I am sorry I did not understand all of it. But, would this allow running large MoE LLMs on a local network with experts spread out over multiple cheaper GPUs (or even CPUs)? This would perhaps be more useful than over the Internet, within offices for example.
Ho thanks for the comment.
Verification does not depend on temperature.
Expert execution is deterministic (pure matmul).
LUMABRI_VERIFY=N re-runs N% of the calls on a second replica and requires byte-identical output.
Temperature (and sampling) happens only on the chatter, after the experts return their activations.
So it can be any value (0, 0.7, 1.2…) without affecting the verification contract.
P2P inference sounds really nice and it would bring us back to the 2000s culture if not for the fact inference is already so cheap. Even so it is an insurance policy if the cloud providers or governments have ideas of further censoring and monitoring chats.
I am sorry I did not understand all of it. But, would this allow running large MoE LLMs on a local network with experts spread out over multiple cheaper GPUs (or even CPUs)? This would perhaps be more useful than over the Internet, within offices for example.
[delayed]
Cool idea. How do you handle temperature in the verification?
Ho thanks for the comment. Verification does not depend on temperature. Expert execution is deterministic (pure matmul). LUMABRI_VERIFY=N re-runs N% of the calls on a second replica and requires byte-identical output. Temperature (and sampling) happens only on the chatter, after the experts return their activations. So it can be any value (0, 0.7, 1.2…) without affecting the verification contract.
Wasn't a p2p ai model how skynet got started?
J/k, this looks cool :)
P2P inference sounds really nice and it would bring us back to the 2000s culture if not for the fact inference is already so cheap. Even so it is an insurance policy if the cloud providers or governments have ideas of further censoring and monitoring chats.
great work
Thanks for the support!