| The use case you describe hardly describes what most workers do though. That's a robot Butler, not a desk worker who takes calls and fills out forms based on what the customer on the other end of the line says, or a factory worker (where automation has already been replacing tons of dangerous jobs without AI since the advent of engineering really). Also, I still think you can probably build something (or rather, many, many somethings) with existing tooling to accomplish exactly that. > A bigger LLM won't fix everything I'm not sure if there's a camp that says it probably won't fix anything, but I'm in that camp if it exists. If you think about how humans actually work, I think a basic, non AGI LLM routing information to different agents/models is closer to how most humans behave (when productivity is their goal). E.g. a person's behavior is driven almost entirely by the current context they are in most of the time. It's not that our minds become overexcited by loads of previous information and we magically are able to do other specialized tasks, we decide based on context what specialty in our toolset best fits the scenario. > The money's a funny one. Global GDP is about $85,000 bn/yr so if someone can spend $50bn on getting AGI and taking it over it's a bargain. But if you spend $50bn and just get a loss making chatbot then less so. If that's true then the same could be said of just dumping $50 billion into grants/research/funding for education around AI so that developers worldwide have an easier time developing AI enabled technologies and services. At least with that plan, there is extremely little risk of creating nothing more than a chatbot (and extremely low risk of tech companies monopolizing labor the same way they try and monopolize everything else; I don't have much faith that if a few companies automate all or most labor that they'll redistribute wealth) |