The news: Meta’s $14 billion investment in Scale AI drove Google to cut ties with the startup.
- Google was planning to pay Scale $200 million this year for its data-labeling services, per Reuters. Losing that contract could hurt Scale, which relies on a handful of large clients.
- With Meta now owning a 49% stake, Google could be concerned that contracting with Scale would give Meta access to its proprietary data.
Data sharing: Meta’s massive investment falls in line with a spree of acqui-hires and licensing deals in the Big Tech space, including a Google-Character AI licensing agreement and Microsoft hiring most of Inflection AI’s employees.
As part of the deal, Meta hired Scale CEO Alexandr Wang and is potentially gaining access to insights on the company’s full customer base. This puts Scale clients in a bind: Either stop working with the AI company, which provides valuable model development resources, or risk letting Meta gain indirect exposure to company data.
Google’s decision to walk away could draw regulatory scrutiny of the deal’s impact on market competition.
Regulatory heat: The Meta-Scale deal isn’t the only tech acquisition with antitrust risks.
The Department of Justice (DOJ) is reviewing Google’s $32 billion purchase of cloud security firm Wiz, per Bloomberg.
- Progress on the deal accelerated in January after President Donald Trump took office, per Reuters. Now, the DOJ is pushing back.
- If the deal falls through, Google will owe Wiz a $3.2 billion breakup fee.
OpenAI has concerns about how regulators may react to its planned $3 billion purchase of Windsurf.
- It wants to exclude that deal from its revenue- and IP-sharing agreement with Microsoft, per The Information, which gives Microsoft the right to OpenAI’s IP through 2030.
- The AI coding startup may directly compete with Microsoft’s Github Copilot. Including it in the partnership could let Microsoft use Windsurf to improve GitHub Copilot, potentially raising antitrust red flags and complicating OpenAI’s plans.
Our take: Big Tech is racing to consolidate control over AI and cloud security infrastructure. Independence and agility could help companies avoid vendor lock-ins and data entanglement as regulators close in.
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