Interview with Murali Kaundinya, Director, Merck - Speaker at Global Artificial Intelligence Conference - Oct - 2017 Posted on : Sep 25 - 2017

We feature speakers at Global Artificial Intelligence Conference - Oct - 23 - 24 2017 - NYC 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 Murali Kaundinya, Director, Merck (Topic : Automated Schema Matching And Data Unification With Smart ETL Services)

Interview with Murali Kaundinya

1.      Tell us about yourself and your background.
I am a researcher and a hands-on technologist.  I began my career conducting scientific research at NASA which led to building distributed systems for AI and Machine Learning.

2.      What have you been working on recently?
I have recently been working on domain specific languages and formal methods to drive efficiency and reliability of large software systems in the enterprise. I have also been working on AI and process automation for information management.

3.      Tell me about the right tool you used recently to solve customer problem?
Enterprises can benefit so much with digitization. I have been realizing capabilities of an Intelligent Process Automation piece meal with open source software. This has huge potential to drive efficiencies.

 4.      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?
AI and related capabilities have begun to deliver true business value and it’s the tip of the iceberg. In the next 5 years, I expect significant lifestyle changes and radical innovation in the enterprise.

5.      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?
There is a balance to be struck between using machines for efficiency and having discerning humans for responsible decision making. Blindly yielding to a machine prematurely can be risky. Need sensible policy and healthy debate and this is an important topic.  

 6.      How do you explain this in a way that maybe has a more positive beneficial impact for society?
The science behind every technology should be made transparent, affordable and accessible. Once the knowledge of how-machines-work becomes prevalent, it will foster good debates, policy and decision making.

 7.      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?
I like to hire talent that has demonstrable acumen to think, analyze and critique systems. With that ability, one can learn new skills and get good at it with practice.

 8.      Will progress in AI and robotics take away the majority of jobs currently done by humans? Which jobs are most at risk?
Yes, some jobs done by humans will be automated but many other jobs cannot be that easily automated. Chances are that some monotonous jobs do not get filled due to lack of applicants and those may be prime candidates for automation.

 9.      What can AI systems do now?
AI systems can detect patterns and extract insights for correlation. AI systems can detect anomalies and help detect signal from noise.

10.  When will AI systems become more intelligent than people?
Depends on how we define intelligence! If mastering a knowledgebase or playing a game is intelligence, then machines like Watson and Google’s DeepMind have already outsmarted human experts.

11.  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?
We are working on several amazingly interesting opportunities and have so much R&D going on to influence progress in life sciences. The work we are doing requires tremendous creativity and innovative mindedness.

12.   What are some of the best takeaways that the attendees can have from your "Automated Schema Matching and Data Unification with Smart ETL Services" talk?
Get an appreciation of the use cases involved in curating internet scale data, common data models, dynamics of ETL/ELT, algorithms for data unification and operationalizing all the moving parts.

13. What are the top 5 AI Use cases in enterprises?
Image Processing, Predictive Maintenance, Anomaly detection, Information Management, Cybersecurity.

14.   Which company do you think is winning the global AI race?
Going by patents, the large technology infrastructure vendors are dominating but I expect to see them make it open and available to the broader scientific research community and Open Source Community.