Will Bryk, co-founder and CEO of Exa, discusses the journey and technology behind building a search engine from scratch, specifically designed for AI systems. He explains why traditional search engines fail in an AI-first world and how Exa's full-stack, compute-heavy approach aims to solve the world's "information blocker" problems.
Ryan Daniels and John Sarihan of Crosby discuss their innovative approach of building an AI-first law firm instead of a traditional legal software company. They detail how integrating lawyers and AI engineers creates a unique feedback loop for automating contract negotiations, moving from billable hours to per-document pricing to achieve deal velocity, and their vision for AI agents that can simulate entire negotiations.
Krista Opsahl-Ong from Databricks introduces Agent Bricks, a platform designed to overcome the key challenges of productionizing enterprise AI agents. The talk covers common use cases, the difficult trade-offs between cost and quality, and how Agent Bricks uses automated evaluation and advanced optimization techniques to build cost-effective, high-performance agents.
This paper challenges the prevailing "bigger is better" narrative in AI, arguing that Small Language Models (SLMs) are not just sufficient but often superior for agentic AI tasks due to their efficiency, speed, and specialization. The discussion explores the paper's core arguments, counterarguments, and the practical implications of adopting a hybrid LLM-SLM approach.
A deep dive into seven essential AI concepts shaping the future of intelligent systems, including Agentic AI, RAG, Mixture of Experts (MoE), and the theoretical frontier of Artificial Superintelligence (ASI).
An overview of the new GPT-realtime speech-to-speech model and the general availability of the Real-Time API, detailing its architecture, advanced capabilities like image input and multilingualism, training methodology, and new enterprise-ready features.