Comment by bob1029 | Hacker News Reader

Comment by bob1029 | Hacker News Reader

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I believe we will see breakthrough success in the B2B/SaaS market sometime in 2026. I am getting an uneasy feeling regarding the notion of a bubble. By most accounts it should have popped by now. I am still using the LLM tech on a daily basis. It definitely adds value. Concerns like whether or not a human needs to be in the loop seem practically irrelevant at this point. Applying this value through productized channels is only a matter of time.

That said, the B2C AI market is a joke compared to the B2B market. Consumer AI use is an undeterminable black hole of money. All the bubble talk does make sense in context of normal-ass people using ChatGPT on their phones all day. Advertising is the only possible application for this market and it's already incredibly saturated.

Don't forget, the bubble talk is more around "AGI is right around the corner, don't get left out!" and not so much the application of an LLM to business process flows. There's definitely value in some use cases to using an LLM but I don't see the massive bets on AGI paying off in timelines Wall St. is comfortable with. Further, my feeling is the AGI promise and investment is what is keeping some of the model providers in business. From what I understand, inference cost per user doesn't scale the way a webserver does. With an LLM, more users means significantly more infrastructure cost and Google, Meta, MSoft can afford to run/train models at a loss because they get revenue elsewhere but not everyone is in that boat.

Yes the problem is not whether LLM have value, but whether they will add enough value in the next two three years to pay for the hundred of billions of trillions needed to match the expectations. OpenAI has to find more than a trillion by the end of the decade, project Stargate still has 500 billions to find, etc. Also add fast depreciation on everything invested. The ZIRP playbook of building a monopoly for years before turning a profit cannot work here, models are commoditizing fast so no moat there either, and capabilities as a function of compute have plateaued.

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