Christopher Manning, Stanford professor and now at Moonlake AI, traces AI history from Dartmouth in 1956 and Shakey the robot through the rise of large language models. He then argues for embodied intelligence built on action-conditioned simulation, and shows how Moonlake turns a photo into a manipulable, code-based world that can close the sim-to-real gap.
Michael Lee, co-founder and CEO of Sequence Holdings, details his thesis on transforming large incumbent businesses with AI through a permanent holding company structure. He discusses the $7.7 billion take-private of Baldwin, an insurance brokerage, alongside the Dell Family Office, and explains why traditional consulting or software models fall short for deep enterprise AI transformations. Lee also shares insights from Sequence's work with BankSouth, the technical architecture of their Atlas platform, and their unique approach to integrating frontier engineering to drive long-term compounding and organizational change.
The AI Engineer Paris 2026 main stage featured discussions on the historical impact of AI as a general-purpose technology, the evolving landscape of AI engineering towards sophisticated "software factories," and Mistral AI's strategic vision for building frontier AI, ensuring agentic safety, and addressing data sovereignty through advanced models and infrastructure.
Sarvam introduces Vision India, a 3B parameter Vision Language Model achieving state-of-the-art in document AI for English and 22 Indian languages. It leverages a State Space Model (SSM) backbone for efficiency with long documents and a novel block-level OCR approach. A four-stage training curriculum, including advanced RL with verifiable rewards, and a robust data engine for low-resource languages underpin its superior performance, enabling the digitization of millions of pages for critical sectors.
Andrew Dai discusses how current frontier models struggle with visual reasoning, often hallucinating or failing to understand spatial relationships and context. He highlights limitations of existing benchmarks and proposes a 'visual thinking' paradigm, exemplified by Elorian's approach using native visual chain of thought, new data, and architectural advances to tackle real-world challenges in robotics, construction, and mechanical design.
Replit founder Amjad Masad and HAA co-founder Gagan Biyani discuss the future of education in the AI era. They argue for fostering young people's natural inclination to question norms, advocating for project-based, curiosity-driven learning over traditional, prescriptive models. The conversation also explores the pitfalls of premature startup professionalization, the evolving nature of work with AI, and the critical importance of trust, discernment, and personal development in tech's high-stakes environment.