Two months after making a $14.3B investment in Scale AI, Meta is relying heavily on its competitors to train next generation AI models. techcrunch.com/2025/08/29/cra…

@TechCrunch 14B to study off someone else’s homework is crazy

@TechCrunch you were right @DannyEarns

@TechCrunch ai szn

@TechCrunch Alexander Wang was always "Theranos for data labeling"

Realistically, at this point Meta will struggle to hire AI researchers motivated by mission rather than money. Meta’s reputation in the AI research community has been damaged for years, and only someone with Yann’s level of academic star power could begin to shift perceptions and draw in mission-driven researchers. Without a fundamental overhaul of culture and leadership, Meta will keep attracting talent that can be bought but isn’t mission-driven.

@TechCrunch How can they have done such a poor job vetting them? It’s like Monopoly money to them.

@TechCrunch Alex is a fraud, just read his ideas/comments about DeepSeek, you will know he has no idea whats the core of AI

@TechCrunch If they breakup, it would once again prove that money cant buy everything, specially an AGI class LLM

@TechCrunch Meta is the yahoo of this AI age.

@TechCrunch Meta's AI talent churn = Canada's R&D attrition. Our engineers flee to UAE hubs where robotics innovation accelerates, unchained by dead-end policies.

@TechCrunch I'm wondering about Scale AI for offering big data to train AI models. My wonder is that is it legal? I mean, do they have the right for the data? Moreover, how do they offer data and label them? I mean, is it a software thing or an analyzing thing?

@TechCrunch Egg on Zuck’s face (illustration)

@TechCrunch Tough competitor in the field of A.I

@TechCrunch

@TechCrunch Dario was right when he focused on coding because coding id what makes better models. Since they are coded too. Simple but very smart. Others just understood it. I bet anthropic are vibecoding next models

@TechCrunch Lol, all this money for a mediocre product.

@TechCrunch @TechCrunch, investing in ai requires collaboration; leveraging competitors can spark innovation.

@TechCrunch here comes another bubble 🫧

@TechCrunch @MaynardJohn8 yeah these are not bubbles at allll

@TechCrunch long ai data infra like $CFLT short ai dramas like $meta or even $nvda

@TechCrunch It’s interesting to see big players turn to competitors for advancements. Innovation is often born from collaboration.

@TechCrunch Interesting pivot from Meta after that huge investment. @JonBrooksQ5 was just talking about how fragile these AI partnerships can be.

@TechCrunch @alexandr_wang @jdroege I can help fix the data quality issues. We should talk. DM me.

@TechCrunch ScAM?!

@TechCrunch makes sense why he sold to Meta

@TechCrunch No way

@TechCrunch Thanks to Alexandr wang.

@TechCrunch So meta.

@TechCrunch Waw cool 🙄

@TechCrunch retarded

@TechCrunch @Madisonkanna @withtenacity @karpathy @karpathy @AnantaVichara @giffmana Alexander want is the Theranos of AI

@TechCrunch People throw a lot of shade on meta based on a couple of rumors

@TechCrunch @TechCrunch, isn't it fascinating how even giants like Meta lean on competitors? What does this mean for the future of collaboration in AI? 🤔 #AIInnovation

@TechCrunch Priscilla thought that little chinese boy was cute 😁

@TechCrunch @TechCrunch, isn’t it interesting how even giants lean on collaboration? Innovation often flourishes in unexpected partnerships. 🤔 #InnovationInsights

@TechCrunch what did y'all expect