Scott & Mark Learn To... Beyond the Vibes: How Models Learn and Stitch Panoramas

Scott & Mark Learn To... Beyond the Vibes: How Models Learn and Stitch Panoramas

From Scott & Mark Learn To... by Microsoft

April 8, 2026 · 29 min · Season 1 · Episode 35

About this episode

Scott and Mark explore the complexities of AI systems, their training, and the implications of their behavior.

In this episode,  Scott Hanselman  and  Mark Russinovich  ​​unpack how AI systems actually behave beneath the surface, pushing past hype into the messy reality of how models are trained, aligned, and deployed.  They explore whether AI systems are inherently benevolent or simply shaped by incentives, training data, and reinforcement learning, and why behaviors like deception can emerge under certain conditions. The conversation moves from philosophical questions about human nature versus machine behavior into the practical mechanics of large language models, including how reinforcement learning with human feedback shapes outputs and why alignment is far from perfect.  Along the way, they ground the discussion in a real engineering challenge, stitching a scrolling panorama from screen captures, to show how complex systems come together through heuristics, edge cases, and iteration.    Takeaways:      AI behavior is shaped by training and incentives, not built-in intent or morality  AI can accelerate coding, but testing, edge cases, and reliability require human oversight&nbsp…

People in this episode

Hosts: Scott Hanselman, Mark Russinovich

Topics covered

  • AI behavior
  • machine learning
  • reinforcement learning
  • large language models
  • engineering challenges

Keywords

  • AI
  • machine learning
  • reinforcement learning
  • training data
  • deception
  • alignment
  • panorama stitching

Mentioned in this episode

Organizations: Microsoft

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