Datadog CEO Olivier Pomel on AI Security, Trust, and the Future of Observability скачать в хорошем качестве

Datadog CEO Olivier Pomel on AI Security, Trust, and the Future of Observability

Uncover the fascinating world of AI observability and security with Olivier Pomel, CEO of Datadog, in this eye-opening episode. Hosted by Guy Podjarny, Olivier shares his expertise in cloud computing and the evolution of observability, highlighting the critical role AI plays in modern applications. Dive into the challenges and innovations that define the intersection of AI and security, and gain valuable insights for your own projects. What You'll Learn: Discover the evolution of observability and its modern significance. Understand the challenges AI presents in security. Explore the potential of AI-powered applications. Learn about the future developments in AI and user interaction. Gain insights into building effective AI-powered teams. 🤔 How do you see AI changing the landscape of security in the next five years? Share your thoughts below! 👇 Join the Community! If you haven't joined the AI Native Developer Discord community simply click here to join us: https://tessl.co/4ghikjh Chapters: 0:00 – Episode highlight: Cloud vs. AI fears 1:00 – Intro to Olivier Pomel and Datadog’s role in observability 4:00 – Three layers of AI opportunity: infra, apps on models, AI-powered automation 7:00 – Datadog’s AI product suite: Watchdog, Bits AI, LLM observability, Toto 10:00 – Trust and accuracy: Why false positives kill AI adoption 16:00 – Human-AI interaction models: Chat, copilots, agents, and UIs 18:00 – Automation in observability: When AI can safely take action 21:00 – AI security concerns: Prompt injection, untrusted code, and sandboxing 26:00 – The importance of building trust while embracing early risks 30:00 – Building Toto: A foundation model for time series 36:00 – Observability and the future of software development 42:00 – Observability in GenAI apps: From infrastructure to outcomes 47:00 – Expanding into product analytics and primary data 51:00 – The future UI of observability: Human-like agents and interfaces 53:00 – The danger of overhyping AI in observability 56:00 – Building an AI research team and the shock of AI’s rapid progress