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Thought Leaders in Artificial Intelligence: FusionOps CEO Shariq Mansoor (Part 5)

Sramana Mitra: We’ve been covering the AI trend quite extensively for a while now. There are so many interesting use cases in all segments. I’ve always been really excited about AI as a technology, but it took a long time to find its stride.

Shariq Mansoor: Yes, that’s because people are now focusing on solving problems. All the pieces needed to come together.

Sramana Mitra: The pieces were not there. All the pieces have come together now. Tell me a little bit about your company. You said you’ve been around since 2005 and you had some angel investors. What was the evolution of the company?

Shariq Mansoor: We started through angel funding. Some of our investors are, themselves, entrepreneurs. We angel-funded until the market >>>

Thought Leaders in Artificial Intelligence: FusionOps CEO Shariq Mansoor (Part 4)

Sramana Mitra: Other than demand forecasting, what are some other use cases?

Shariq Mansoor: We are focused on things that many providers can’t even do right now. They do demand forecasting, but we do it better. Today, they are using machine learning and AI, but we can still do it much better. We have scenarios that we’ve created in our system that no other company has been able to.

An example is how can you predict the shortage of my competitors before the competitors even know. We combine data like what people are searching on Google. If you have one drug, we search for symptoms of that drug. How many prescriptions are getting written outside? What is the shortage historically? The >>>

Thought Leaders in Artificial Intelligence: FusionOps CEO Shariq Mansoor (Part 3)

Sramana Mitra: What information are you extracting?

Shariq Mansoor: All the supply chain intelligence. Our definition of supply chain is not just sending packages to your customers. Our supply chain is your entire company from the moment you have a demand, to manufacturing, purchasing, and to everything that happens in between. What this means is, we go after these big systems and we have these crawlers that extract all the sales data and historical data of how they’re running their business. It’s all automated.

Once it’s extracted, we start putting all the correlation and algorithms that we have developed on top of the data. From there, we start figuring things out. Then it uses our cognitive engine, which is based on machine learning, to figure out what is going to happen. We apply all these algorithms and not just one algorithm. >>>

Thought Leaders in Artificial Intelligence: FusionOps CEO Shariq Mansoor (Part 2)

Sramana Mitra: Big Data is AI. To me, the difference between Big Data and regular data is that you have to use machine learning to make sense of Big Data. With small amounts of data, you can do it without machine learning.

Shariq Mansoor: One of the challenges that everybody is running into right now is what to do with all the data. That’s the biggest problem. You can create data lakes. You can create everything there, but what are you doing to do with it? How are you going to deliver the data?

Sramana Mitra: Let’s talk about that. Let’s talk about where in the supply chain your customers are using your technology. What kinds of dramatically additional value are you adding? >>>

Thought Leaders in Artificial Intelligence: FusionOps CEO Shariq Mansoor (Part 1)

FusionOps was ahead of its time. Founded in 2005, the company has only recently found its groove with the AI wave. Focused on the supply chain area, they are doing some very cool stuff with Cloud, Big Data, and AI.

Sramana Mitra: Tell us about the company and yourself.

Shariq Mansoor: FusionOps is focused on the supply chain. We started in 2005. At that time, we had a vision and we still have the same vision. We believe that data is going to change things. At that time, cloud was just emerging. We were a little early in the space. >>>

Thought Leaders in Artificial Intelligence: Jack Porter, CEO of Razorthink (Part 4)

Sramana Mitra: Let’s switch to the 30,000-foot question. If you were advising new entrepreneurs to look for open problems in the AI deep learning space, where would you point them to?

Jack Porter: First, I’d point them to the ground zero for where the next big disruption is going to happen. When disruption for AI happens, it’s going to be in orders of magnitude bigger than anything we’ve ever seen before. It’s bigger than web or mobile. Mobile and web put a lot more people on the Internet. When they disrupted their industries, the industry itself was significantly smaller than it is today.

I was in China about a month ago. I was in Beijing and I decided to go up to the Wall for a little trip. I’m driving through rice paddies and we stop at this little >>>

The Future: White Collar Jobs Will Be Automated as Well

Right now, we’re still processing the 2016 US Presidential election, and focusing on blue-collar job losses that led to Trump’s victory.

But the truth is, within the next election cycle or two, we will see the pain being felt not only by blue-collar workers, but also white-collar folks.

Inequality: Technology & Automation: In the 30-50 year timeframe and beyond, technology and automation will create tremendous disruption. 60-80% of ALL jobs will, likely, get automated.
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Thought Leaders in Artificial Intelligence: Jack Porter, CEO of Razorthink (Part 3)

Sramana Mitra: I have a couple of follow-up questions. First question is on adoption. Where are you seeing adoption? What kinds of companies are adopting your technology? One thing you said which completely perplexes me is the example you chose to share was from one of the largest banks in India. Why? We never hear that. Silicon Valley companies, generally, go out to sell to the American banks.

Jack Porter: I do a lot of speaking on artificial intelligence around the world. After I speak, I have customers coming up to me and saying, “Hey, I have that problem that you were talking about.” That’s what ended up happening in this situation. I was giving a presentation of the research board at Gartner Group. The CIO of this bank was in the audience and came up to me after the presentation. >>>