Traditionally, the development of robust intelligent agents and algorithms for commercial products is a slow and inefficient process that takes months or even years. We estimate that up to 70% of the resources in industry and even academia are spent on tasks that do not advance the state-of-the-art for intelligent algorithms. Instead, an enormous amount of time is spent building data collection infrastructures, managing data collection campaigns, experimenting with existing machine learning techniques, and finally porting the algorithms from analytics tools (e.g., Matlab) to target devices where they are tested and optimized. In this talk, we will review these pain points and present our platform which accelerates the algorithm development cycle over 100x while making it less expensive using automation, crowdsourcing, and crowdfunding so that businesses can ship algorithms in days instead of years. We will also introduce CrowdSignals.io, an effort to ethically collect the largest mobile dataset across the United States so progress on intelligent algorithms that use sensor data can catch-up with progress made in other areas such as vision via large datasets such as ImageNet and enable the application of techniques such as Deep learning.
Dr. Emmanuel Munguia Tapia is presently the cofounder and chief technology officer of AlgoSnap Inc., a startup focused on creating intelligent algorithms and analytics from massive sensor datasets to achieve unprecedented IoT device intelligence.Dr. Emmanuel Munguia Tapia