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Anthropic Says US Google Search Proposal Will Hurt AI Investment

Hana.haghani by Hana.haghani
2025-02-15
in Ai, Technews
Reading Time: 2 mins read
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Anthropic, an artificial intelligence (AI) developer, has requested a federal court to reject a proposal from the US government that would prevent Alphabet’s Google from investing in AI startups as a means to address its unlawful monopolization of the online search sector. In a court filing dated February 14, the AI firm argued that a remedy requiring Google to sever ties with Anthropic would negatively impact both the startup and overall market competition. Google has invested approximately $3 billion in Anthropic, which also counts Amazon.com among its investors. The Justice Department, along with several states, has suggested significant alterations to Google’s operations, including the forced divestiture of its Chrome web browser, following a federal judge’s ruling last year that determined the company had unlawfully monopolized the online search and advertising markets. The proposed remedies would also prevent Google from acquiring, investing in, or partnering with firms that manage consumer search data, including those involved in AI technologies. Anthropic, based in San Francisco, expressed in its filing that such a forced sale would unfairly benefit its larger competitors in the AI field, like OpenAI, Meta, and even Google itself, which markets its own AI language model, Gemini, through its DeepMind subsidiary.

Anthropic is recognized for its Claude series of large language models, which compete with those developed by OpenAI. Like others in the industry, the company has been securing substantial funding to enhance its computing capabilities and remain competitive in the rapidly evolving AI landscape. The US Federal Trade Commission (FTC) has voiced concerns regarding these investments, including Microsoft’s backing of OpenAI.

In a report released in January, the FTC highlighted that these companies often require their funding directed toward AI startups to be utilized for their own products and services, potentially leading to a consolidation of advantageous data related to chip development, model training, and data center infrastructure within these tech giants.

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