AI hardware design could filter out irrelevant visual data to reduce energy use

When we read a car’s license plate, we tend to focus on the numbers and letters, paying little attention to the surrounding buildings or sky. An artificial-intelligence (AI) system, however, may still process those surrounding details, consuming energy even when they contribute little to the task. As cameras capture ever more detailed images, this unnecessary …

Compressing Streaming Neural Audio Encoders via Latent-Space Distillation

System-wide Dictation on Apple devices runs entirely on-device, and the speech it transcribes reaches the foundation model through a tokenizer: an encoder that maps short windows of waveform onto the representation the language model reads. Because that model is sparsely activated under Instruction-Following Pruning, only a small subset of its experts occupies DRAM at any …

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Speaker-labeled transcription with WhisperX on SageMaker AI

Any team working with spoken audio hits the same wall with generic speech-to-text. Think contact-center calls, all-hands meetings, podcasts, depositions, and broadcast media. These workloads need two things that standard transcription gets wrong. First, timestamps land at the utterance level, off by several seconds. Second, there’s no reliable answer to “who said what.” Those gaps …

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Power your agents: Gemini 3.8 Live with Live Avatar is now generally available

Following our announcement of Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking last week, we are thrilled to share that Gemini 3.8 Live with Live Avatar is now generally available in Gemini Enterprise. First previewed at Google Cloud Next 2026, the technology is now officially ready for enterprise production. As enterprise voice AI evolves …