From symbols to AI pair programmers 💻 (Practical AI #140)

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).

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 – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, Website

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!