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In this episode, we talk with Michael Lanham, an AI and software innovator with over two decades of experience spanning game development, fintech, oil and gas, and agricultural tech. Michael shares his journey from building neural network-based games and evolutionary algorithms to writing influential books on AI agents and deep learning. He offers insights into the evolving AI landscape, practical uses of AI agents, and the future of generative AI in gaming and beyond.

TIMECODES 00:00 Micheal Lanham’s career journey and AI agent books 05:45 Publishing journey: AR, Pokémon Go, sound design, and reinforcement learning 10:00 Evolution of AI: evolutionary algorithms, deep learning, and agents 13:33 Evolutionary algorithms in prompt engineering and LLMs 18:13 AI agent books second edition and practical applications 20:57 AI agent workflows: minimalism, task breakdown, and collaboration 26:25 Collaboration and orchestration among AI agents 31:24 Tools and reasoning servers for agent communication 35:17 AI agents in game development and generative AI impact 38:57 Future of generative AI in gaming and immersive content 41:42 Coding agents, new LLMs, and local deployment 45:40 AI model trends and data scientist career advice 53:36 Cognitive testing, evaluation, and monitoring in AI 58:50 Publishing details and closing remarks

Connect with Micheal Linkedin - https://www.linkedin.com/in/micheal-lanham-189693123/ Connect with DataTalks.Club: Join the community - https://datatalks.club/slack.htmlSubscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/...Check other upcoming events - https://lu.ma/dtc-eventsGitHub: https://github.com/DataTalksClubLinkedIn -   / datatalks-club   Twitter -   / datatalksclub   Website - https://datatalks.club/

​Micheal Lanham has been building intelligent systems since the early 2000s, starting with neural networks and evolutionary algorithms in games and moving through enterprise software, geoscience, AR/VR, and now AI agents. Over the years, he has written more than ten technical books and worked across industries as an architect, manager, and hands-on AI engineer.

​In this conversation, Micheal shares hard-earned lessons from two decades at the intersection of data, software, and AI. We’ll explore what games can teach us about intelligence, why evolutionary methods are resurfacing, and how to think about AI agents beyond the hype. ​ ​We plan to cover:

• ​What games can teach us about AI and data products
• ​The promise (and limits) of evolutionary deep learning
• ​AI agents in practice: beyond LLMs and prompts
• ​How XR and intelligent systems are converging
• ​What it takes to productionize AI across industries
• ​What has really changed in AI over the last 20 years

​ ​About the speaker

​Micheal Lanham is a best-selling author, innovator, and AI engineer based in Calgary, Canada. His work spans games, graphics, GIS, enterprise software, and machine learning. He has published over ten technical books, including Evolutionary Deep Learning, Hands-On Reinforcement Learning for Games, and AI Agents in Action. Micheal has worked as a lead AI developer, architect, and manager across industries from oil and gas to fintech, and today focuses on building intelligent systems with deep reinforcement learning, evolutionary methods, and generative AI.

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Learn the building blocks of autonomous agents, including core architectures, planning methods, memory systems, and leading development frameworks.

Learn the building blocks of autonomous agents, including core architectures, planning methods, memory systems, and leading development frameworks.

Focus on real-world applications with sessions on agent evaluation, reliability, deployment strategies, and cumulative demo showcases.

Learn the building blocks of autonomous agents, including core architectures, planning methods, memory systems, and leading development frameworks.