Schedule: Design, Interfaces, and UX sessions

AI assistants are among the most in-demand topics in tech. Get hands-on experience with Justina Petraityte as you develop intelligent AI assistants based entirely on machine learning and using only open source tools—Rasa NLU and Rasa Core. You'll learn the fundamentals of conversational AI and the best practices of developing AI assistants that scale and learn from real conversational data. Read more.

Hagay Lupesko explores AI-powered personalization at Facebook and the challenges and practical techniques it applied to overcome these challenges. You'll learn about deep learning-based personalization modeling, scalable training, and the accompanying system design approaches that are applied in practice. Read more.

Developments in ML and DL provided remarkable advances in the predictive capabilities of AI. However, the black box nature of the modern models creates challenges for those looking to adopt these techniques. Bahman Bahmani examines a framework and presents design and operating principles, recommendations, and best practices for human-AI integration in enterprise workflows, products, and services. Read more.

Consumers want everything now, at their fingertips, with very little effort. To meet these demands and compete, companies need to fundamentally rethink how they operate. Yi Zhang explores some predictions on how conversational technology will evolve from its current state in 2019. She outlines some common misunderstandings about the technologies and provides case studies from several industries. Read more.

Machine learning has enabled the move from manually programming robots to allowing machines to learn from and adapt to changes in the environment. Bastiane Huang examines how AI-enabled robots are used in warehouse automation, including recent progress in deep reinforcement learning, imitation learning, and real-world requirements for various industrial problems. Read more.

Robot technologies are becoming more capable and affordable. Yet even though technologies like natural language processing, mapping, and navigation are becoming more mature and standardized, it's often difficult to quantify human social behavior with algorithms. Dylan Glas and Phoebe Liu highlight some of the ongoing research to enable human-robot interaction. Read more.

Modern machine learning models often significantly benefit from transfer learning. Anusua Trivedi details a study of existing text transfer learning literature. She explores popular machine reading comprehension (MRC) algorithms and evaluates and compares the performance of the transfer learning approach for creating a question answering (QA) system for a book corpus using pretrained MRC models. Read more.

Design thinking is a methodology for creative problem-solving developed at the Stanford d.school. The methodology is used by world-class design firms like IDEO and many of the world's leading brands like Apple, Google, Samsung, and GE. Michael Radwin prepares a recipe for how to apply design thinking to the development of AI/ML products. Read more.