Global: AI Companies’ Regulatory Evasion Efforts Meet Skepticism from Antitrust Authorities

Federal Trade Commission (FTC) Chair Lina Khan
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Attempts by AI firms to advocate for a lax regulatory approach have met with skepticism from antitrust regulators, according to recent remarks from Federal Trade Commission (FTC) Chair Lina Khan at an antitrust conference in Washington.

As reported by Bloomberg News, Chair Khan emphasized that dazzling technological advancements would not exempt companies from adherence to existing antitrust laws, including those against collusion, price fixing, monopolization, and fraud. “The FTC is going to take action,” Khan firmly stated.

The report further highlighted growing concerns among global antitrust authorities that some of the most innovative startups in the AI space are becoming overly dependent on tech giants like Microsoft and Google for both funding and infrastructure. This dependency is seen as a strategic move by larger companies to maintain dominance in the rapidly evolving AI sector.

At the conference, representatives from major technology companies argued that AI has the potential to significantly transform the economy. Google’s attorney Kent Walker likened AI technology to the groundbreaking mRNA vaccine technology used in fighting COVID-19.

Haidee Schwartz, associate general counsel for antitrust at OpenAI, described AI as a “positive disruptor,” capable of fostering competition and catalyzing growth across new sectors.

Meta, for instance, has launched a new generation of custom computer chips aimed at boosting its AI capabilities and lessening its reliance on external hardware providers like Nvidia. This development is in line with moves by other companies such as Intel and Google, which are also advancing their in-house AI chip technology.

Amrit Jassal, co-founder and chief technology officer of Egnyte, explained in an interview that these custom chips could democratize AI by lowering the costs associated with training models for specific customer tasks, shifting away from solely relying on large language model APIs for specialized and secure applications.

The move towards custom chips could potentially make AI more accessible for businesses, with integration costs varying widely depending on whether companies opt for simple monthly subscriptions or invest in bespoke solutions based on finely tuned open-source models, as noted by software development firm Itrex.

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