Machines that Learn Through Action: The Future of AI

location_city Sydney schedule Dec 7th 03:40 - 04:30 PM place Green Room people 231 Interested

Deep Learning has led to breakthroughs in many previously unsolved problem domains, from image classification to machine translation to medical imaging analysis. Venture capital firm Andreessen Horowitz recently cooked up an AI playbook, which posits that AI will impact software as broadly as relational databases have since the late 20th century. It’s hard to think of a technological problem that AI doesn’t touch.

In this talk, we will explore the limits of today’s most popular approaches to AI. In particular, what kinds of problems can’t we solve today and how might the solutions shape the way we approach software development? Training a model for your particular domain is easier than ever, but why is it so difficult to make sense of what is going on inside the model? How can we move toward a more intuitive and accessible model for understanding what our AI has learned?


Target Audience

Software engineers and anyone with an interest in artificial intelligence and machine learning.



schedule Submitted 3 years ago

  • Joshua Kerievsky

    Joshua Kerievsky - Modern Agile Workshop

    Joshua Kerievsky
    Joshua Kerievsky
    Industrial Logic Inc.
    schedule 3 years ago
    Sold Out!
    480 Mins

    Much has changed since the publishing of the Agile Manifesto in 2001.

    Pioneers and practitioners of lean and agile methods have examined weaknesses and friction points, experimented with simpler approaches, and produced agile processes that are safer, simpler and far more capital efficient. The result is modern agile. It’s values-driven, non-prescriptive and an easier starting point than antiquated agile processes. Modern agile amplifies the values and practices of organizations that have discovered better ways of achieving awesome outcomes. Are you still cramming low-quality work in the end of each sprint, struggling with growing technical debt, guessing about requirements, focusing on output over outcomes.