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Interview with Adnan Boz (Founder, Move To AI) - Speaker at Global Data Science Conference April 2018 Posted on Mar 13 - 2018

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We feature speakers at Global Data Science Conference - April 2 - 4 2018 - Santaclara - CA 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 Adnan Boz (Founder, Move To AI) Topic - "AI Strategy And Techniques For CEO, CTO And CIO"

Interview with Adnan Boz

1. Tell us about yourself and your background.

I'm the co-founder of Move to AI, former Yahoo Product Manager and former CTO of 3 tech startups. In the last 25 years, I deployed enterprise software solutions in video, media, healthcare, and online advertisement industries with the most notable two being Yahoo Sports news recommendation system, for millions of daily sports fans, and Apple Finance Stocks app news recommendation in 23 countries. 

 2. What have you been working on recently?

Nowadays I help mid-size companies with their end-to-end Artificial Intelligence transition, aka "Cognification". One interesting project was real-time object detection on iOS for detecting products on the grocery store shelves using Convolutional Neural Network models and real-time inference.

 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 think currently we are approaching the 3rd stage of AI. While every industry is at a different point in these stages, it seems like all of them will go through four stages: Automation Stage: AI helps to automate well-known processes. Decision Support Stage: AI acts as a decision support system to human or machine. Decision-Making Stage: this is the stage where AI makes decisions to help us. And lastly, Consciousness Stage: at least as far as I can see, the fourth stage is where AI lives for a purpose which is directly or indirectly unrelated to humans.

 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?

The concerns are valid and I see two potentially harmful cases: 1) AI vs. Human, 2) Human vs. Human using AI. The first case is when AI becomes a new species. This is a problem because it will be the only other species which highly depends on and controls electricity. The second case is if AI stays as a technology, but when humans deploy it to harm living beings. Especially when people start doing the wrong thing for a "right" reason. e.g. chicken slaughter machines or weapons. I think we will keep protecting ourselves in either case with counteracting systems. e.g. in the simplest sense: anti-virus software.

 5.  Will progress in AI and robotics take away the majority of jobs currently done by humans? Which jobs are most at risk?

Of course. Check out any job board; 90% of the job titles did not exist 20 years ago. While the industries moving through the four AI stages I explained before, the corresponding tasks will get obsolete for the human. e.g. self-driving car is the 3rd stage of the "vehicle driver" technology, or name it vehicle operator, and one day there won't be any human drivers left. And, new type jobs we can't even imagine today will come along.

6.  What can AI systems do now?

Object detection task in the Large Scale Visual Recognition Challenge (LSVRC) Competition exceeded human performance (, algorithms for The Stanford Question Answering Dataset almost exceeded human performance (, algorithms exceeded human performance on Switchboard Hub5’00 benchmark (

7.  When will AI systems become more intelligent than people?

I don't know. But there is a possibility that this won't ever happen because we keep utilizing AI to improve our ability to acquire and apply knowledge, aka intelligence. So, for AI to catch up it has to utilize human as well.

 8.  What are some of the best takeaways that the attendees can have from your talk?

I'm assuming by now everybody understands "Why" they have to cognify their business processes. There are also tons of online APIs, libraries and many free courses for the machine and deep learning engineers, explaining the "What" part. But there is almost no strategy, technique or framework which explains "How" to navigate through a large scale machine learning project from research to production. At the end of my presentations, attendees will have a firm framework they can apply to real-world projects in their companies, aka cognification.

 9.  What are the top 5 AI Use cases in enterprises?

Based on our experience:

- Marketing use cases to improve user acquisition and retention, and improve the top line

- Value-added product use cases to improve user interaction with the product or services

- Security use cases to secure digital communication and assets

- IT use cases to optimize asset utilization

- Production use cases to optimize cost and improve the bottom line

 10.  Which company do you think is winning the global AI race?

Google, Amazon and NVIDIA

 11.  Any closing remarks

Thank you for the opportunity to share our enterprise AI solutions expertise. We hope you find useful information to apply it to your cognification process.



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