Bastiane Huang leads product strategy at Osaro, a San Francisco based machine learning company building Deep Reinforcement Learning software for industrial robots, backed by Peter Thiel and Jerry Yang’s AME Cloud. Bastiane has close to a decade of experience in the automation and manufacturing industries. Her experience in the field started in 2009 at e2v, a British space and industrial image sensor and machine vision camera manufacturer that is now part of Teledyne. She has broad experience in product marketing, business development, and operations at international technology companies across the industrial automation, IoT, AI, and robotics industries. She co-founded a software business at Advantech, the world’s biggest industrial computer manufacturer. The product offered video analytics solutions to improve traffic congestion and shopping experiences through people counting, and facial and heat map analysis. She was also an investor and advisor to early stage IoT and AI startups in the U.S. and Greater China and previously worked as a Senior Product Manager at Amazon Alexa. In addition, she is actively involved with Harvard’s 'Managing the Future of Work' initiative on AI and robotics writing case studies and articles. Bastiane holds a B.S. in Information Management (2009) from National Taiwan University and an M.B.A in Technology and Entrepreneurship (2018) from Harvard Business School.
There are only 3 million existing industrial robots in the world. Contrast that with 1 billion cars, and you see why self-driving gets more attention. Yet every other robot manufacturer we talk to says they cannot make robots fast enough. The International Federation of Robotics numbers just showed another year of 30% growth. The commercial opportunity for AI-enabled robots is huge, particularly in the logistics and materials handling industry and the automotive industry. These market opportunities are compelling because they are large, have already embraced some measure of automation, and have problem characteristics which are well suited to AI solutions.
At a societal level, AI-enabled robots will address the challenges of outsourcing/balance of trade, per capita productivity, competitiveness, inequality, and safety--some of the most long-standing and important problems facing the United States today. The best market for this opportunity is e-commerce fulfillment. Estimates of the total size of the materials handling and logistics market vary but most agree that it will approach $50 billion globally by 2022, and experience annual growth rates of 20%. After materials handling and logistics, the best use case is the automotive manufacturing industry. Automotive manufacturing is a $95 billion industry within the U.S., where approximately 10% of the final cost of goods go toward manual labor.
In this talk, I will discuss how AI-enabled robots are used in warehouse automation and how we can use warehouse robotics as a crystal ball and example for other industries (manufacturing, food assembly, surgical robots).