What is AI really, and how does it work?
If you are interested in AI, you’ll undoubtedly know that many of the concepts are a bit overwhelming. There are plenty of terminologies to understand, such as machine learning, deep learning, neural networks, algorithms, and much more.
With the world of AI continually evolving, it’s good to go over some of the basic concepts to better understand how it’s changing.
In this episode of Short and Sweet AI, I address some of the questions that I get asked a lot: what is AI? How does AI work? I also delve into some of the limitations of AI and their possible solutions.
In this episode find out:
- How AI works
- What machine learning and neural networks are
- How deep learning works
- The limitations of AI
- How AI neuroplasticity could solve the limitations of AI
Important Links & Mentions:
- SAS: Neural Networks: What they are & why they matter
- ExplainThatStuff: Neural networks
- Quanta Magazine: Artificial Neural Nets Finally Yield Clues to How Brains Learn
Hello to you who are curious about AI. I’m Dr. Peper.
If you’re listening to this, you probably think AI’s interesting and important like me. But sometimes I find the concepts are a little overwhelming. I want to go over something I get asked a lot. People ask me, what is AI really, how does it work? Actually, there’re new things going on with how AI works. So, it’s good to go over some of the basic concepts in order to understand the way AI is changing.
How does AI work?
Artificial Intelligence happens with computers. They’re programed using algorithms. Algorithms are step by step instructions telling the computer what to do to solve a problem. Just like a recipe has specific steps you follow in sequence, to bake a cake, or cook something. Computer scientist write algorithms using a programming language the computer understands. These computer languages have strange names like Python or C plus, plus.
The computers also perform math calculations or computations to analyze the information and give an answer. This is known as computational analysis. Basically, the programing language and math calculations are computer software. Using this software, the algorithms come up with an answer from data sets fed into the computer.
Machine Learning is a type of AI
The major AI being used today is called machine learning. Machine learning is carried out by artificial neural networks, or nets for short. Neural nets underpin the most advanced artificial intelligence being used today. They’re called neural networks because they’re based in part on the way neurons in the brain function. In the brain the neuron receives inputs or information, processes the information, and then gives a result or output.
Artificial intelligence uses digital models of brain neurons. These are artificial neurons, based on the computer binary code of ones and zeros. The digital neurons process information and then pass it along to other higher layers of processing. Higher, meaning the results become more specific, just like in the brain.
Deep Learning is a type of Machine Learning
Before computers can give us the answers, they have to be trained on large amounts of data. As the computer processes more and more information, it learns from the data. This is called training the machine. Then when you give the computer completely new data, the machine knows what to do with it and can give you a correct answer to your specific question.
If you have many, many layers of neural networks, each processing and passing the information to another layer, it’s called a deep neural network. When machines learn from deep neural networks, it’s called deep learning.
Present day AI has Limitations
All of the software and computer calculations used in machine learning, especially deep learning, require absurd amounts of data and computer power. The neural nets can be hundreds of layers deep with billions of parameters like AlphaFold or GPT-3 which I talked about in previous episodes. These are gargantuan machine learning algorithms and require very powerful supercomputers to run them. This limits who can use machine learning to only large tech companies and corporations.
Yet as mighty as these neural nets appear, at a core level they are very narrow. And that’s another limitation. They do exactly the one thing they’re trained to do such as recognize an image, steer a car to the left or right, or translate something from one language to another. When you ask a neural net to do something that deviates from its training, it acts brittle and breaks.
New AI Neuroplasticity
But there’s something new in artificial intelligence. AI has reached a point where it’s less artificial and more biological. Like the human brain, AI has developed “neuroplasticity.” Now that you understand basic artificial intelligence, next time let’s discuss something called “liquid” AI which is so cool. It solves a lot of these limitations with a type of artificial neuroplasticity.
I hope you found this helpful. Be curious and if you like this episode, please follow my channel. Or you can leave a comment and click the thumbs up button, which lets me know you like the content. From Short and Sweet AI, I’m Dr. Peper.