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Economist: AI company profits threatened by shallow moats and commoditization

Economist Brad DeLong of UC Berkeley argues that AI companies face significant challenges in maintaining profitability due to shallow competitive moats. He posits that rivals can easily replicate or distill advanced models, and any technological edge quickly becomes commoditized as competitors catch up. DeLong concludes that the business of selling LLM model services is likely to become a commodity market, which historically does not yield large economic profits. AI

IMPACT Suggests that AI companies may struggle with long-term profitability due to intense competition and rapid commoditization of their core technologies.

RANK_REASON Opinion piece from a named economist discussing the business model of AI companies.

Read on Mastodon — fosstodon.org →

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Economist: AI company profits threatened by shallow moats and commoditization

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  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    Professor (UC Berkeley) Brad DeLong, one of my favorite economists, says this about # AI companies & their profit potentials: “The problem is this: the moats ar

    Professor (UC Berkeley) Brad DeLong, one of my favorite economists, says this about # AI companies & their profit potentials: “The problem is this: the moats are shallow. Nothing stops a rival from offering a near-equivalent model—if only by distilling yours, training a cheaper s…