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Safe and Sound AI is your go-to podcast for staying ahead in predictive and generative AI development. From pre-production design and post-production monitoring to governance and compliance, we deliver bite-sized episodes packed with technical insights and best practices. Designed for data scientists, engineers, trust and safety teams, and business leaders, our focus is to help you deliver and scale AI innovations with safety, trust, and transparency in mind. Safe and Sound AI is brought to you by Fiddler AI.
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- The Anatomy of Agentic Observability · 16 min · Jakso 7As AI evolves from single agents into complex, multi-agent systems, the challenge of monitoring and trusting these autonomous collaborators grows. Traditional monitoring tools…
- Agentic Observability: The AI Architect's Essential Blueprint · 14 min · Jakso 6In this episode of Safe and Sound AI, we dive into the challenge of moving AI agents from impressive demos to robust, production-ready systems. We break down the principles of…
- How to Identify ML Drift Before You Have a Problem · 9 min · Jakso 5In this episode of Safe and Sound AI, we dive into the challenge of drift in machine learning models. We break down the key differences between concept and data drift (including…
- Industry’s Fastest Guardrails Now Native to NVIDIA NeMo · 10 min · Jakso 4In this episode, we discuss the new integration between Fiddler Guardrails with NVIDIA Nemo Guardrails, pairing the industry's fastest guardrails with your secure environment. We…
- Introducing Fiddler Guardrails: The Fastest in the Industry · 7 min · Jakso 3In this episode, we explore how Fiddler Guardrails helps organizations keep large language models (LLMs) on track by moderating prompts and responses before they can cause…
- Should you Observe ML Metrics or Inferences? · 13 min · Jakso 2In this episode, we explore two key approaches for monitoring AI models: metrics and inference observation. We break down their trade-offs and provide real-world examples from…
- Tracking Drift to Monitor LLM Performance · 12 min · Jakso 1In this episode, we discuss how to monitor the performance of Large Language Models (LLMs) in production environments. We explore common enterprise approaches to LLM deployment…
