Impli reveals the exact APEX method professionals use to optimize AI prompts. The article shows the complete system specification—from analyzing requests to executing optimized prompts that work across all platforms.
Web scraping has quietly become the backbone of AI training data. But legal gray areas and sophisticated anti-blocking measures make success tricky. This guide reveals what works in 2025.
Sean Grove from OpenAI says coding is dead. Instead of writing code, developers should write specifications that generate software. AWS just launched Kiro to make this real, while GeneXus claims they've done it for 35 years
Meta just paid $15 billion for a 49% stake in Scale AI after its own models flopped. CEO Alexandr Wang gets control while leading Meta's new "superintelligence" team. The deal reveals how desperate big tech has become to acquire AI talent at any cost.
💡 TL;DR - The 30 Seconds Version
💰 Meta agreed to pay $14.8 billion for a 49% stake in Scale AI, its largest external AI investment ever.
📊 The deal makes 28-year-old Scale CEO Alexandr Wang the voting controller while he leads Meta's new "superintelligence" team.
🏭 Scale generated $870 million revenue in 2024 and expects $2 billion this year from data labeling services using global contractors.
😤 Meta's desperation stems from Llama 4's April flop and losing 4.3% of top AI talent to competitors in 2024.
⚠️ Scale will likely lose major customers like Google and OpenAI who won't work with a Meta-controlled data provider.
🚀 The quasi-acquisition mirrors Microsoft's Inflection deal, letting tech giants acquire talent while avoiding full regulatory scrutiny.
Meta has agreed to pay $14.8 billion for a 49% stake in Scale AI, marking the social media giant's largest external AI investment and one of the most expensive talent acquisitions in Silicon Valley history. The deal represents Mark Zuckerberg's frustration with Meta's lagging position in the artificial intelligence race, where competitors like OpenAI and Google have pulled ahead.
Zuckerberg has grown frustrated that rivals like OpenAI appear to be further ahead than Meta in underlying AI models and consumer-facing apps, according to current and former Meta employees. The company's recent struggles became evident when Meta's release of its Llama 4 AI models in April was not well received by developers, further frustrating Zuckerberg.
The investment comes with significant strings attached. A big chunk of Meta's $15 billion investment in Scale AI requires the startup to provide future work to Mark Zuckerberg's firm, essentially functioning as an advance payment for years of data services.
Scale AI built its reputation on the unglamorous but essential work of data labeling. The company employs contractors worldwide to teach AI systems through manual data preparation and annotation. Scale AI saw $870 million in revenue last year and expects to bring in $2 billion this year, making it a crucial player in the AI training ecosystem.
Scale has seen demand for its network of experts increase in the wake of DeepSeek, as more companies invest in models that mimic human reasoning and carry out more complicated tasks. The company has evolved beyond basic labeling to employ highly skilled contractors, including PhD scientists and senior software engineers, to generate sophisticated training data.
The startup's influence extends beyond Silicon Valley. Scale AI has increasingly made in-roads into the defense industry, and in March announced a multimillion dollar deal with the Department of Defense. CEO Alexandr Wang has positioned himself as a China hawk and cultivated relationships with Pentagon officials and lawmakers concerned about China's AI advancement.
As part of the deal, Scale AI CEO Alexandr Wang will take a top position inside Meta, leading a new "superintelligence" lab. The 28-year-old will maintain his CEO role at Scale while heading Meta's ambitious new AI research effort. Wang will still be Scale's CEO even as he takes on substantial responsibilities at Meta.
Wang brings more than technical expertise to Meta. Wang has built a reputation as an ambitious leader who understands AI's technical complexities and how to build a business, according to former Meta AI employees. His Pentagon connections could prove valuable as Meta seeks to expand its defense technology partnerships.
The deal gives Wang unprecedented control over Scale's future. Meta will end up owning just under half of Scale, but the investment structure transfers voting rights to Wang, giving him control despite Meta's substantial stake.
The Scale AI deal shows how fierce the fight for AI talent has become. Meta offers compensation packages worth tens of millions of dollars to individual researchers. The company lost 4.3% of its top talent to AI labs in 2024, according to SignalFire data.
Meta has won some recruiting battles. The company hired Jack Rae from Google DeepMind and Johan Schalkwyk from AI voice startup Sesame AI. But it has also lost key targets, failing to recruit Google's Koray Kavukcuoglu and OpenAI's Noam Brown despite substantial offers.
The recruitment challenges highlight the premium companies are paying for AI expertise. Zuckerberg has been personally involved in recruitment efforts, meeting with candidates at his homes in Lake Tahoe and Palo Alto. The CEO aims to assemble a team of around 50 top researchers for Meta's new superintelligence initiative.
The Scale AI deal follows a pattern of quasi-acquisitions that allow tech giants to acquire talent while avoiding full regulatory scrutiny. Microsoft employed similar strategies with Inflection AI and its OpenAI partnership, while Google made comparable moves with Character.AI.
Some journalists commenting on the deal said that it was merely an acquisition of Scale disguised as an investment for the purposes of avoiding antitrust scrutiny. The structure may help Meta sidestep the regulatory challenges that have complicated its previous acquisitions of Instagram and WhatsApp.
However, the deal carries significant risks. Scale AI is likely to lose business from Meta's competitors, including Google and OpenAI, who have been major customers. The company's neutrality as a data provider becomes questionable when nearly half-owned by a major AI competitor.
The investment also reveals the massive costs associated with AI development. Meta's investment in Scale AI is, in part, an advanced payment on data collection fees and, for the first time, offers a glimpse into the mammoth costs associated with the endeavor.
The deal arrives as the data labeling market faces increasing competition and disruption. New entrants like Handshake, Mercor, and Surge AI are challenging Scale's dominance. Some AI companies are also moving data collection efforts in-house or experimenting with synthetic, AI-generated training data.
More tech firms have begun to experiment with using synthetic, AI-generated data to train AI systems, potentially reducing the need for some of the services Scale historically provided. This trend could limit the long-term value of Meta's investment if companies reduce their reliance on human-labeled data.
Scale's competitors have already begun capitalizing on uncertainty around the Meta deal. Rival companies report increased interest from customers seeking alternatives to Scale's services, particularly those concerned about working with a Meta-affiliated provider.
Wang's Pentagon connections add a geopolitical dimension to the deal. Scale has also deepened its relationship with the US government through defense deals. Wang, a China hawk, has cozied up to lawmakers on the hill who are concerned about China's ascendance in AI.
The defense industry relationships could benefit Meta as it seeks to expand beyond consumer applications. In November, it collaborated with Meta on Defense Llama, a custom version of Meta's open-source Llama foundation model designed specifically to support American national security missions.
This positioning aligns with broader efforts by tech companies to demonstrate their value to national security priorities, particularly as concerns about Chinese AI development influence government policy and funding decisions.
Why this matters:
Q: How does this deal differ from a normal acquisition?
A: Meta gets 49% ownership and voting control transfers to Scale CEO Alexandr Wang, who joins Meta while staying Scale's CEO. This structure avoids full regulatory review like Microsoft's Inflection deal. Scale continues operating independently while providing guaranteed future services to Meta.
Q: What exactly does Scale AI do that's worth $15 billion?
A: Scale employs contractors worldwide to label and annotate data for AI training. They've evolved from basic tasks to hiring PhD scientists and engineers for specialized work. Scale generated $870 million revenue in 2024 and expects $2 billion this year, making it the largest data labeling company.
Q: Why is Meta so desperate to catch up in AI?
A: Meta's Llama 4 models flopped in April and failed to match Chinese competitor DeepSeek's performance. The company lost 4.3% of its top AI talent to competitors in 2024. Meta delayed its flagship "Behemoth" model due to capability concerns compared to rivals like OpenAI and Google.
Q: Will Scale AI lose customers because of this Meta deal?
A: Yes, Scale will likely lose business from Meta rivals like Google and OpenAI who are major customers. Competitors like Turing already report increased interest from customers seeking alternatives. This neutrality problem is why rival data companies see the deal as an opportunity to steal clients.
Q: How much is Meta paying individual AI researchers to join?
A: Meta offers compensation packages worth tens of millions of dollars over several years, with some reaching seven to nine figures. Zuckerberg personally recruits at his Lake Tahoe and Palo Alto homes. The company aims to hire around 50 researchers for its new superintelligence team.
Q: What is Scale AI's connection to the Pentagon and defense work?
A: Scale AI signed a multimillion-dollar deal with the Department of Defense in March to build ThunderForge, an AI system for military planning. CEO Alexandr Wang is a known China hawk who has cultivated relationships with Pentagon officials and lawmakers concerned about China's AI advancement.
Q: How does this compare to other big tech AI investments?
A: Microsoft invested $13+ billion in OpenAI, while Google and Amazon have backed Anthropic. However, Meta's deal is structured as a quasi-acquisition rather than a pure investment, similar to Microsoft's Inflection AI deal where key talent joined Microsoft while the company remained independent.
Q: Could synthetic AI-generated data replace Scale's human labeling services?
A: Some AI companies are experimenting with synthetic data, but leading labs still struggle to get enough high-quality training data. Scale has adapted by hiring PhD scientists and engineers for specialized tasks that require human expertise, moving beyond basic data labeling work.
AI companies abandon rivalry to warn: our window to understand AI reasoning is closing. Models currently 'think out loud' for complex tasks, revealing plans to misbehave. But this transparency could vanish as technology advances.
Disney Research addresses a major problem with digital humans: they look fake up close. New ScaffoldAvatar system renders photorealistic 3D head avatars with individual freckles and wrinkles at 100+ FPS on consumer hardware.
Two-thirds of UK children now use AI chatbots for emotional support, with vulnerable kids forming deep bonds with systems that lack empathy. Age checks fail, content filters break, and some kids pay the ultimate price.
Experienced developers work 19% slower with AI coding tools but think they're 20% faster. New study challenges AI's flagship use case and shows why self-reported productivity gains can't be trusted.
Get the 5-minute Silicon Valley AI briefing, every weekday morning — free.
