The Rise of the Robots: Making Software Smarter

wall-eblog2016 was a huge year for artificial intelligence and machine learning innovation. From the historic AlphaGo victory over some of the world’s best Go players to Boston Dynamics and their apparent quest to make humanity irrelevant, the rise of the robots has really captured the world’s attention.

However, it’s not all fun and games and poking robots with hockey sticks. Artificial intelligence is starting to shape the way we live, the way we work and the future of mankind in general. Until recently, a manually written computer program would tell a computer what you wanted it to do… The program would execute, the computer would carry out its series of instructions and then stop, or repeat if programmed to do so. Today, the computers are learning what to do next by themselves, making smarter decisions and helping to enhance efficiency and productivity.

But how is artificial intelligence shaping the future of software? In what ways can machine learning make software more agile and useful?

The Power of Deep Reinforcement

Deep reinforcement learning takes its inspiration from how an animal might learn that a certain behavior or condition can trigger a negative or positive outcome. For example, a mouse in a maze will learn that if he reaches the end of the maze he will be rewarded with a piece of cheese. Over time he will become so adept at remembering the layout of the maze that he will reach the cheese in seconds. Machines are being programmed to learn in the same way.

Neural networks like this have been around for years, but it is only now that this capability is starting to show promise for real-world scenarios. We have seen how this works already in the form of driverless cars and industrial robotics. Microsoft and Google have also recently added neural network functionality to their translation apps. Todoist has introduced similar AI-driven smarter technology to suggest to users when they should complete a task.

Language Learning Making Huge Progress

If you were to ask AI scientists what their next big objective is likely to be, most would mention communication or, more specifically, language learning. Speech recognition made huge inroads in 2016, with personal assistants like Amazon’s Echo gaining popularity and excellent reviews. Microsoft’s research also revealed that for the first time its automatic speech recognition results were comparable to the same results achieved by a human.

Language learning is currently a subject that is very close to our hearts. We are working with IBM Watson, a supercomputer that combines sophisticated analytical software and artificial intelligence, to recognize key phrases and to perform efficient and effective question answering processes. Our project will take advantage of Watson’s advanced text-to-speech functionality and will help managers respond to staff coaching and training requirements.

What Does the Future Hold for Artificial Intelligence?

While you won’t be having a deep and meaningful conversation with your smartphone just yet, it won’t be long before computers are able to grasp the subtlety, complexity and power of human interaction in ways that can be applied successfully to many real-world scenarios.

Although we don’t know exactly what the future holds, it is becoming more and more evident that our daily lives will soon involve more interactions with systems and devices driven by artificial intelligence and machine learning. These interactions can only help us to evolve as a society and will undoubtedly have a massive influence on our personal and working lives.

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