"If you do not want us to use your User Submissions to train our models, you can opt-out by setting the ‘Improve the model for everyone’ option under User Settings in the API Platform to OFF."
Inception is one of the most interesting neolabs with their diffusion-based architectures. My understanding is that their primary business is low latency voice applications but they are seriously pursuing coding.
We tested Mercury 2.5 Preview, which is nowhere close to the frontier (and not advertised as such), but it's actually usable as a general-purpose chatbot. It's comparable in problem solving ability to some last-gen open weights models, and the price and cost make it compelling. However, they have not figured out general purpose tool use and agentic coding (their model performs worse on our problems when given a custom harness). If they do, I see a lot of real-time applications that the speed and cost will enable.
I'd imagine at this point they are likely an acquisition target if they can get a halfway decent model. I can't imagine having diffusion sub-agents (or sub-sub-agents) in an orchestration wouldn't be beneficial.
Same. Models that are fast (and thus by extension, in some direction, efficient) but not local/self-hosted IMO fill a niche for quick and cheap (and acceptable quality, of course) inference in business contexts.
Got my hopes up when it said widely available GPUs that it would be open weights but it doesn’t seem like it sadly
I like the model.
FYI:
"If you do not want us to use your User Submissions to train our models, you can opt-out by setting the ‘Improve the model for everyone’ option under User Settings in the API Platform to OFF."
Inception is one of the most interesting neolabs with their diffusion-based architectures. My understanding is that their primary business is low latency voice applications but they are seriously pursuing coding.
We tested Mercury 2.5 Preview, which is nowhere close to the frontier (and not advertised as such), but it's actually usable as a general-purpose chatbot. It's comparable in problem solving ability to some last-gen open weights models, and the price and cost make it compelling. However, they have not figured out general purpose tool use and agentic coding (their model performs worse on our problems when given a custom harness). If they do, I see a lot of real-time applications that the speed and cost will enable.
I'd imagine at this point they are likely an acquisition target if they can get a halfway decent model. I can't imagine having diffusion sub-agents (or sub-sub-agents) in an orchestration wouldn't be beneficial.
Congrats! Happy to see someone seriously pursuing this direction.
Same. Models that are fast (and thus by extension, in some direction, efficient) but not local/self-hosted IMO fill a niche for quick and cheap (and acceptable quality, of course) inference in business contexts.
I thought this was going to be about a boat motor.
I thought it was going to be about Mercury[1] the programming language, and was confused about the domain name.
[1] - https://www.mercurylang.org/