Inference speed is being rapidly optimized, especially for edge devices.
too expensive,
The half-life of OpenAI's API pricing is a couple of months. While the bleeding edge model is always costly, the cost of API's are becoming rapidly available to the public.
and too unreliable
Out of the 3 points raised, this is probably the most up in the air. Personally I chalk this up to sideeffects of OpenAI's rapid growth over the last few years. I think this gets solved, especially once price and latency have been figured out.
IMO, the biggest unknown here isn't a technical one, but rather a business one- I don't think it's certain that products built on multi-agent architectures will be addressing a need for end users. Most of the talk I see in this space are by people excited by building with LLM's, not by people who are asking to pay for these products.
Comments
Inference speed is being rapidly optimized, especially for edge devices.
The half-life of OpenAI's API pricing is a couple of months. While the bleeding edge model is always costly, the cost of API's are becoming rapidly available to the public.
Out of the 3 points raised, this is probably the most up in the air. Personally I chalk this up to sideeffects of OpenAI's rapid growth over the last few years. I think this gets solved, especially once price and latency have been figured out.
IMO, the biggest unknown here isn't a technical one, but rather a business one- I don't think it's certain that products built on multi-agent architectures will be addressing a need for end users. Most of the talk I see in this space are by people excited by building with LLM's, not by people who are asking to pay for these products.