful models before joining Meta, with a focus on both reasoning and multimodal integration.
What sets Lin apart is his mix of research and real-world application. He interned at NVIDIA, Adobe, and Google before landing at OpenAI.
Hongyu Ren
Source: X
If you're improving an AI model after it's built—teaching it to be more ethical, more accurate, or more human—you're doing post-training.
That's Hongyu Ren's specialty.
Educated at Peking University and Stanford, Ren led a post-training team at OpenAI and is one of the more philosophically-minded researchers in the group.
Shengjia Zhao
Source: X
As a co-creator of ChatGPT, Shengjia Zhao is no stranger to AI that captures public imagination. But behind the scenes, he was also working on one of the field's most quietly important trends: synthetic data. By helping machines generate their own training material, Zhao advanced a method to keep AI learning, even as real-world data dries up.
After graduating from Tsinghua University and Stanford, Zhao joined OpenAI in 2022 and quickly rose through the ranks.
Johan Schalkwyk
Source: X
Hailing from South Africa, Johan Schalkwyk has always worked on the frontier of communication. At Google, he led the company's ambitious effort to support 1,000 spoken languages, a moonshot project that blended linguistics, machine learning, and cultural preservation.
Most recently, he served as machine learning lead at Sesame, a startup trying to make conversational AI feel like real dialogue.
Pei Sun
Pei Sun helped power the brains behind Waymo, Google's self-driving car unit. His work involved building next-generation models for perception and reasoning—skills that translate neatly into the world of chatbots, robots, and beyond.
Educated at Tsinghua University and Carnegie Mellon, Sun began a PhD before dropping out to join the industry faster.
Joel Pobar
Source: LinkedIn
An AI infrastructure veteran, Joel Pobar most recently worked at Anthropic, where he helped scale inference systems for some of the most advanced models in the world.
Before that, he spent nearly a decade at Facebook, leading engineering teams.
Educated in Australia at Queensland University of Technology, Pobar brings a rare mix of insider knowledge and outsider grit. His job at Meta will likely focus on making sure the lab's most powerful creations can actually run reliably, at scale, and in real time.