AutoGPT sparked the imaginations of millions, it’s exciting because you can see what they will be able to do just by talking to them like you would with a human. It blew up because of this, not because of actual use case. First, what is an interact through natural language, performs actions in the real world. RPA. What agents could do in the future. But they suck right now. Why no actual use case yet? Reliability Memory, llm model complexity, architecture, tokens per second But ultimately we need a loss function to do tdd and improve agents. Getting thousands of prs and no way to test them. Don't know how to step if you don't know where you're going. How to get there, related to building language models Performance (benchmark) Safety (monitor) Standardization (agent protocol) Research pedigree is no longer the barrier to making an impact in the space, creativity is. And now there's a clear way to make it happen, mention and some of the work there AutoGPT.
