Machine learning

Let's integrate AI Agents in Event-Sourced Systems — Divakar Kumar, FlyersSoft

Let's integrate AI Agents in Event-Sourced Systems — Divakar Kumar, FlyersSoft

This presentation explores integrating AI agents into existing event-sourced architectures to resolve ambiguous cases in real-time fraud detection. By leveraging a semantic layer built from various bounded contexts (transaction, device, account), specialized agents like Risk Analyzer and Behavior Analyzer use tools and short-term memory to reach a verdict, addressing the "gray zone" where traditional rule-based and ML systems fall short. The approach emphasizes layering agents without replacing existing infrastructure, enhancing judgment in production systems.

Morgan Stanley's ALPHALAB: Multi-Agent Research Across Optimization Domains — Brendan Rappazzo

Morgan Stanley's ALPHALAB: Multi-Agent Research Across Optimization Domains — Brendan Rappazzo

Morgan Stanley's AlphaLab is an open-sourced multi-agent system designed to automate quantitative research. Initially, AlphaLab 1.0 automated code generation, backtesting, and experimentation. Facing challenges, AlphaLab 2.0 evolves to prioritize building robust, verifiable environments, which serve as reinforcement learning signals, enabling the system to meta-optimize itself. This shift redefines the human role from performing research to designing these critical environments.

What Actually Makes an Algorithm Terrifying (with Cathy O'Neil)

What Actually Makes an Algorithm Terrifying (with Cathy O'Neil)

Dr. Cathy O'Neil, author of "Weapons of Math Destruction," asserts that terrifying algorithms are defined by secrecy, unaccountability, and a lack of opt-out, not mathematical complexity. She details how Taylorism's labor degradation now extends to white-collar jobs via AI surveillance. O'Neil discusses her firms, ORCAA and OCEAN, which provide statistical evidence for lawsuits against tech giants and advocate for algorithmic accountability through "cockpits" of metrics and transparent auditing, urging collective action against unchecked technological power.

Jensen Huang: The Mindset That Built NVIDIA

Jensen Huang: The Mindset That Built NVIDIA

Jensen Huang, CEO of NVIDIA, shares critical lessons from NVIDIA's journey, emphasizing how early failures and a commitment to learning new technologies, like purchasing textbooks from Fry's to pivot the company, laid the groundwork for their success. He discusses NVIDIA's strategic vision, driven by accelerating algorithm domains and seeing AlexNet as a universal function approximator, which led to a reinvention of the computing stack. Huang also explores the future of AI with agents, the importance of fine-grained control, and the "Linux moment" of open-source AI, while also forecasting the rise of physical AI and job creation. He concludes with profound advice on resilience, systems thinking, and the "how hard can it be?" mindset for aspiring entrepreneurs in this unprecedented era of technological reset.

Anthropic’s first technical PM on token maxing, the jagged edge, and living in the future

Anthropic’s first technical PM on token maxing, the jagged edge, and living in the future

Dianne Penn, Head of Product for Anthropic’s AI Research and Labs teams, discusses Anthropic's journey, the evolving AI landscape, and the changing role of product management. She highlights the importance of adaptability, 'evals as the new PRDs,' and how Anthropic's focus on alignment and safety makes Claude a more effective 'thinking partner' by enabling it to push back on user ideas.

How Two French Engineers In New York Built The Company That Monitors The Entire Cloud

How Two French Engineers In New York Built The Company That Monitors The Entire Cloud

Datadog CEO Olivier Pomel shares his journey, emphasizing the company's evolution from a DevOps insight to a public tech giant. He discusses the resilience required to overcome early rejections, his hands-on leadership style focused on raw customer feedback, and how Datadog is rapidly adapting to the AI revolution by prioritizing automation and faster iteration in product development and internal processes. Pomel also offers candid advice on co-founder relationships and the critical importance of moving quickly in both hiring and firing.