Imagine what your company could accomplish if all interplay with machinery computers and technology were intelligent?
AI gives priority to the development of intelligent machines that work and conduct themselves similar to humans.
Speech recognition, Learning, Planning, Problem solving
- Artificial Intelligence
- Machine Learning
- Deep Learning
- Computer Vision
- Human Computer Interaction
Automation, Make it Smarter
The next industrial revolution
The easiest way to think about artificial intelligence is in the context of the Human. After All Humans are the most intelligent creatures on earth. We don't have is a broadband computer science the goal of AI is to create systems that can function intelligently and independently. Humans can speak and listen to communicate through language. This is a field of speech recognition. Much of speech recognition is statistically based hence it's called statistical learning. Humans can write and read text in a language. This is a field of NLP or natural language processing humans can see with their eyes and process what they see. This is a field of computer vision. Computer vision Falls under the symbolic way for computers to process information. Humans recognise seen around them to their eyes which creates images of that world. This field of image processing. AI is required for Computer Vision. We, humans have the ability to see patterns such as grouping of objects. This is a field of pattern recognition. Machines are even better at pattern recognition because they can use more data and dimensions of data. This is the Field of machine learning.
The human brain is a network of neurones and we use these to learn things. If we can replicate the structure and the function of the human brain, we might be able to get cognitive capabilities in machines. This is a field neural network. If these networks are more complex and deeper and we use those to learn complex things, that is the Field of deep learning. There are different types of deep learning in machines which are essentially different techniques to replicate what the human brain does. If we get the network to scan images from left to right top to bottom it's a convolution neural network. The CNN is used to recognise objects in a scene. All computer vision fits in an object recognition is accomplished through AI. Humans going to remember the past, like what you had for dinner last night. We can get a neural network to remember a limited past. This is a recurrent neural network. There are two ways AI works: one is symbolic based, and another is data based. For the database side called the machine learning we need to feed the machine lots of data before it can learn. For example, if you had lots of data for sales vs advertising spend you can put that data to see pattern. If the machine can learn this pattern, then it can make predictions based on what he has learnt while one or two or even three dimensions is easy for humans to understand. Machines can learn in many more dimensions like a human. 100 or thousands. That's why machines can look at lots of high-dimensional data and determine patterns. Thus, AI is able to make predictions that humans can't even come close to.