What is AI and machine learning? Before we go further, we should first take a look at precisely what AI and machine learning actually are. These are two related but also distinct terms, which often get confused. Both will impact on marketing, but in different in unique ways. Ai then is artificial intelligence. That means software and hardware designed to act and appear intelligent.
Such software is capable of making meaningful choices and conducting activities that we would normally consider the domain of humans. Ai comes in two broad flavors. One is weak AI, which is also known as narrow AI. Weak AI is essentially a form of AI that is designed to perform a specific job. An example of this is a self driving car. This form of AI is capable of knowing the positions of countless cars on the road, and being able to respond by steering, accelerating, braking, etc.
If you were to watch a self driving car from the outside, you might think a human were driving in that way. It does A job that would normally be considered a human role. But at the same time, you can't speak with a self driving car and you can't ask it how it's feeling. A self driving car would certainly not passed the Turing test. No, the Turing test is a test designed to measure the effectiveness of an AI. If you talk to an AI on a chat app, and you don't know that it isn't human, then it is considered to have passed the Turing test.
Another example of weak AI is used when creating bad guys in computer games. These use programming in order to behave in a human like manner, and to provide a challenge for the player. However, the code is only useful in the context of the video game. And so it's not about to turn into Skynet anytime soon. Weak AI might not sound as exciting, but it is being used for a huge range of extremely exciting things, from helping to treat disease to improving the economy. Conversely, the type of AI that we often see in science fiction is what we know as general AI.
This is AI that doesn't just have one purpose, but then is designed to do Everything that a human might be able to do. So you can play a word game with this AI, ask it how it's feeling, or get it to look up something useful. And example of a general AI is DeepMind owned by Google. DeepMind is a company that has developed a neural network that employs general learning algorithms to learn a huge range of different skills. Many API's such as IBM, Watson are actually pre programmed. That means that they work using a kind of flowchart and will answer questions with the same answer every time.
On the other hand, deep mind is apparently able to think and respond via a convolution neural network. certain behaviors are reinforced and encouraged, and these will begin to become more prominent. This isn't a perfect simulation of how a human brain works. Cognitive behavioral psychology teaches us the importance of having internal dialogues and bottles for thinking. However, it is the closest thing we currently have to a true general intelligence, machine learning. Machine learning on the other hand works differently.
Machine learning utilizes Huge datasets in order to gain surprising and almost frightening capabilities at times, machine learning essentially allows a piece of software to be trained. An obvious example of this would be computer vision. Computer Vision describes the ability that some machines have to understand visual information. An example is Google lens, which can tell you what you're pointing your phone's camera at, whether that's the type of flower or product you can buy in stores. Computer Vision is necessary for self driving cars to successfully navigate their environments. And it's used by apps like Snapchat, which use filters to change people's faces.
How do these work by looking at thousands and thousands of pictures of every type of object? While the machine learning algorithm will never understand what it is looking at, it can look for patterns in the data which will then be used to identify those objects in the future. For example, it might notice that faces are typically oval in shape with a dark patch of hair on top. It then knows that if it sees an oval shape with a dark patch at the top, it's possibly looking at a face. Machine learning has huge potential in just about every field. In the future.
It can be used to diagnose diseases more accurately than a human doctor to advise on financial decisions, to identify fraudulent bank transfers, and much more. All of this has huge potential implications for internet marketing. And that's what we'll be exploring in the following videos.