A developer-focused, demo-heavy session on rapid AI prototyping using the Google DeepMind stack. It covers how to leverage the full capabilities of AI Studio, from video analysis and code execution with Gemini 3.1 Flash, to building full-stack applications with databases, and exploring the frontiers of generative media with Genie 3, Veo 3.1 Lite, and Lyria 3.
Sander Dieleman from Google DeepMind provides a behind-the-scenes look at the key components of training large-scale diffusion models for audio-visual data. The talk covers the entire pipeline, from the critical role of data curation and latent representations to the mechanics of diffusion, network architectures, sampling with guidance, and advanced control signals.
Giedrius Praspaliauskas from AWS explores the ten stages of the API lifecycle, demonstrating how modern AI, Generative AI, and agentic systems are reshaping API strategy, development, security, and governance on AWS using services like API Gateway, AppSync, and Amazon Q.
Donné Stevenson (Prosus) and Pedro Chaves (OLX Group) explore the future of e-commerce, where AI agents will automate buying and selling. They discuss the transition from traditional search to agent-driven experiences, the critical challenges of user trust and UI/UX design, and a future vision for an agent-to-agent marketplace that handles everything from negotiation to logistics.
Microsoft researchers unpack the New Future of Work Report 2025, exploring AI's real-world impact. They discuss adoption trends, the shift in job tasks, and the crucial distinction between viewing AI as a simple tool versus a collaborator. The conversation emphasizes moving beyond pure efficiency to consciously design a future where AI supports human flourishing and meaningful work.
This episode explores the transformative impact of AI through three key discussions: a homeowner using ChatGPT to sell his house, a study on AI adoption in scientific research, and Adobe's CFO building an internal AI lab. The experts deliberate on AI's role in democratizing expertise, the future of professional roles, the challenges and biases in measuring AI's scientific impact, and the critical factors for successful enterprise AI adoption, including process and cultural shifts, and identifying the hottest areas for implementation.