Topic: latency

Build Unity interaction and rendering features and a Python language-model backend for the Digital Einstein platform. Evaluate conversational quality and latency, maintain the system and support selected demonstrations; the semester workload is approximately fifteen hours per week.

Google DeepMind research director Brendan O'Donoghue examines discrete diffusion as an alternative to autoregressive text generation. He discusses sample diversity, reinforcement learning, latency and potential on-device or robotics applications. The episode also addresses the costs of serving diffusion models, hardware trade-offs between computation and memory bandwidth, and practical limits on progress toward more capable AI. Hosted by Ravid Shwartz Ziv and Allen Roush. Watch the full conversation on the publisher’s YouTube channel.