Real time ai

Local Agentic Theory For Mobile Games — Shafik Quoraishee & Joanne Song, The New York Times

Local Agentic Theory For Mobile Games — Shafik Quoraishee & Joanne Song, The New York Times

This presentation explores the innovative concept of running agentic AI entirely on mobile devices to enhance game accessibility and personalization. It delves into the technical challenges of local AI (space, time, energy budgets), contrasts agentic systems with traditional reinforcement learning, and demonstrates practical applications with a Space Invaders agent and a crossword solver. A key takeaway is the transformation of accessibility from fixed toggles to dynamic, real-time adjustments based on player needs, ultimately envisioning a future of billions of small, personalized local AI brains.

Voice In, Visuals Out: The Agony and the Ecstasy - Allen Pike, Forestwalk Labs

Voice In, Visuals Out: The Agony and the Ecstasy - Allen Pike, Forestwalk Labs

Allen Pike (Forestwalk Labs) discusses the power of "voice-in, visuals-out" AI experiences, a paradigm championed by Andrej Karpathy. He highlights the critical challenge of latency in real-time AI interactions and shares three key techniques for achieving low-latency, delightful user experiences: utilizing fast models, employing short inference intervals, and implementing stable caching regimens.

You Might Not Need 50 Diffusion Steps — Ziv Ilan, Nvidia

You Might Not Need 50 Diffusion Steps — Ziv Ilan, Nvidia

Ziv Ilan from NVIDIA details how latency in video diffusion models can be drastically reduced to achieve real-time generation. He presents a layered approach combining dynamic quantization for memory and speed, chunk-based caching to skip redundant denoising computations, and, most critically, step distillation—training models to achieve high-quality output in significantly fewer steps. These techniques, packaged in the open-source FastGen repository, offer additive performance gains, enabling real-time video on a single Blackwell B200 GPU.

From Transcription to Live Music: Gemini's Audio Stack — Thor Schaeff, Google DeepMind

From Transcription to Live Music: Gemini's Audio Stack — Thor Schaeff, Google DeepMind

Thor Schaeff from Google DeepMind demos the advanced audio AI stack, starting with a single API call to Gemini for rich transcription (speaker names, emotions, translation). He showcases speech generation directed by "director's notes" instead of a voice catalog, the real-time, sound-to-sound Gemini 1.5 Flash Live model, and a live demo of Gemini Live using the Lyria 2 model as a tool to generate a full song on stage.

This Startup Built the Infrastructure Powering Voice AI

This Startup Built the Infrastructure Powering Voice AI

In a YC Founder Fireside chat, AssemblyAI founder Dylan Fox discusses his journey from a solo founder in 2017 to leading a major voice AI infrastructure platform. He covers the early challenges, the technological shifts that fueled growth, the development of intelligent, promptable voice models, and the lessons learned in scaling a deep-tech company.

Real-Time Voice Agents in Production

Real-Time Voice Agents in Production

Panos Stravopodis, CTO of Elyos AI, shares the infrastructure and orchestration challenges of building production-ready voice AI agents. He details the four pillars for success—latency, consistency, context, and recovery—and provides engineering patterns for error handling, context management, and achieving conversational coherence in real-time systems.