NYT data scientist Chris H. Wiggins discusses the use of AI in asset allocation

The latest episode of Improving Alpha The podcast, moderated by Michael Oliver Weinberg, includes a discussion with Chris H. Wiggins, Chief Data Scientist at The New York Times and Associate Professor of Applied Mathematics at Columbia University. The episode focuses on the use of AI and large language models (LLMs) in asset allocation and investment strategies.

The main points discussed include:

• How to transform and enhance investor data to improve asset allocation and investment strategies
• Understanding the strengths and limitations of AI in investment decisions
• The advantage of AI adoption between industry disruptors and established companies
• The framework of descriptive datasets, predictive models and prescriptive solutions in data science
• Considerations when hiring a data scientist for an investment team
• The broad acceptance of AI-related challenges
• Possible impact of AI on the world of work in the near future
• Investment opportunities in AI, including deep learning networks and supporting infrastructure (data centers, model training and data)

The Improving Alpha The podcast is provided by Vidrio Financial and sponsored by Observe alternatives alongside The Fund Marketer and PEVCtech.