ChatGPT's inflection and packaging matter

In this episode, Christian Keller joins Henrik and Jeremy to explain how world models are shaping the next stage of generative AI. He talks through how AI learns using different types of inputs, and why video adds a sense of continuity, change, and cause and effect that text alone does not provide. Christian shares vivid analogies and clear examples to show what multimodal models make possible.

The conversation moves into how AI is now used throughout the research process, from generating synthetic data to evaluating model outputs. Christian shares how this loop is already in motion and how AI is helping scale and accelerate experimentation. He also reflects on the shift after ChatGPT launched, and how that changed the pace and structure of research work.

Later in the episode, Christian describes how individual workflows are evolving, and how asking simple questions like “Could AI help with this?” often opens new possibilities. He shares examples from his own work and home life, including how his wife built and graded her own French exercises using generative tools.

Key Takeaways:

• Text removes essential information
  Christian explains that text compresses reality and loses detail, context and temporality. Images and video help restore what text leaves out.
• World models give AI a sense of change
  Video introduces the before and after and how things move or enter a scene. This helps models learn cause and effect and builds more robust understanding.
• AI helps build AI
  Models can generate data, evaluate results and support researchers during development. Christian shows how this creates new ways of scaling experimentation and training.
• Workflows shift when AI handles early steps
  Christian shows how tasks like debugging and prototyping change with generative tools, which reshapes roles and opens new opportunities for innovation.

LinkedIn: Christian Keller | LinkedIn

00:00 Intro: Information Compression
00:37 Meet Christian Keller: AI Expert
01:13 The Evolution of AI Products
02:11 Impact of ChatGPT on AI Development
02:38 Understanding PyTorch and Its Role
07:41 The Bitter Lesson in AI
09:12 Challenges and Future of AI Models
18:57 Using AI to Build AI
23:25 Innovative Chat Interfaces
23:41 Building the Autos Platform
24:35 Epiphanies in AI Integration
25:18 AI in Entrepreneurial Workflows
26:32 Challenges in AI Integration
31:15 Bias in AI Models
38:06 Debrief 

For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin:

Henrik: https://www.linkedin.com/in/werdelin
Jeremy: https://www.linkedin.com/in/jeremyutley

Show edited by Emma Cecilie Jensen.