BUILDING INTELLIGENT MACHINES (PART 1)

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Imagine a future where you are not stuck in traffic because machines are driving the vehicles, not humans. A future where everyone has a personal assistant to do mundane tasks. A future where industry is more productive and per capita income is rising.

That future is already here, just not evenly distributed across the world. Some parts of the world are experiencing it earlier than the others. A big driving force behind this development is advancement of AI technologies. 

The impact of AI on economy and industry productivity is growing exponentially. Look at the chart below – it shows that — AI is doubling the baseline growth in most sectors. This happens rarely. It means new markets, improved GDP, improved per capita income and improved quality of life.

Source : Accenture and Frontier Economics.
 

Industrial revolution took people out of field jobs and moved them to offices to manage processes and troubleshoot problems. Humans switched to managing the job while the real job was done by robotic assembly lines or machines.

Similarly, AI technologies automate repeated tasks and free humans from drudgery of mundane jobs. Some jobs will be taken away but new jobs will be created for humans to do what they do best — Thinking and Imagining.

“The last 10 years have been about building a world that is mobile-first. In the next 10 years, we will shift to a world that is AI-first.” 

Sundar Pichai, CEO of Google, (October 2016)

AI technologies are all about building intelligent machines and to do that you need to make machines that learn and understand our world. Now, how can we make machine learn and what does learning mean for a machine anyway? In this series of posts, I want to take a non-technical view on AI and  Machine Learning.

Before we start thinking about artificial intelligence. Let’s first understand natural intelligence — the biological kind – the one that you and I are born with. Later, we’ll look at the process of creating the artificial one. There are few thinking exercises in this post so, I would suggest grabbing a notepad.

What is intelligence?

Our brain is a fascinating organ with unimaginable capabilities. We are intelligent beings. But what is this intelligence? Take a moment and think about it…  Try writing down your answers.

The questions to think about this –  How do you know that you are intelligent? What differentiates you from something which you consider less intelligent?

 

 

 

 

 

 

If you are done with writing or thinking your answers about intelligence, you will notice that most of what we call intelligence, is a process called Decision Making.

We, or our brain take decisions all the time. Sometimes it is a conscious choice but many a times it is an unconscious process. Even for putting our foot forward to take a step, brain calculates and decide where and how to do it. We calculate and decide all the time. But there are other aspects of intelligence that are different which we don’t fully understand yet-  for example, creating art, poetry or music and even something like consciousness, the voice which speaks to you in your head, what kind of intelligence is that?

If we have to sum up everything about intelligence to cover all aspects of it, can we look at from the point of view of Interaction? Humans, animals, insects, non living things all interact with this world – but in dramatically different ways. These limitations and dimensions of interactions with their environment tells us about the scale of their intelligence. So for me –

Intelligence is a measure of the magnitude of our interaction with this world.

Intelligence therefore, is not binary but a spectrum – a pup interacts with the world but rarely thinks about consciousness or happiness. It’s dimensions of interaction are limited as compared  to humans. But is still intelligent.

An intelligent pup.

Decision making + interaction with the world

A reason why most computers and machines today focus on decision making is because it is a kind of intelligence which we have understood well scientifically. We have good frameworks for it which can be applied to create machines with more decision making power. We will deep dive into human decision making in part 2 of this series but let’s look at the decision making and interaction with the world together. We can gain some interesting insights. It’s a good framework to study about current machines and how they will transform in the AI era.

This is a machine — a logical machine or as we call it, software.

If you observe the behavior of this software and its interaction with the world – it’s fixed and rigid. As a user, you can only provide a fix type of inputs to which it will validate and act logically to respond. I think we can safely say that the interaction is very limited.

Its a good software because it works great. But this software is not capable of taking a lot of decisions. Every possibility is thought of beforehand by its developer, starting from validating the inputs.

Now, have a look at Alexa. This software is expected to interact with the world in a very different way. There are infinite possibilities to interact with this kind of software . The developer of this machine can never think of all kind of inputs it will receive and how to respond to it. Anyone can ask anything. The decision making power of such machines has to be great. 

If we understand the core of the decision making process of natural intelligence, we will be able to add amazing capabilities to our machines. We can greatly extend their interaction with the environment they operate in.

So, the quest of all AI technologies will be to add more dimensions of interaction and understanding the process of decision making will be the key. In Part 2, I discuss the process of human decision making and later apply it to create softwares or machines capable of taking more decisions.

Co-Founder and CTO of Spext. Wanders in deep thoughts of science, spirituality and human nature. Often goes to trek Himalayan trails.

About the author

Ashutosh Trivedi

Co-Founder and CTO of Spext. Wanders in deep thoughts of science, spirituality and human nature. Often goes to trek Himalayan trails.

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