• Ep 251 - Dr. Shmuel Kliger on Causely, Causal AI, and the Challenging Journey to Reduce IT Labor

  • 2024/04/03
  • 再生時間： 1 時間 7 分
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Ep 251 - Dr. Shmuel Kliger on Causely, Causal AI, and the Challenging Journey to Reduce IT Labor

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  • Dr. Shmuel Kliger, the founder of Causely.io, discusses his journey in the IT industry and the development of Causely. With a strong focus on reducing labor associated with IT operations, Dr. Kliger emphasizes the importance of understanding causality and building intelligent systems to drive insights and actions in complex IT environments. He highlights the need to focus on purpose-driven analytics and structured causality models to effectively manage and control IT systems.

    Dr. Kliger also touches on the role of human interaction in influencing system behavior, mentioning the importance of defining constraints and trade-offs to guide automated decision-making processes. He envisions a future where humans provide high-level objectives and constraints, allowing the system to automatically configure, deploy, and optimize applications based on these inputs. By combining human knowledge with machine learning capabilities, Dr. Kliger aims to create a more efficient and effective approach to IT management, ultimately reducing troubleshooting time and improving system performance.

    The DiscoPosse Podcast is brought to you in thanks to GTM Delta.
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あらすじ・解説

Dr. Shmuel Kliger, the founder of Causely.io, discusses his journey in the IT industry and the development of Causely. With a strong focus on reducing labor associated with IT operations, Dr. Kliger emphasizes the importance of understanding causality and building intelligent systems to drive insights and actions in complex IT environments. He highlights the need to focus on purpose-driven analytics and structured causality models to effectively manage and control IT systems.

Dr. Kliger also touches on the role of human interaction in influencing system behavior, mentioning the importance of defining constraints and trade-offs to guide automated decision-making processes. He envisions a future where humans provide high-level objectives and constraints, allowing the system to automatically configure, deploy, and optimize applications based on these inputs. By combining human knowledge with machine learning capabilities, Dr. Kliger aims to create a more efficient and effective approach to IT management, ultimately reducing troubleshooting time and improving system performance.

The DiscoPosse Podcast is brought to you in thanks to GTM Delta.
リーダーシップ 就職活動 経済学
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