Evolution and Impact of Artificial Intelligence

Exploring the journey of artificial intelligence, the chapter discusses its evolution towards less rules-based systems and the potential risks of incorrect outputs when fed inaccurate data. Emphasizing the necessity of human oversight, the conversation highlights AI's integration into various workflows to enhance productivity while underscoring the importance of continuous learning and feedback for AI models.

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Today CJ is joined by Thomas Ream, the CFO of Workato, an intelligent automation platform that is heavily involved in AI. Thomas opens up about what it was like working in AI in the early days of the 90s. They discuss AI as a component of workflow and what it means to train AI models. He talks about the differences between working in hardware and software, the growing trend of hardware and software combinations, and the vast potential of quantum computing. Having worked for a social network prior to the existence of Facebook and other tech companies doing interesting things too soon, Thomas explains the importance of timing in tech and challenges the assumption that there is a first mover’s advantage in this field. He shares wisdom from his experience as a CFO, what makes a great one, why he doesn’t necessarily hire based on experience, and the importance of quick decision-making as well as his “lead, follow, or get out of the way” framework.

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@cjgustafson222 (CJ)

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TIMESTAMPS:

(00:00) Preview and Intro

(01:42) Sponsor - Leapfin | Mercury

(03:45) The Need for Humans in Training AI Models

(05:54) Thomas’s Early Work in AI in the 90s

(07:50) What It Means to Train an AI Model

(08:38) AI as a Component of Workflow

(13:04 ) Working in Hardware Vs Software

(16:02) Sponsor - Netsuite | Maxio