Interview with Ranjeeta Singh, VP, Data Science & AI, Teradata - Speaker at Global AI Conf - SCA - Jan 2019 Posted on : Jan 11 - 2019

We feature speakers at 3rd Annual Global Artificial Intelligence Conference - 2019 Jan 23 - 25 – Santa Clara to catch up and find out what he or she is working on now and what's coming next. This week we're talking to Interview with Ranjeeta Singh, VP, Data Science & AI, Teradata Topic - "Delivering Transformative Business Outcomes With AI"

Interview with Ranjeeta Singh

1. Tell us about yourself and your background.
I am a VP of Data Science & Artificial Intelligence at Teradata where I am focused on driving Artificial Intelligence Capabilities in the Teradata Platform and make it a solid workbench for data scientists.
I have been in the technology industry for over 21 years with the last 18 years at Intel, where I was most recently Senior Director of Incubation & Segment GM of Connected Worker Portfolio & Environmental Monitoring in Internet of Things (IOT) Group. I have held multiple leadership positions spanning across strategy, business planning, product management & marketing, architecture and engineering across various platforms.

2. What have you been working on recently?
Incubating new AI capabilities for Teradata Platform and making it a solid workbench for data scientists

3. Where are we now today in terms of the state of artificial intelligence, and where do you think we’ll go over the next five years?
I still think that AI is still in its infancy with few market segments that are ahead in leveraging AI. As artificial intelligence evolves and seeps into people's lives, it will impact how they work, live and grow.

4. There is a negative perception around AI and even some leading technology folks have come out against it or saying that it’s actually potentially harmful to society. Where are you coming down on those discussions? How do you explain this in a way that maybe has a more positive beneficial impact for society?
Artificial Intelligence is commonly associated with the fear that the more this discipline improves, the more human activities could be easily replaced by a robot. For this reason, many people don’t want to recognize how AI can contribute greatly to the progresses of human life. Artificial Intelligence is not eliminating jobs – it is eliminating tasks of jobs and creating new jobs. New jobs that are getting created are those that require traits that robots haven’t yet mastered like empathy, communication and interdisciplinary problem-solving.
Artificial Intelligence algorithms analyze quantities of data that until now had been a big concern for human beings, because it is very hard to examine such huge quantities of data in a fast and accurate way, without major mistakes.

5. When you’re hiring, what types of people are you hiring? The job market for traditional programmers, engineers is  very difficult to get into AI space. Are you hiring from that talent pool or is that a different talent pool? In terms of talent, how do you go about ensuring you get the best AI people at your company?
There is definitely shortage of AI and data science talent in the market. We leverage this small talent pool of AI s/w engineers and data scientists. However, I also look at this as an opportunity for folks interested in AI and data science space to leverage online resources as well as courses offered to beef up their skills. If your foundation in Mathematics, Statistics and Computer Science is strong, you can ramp up in this area easily.
We invest in academic engagements to ensure universities are training students well. We also provide internship opportunities.

6. Will progress in AI and robotics take away the majority of jobs currently done by humans? Which jobs are most at risk?
Artificial Intelligence is commonly associated with the fear that the more this discipline improves, the more human activities could be easily replaced by a robot. Artificial Intelligence is not eliminating jobs – it is eliminating tasks of jobs and creating new jobs. New jobs that are getting created are those that require traits that robots haven’t yet mastered like empathy, communication and interdisciplinary problem-solving. By taking over rote tasks, Artificial Intelligence in the enterprise frees up human worker to focus on product innovation and service improvement; allowing the company to transcend conventional performance trade-offs and achieve unparalleled levels of quality and efficiency.

7. What can AI systems do now?
We are already seeing widespread uses of AI across various verticals like Retail, Healthcare, Banking and Manufacturing. AI has enabled has to automate many tasks as well as analyze lot more data than was possible before to drive actionable insights.

8. When will AI systems become more intelligent than people?
In certain cases, AI systems are already more intelligent than people like playing Go. However, overall, we are still decades away from having AI systems that would surpass human intelligence across the board.

9. You’ve already hired Y number of  people approximately. What would be your pitch to folks out there to join your Organization? Why does your organization matter in the world?
Come, join us to jumpstart new AI and data science initiatives grounds-up and help enterprises find answers leveraging Artificial Intelligence capabilities in our platform. Be part of the team that helps enterprises find answers to the problems.

10. What are some of the best takeaways that the attendees can have from your talk?
Some of the biggest takeaways attendees can have from my talk are (a) understanding of key trends & challenges with implementing enterprise AI (b) how can enterprise AI get done well

11. What are the top 5 AI Use cases in enterprises?
AI in Banking, Retail, Healthcare & Lifesciences, Manufacturing & Telco is showing sign of interest & adoption. Key use cases are chatbots and fraud detection/prevention in banking & financial industry, precision medicine & medical diagnosis in Healthcare & Lifesciences, predictive maintenance & yield optimization in manufacturing, personalized recommendations in Retail. Enterprises are leveraging AI models for customer sentiment analysis, sales forecasting analysis, and customer churn predictions.

12. Which company do you think is winning the global AI race?
Many companies are doing very interesting things in the AI space. For me, the winning companies are effectively able to monetize AI and also make a difference in the lives of people. Amazon, Apple and Google have already been implementing AI in production. Amazon has grown its e-commerce empire by making targeted and differentiated purchase recommendations.

13. Any closing remarks
Thank you for the opportunity to share our insights around Enterprise AI. I look forward to answering questions and learning from your experience during the conference.