Prepare to Design the Future
March 19–20, 2017: Training
March 20–22, 2017: Tutorials & Conference
San Francisco, CA

The future will see you now: Machine learning transforms design

Mike Haley (Autodesk, Inc.)
11:20am–12:00pm Tuesday, March 21, 2017
Beyond the screen
Location: Grand Ballroom
Level: Intermediate
Average rating: ****.
(4.22, 9 ratings)

Who is this presentation for?

  • Designers, product developers, and executives managing design

Prerequisite knowledge

  • A general awareness of trends in information technology and design and product development practices

What you'll learn

  • Explore recent advances in computer science and data collection that have made machine learning and AI viable system options for designers and product developers
  • Understand how machine learning can remove barriers to creativity, making it easier and faster for designers to create new products and enriching the user experience
  • Learn the three stages by which machine learning will transform how designers work, including how it will accelerate workflows


Machine learning has made significant advances in recent years thanks to the development of computers’ ability to simulate very complex networks of neurons, the increased availability of enormous amounts of information through centralization of data and computing in the cloud, and the explosion of sensors and the resultant ability to collect constant streams of data from around the world.

Mike Haley explores how machine learning (aka artificial intelligence) is changing how designers build products and how people experience them—a transformation driven by advances in computer science that enable designers to remove barriers to creativity, making it easier and faster to create than ever before. This dramatic evolution is already happening and will continue through three stages:

  1. Easing the laborious tasks that designers face, such as having to continually search for appropriate content, fix errors, determine optimal solutions, communicate changes, and monitor for design failure—tasks that machine learning can rapidly accelerate.
  2. Assisting in the creation of sophisticated designs by suggesting alternative components, incorporating real-world, sensor-based performance, automatically generating design precursors, optimizing supply-chain processes, and intelligent manufacturing.
  3. Enabling products to function more like human assistants during the design and creation process, with designers able to “design” merely by expressing intent and curating results. Most artifacts will then be manufactured or assembled automatically, resulting in rapid prototyping and feedback cycles.

Through advances such as these, designers will ultimately be able to apply machine learning to all of their content, helping them create designs that were previously out of reach. In addition, better, safer designs will be easily achievable through applying machine learning to issues such as job-site risk in construction and predicting building performance.

Photo of Mike Haley

Mike Haley

Autodesk, Inc.

Mike Haley is senior director of machine intelligence at Autodesk, where he leads the group at Autodesk Research that identifies, evaluates, and develops disruptive technologies that improve the practice of imagining, designing, and creating a better world. Mike’s team combines research, development, and user experience in coupled iterative cycles to develop new products and foundational technology. For the last several years, the team has been focused on bringing geometric shape analysis and large-scale machine learning techniques to 3D design information with the intent to make software a true partner in the design process. Previously, Mike led the move of Autodesk products from the desktop to the cloud by driving the adoption of scalable, distributed compute and data technology. Prior to joining Autodesk, he performed research and product development in the fields of volumetric graphics, distributed multimedia, computer vision, and embedded systems. He is drawn to areas where he can combine his 25 years of experience in computer graphics, distributed systems, and mathematical analysis. Mike holds a master’s degree in computer science from the University of Cape Town, South Africa.