The latest industry news, interviews, technologies, and resources.
Measure AI inference energy consumption across GPUs, complete servers and cooling, then compare power per successful avatar conversation.
A practical method for validating AI model quantisation across speech, reasoning, voice and rendering before deploying real-time avatars on private GPUs.
Build a governed LLM evaluation dataset for real-time avatars across speech, knowledge, permissions, actions, multilingual delivery and release decisions.
Design an LLM semantic cache for real-time avatars with tenant-safe keys, freshness rules, permission checks, invalidation and measurable bypass controls.
Build an AI load-testing plan for real-time avatars across speech, reasoning, voice, rendering, WebRTC, concurrency and private GPU capacity.
A practical AI decommissioning framework for retiring avatar models, identities, data, GPUs, integrations and suppliers without leaving hidden risk.
