Trends in AI, Data Science, and Big Data (2017)

In this video, O’Reilly’s Chief Data Scientist, Ben Lorica highlights some recent research initiatives and trends in data from both the AI community and the big data/data science world. Topics include: the emergence of deep learning as a general-purpose machine learning technique; strategies for overcoming the main bottlenecks in running successful AI/machine learning projects (i.e., lack of training data and deploying/monitoring models in production); the transition from offline to continuous learning (including reinforcement learning); and the emerging software and hardware infrastructure for AI and machine learning. This is a must-view for every data scientist, data architect/engineer, data/business analyst, and manager or CxO who wants to stay current in the rapidly evolving world of big data, data science, and AI.

• Survey and understand the latest trends in deep learning
• Discover new open source tools bringing computer vision and text recognition to wide audiences
• Learn about the emergence of the machine learning engineer
• Explore opportunities to do machine learning for start-ups
• Hear about the recent trends in real-time, streaming, and reinforcement learning
• Become familiar with the hardware infrastructure for AI and machine learning
• Learn how labeled data, generative models, and weak supervision overcome the main bottlenecks in running successful AI/machine learning projects

Ben Lorica is the Chief Data Scientist at O'Reilly Media, Inc. and is the Program Director of both the Strata Data Conference and the O'Reilly Artificial Intelligence Conference. He has applied business intelligence, data mining, machine learning and statistical analysis in a variety of settings, including direct marketing, consumer and market research, targeted advertising, text mining, and financial engineering. His background includes stints with an investment management company, internet startups, and financial services.