Leon Palafox Breaks Down the Limits of Autoregressive AI Models
Why AI makes mistakes is a question more leaders and professionals are asking as tools like GPT-4 become more integrated into business and decision-making. In this concise yet illuminating video, Leon Palafox, Director of the Innovation Lab at Novartis, explains how advanced AI models function and why they can still deliver inaccurate or nonsensical answers. Joined by Bärbel Wetenkamp, CEO of Claruna, and hosted by The Swiss Quality Consulting, this interview offers a clear, non-technical explanation of how probability and prediction shape — and sometimes mislead — AI responses.
Key Highlights
- Probabilities, Not Facts: AI models like GPT-4 operate by predicting the next most likely word based on prior data — not by validating truth.
- What Are Hallucinations?: When one prediction goes wrong, it can cascade through the entire response, leading to surprisingly false results.
- Autoregressive Chains: GPT-4 builds each word on the last; an error early in the process multiplies downstream, making the output less accurate.
- AI Needs Human Oversight: Understanding these limitations empowers leaders to use AI more responsibly and with greater confidence.
Claruna’s Perspective on Responsible AI Use
At Claruna, we equip leaders to not only adopt AI but to understand and apply it ethically and effectively. With training, executive coaching, and strategic consulting, we help organizations leverage AI tools while staying grounded in human intelligence, responsibility, and purpose.
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