A tour of MLX, the on-device AI framework for Apple Silicon. This talk explores real-world applications from real-time vision and multimodal omni models to sub-100ms speech synthesis and video generation, all running locally. It highlights breakthrough techniques like Turbo Quant for 1M context and showcases community projects in robotics and native apps, arguing for a future where powerful AI runs without the cloud.
Alexander Taubman, CEO of Long Lake Management, details their pioneering 'AI take-private' strategy, using a horizontal AI platform called Nexus to acquire and transform traditional service businesses. He explains why ownership trumps SaaS for driving real-world AI adoption, focusing on growth and creating a positive-sum flywheel for employees and customers, exemplified by their acquisition of Amex GBT.
This talk explores the architectural shift required to build durable, long-running AI agents. It argues against traditional replay-based durability, proposing a two-part solution: treating LLM context as a durable, append-only log and managing the compute state (memory, files, processes) with OS-level snapshot and restore, implemented efficiently using Firecracker microVMs.
A product engineer from Granola shares a candid account of the challenges in moving AI features from the playground to production. This talk covers the pitfalls of "one-shot" solutions like web search and generic prompts, and details Granola's strategy of building custom internal tracing and development tooling to create a tight, effective feedback loop for iteration.
Grant Miller from IBM explains Agentic Consent, a dynamic framework for governing AI agents. The model moves beyond static permissions, using identity, context, and just-in-time user prompts to ensure AI agents act with, not instead of, their human counterparts, enabling trust and safety as autonomy scales.
Samuel Humeau from Mistral explains the dominant architecture for modern text-to-speech (TTS) systems, which mirrors large language models. He details how neural audio codecs solve the information density problem, the autoregressive transformer backbone for generation, and the streaming techniques used to achieve low perceived latency in voice agents. The talk uses Mistral's open-weight TTS model as a practical example.