Inferencing is where AI comes to life in the real world - putting all the know-how it’s gathered during training into action to make decisions, deliver insights, or enhance systems.

The reality: Training happens occasionally. Inference happens continuously. Once a model is deployed, inference workloads don't just run once; they run millions (sometimes billions) of times a day.

Currently, models available for cross-inferencing include Claude 3.5 Sonnet, Claude 3 family of large language models (LLMs) — Haiku, Sonnet, and Opus.

When we last focused on Untether AI in 2021, the AI inferencing hardware startup had just secured $125 million in funding, which came a year after the company officially launched with its ...

Inference efficiency will likely become a big focus given the high training costs and reliance on the latest GPU chips for performance and smarter power use. We believe most companies will seek ...