A bank's AI demo works but cannot ship due to non-engineering problems like security, data ownership, and risk approval. Paden Gayle outlines a method focusing on early stakeholder discovery, iterative workflow scoping, gradual autonomy, and a comprehensive evidence pack to build AI systems with a credible path to production, emphasizing that "discovery is the engineering."
Boris Scharinger, Industrial AI Strategist at Siemens and author of "Industrial AI: From Pilot to Profit," discusses why 95% of AI proofs of concept fail in industrial settings. He highlights the 5-10x cost multiplier from pilot to production, the critical role of the "harness" around AI models, and the unique challenges of data access and legacy systems in physical environments. Scharinger advocates for a two-tiered investment strategy, separating foundational data capabilities from use-case-specific ROI, and addresses cultural resistances from engineers. He provides guidance on differentiating commodity from strategic AI applications and how to effectively scale industrial AI for profit.
Chelsea Finn, co-founder of Physical Intelligence, discusses the path to building general-purpose robots that operate reliably in the real world. She details how advanced reinforcement learning with human intervention, coupled with multi-scale memory systems, significantly boosts robot autonomy and throughput. Finn argues that robotics is entering its "GPT era," moving from specialized models to powerful, out-of-the-box foundation models like their PIO7, which demonstrates strong compositional generalization across tasks, objects, and robot platforms, matching or exceeding specialist performance without fine-tuning. The talk also covers the unique challenges and opportunities in robotics data, model deployment, and career paths.
Pauline Brunet, VP of Forward Deployed Engineering at Cursor, details how FDE drives AI adoption in enterprises. She distinguishes FDE from traditional services, outlines the 'magical unicorn' FDE profile, shares Cursor's project-based co-development approach, and offers best practices for team structure, customer engagement, and measuring ROI.
This session explored Multimodal and Embodied Intelligence, featuring talks on hybrid AI in robotics (classical vs. end-to-end), AI's role in healthcare (focusing on NCDs, deployment, and uncertainty modeling), and fundamental perception challenges in multimodal reasoning (using educational video QA and visual puzzles). A panel discussed the impact of foundation models, the blurred lines between AGI and human-like AI, critical deployment pitfalls (human factors, efficiency, architectural limits), and future directions, emphasizing task-specific models and the redefinition of 'foundation models.'