Super Data Science: ML & AI Podcast with Jon Krohn cover image

Super Data Science: ML & AI Podcast with Jon Krohn

808: In Case You Missed It in July 2024

Aug 9, 2024
Guests include Daliana Liu, a leading data science expert, Charles Duhigg, a best-selling author on habits, and emerging talent Andrey Kurenkov. They discuss critical advice for new data scientists, emphasizing soft and hard skills in an AI-driven landscape. The future of model merging in AI is explored, highlighting its efficiency and industry impacts. Conversations around AI's role in podcasting showcase optimism about technology's evolution. Strategies for effective communication, especially in conflict, are unpacked, featuring techniques for enhancing dialogue.
38:23

Podcast summary created with Snipd AI

Quick takeaways

  • Emerging data scientists must focus on relevant technical skills and adaptability in response to advancements in generative AI technologies.
  • Model merging optimizes AI performance by combining pre-trained models efficiently, reducing computational costs and enabling faster task deployment.

Deep dives

Essential Skills for Data Scientists in Evolving Landscapes

The importance of adapting to industry changes is emphasized, particularly for data scientists. Relevant technical skills are crucial, especially in light of advancements in generative AI, so data scientists are encouraged to focus on understanding various technologies and their applications. For instance, while traditional forecasting roles may not be significantly affected by generative AI, opportunities in smaller firms could arise from leveraging large models to create innovative solutions like chatbots. Furthermore, companies are increasingly seeking candidates with proficiency in modern APIs and AI platforms, which positions job seekers as advisors to hiring managers regarding the best technological strategies.

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