140 - AI Frontiers: The future of causal reasoning with Emre Kiciman and Amit Sharma

In this episode of the Microsoft Research Podcast, AI scientist and engineer Ashley Llorens interviews Senior Principal Researcher Emre Kiciman and Principal Researcher Amit Sharma regarding their research paper on "Causal Reasoning and Large Language Models: Opening a New Frontier for Causality." The discussion focuses on large language models (LLMs) like GPT-4 and their potential to revolutionize causal inference, problem-solving, and language capabilities. Kiciman and Sharma share their insights on the journey from GPT-3.5 to GPT-4, examine cause and effect, and discuss how LLMs are expected to augment the ways of reasoning in causal inference and make causal methods more accessible.

With the rise of powerful AI models like GPT-4 showing dramatic improvements in reasoning, language capabilities, and problem-solving, the future of AI is looking very promising. This podcast episode is part of a series that delves into the implications of these advancements and what they mean for the field in general. It provides insights into the cutting-edge research work being pursued in this area and offers a glimpse into how AI may impact various sectors like healthcare and education, among others.

If you're interested in learning more about the potential that LLMs like GPT-4 hold for the future of AI and the broader implications for healthcare and other fields, this podcast is a must-listen. You'll come away with a deeper understanding of the latest developments in artificial intelligence and a vision of what the future may hold for the field.

References:

• "Causal Reasoning and Large Language Models: Opening a New Frontier for Causality" publication by Kiciman and Sharma, April 2023
• "The AI Revolution in Medicine: GPT-4 and Beyond" book by Peter Lee, April 2023
• "AI and Microsoft Research" for more information on Microsoft's AI research

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