The latest industry news, interviews, technologies, and resources.
Learn how to govern WebRTC jitter buffers for smooth AI-avatar speech, bounded playout delay, lip-sync and reliable interruption.
Learn how to stream LLM output into voice and avatar systems using stable speech segments, bounded queues, backpressure and safe interruption.
Learn when tensor parallelism helps private LLM inference, when replicas are better, and how to test multi-GPU latency, topology and failover.
Learn how to govern continuous LLM batching across admission, prefill, KV memory and fairness without damaging real-time AI-avatar conversations.
Decide whether to split LLM prefill and decode across private GPU pools for lower tail latency without ignoring KV-transfer and operational costs.
Govern LLM KV cache memory, prefix reuse, eviction and offloading without crossing tenant or session boundaries in real-time AI avatars.
