The news of the recent Cambridge Analytica scandal did not just bring privacy concerns to the fore, it also signified how valuable a commodity data has become in today's information age. It showed us how impactful the process of leveraging data can be, and why companies across the board are adopting Machine Learning to learn from their data and completely transform their businesses. Despite the clear need, global enterprises and start-ups are struggling to scale their Machine Learning initiatives. One of the major factors limiting scale is the inability to acquire and retain the right talent. In a recent Zinnov Talent Hotbeds Forecast, we analyzed multiple cities for Machine Learning talent and predicted new hubs that would emerge over the next two decades. In the study, we found that Global top 500 R&D spenders together employ over 92,000 employees skilled in Machine Learning technologies and that 32% of this number are employed by the world's Tech Giants such as Google, Amazon, Facebook, and Microsoft.

"What do you do for a living?" That question used to have a pretty clear answer: "I'm a data scientist." But lately, it's gotten more complicated… The three of us -- Jorge Castañón, Óscar D. Lara Yejas, and Adarsh Pannu -- do data science at IBM's Machine Learning Hub, where clients from around the world bring us their mission-critical goals for turning data into knowledge. The clients range across industries from insurance to retail to energy to finance. On Monday, a manufacturer needs to use data from the quality control process to fast-forward the testing of components -- with no forfeit of excellence.

Yesterday, IBM opened its first Machine Learning Hub in Bengaluru. The company hopes that the Hub will allow engineers, data professionals, business analysts and organizations to greatly benefit and learn through collaboration with like-minded organisations. IBM says that various enterprises will now have an opportunity to work closely with IBM data experts to understand the technology to analyze, visualize and interpret data. The Bengaluru ML hub is an addition to IBM's growing ML Hubs, similar to the ones in Toronto, San Jose, California, Beijing, Boblingen, and at IBM's Silicon Valley Lab. According to IBM, their experts will also assist visitors build and test rapid, scalable prototypes for fast deployment of their models.