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

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

2025/1/8
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Demetrios
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Egor Kraev
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Egor Kraev: 我认为大型语言模型最大的作用之一是作为非结构化数据之间的桥梁。过去的数据科学需要将所有内容转化为向量或矩阵才能开始工作,而现在主题分类可以直接使用文本描述,更容易理解和修改。我所见过的 LLM 的大部分生产应用是将非结构化的语言数据转化为结构化的数据。实际上在生产环境中,LLM 的大部分用例不是作为一个神奇的代理来完成所有事情,而是作为额外的乐高积木与其他积木结合使用。 Demetrios: LLM可以将非结构化的混乱数据转化为结构化数据。

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Egor Kraev, principal AI scientist at Wise, shares his diverse background, from studying mathematics in Russia and the US to working with nonprofits in Africa and then transitioning to a career in finance and AI. He discusses his journey and his current focus on causal inference and AI applications in Fintech.
  • Egor's diverse background in mathematics, economics, and finance.
  • His experience working with nonprofits in Africa.
  • His transition to a career in AI and Fintech.
  • His current role as Principal AI Scientist at Wise.

Shownotes Transcript

Since three years, Egor) is bringing the power of AI to bear at Wise), across domains as varied as trading algorithms for Treasury, fraud detection, experiment analysis and causal inference, and recently the numerous applications unlocked by large language models. Open-source projects initiated and guided by Egor include wise-pizza, causaltune, and neural-lifetimes, with more on the way.

Machine Learning, AI Agents, and Autonomy // MLOps Podcast #282 with Egor Kraev, Head of AI at Wise Plc.

// Abstract Demetrios chats with Egor Kraev, principal AI scientist at Wise, about integrating large language models (LLMs) to enhance ML pipelines and humanize data interactions. Egor discusses his open-source MotleyCrew framework, career journey, and insights into AI's role in fintech, highlighting its potential to streamline operations and transform organizations.

// Bio Egor first learned mathematics in the Russian tradition, then continued his studies at ETH Zurich and the University of Maryland. Egor has been doing data science since last century, including economic and human development data analysis for nonprofits in the US, the UK, and Ghana, and 10 years as a quant, solutions architect, and occasional trader at UBS then Deutsche Bank. Following last decade's explosion in AI techniques, Egor became Head of AI at Mosaic Smart Data Ltd, and for the last four years is bringing the power of AI to bear at Wise, in a variety of domains, from fraud detection to trading algorithms and causal inference for A/B testing and marketing. Egor has multiple side projects such as RL for molecular optimization, GenAI for generating and solving high school math problems, and others.

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// Related Links https://github.com/transferwise/wise-pizza) https://github.com/py-why/causaltune) https://www.linkedin.com/posts/egorkraev_a-talk-on-experimentation-best-practices-activity-7092158531247755265-q0kt?utm_source=share&utm_medium=member_desktop )

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Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/) Connect with Egor on LinkedIn: https://www.linkedin.com/in/egorkraev/)