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Like I said above, I think there will be some very specific cases where running an LLM makes sense. Think along the lines of querying lakes of scientific data. This won’t be something of value to the average Joe or the average company. My experience with using LLMs for general search has been very hit or miss. I always end up using a general search engine, even for internal data sources.
Maybe that’s just you but millions of people are interfacing with LLMs every day as a replacement to a traditional search engine. I don’t see that changing. Either way, sounds like you are agreeing that AI will not go away entirely. That would be a silly thing to say.
It’ll also go dormant as LLMs are only one AI tech. Other AI tech will be developing while supporting infrastructure grows until we have another boom. World models for example and JEPA. That’s why Meta is pushing AI glasses. They need training data.
Those millions of people using AI for general search are currently getting it for free, which is going to end when the bubble bursts and the companies providing it go under, if not sooner when said companies try to make a profit. This is exactly what’s happening to corporate AI customers now. They are realizing there isn’t a good ROI now that OpenAI and other AI providers are being forced to charge proper costs for queries and tokens, rather than the teaser or “adoption” rates they charged before.
Interesting theory. I’d be surprised if Google started charging for their AI results. Too much free training data and they can afford to keep models running for the masses. They’re not solely an AI company. At the worst, these AI companies get swallowed up by bigger companies that can keep running even if AI is not profitable, which it is in some cases.