Facebook shows roadmap to AI, Qubole addresses Big Data’s low success rate

NEW YORK—Why do companies struggle with Big Data and why is Ashush Thusoo, founder and CEO at cloud-scale data processing Qubole, concerned about it? The answer is obvious: Big Data gives you competitive advantage if companies can manage it; unfortunately, not all the time. It has been reported that only 27 percent of Big Data initiatives are classified as successful in 2014.

What are the impediments of aspiring data-driven enterprises? Thusoo enumerated it as follows: a rigid inflexible infrastructure, non-adaptive software services, highly specialized systems, and how it’s difficult to build and operate.

Thusoo was joined by Antoine Bordes, AI research scientist at Facebook; Katrin Ribant, founder and CSO at Datorama and Nick Elprin, founder and CEO at Domino Data Lab last October 26 at the Data Driven meetup at Bloomberg. The meetup, hosted by First Mark Capital’s Matt Turck, was back at Bloomberg after holding several events at AXA Equitable Center.

Why is data important? “You get left behind (if you don’t tackle it),” Thusoo said. “Data has been the driver. What data can do if you open it up if you make it available on the cloud? A cloud-based SaaS approach is turnkey. Get there quickly.”

“There has been a marked change in cloud. It’s more secure now. It keeps everybody honest,” he added.  

Qubole simplifies, speeds and scales big data analytics workloads against data stored on AWS, Google, or Azure clouds.

It’s refreshing to hear a grounded perspective on the state of artificial intelligence.

An AI research scientist at Facebook, Bordes showed decks showing how computer vision is not full-proof yet as he showed photos where the captions were not translated properly. “We have 20-year roadmap to AI.”

A team of 80 researchers at the social network is making use of synthetic tasks, even Wikipedia, as it works on improving AI. “Our motivation for work is not project driven. Our mission is to advance what AI can do. Everything we do should be applied to any format/visual input.” These include bAbl tasks, end-to-end memory networks, neural reasoner, and dynamic memory networks.

Facebook now has 1 billion stories posted every day; 100 million hours of video watched every day and 2 billion photos shared every day.

Domino Data Lab’s Elprin, for his part, talked about his belief in experimental agility and deployment agility. He thinks the best organizations work together as teams to advance common knowledge, even if “many data scientists think of their work as a solo act.

“Great outcomes come from a culture of discipline, collaboration, constant improvement,” he said.

Dataroma’s Ribant, which offers Big Data management for advertisers and ad agencies, talked about how marketing with data puts you ahead of the digital revolution

“We’re an end-to-end marketing analytics platform. Next year, we will apply machine learning to create insights from existing data assets.”