My point is that we’ve built our model on top of these “generalist” models. You hook it up to an API and then let Claude, Mistral, etc. (I try to avoid GPT and some other) do the generalist job of translating human language into actionable tasks. You give it tools to parse documentation and actually do the tasks.
The generalist models are fairly good at taking a set of instructions and translating that to the correct tool calls, then our tools enforce correctness on the final output. Building an agent like the one we have would be nearly impossible without having some generalist model to do the “translation” step.
I think we’ll see two major changes going forward in how LLM’s are used: 1) they’ll become much more expensive and less widely used, since today they’re run at a loss. 2) they’ll be integrated into larger systems where they can do what they’re good at (parsing and outputting natural language), while offloading technical tasks to other tools that are actually built for technical tasks where formal correctness is paramount.
The two of you are using the word “generalist” differently. You don’t need your tool-using language model to be able to wax poetic about ancient egyptian burial practices. That’s why ChatGPT will become useless. It’s too large and expensive to continue running without subsidies, and it’s too useless for serious tasks. You can get away with a small local model that knows nothing about ancient egypt if all you need is to translate natural language into tool calls.
My point is that we’ve built our model on top of these “generalist” models. You hook it up to an API and then let Claude, Mistral, etc. (I try to avoid GPT and some other) do the generalist job of translating human language into actionable tasks. You give it tools to parse documentation and actually do the tasks.
The generalist models are fairly good at taking a set of instructions and translating that to the correct tool calls, then our tools enforce correctness on the final output. Building an agent like the one we have would be nearly impossible without having some generalist model to do the “translation” step.
I think we’ll see two major changes going forward in how LLM’s are used: 1) they’ll become much more expensive and less widely used, since today they’re run at a loss. 2) they’ll be integrated into larger systems where they can do what they’re good at (parsing and outputting natural language), while offloading technical tasks to other tools that are actually built for technical tasks where formal correctness is paramount.
The two of you are using the word “generalist” differently. You don’t need your tool-using language model to be able to wax poetic about ancient egyptian burial practices. That’s why ChatGPT will become useless. It’s too large and expensive to continue running without subsidies, and it’s too useless for serious tasks. You can get away with a small local model that knows nothing about ancient egypt if all you need is to translate natural language into tool calls.