Ambient Intelligence is on the rise as companies look to create products that will act more like a best friend who knows everything about you and can predict what your next move will be, and less like a simple gadget used to make calls, text friends and make posts on Yelp from time to time.

We had a chance to speak with Lars Hard, CTO and founder of Expertmaker, which is  an Artificial Intelligence (AI) software company that is currently in the process of developing a new AI platform for independent mobile developers as well as major label brands. We were able to get his opinion on how he feels about ambient data and whether or not it is a good thing for technology to be so personable.

 The evolution of AI

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According to Hard, using evolutionary computation is like the engine of Expertmaker. He believes evolution is most certainly the future of computing, especially because he believes it is the best instrument to handle difficult tasks, making AI self-aware so that it has the ability to learn.

We inquired about how Hard thinks machines will learn in the future. He sees “brain builders,” which are machines that want to represent brains as much as possible, using AI as a tool to see just how much we are able to reach recognition in computers.

According to Hard, “machine learning can be a profound add-on to humanity and do other things we’re not so good at, rather than replace humans…”

Although it is beneficial for machines to better understand us, we should not let them replace us as humans. We need to stay in control and remember one important thing: a machine is absolutely nothing without a human hand and brain to operate it.  But the human brain is the inspiration behind much of what Hard does, designing AI systems to become better recommendation tools and services.  For Hard’s company, biological inspiration is at the core of what his team does, using evolutionary computation.

“That means that we are growing, so to speak, a number of alternative solutions to a problem.  Those solutions are like individuals in a population.  when we can recombine them, mate them…and mutate them, and do all these other computations that evolution normally provides us with, it has proven an effective way of removing a lot of the complications you typically run into with an advanced AI system.

“We can let the system evolve itself to find the best possible solution to your problem.  From desktops to servers — the servers of course…you can have a server for recommendations that use statistical analysis.  To optimize the system you’re using collaborative filtering (if you like A, you probably like B).  But for us, we use an evolutionary system so it automatically tweaks the solution.  There are many instances at play.  It’s a revolutionary step for AI, and creates robustness.

“Evolution is the best instrument known to handle really complicated tasks.  It’s definitely the future of computing.  There are no mathematical techniques that can match it.”

How will machines learn in the future?

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“There’s so much happening right now,” Hard says.  “I’d say there’s a couple of different schools of thought.  there’s brain builders that want to replicate brains as much as possible.  They use AI as a tool to see how far we can reach recognition in computers.  I’m not part of that camp.  I think machine learning can be a profound add on to humanity and do other things we’re not so good at, rather than replacing humans with a hyper-big box that knows and replaces everything.  Working with Expertmaker, knowledge is so vast.  There’s so many perspectives based on experience and knowledge.  It’s a very important thing because it’s about democratizing AI so we can represent all of those perspectives.

“In the future we’ll see something that’s not so similar to human learning — it will be its own form and should be in the control of the people.  It should amplify humans to represent their knowledge and scale that computers can offer.  As far as intelligence is concerned, I don’t really see the benefit for humanity for machines to replace that.”

What businesses will emerge from consumerized AI systems?

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“I think that in the initial stages, of course it will be a different enterprise system, something that’s selling products,” says Hard. ” And I think we’ll see more creativity coming from this space down the road because the interest is so huge for those that already have data.  They may have digital products too, which is even better because you can model and play with it better, put it into a predictive model.

“A huge competitive edge is the quality on how you bring products to customers.  eCommerce customers all have the same problem — keyword search isn’t sufficient.  By allowing AI to help out and create models to give new user experiences, you help with discovery and exploration.  It’s enormously beneficial for everyone.

“If you want to move away from a keyword world to exploration and discovery, you need metadata.  Many companies don’t have this metadata.  You need to have efficient tools to transform the old world of databases to new metadata resources.  Then you can use different recommendations and decision models and prediction models to bring a more relevant experience to the customer.”

This article was written by Amber Harris and Kristen Nicole