One of the more complex and misunderstood topics making headlines lately is artificial intelligence . People like Elon Musk warn that robots could one day destroy us all, while other experts claim that we’re on the brink of an AI winter and the technology is going nowhere. Making heads or tails of it all is difficult, but the best place to start is with deep learning . Here’s what you need to know.
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Artificial intelligence has become a focal point for the global tech community thanks to the rise of deep learning. The radical advance of computer vision and natural language processing, two of AI’s most important and useful functions, are directly related to the creation of artificial neural networks.
For the purpose of this article we’ll refer to artificial neural networks as, simply, neural networks. But, it’s important to know that deep learning techniques for computers are based on the brains of humans and other animals.
What is a neural network?
Scientists believe that a living creature’s brain processes information through the use of a biological neural network. The human brain has as many as 100 trillion synapses – gaps between neurons – which form specific patterns when activated. When a person thinks about a specific thing, remembers something, or experiences something with one of their senses, it’s thought that specific neural patterns “light up” inside the brain.
Think of it like this: when you were learning to read you might have had to sound out the letters so that you could hear them out loud and lead your young brain to a conclusion. But, once you’ve read the word cat enough times you don’t have to slow down and sound it out. At this point, you access a part of your brain more associated with memory than problem-solving, and thus a different set of synapses fire because you’ve trained your biological neural network to recognize the word “cat.”
Scientists use neural networks to teach computers how to do things for themselves. Here are a few examples of what neural networks do:
- This neural network takes dark images and makes them clear
- This one analyzes MRIs and displays what you’re thinking
- Here’s one that plays Super Mario Bros
- And one that creates pick-up lines
- Finally, this one is self replicating
As you can see neural networks tackle a wide variety of problems. In order to understand how they work – and how computers learn – let’s take a closer look at three basic kinds of neural network.
There are many different kinds of deep learning and several types of neural network, but we’ll be focusing on generative adversarial networks (GANs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs). […]
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read more – copyright by thenextweb.com
One of the more complex and misunderstood topics making headlines lately is artificial intelligence . People like Elon Musk warn that robots could one day destroy us all, while other experts claim that we’re on the brink of an AI winter and the technology is going nowhere. Making heads or tails of it all is difficult, but the best place to start is with deep learning . Here’s what you need to know.
copyright by thenextweb.com
For the purpose of this article we’ll refer to artificial neural networks as, simply, neural networks. But, it’s important to know that deep learning techniques for computers are based on the brains of humans and other animals.
What is a neural network?
Scientists believe that a living creature’s brain processes information through the use of a biological neural network. The human brain has as many as 100 trillion synapses – gaps between neurons – which form specific patterns when activated. When a person thinks about a specific thing, remembers something, or experiences something with one of their senses, it’s thought that specific neural patterns “light up” inside the brain.
Think of it like this: when you were learning to read you might have had to sound out the letters so that you could hear them out loud and lead your young brain to a conclusion. But, once you’ve read the word cat enough times you don’t have to slow down and sound it out. At this point, you access a part of your brain more associated with memory than problem-solving, and thus a different set of synapses fire because you’ve trained your biological neural network to recognize the word “cat.”
Scientists use neural networks to teach computers how to do things for themselves. Here are a few examples of what neural networks do:
As you can see neural networks tackle a wide variety of problems. In order to understand how they work – and how computers learn – let’s take a closer look at three basic kinds of neural network.
There are many different kinds of deep learning and several types of neural network, but we’ll be focusing on generative adversarial networks (GANs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs). […]
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
read more – copyright by thenextweb.com
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