Aurélien Géron is a Machine Learning consultant. A former Googler, he led the YouTube video classification team from 2013 to 2016. He was also a founder and CTO of Wifirst from 2002 to 2012, a leading Wireless ISP in France, and a founder and CTO of Polyconseil in 2001, the firm that now manages the electric car sharing service Autolib'. Before this he worked as an engineer in a variety of domains: finance (JP Morgan and Société Générale), defense (Canada's DOD), and healthcare (blood transfusion). He published a few technical books (on C, WiFi, and Internet architectures), and was a Computer Science lecturer in a French engineering school.

Two years after Vishal Sikka stepped down as the CEO and executive vice chairman of Infosys, an Indian IT services company, he has launched a new venture in artificial intelligence. Vianai, a Palo Alto, Calif.-based startup, last week announced its arrival with $50 million in seed financing. Sikka believes AI has the potential not just to transform business but also to "amplify humanity," as he puts it. He sees AI as a force multiplier that can tackle issues ranging from climate change to self-improvement. "I would love to see tens of millions of people to be able to build intelligent systems, and billions to be able to bring basic intelligence into anything that they do," he says. Sikka, who holds a Ph.D. in AI from Stanford University, demonstrated the Vianai platform at a keynote address at the Oracle OpenWorld conference on September 17. Before his tenure at Infosys, he spent 12 years at German software company SAP, where he was last a member of its executive board. Sikka also serves on the supervisory board of the BMW Group and as an advisor at the Stanford Institute for Human-Centered Intelligence (HAI).

The landscape of technical professions is constantly changing, and the resurgence of work in Artificial Intelligence has opened up new opportunities that differ from traditional Data Engineering and Data Science positions. Data Engineers build data pipelines and infrastructure to ensure a constant availability of transformed data. Data Scientists analyze and build models from these data to develop new product features or drive the bottom line of the business. The goal of newly-formed AI teams is to build intelligent systems, focused on quite specific tasks, that can be integrated into the scalable data transformations of Data Engineering work and the data products and business decisions of Data Science work. The differences between Artificial Intelligence, Data Science, and Data Engineering can vary considerably among companies and teams.

I have been a collector of books and classes of machine learning and deep learning for the last few years. Even though I come from a strong theoretical background, I have to say one must do hands on tinkering to be able to solve one's own problem successfully. Then for deep learning one must work with Tensorflow or Theano. However, I have been searching for a good hands-on book on tensorflow and had found none until this book. I purchased the kindle version so I can dive into this book early before the book comes out.

Thirty users of AI systems, 8. Make sure everyone knows at the Intelligence has announced that, key role in systems that enhance the 1. Integrating AI with traditional starting next year, its National Conference human values of the world we live in." He 2. AI may be only part of the system/ The 1991 AAAI Conferences will noted that, "Some of the most important solution, but it is increasingly the take place in Anaheim, California results of technology transfer part that makes the whole work. The National Conference will be the unexpected." "This is a recognition of changing significant benefits." "As AI moves more broadly champion" outside the AI/IS area, presentations focused on the approaches AI solutions that were only theory 12 to 18 months ago."