From symbols to AI pair programmers 💻

How did we get from symbolic AI to deep learning models that help you write code (i.e., GitHub and OpenAI’s new Copilot)? That’s what Chris and Daniel discuss in this episode about the history and future of deep learning (with some help from an article recently published in ACM and written by the luminaries of deep learning).

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Featuring:

• Chris Benson – Website, GitHub, LinkedIn, X
• Daniel Whitenack – Website, GitHub, X

Show Notes:

• ACM article: “Deep Learning for AI”
• GitHub Copilot

Books

• “Human-in-the-Loop Machine Learning” by Robert (Munro) Monarch (use podpracticalAI19 for 40% off)
• “A Thousand Brains” by Jeff Hawkins

Something missing or broken? PRs welcome!

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Creators & Guests

Host

Chris Benson

Host

Daniel Whitenack

What is Practical AI?

Making artificial intelligence practical, productive & accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, GANs, MLOps, AIOps, LLMs & more).

The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!