The Future Is Now: Rajeev Dutt Of AI Dynamics On How Their Technological Innovation Will Shake Up The Tech Scene

An Interview With Fotis Georgiadis

Don’t invest too early or too fast in building a team. I think we could have gradually grown the organization as the solution evolved. I believe this is a common mistake a lot of startups make. They want to hire quickly and grow too quickly, but sometimes it’s a blessing in disguise to not be well-funded at the start.

As a part of our series about cutting edge technological breakthroughs, I had the pleasure of interviewing Rajeev Dutt.

Theoretical Physicist and Technologist Rajeev Dutt has held leadership positions at Hewlett-Packard, Compaq, Microsoft, and Intel, among others. He launched his first company at age 26, and has since focused on using artificial intelligence to solve increasingly complex problems. His efforts have led to the creation of self-diagnosing, self-healing systems and utility-based computing solutions.

Today, he is the CEO of AI Dynamics, a global organization founded on the belief that everyone should have access to the power of AI to change the world. AI Dynamics has created the only AI platform that provides data governance and can be deployed on any on-premise device, cloud, or IoT environment.

Thank you so much for doing this with us! Can you tell us a story about what brought you to this specific career path?

I’ve always been interested in machine learning — it’s been a passion of mine since I was a child. I used to create video games and wrote my first game using AI when I was in seventh grade. I also loved reading science fiction novels involving robots or intelligent machines.

But throughout my career, I’ve worked for a number of companies including BBC, Compaq and Hewlett-Packard, and then Microsoft and Intel. Then, I finally launched this company, and along the way I’ve picked projects that involve large quantities of data. The common theme has always been that whenever I wanted to use AI or an intelligent way of processing information, it was difficult to do so. So, launching an AI project that made it accessible to anybody was always a dream of mine, because I see there are a plethora of problems around the world that are amenable to the use of AI or machine learning.

I wanted to do something that would bridge the gap between technologies such as AI and the average person, because I think that the applications are really beyond anything that we can even imagine at this stage. It’s almost like every aspect of our lives could potentially be enhanced using AI.

Can you share the most interesting story that happened to you since you began your career?

When I joined HP and started working on my first truly intelligent enterprise application, we got a patent on it and it was really exciting to see that a machine could actually identify problems and configurations in a network that humans couldn’t.

When I was part of Intel, I was tasked with launching my own group based in Redmond. And again, it was like an opportunity to use intelligent systems to predict or correlate issues between later stage development to earlier stage development. Those are the sort of things that I remember quite distinctly in my career and points in time I cherish.

Can you tell us about the cutting edge technological breakthroughs that you are working on? How do you think that will help people?

AI Dynamics was founded about 5 years ago, and we spent most of that time in engineering. Our mission has always stayed the same, which is to make AI universally usable — something that can be easily integrated into enterprise applications. In the last couple of years, we have shifted our focus quite a bit, and although we are still focusing on the tech and ubiquity of AI, we’ve focused on two key areas.

One is in the industrial and manufacturing sector where we see there are plenty of opportunities from quality control, to manufacturing processes, to supply chain management, logistics, and so on. The second is using AI or machine learning to work on biotechnology problems within cells and the interaction of these biological systems of molecules. We believe machine learning can play a very pivotal part in that.

How do you think this might change the world?

One of the projects that our organization is working on could potentially lead to some novel treatments in cancer and would be, of course, an enormous benefit to humankind if we were able to.

We’re also pushing the boundaries of diagnostics to provide low cost diagnostics for several types of illnesses. One of them is tuberculosis, which, according to the CDC, is the number one killer in the world, which surprised us. Being able to provide low cost diagnostics to detect tuberculosis in its earlier stages, which can be deployed everywhere including cell phones and lower cost devices, would affect the world dramatically.

Keeping “Black Mirror” in mind, can you see any potential drawbacks about this technology that people should think more deeply about?

When you democratize any technology, and our ambition is ultimately to make it accessible to anybody and everybody, there are of course bad players that may discover it. But, there are problems that can be solved that will ultimately lead to the betterment of people and certainly underserved markets. For example, in Africa there are many issues that can be solved with machine learning that are simply not of interest to some of the larger companies in the West, and we see these problems go relatively unnoticed.

We plan to eventually release a free version of our software to make it even more accessible, but the drawback, of course, is that if you’re putting such a powerful tool into people’s hands and it becomes something that anybody can use, there are those in the world who may try to use it to impinge on people’s privacy or for criminal activities. We’ve certainly seen the rise of, for example, A.I. generated malware, and increasingly A.I. is being used in cyber attacks.

We are looking to introduce an extensive governance component to our platform that will allow us to, at the very least, identify who these bad actors are, so if we do see something going wrong, we would be able to identify who is responsible for doing so.

Was there a “tipping point” that led you to this breakthrough? Can you tell us that story?

Early on in the life of AI Dynamics we noticed that we were solving the same problems over and over again, so we ended up designing our own language that would solve these problems much faster. We then saw that there were more opportunities which evolved into what we have now, which is essentially guided AI development where we have an expert system that is able to help people determine the right set of algorithms, or to guide people to picking the right set of algorithms.

What do you need to lead this technology to widespread adoption?

Although we have a complete end-to-end enterprise version, the reality is that most people just want to solve a problem and solve a problem quickly. What we wanted to do is develop a free version of our software that would allow people to do so. There are two components to our free version:

The first is the ease of use — the ability for anyone to solve machine learning problems. The second is not just simply having the ability to solve those problems, but to also deploy those solutions and monetize them.

We also have a language which dramatically cuts down the amount of code required for machine learning. So literally within about 14 lines of code, you can write an entire ML algorithm. What we’d like to do is Open-Source that so that we expand our libraries and the set of capabilities. Having a free version will allow the public to build and construct more algorithms for our platform, which will of course, continue to spread its use and demand the process of AI democratization.

What have you been doing to publicize this idea? Have you been using any innovative marketing strategies?

We are about to launch a competition in the biotechnology space. We are looking for a powerful solution to an interesting problem that is both challenging and has strong potential to benefit people. We will actually build the solution for the winners, and they can monetize the solutions that are being developed. It’s also an opportunity to solve very meaningful machine learning problems. So though this is a very targeted domain we’re offering this to, we also think it will have a lasting impact and attract a number of people who would otherwise not have considered machine learning.

None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful towards who helped get you to where you are? Can you share a story about that?

There are two people I would like to thank personally. The first is Ken Johnson, who is a leading investor on this project and something of a mentor. He helped us get seed capital and has been a constant supporter of AI Dynamics.

The second is Bob Genise, who is basically the reason we exist. He’s the one who saw the merits of this solution and helped make the connections we needed. He has put in both his own personal resources as well as offered constant advice to our company. He was primarily focused on the aviation sector, but a lot of his experience and know-how directly translated into how to run a business. We have a very different business in the sense that building a platform is never easy, but having people like Bob and Ken has been pivotal in the company’s success and evolution. We couldn’t have done it without them.

How have you used your success to bring goodness to the world?

We believe in an ethical use of AI and that it should be used for the betterment of humankind, not to its detriment. What better way than to improve the efficiencies of how we produce and deploy goods, and also develop novel treatments to save human lives?

What are your “5 Things I Wish Someone Told Me Before I Started” and why. (Please share a story or example for each.)

1. Don’t build battleships. If I could go back, I would start small and build a much more targeted solution.
2. Don’t invest too early or too fast in building a team. I think we could have gradually grown the organization as the solution evolved. I believe this is a common mistake a lot of startups make. They want to hire quickly and grow too quickly, but sometimes it’s a blessing in disguise to not be well-funded at the start.
3. Engage a VC early in the process, whether through incubation groups or through a strategic investor like Microsoft or Intel. Ken Johnson and Bob Genise were pivotal in acquiring funds, but I think part of what I should have done is raise funds through other channels.
4. There is no universal recipe for success. If there were, then I think there’d be any number of successful companies. Recognize that changing power and changing direction is not a bad thing. It’s in fact healthy when you realize that a certain path is not for you and your business. Do not be married to any particular concept. Our vision never changed, but how we get there is continuing to evolve.
5. Never assume that if you build it, they will come. It is far better to start building a customer base, even if you have an imperfect solution. What we’ve found over the last three years as we begin to commercialize is that the customer requirements have altered some of the decisions we’ve made for the better.

You are a person of great influence. If you could inspire a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. :-)

I love machines, and I like the potential opportunities or advantages that they can give humankind. But I also believe it’s important for us to internalize the concept of what is ethical AI. It’s something we need, but unfortunately too many people are simply paying lip service. They don’t describe what it means exactly, and so we see pernicious and unpleasant uses of it, for example invading our privacy, creating new ways of surveilling people, weapons systems, and the like.

What I would love to see is a more concerted effort toward building solutions that are geared toward helping people rather than constraining or imprisoning us, or solutions working toward democracy rather than subverting it. Having companies that are involved in these areas start to build an ethical framework for how they operate is important, as we are continuing to see a rise in surveillance in many countries. Maybe it’s a bit idealistic to imagine that, but having a framework of what is considered ethical or unethical will at least allow us to separate the different types of solutions so that we are not under any illusions that when we do something, it is considered unethical. It is wrong. We need to spell it out clearly rather than just talking the talk.

Can you please give us your favorite “Life Lesson Quote”? Can you share how that was relevant to you in your life?

Everyone knows the quote “death by a thousand cuts”, but I’d like to turn it around and say that it’s a life by a thousand cuts. There will never, ever be a time in life where you’re not running into problems, but life is about problem-solving, and it’s by the moment that you start to feel empowered because you’re never going to feel like a victim again.

The second is simply “don’t panic”, or “If I worry, does it help?” People are always a little bit surprised that I stay calm in certain situations, but it’s largely because I just don’t believe in worrying about things that I can’t control.

Some very well known VCs read this column. If you had 60 seconds to make a pitch to a VC, what would you say? He or she might just see this if we tag them :-)

Imagine a world where AI is universally accessible — something where every person, every engineer, every organization has the power to transform its business using machine learning. Imagine it as a platform or solution that can completely democratize AI and put it into the hands of every single person. It has the ability to provide knowledge and understanding and intelligence to help solve almost any problem. This is precisely what we are building with NeoPulse.

Thank you so much for joining us. This was very inspirational.