Meta has invested heavily in generative AI, with the majority of its planned $72 billion in capital expenditure this year earmarked for data centers and servers. The deal underlines the high price AI companies are willing to pay for data that can be used to train AI models.
Zuckerberg pledged last year that his companyβs models would outstrip rivalsβ efforts in 2025, but Metaβs most recent release, Llama 4, has underperformed on various independent reasoning and coding benchmarks.
The long-term goal of researchers at Meta βhas always been to reach human intelligence and go beyond it,β said Yann LeCun, the companyβs chief AI scientist at the VivaTech conference in Paris this week.
Building artificial βgeneralβ intelligenceβAI technologies that have human-level intelligenceβis a popular goal for many AI companies. An increasing number of Silicon Valley groups are also seeking to reach βsuperintelligence,β a hypothetical scenario where AI systems surpass human intelligence.
The core of Scaleβs business has been data-labeling, a manual process of ensuring images and text are accurately labeled and categorized before they are used to train AI models.
Wang has forged relationships with Silicon Valleyβs biggest investors and technologists, including OpenAIβs Sam Altman. Scale AIβs early customers were autonomous vehicle companies, but the bulk of its expected $2 billion in revenues this year will come from labeling the data used to train the massive AI models built by OpenAI and others.
The deal will result in a substantial payday for Scaleβs early venture capital investors, including Accel, Tiger Global Management, and Index Ventures. Tigerβs $200 million investment is worth more than $1 billion at the companyβs new valuation, according to a person with knowledge of the matter.
Additional reporting by Tabby Kinder in San Francisco
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