Ai agents

NVIDIA’s USD 100bn investment and Google's AP2

NVIDIA’s USD 100bn investment and Google's AP2

The panel discusses NVIDIA's $100 billion investment in OpenAI, analyzing the trend towards vertically integrated AI 'tribes'. They also explore the rise of specialized open-source models like Tongyi DeepResearch, Google's new AP2 agent protocol for secure e-commerce, the ongoing debate on AI existential risk, and Apple's practical approach to wearable AI with the new real-time translation feature in AirPods.

Juicebox: AI Agents for the Hiring Process

Juicebox: AI Agents for the Hiring Process

Co-founders David Paffenholz and Ishan Gupta share their journey building Juicebox, an AI recruiting platform. They discuss their pivot from a music app to leveraging LLMs for talent search, how they achieved product-market fit, and their vision for AI agents that automate top-of-funnel recruiting.

Data Analytics & AI for Engineers | Altair RapidMiner

Data Analytics & AI for Engineers | Altair RapidMiner

A detailed walkthrough of the Altair RapidMiner platform, demonstrating how to build a complete predictive maintenance solution. The session covers low-code data preparation and visualization, automated machine learning with AutoAI, text analytics using both traditional methods and generative AI, and culminates in the creation of a sophisticated AI agent for operator support.

Designing AI Agents for the Complex Realities of Healthcare

Designing AI Agents for the Complex Realities of Healthcare

Dr. Sarah Gebauer presents a clinical framework for deploying AI agents in healthcare, drawing a powerful analogy between AI agents and medical residents. She outlines the critical risks, validation strategies, and post-deployment monitoring required to make agents useful, safe, and credible in high-stakes clinical environments.

Upwork's Radical Bet on Reinforcement Learning: Building RLEF from Scratch | Andrew Rabinovich (CTO)

Upwork's Radical Bet on Reinforcement Learning: Building RLEF from Scratch | Andrew Rabinovich (CTO)

Andrew Rabinovich, CTO and Head of AI at Upwork, details their strategy for building AI agents for digital work. He introduces a custom reinforcement learning approach called RLEF (Reinforcement Learning from Experience), explains why digital work marketplaces are ideal training grounds, and shares his vision for a future where AI delivers finished projects, orchestrated by a meta-agent named Uma.

No Priors Ep. 132 | With Decagon CEO and Co-Founder Jesse Zhang

No Priors Ep. 132 | With Decagon CEO and Co-Founder Jesse Zhang

Jesse Zhang, co-founder and CEO of Decagon, discusses how their AI agents are revolutionizing customer service for large enterprises by replacing mundane human labor. He covers their go-to-market strategy, the importance of a hardworking in-office culture, his journey as a second-time founder, and the future of an agentic world where AIs interact on behalf of companies and consumers.