Mark Zuckerberg's $14b 'AI prodigy' to lead Superintelligence team - who is Alexandr Wang?

Mark Zuckerberg has announced a new Meta 'Superintelligence' team which will be led by some of his recent high-profile hires, including former Scale AI CEO Alexandr Wang who has been labelled an "AI prodigy".

Bloomberg reported Zuckerberg announced the new unit called MSL (Meta Superintelligence Labs) on Monday (30 June). A further report from CNBC said the unit will be home to Meta's Llama models and AI research projects.

Wang was hired earlier in June as Meta's new AI chief along with some of his colleagues as part of an eye-watering $14b investment from Zuckerberg into Scale AI.

Scale AI provided accurately labelled, high quality training data for AI services such as Google, Microsoft and OpenAI with Meta now owning a 49 per cent stake in it.

Since the deal, these companies have started looking at alternatives as Meta's stake means it has access to all the data that made the AI models these companies used tick.

And Zuckerberg poached Wang to lead his new Meta team while Wang remains on the Scale AI board. Commentators online have claimed that this could "save Meta" after its struggles with its own AI models.

Alexandr Wang is now leading Meta's 'Superintelligence' team / Getty Images

Who is Scale AI's 28-year-old CEO, Alexandr Wang?

Wang cofounded Scale AI, a startup, in 2016 and by 2022, he became the youngest self-made billionaire of all time.

From New Mexico but now living in San Francisco, aged just 17, he got his first full time engineering jobs in Silicon Valley with fintech Addepar and then Quora, according to Forbes.

At 19, Wang dropped out of studying machine learning at MIT to attend the Y Combinator accelerator and launch Scale.

Speaking to TIMEearlier this year, he spoke about Scale's approach within the industry, saying: "If you take a big step back, AI progress fundamentally relies on three pillars: data, compute and algorithms. It became very clear that the data was one of the key bottlenecks of this industry. Compute and algorithms were also bottlenecked, but data was sort of right there with them.

"I think before Scale, there weren't companies that treated data as the first-class of a problem it really is. With Scale, one of the things that we've really done is treat data with the respect that it deserves. We’ve really sought to understand, “How do we solve this problem in the correct way? How do we solve it in the most tech-forward way?”"

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