Dexa/Demetrios Brinkmann

Published Jan 8, 2025

Machine Learning, AI Agents, and Autonomy // Egor Kraev // #282

Egor Kraev, principal AI scientist at Wise, discusses AI's transformative impact across diverse domains including finance, where it enhances fraud detection and treasury management, and marketing where causal inference is refining strategies. He also highlights the role of Large Language Models in data transformation and the benefits of fostering autonomous organizational structures for innovation.

Episode Highlights

Topics covered

Questions from this episode

- Tell me something about artificial intelligence
  Asked by 16 people
- How is AI used in tech companies as discussed in the episode AI, Big Data, and the Power of Framing — with Kenneth Cukier and the clip Data-Driven Mindset?
  Asked by 8 people
- What are some applications of language models?
  Asked by 7 people
- What's next in large language models (LLMs)?
  Asked by 7 people
- How can companies leverage data?
  Asked by 6 people
- What are some hot takes on web-based AI agents?
  Asked by 6 people
- What are the most recent developments and trends in AI, large language models (LLMs), retrieval-augmented generation (RAG), etc., as discussed in the episode #159 - Inflection-2.5, Devin, OpenAI board update, SIMA, EU AI Act passed and the clip Cohere's Command R?
  Asked by 5 people
- How can marketers leverage data?
  Asked by 4 people
- What are the next advancements in large language models (LLMs)?
  Asked by 4 people
- How can machine learning models help companies?
  Asked by 4 people
- Is this chatbot a large language model (LLM)?
  Asked by 3 people
- What technologies contribute to AI reasoning breakthroughs?
  Asked by 3 people
- How is machine learning used in trading?
  Asked by 3 people
- How is machine learning evolving as discussed in the episode Peter Norvig: Artificial Intelligence: A Modern Approach | Lex Fridman Podcast #42 and the clip AI Learning Paradigms?
  Asked by 3 people
- What are the pros of language models?
  Asked by 3 people

Episode Highlights

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