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AI, Corporate Responsibility & Democratic Legitimacy: Extended Q&A • Joanna Bryson • GOTO 2025

AI, Corporate Responsibility & Democratic Legitimacy: Extended Q&A • Joanna Bryson • GOTO 2025

Joanna Bryson challenges popular AI assumptions, positing current generative AI as powerful tools for cultural knowledge compression, not autonomous intelligences. She emphasizes that AI's capabilities are nearing the human knowledge frontier, requiring focus on human coordination and governance. Bryson critically examines AI's impact on mental health and law, advocating for data-driven regulation and comprehensible systems. She calls for engineering activism, asserting human agency over technological determinism and stressing the importance of transparency and critical thinking in shaping AI's future.

AI on Your Lakehouse: Context Comes in Shapes, Not Queries — Zach Blumenfeld, Neo4j

AI on Your Lakehouse: Context Comes in Shapes, Not Queries — Zach Blumenfeld, Neo4j

AI agents often struggle with context in lakehouses, leading to confident but incorrect answers. This workshop by Zach Blumenfeld introduces three Neo4j graph shapes built on lakehouse data—Connections (semantic layer), Trees (document outlines), and Communities (themes)—to provide essential context, enabling agents to accurately navigate structured and unstructured data, answer complex estate-level questions, and overcome limitations of traditional Text2SQL and vector search.

Learned Execution Graphs for Anomaly Detection & Drift in APIs — Ritvik Pandya, JP Morgan Chase

Learned Execution Graphs for Anomaly Detection & Drift in APIs — Ritvik Pandya, JP Morgan Chase

Ritvik Pandya from JP Morgan introduces 'learn execution graphs'—short-lived DAGs representing API request processing—to detect anomalies and drift in high-throughput systems. This approach localizes performance issues to exact nodes, identifies skipped or reordered steps, and differentiates between transient anomalies and fundamental system drift (structural, volume, or behavioral). It leverages per-client baselines and OpenTelemetry data to reduce mean time to discovery (MTTD) from hours to seconds, enhancing system reliability and observability.

Active Graph Agent Runtime (BabyAGI 4) — Yohei Nakajima, Untapped Capital

Active Graph Agent Runtime (BabyAGI 4) — Yohei Nakajima, Untapped Capital

Yohei Nakajima, creator of BabyAGI, introduces ActiveGraph, a novel agent architecture that builds around an immutable event log rather than the LLM. This log-centric approach enables auditable agents with native replay, rollback, and self-improvement capabilities, drawing inspiration from blackboard systems and Kafka.

Claude for Long-Horizon Tasks — Lance Martin, Anthropic

Claude for Long-Horizon Tasks — Lance Martin, Anthropic

Lance Martin from Anthropic shares insights into building reliable and secure long-horizon agents with Claude. He details architectural principles like decoupling the 'brain' from the 'hands' for reliability and security, implementing independent verifiers for self-correction, and developing advanced self-learning memory systems akin to human memory's in-band writing and offline 'dreaming' consolidation. The talk concludes with a vision for evolving agent harnesses towards organizational-level, proactive, and multiplayer capabilities.

GPT-Red: Can AI read teams stop prompt injections?

GPT-Red: Can AI read teams stop prompt injections?

This podcast explores AI's impact on cybersecurity, discussing OpenAI's GPT-Red for automated red-teaming against prompt injections, the open-source ScamBuster that uses AI to bait scammers for threat intelligence, and Bruce Schneier's insights on the widening gap between skill and ability in the AI era and its ethical implications for the field.