How big data and AI bring synergies to data science

Data science is having its day in the sun, delivering a wealth of possibilities for women in technology. Talent is in high demand, open source is democratizing access, and innovation is blossoming. This roundup of insights and advice from female tech leaders highlights the potential of this exciting era.

Sindhu Gangadharan, Global VP and Head of Integration at SAP, gave this advice for businesses and consumers alike. “Get prepared to embrace that digital transformation. Today with IoT and Big Data, you are already able to find out a lot of insights from that massive wealth of data that you can’t normally do as a human being. If you add aspects like machine learning and AI to the mix, there are unprecedented opportunities for us to look forward to.” Let the exploration begin…

Open source is enabling the data science and AI revolution

In the data science realm, AI is being added to the mix in a big way. Ritika Gunnar, VP of Watson Data & AI, revealed that half of all applications currently being developed may include some form of AI. “Why? Because of the ubiquitous access to Scala, Python, R, Spark, all so openly and readily available in the market.” Open source is crucial to this transformation. “When we look at why we have the effects of every industry and profession being re-imagined because of AI, it’s because of the way open source technologies are being used. We have very fluid mechanisms to implement that via cloud and other distributed tech as well as the abundance of data…AI has been around for a long time, what has changed is that it is not so proprietary.”

Now that data science is being used everywhere, it has lost its ivory tower sheen. The focus is on utility. According to Jennifer Shin, Director of Data Science at Comcast, “Over the last few years, machine learning has become more prevalent and more people know about it. The expectations are changing; it’s not as impressive anymore. Everyone has access; everyone can write APIs themselves. Now people want to know what the data is actually saying, what the API is doing, and how the data is being manipulated. That’s where statistics and mathematics come into play. How do we quantify the impact or improvement, so we know when one algorithm is better than the other? How do we check and verify that?” The goal is to work with data in newer, less traditional ways, building abstract models and efficient algorithms that increase speed.

Data science is big business

Cloud vendors are building robust, commoditized solutions based on open source platforms like Spark to support large-scale deployment. Enterprises are leveraging this foundation to build their own infrastructure on top. What does it look like when big business embraces data science for analytics and artificial intelligence?

Gayle Sheppard, VP and GM of Saffron AI Group at Intel Corporation, spoke at the Spark Summit about her expectations for the future. “In my career, this is the most exciting time ever to be on the forefront of AI systems, distributed intelligent systems, from cloud to edge and back again. We are building solutions at Intel using a variety of machine learning technologies whether it’s statistically based, deep learning, or associative learning. All of these learning mechanisms are coming into business today. There’s no industry that won’t be touched by this.”

She pointed to several examples including the adoption of IBM Watson in healthcare and life sciences to improve the information available to doctors for decision-making and for the development of precision medicine for cancer treatment. Another use case involved an insurer in Texas using drones and visual cognition to survey areas of tornado damage. Based on this data, the insurer could automatically queue up service professionals and proactively assist customers in filing claims.

Number crunching in the cloud is useful, but some of the most intriguing tech inventions interface more directly with the human world. Being able to manipulate and program data at a massive scale is the key to creating more-complex systems on the physical plane. Professor Katja Patzel-Mattern from the University of Heidelberg spoke about taking 3D printing to the next level. “4D printing is the next step after 3D printing. Imagine you have a material that can be printed with a 3D printer but then change its form over time due to external factors.”

Innovators at MIT have already created a self-folding robot that can grip and release objects in response to heat stimulus. BMW envisions building 4D printing into vehicles that can change shape depending on velocity. The possibilities are endless. “Imagine what this would mean for manufacturing. In the end you would have an iPhone which can assemble itself. You don’t have shop floors with machine parts. You have a cup where you can put in pieces and they assemble themselves.” Distribution would also be changed forever. “Imagine buying something on the internet that only takes on its final form when it reaches your house, and what that would mean for logistics.”

Professor Jivka Ovtcharova, Head of the Institute for Information Management and Engineering, talked about what technologists can expect from current research and invention. “We are living in a very exciting time in the transformation of physical reality to digital and immersive reality. Virtual reality helps people experience anything. The emphasis is on EXPERIENCE, not just looking. We are moving very fast. The hype last year was the brain computer interface, pushing communication between humans and computers in a more intuitive way.”

Ovtcharova’s students have created programs and interfaces that simulate driving a car or even traveling through time and space. But there are practical implications for business and education in the midst of the fantastical realm of VR. “Things are connected to each other and influencing each other. The world is all-in-one, merging material and virtual realities.” In Jivka’s opinion, virtual reality is motivating people to communicate more in real time and space and supporting work in real-time environments. Collaboration for distributed teams is no longer restricted to Slack channels or conference calls, as people learn to work together in augmented reality. “To be able to interact using all the senses is very interesting and this is the right direction for education in the future.”

Right now, the world of the future is being shaped one petabyte at a time. How we communicate, what we buy and use, how our children learn, and how we live are all in the balance. In Katja’s words, “As women, we must be in the game. Don’t leave this field to men.”

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