by Angela Guess
Jennifer Bi of Salesforce recently wrote in Business2Community, “Big Data has been a hot topic since the Information Age took the world by storm in the 21st century. What quickly followed was the birth of the ‘data scientist’ as an occupation to manage this influx of information, a job title our past VP of Product, DJ Patil coined in 2008. Having witnessed the growth of data science as a discipline, our Chief Data Scientist, Vitaly Gordon is excited for its future. Vitaly currently leads our data science team at SalesforceIQ, where they are developing sophisticated machine learning tools for the intelligent Customer Success Platform. We sat down with Vitaly to get his perspective on what he envisions for the future of data science.”
Gordon said, “‘Data Scientist’ is a relatively new term, but that doesn’t mean data scientist jobs didn’t exist before. There were data analysts, data mining, engineers. Google was doing it, Amazon— there were companies with data roles before it was called ‘data science.’ And that’s for a reason. It is new. As many people mention, it’s the Information Age. It’s similar to social media marketing managers. It isn’t as if social media didn’t exist before, but as the industry changes and the need grows, it forms a specific job function: the social media manager. It’s the same situation for data science.”
He went on, “Let’s look at where data science is now. In the last few weeks, Google created an AI that beat Go world champion Lee Sedol. In ’97, IBM’s supercomputer Deep Blue beat world chess champion Garry Kasparov in a six game match. But this time, it’s different from the match in 1997, because Deep Blue was an expert system — which I’ll explain further in a moment. Deep Blue was taught by chess grand players to play chess, but the DeepMind Go system taught itself how to play Go. There were not as many experts involved, so this is a mind blowing breakthrough.”
Photo credit: Flickr/ collision.conf