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OpenAI has just debuted its GPT-5 large language model (LLM) to mixed reviews, spurring broader conversation around the sustainable monetization avenues for these resource-hungry chatbots/LLMs. Now, one celebrated Wall Street analyst has identified the definitive sign that should precede the ongoing AI bubble's implosion.
As we noted in a dedicated post last week, OpenAI's Sam Altman has hailed the GPT-5 chatbot as the best AI model in the world, one that operates as a unified system, using an intelligent router to switch between various sub-models, based on the nature of the prompt employed.
Nonetheless, users have identified several cons that limit the utility of OpenAI's latest offering, including substantially longer response times, needlessly complicated response structure and syntax, and an inability to remember context despite a larger context window.
Against this backdrop, the X user @philoinvestor has penned an interesting thread, comparing the monetization path charted by Netflix to the one currently being employed by AI chatbots/LLMs.
At present, AI chatbot peddlers have just one recipe to generate sustainable revenues: increase average revenue per user (ARPU) by onboarding a mix of free and paid users, and reduce overall costs.
Unlike Netflix, whose bespoke content created a huge differentiation factor for end-users, thereby increasing the opportunity cost of switching to another streaming platform, most AI chatbots and LLMs are not that different from each other in terms of raw capability, which allows free users to flit between various AI model platforms.
So, even as costs continue to escalate to keep ever-complex models in operation, the peddlers of these AI models must continue to compete with one another to retain their users by offering extraneous bells and whistles, which erodes the overall economics of these chatbots and LLMs. In fact, AI chatbots might never become the monetization engines that their creators are currently dreaming of.
Meanwhile, Bank of America's Michael Hartnett has just penned an interesting note, identifying the critical sign that is likely to precede an implosion in the AI bubble:
"Expect concentrated US stock returns [Mag7 + AVGO, ORCL, and PLTR responsible for 80 percent of SPX gains since Trump's Liberation Day] to continue until tech credit spreads widen...as that will be the signal AI cash burn threatening AI overbuild trade. Indeed it was the same story in the second half of 1999, and it was the ensuing recession that was the true spark for the 2000s productivity spurt."
As we noted in a previous post, with around 250 data centers under construction in the US currently, this massive AI CapEx boom is now having a noticeable impact on the US GDP, one that might be as high as $624 billion (or 2.08 percent of the US GDP) in 2025 alone.
Of course, excesses lead to capital inefficiencies, which might eventually prompt the implosion of the ongoing AI mania, as per Hartnett's thesis.
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