Digital: Artificial Intelligence - no magic, just code

It’s 8:00 am on a Tuesday morning. You are awake, scanned headlines on your phone, responded to online post/s, ordered breakfast to be delivered by the time you reach, locked house, and are driving to work, listening to some great new music on radio.

You’ve also used artificial intelligence (AI) more than a dozen times, already.

AI is already pervasive in our world, and it’s making a huge difference in our everyday lives. But this is not the AI you have seen in sci-fi movies with nervous scientists clacking on keyboards and attempting to halt machines from destroying the world.

AI is going to bring major shifts in society through developments in self-driving cars, medical image analysis, better medical diagnosis, and personalized medicine. And it will also be the backbone of many of most innovative apps and services of tomorrow. But for many it remains mysterious.

No magic, just code

AI is a rigorous science focused on designing intelligent systems and machines, using algorithmic techniques somewhat inspired by what we know about the brain. Many modern AI systems use artificial neural networks, computer code that emulates large networks of very simple interconnected units, a bit like neurons in the brain. These networks can learn from experience by modifying the connections between the units, a bit like human and animal brains learn by modifying the connections between neurons. Modern neural nets can learn to recognize pattern, translate languages, learn simple logical reasoning, and even create images and formulate new ideas. Recognizing patterns is particularly important — AI is good at recognizing patterns in large amounts of data, something that is not as easy for humans.

All of this happens at blinding speed through a set of coded programs designed to run neural networks with millions of units and billions of connections. Intelligence emerges out of the interaction between this large number of simple elements.

Artificial intelligence is not magic, but we have already seen how it can make seemingly magical advances in scientific research and contribute to everyday marvel of identifying objects in photos, recognizing speech, driving a car, or translating an online post into dozens of languages.

What is learnable?

This raises a central question: What is intelligence? Philosophers and scientists have struggled with this question for ages. The answer is elusive and mysterious, yet this central attribute makes us uniquely human.

Concurrently, AI also prompts the large philosophical and theoretical question: What is learnable? And since mathematical theorems tell us that a single learning machine cannot learn all possible tasks efficiently, we also get a sense of what cannot possibly be learned regardless of how much resources you throw at it.

In this way, AI machines are very much like us. We don’t always excel at being general learning machines. Our human brains are incredibly specialized, despite their apparent adaptability.

Still current AI systems are very far from having the general intelligence that humans possess.

The future

Increasingly, human intellectual activities will be performed in conjunction with intelligent machines. Our intelligence is what makes us human, and AI is an extension of that quality.

On the way to building truly intelligent machines, we are discovering new theories, new principles, new methods, and new algorithms that have applications and will improve our everyday life today, tomorrow, and next year. Many of these techniques quickly find their way into products and services for image understanding, natural language understanding, and more.

The Goal: Understand intelligence and build intelligent machines