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Frontier AI slowdown a distraction: Menlo Ventures

Menlo Ventures, a pioneer in backing AI startup Anthropic, contends that the real bottleneck in the technology sector isn't a slowdown in the creation of cutting-edge models, but rather the availability of computational resources. Menlo's co-partners, Matt Murphy and Venky Ganesan, both former investors in Anthropic, argue that the hype around a decrease in frontier model development is misleading.

They assert that the models are already intelligent enough to serve current market demands, thereby opening a vast market for all AI enterprises.

Menlo Ventures has previously demonstrated its confidence in Anthropic by spearheading a $750 million funding round, marking the largest investment in the firm's 50-year history. This led to Menlo raising an impressive $3 billion across two new funds in June, the largest corpus ever amassed by the venture capital firm. The AI portfolio of Menlo encompasses a variety of ventures such as Suno, Lovable, Modal, and Town, a work assistant, as well as OpenRouter, which was acquired by Stripe for approximately $7.5 billion.

Murphy asserts that there will likely be both enterprise and consumer-focused iterations of these AI assistants, reminiscent of Anthropic's approach to enterprise and OpenAI's consumer-focused model.

On a separate but related note, Bhavish Aggarwal, the CEO of Ola Electric, has pledged a 4.32% stake in the company to facilitate his subscription to a proposed rights issue. This pledge, documented in a regulatory filing, is solely intended to fund Aggarwal's subscription and does not involve the sale of any shares. This move comes amid a significant decrease in the value of Aggarwal's Ola businesses, as competing electric vehicles and ride-hailing services struggle with falling revenues.

Ola Electric's stock price has plummeted, with major investors including SoftBank, Warburg Pincus, Temasek, Tiger Global, and Z47 witnessing a substantial decline in their holdings.

Written by urgent.news from Economic Times Tech's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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