Let's dig a little deeper into AI. This is going to be an interesting topic going into the future, and there's little doubt it's going to have an increasingly profound impact on our lives. The more we know about it, the better.
Let's start with asking the question, what exactly is AI? Artificial Intelligence is technology that enable computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy. Notice that the word 'simulate' is in bold letters. I will come back to the significance of that later. Applications and devices that are equipped with AI can see and identify objects. They can understand and respond to human language. They can learn from new information and experience. They can make detailed recommendations to users and experts. They can act independently, replacing the need for human intelligence or intervention. A good example of this is self-driving cars...
In 2024 most AI research focused on breakthroughs in generative AI. This is a technology that can create original text, images, video and other content. To fully grasp how generative AI works it's necessary to first understand the technologies on which generative AI tools are built: machine learning and deep learning. The first 'layer', if you will, under AI is machine learning, which involves creating models by training an algorithm to make predictions or decisions based on data. It involves a broad range of techniques that enable computers to learn from and make inferences based on data without being explicitly programmed for specific tasks. There are many types of machine learning techniques or algorithms including: linear regression, logistic regression, random forest, support vector machines (SVM's), k-nearest neighbor (KNN), clustering, and more. Each of these approaches is suited to different kinds of problems and data.
One of the most popular types of machine learning algorithms is called a neural network, or I should say, an artificial neural network. Neural networks are modeled after the human brain's structure and function. A neural network consists of interconnected layers of nodes (analogous to neurons) that work together to process and analyze complex data. Neural networks are well suited to tasks that involve identifying complex patterns and relationships in large amounts of data.
The simplest form of machine learning is called supervised learning, which involves the use of labeled data sets to 'train' algorithms to classify data or predict outcomes accurately. In supervised learning, humans pair each training example with an output label. The goal is for the model learn the mapping between inputs and outputs in the training data, so it can predict the tables of new, unseen data.
Now for a look at Deep Learning. Deep learning is a subset of machine learning that uses multilayered neural networks, called deep neural networks that more closely simulate the complex decision-making power of the human brain. Deep neural networks include an input layer, at least three, but usually hundreds of hidden layers and an output layer. This is unlike neural networks used in classic machine learning models, which usually have only one or two hidden layers. Deep learning doesn't require human intervention. It enables machine learning at a tremendous scale. It is well suited to natural language processing, computer vision and other tasks that involve the fast and accurate identification of complex patterns and relationships in large amounts of data.
Before we go any further, let's stop and ask a few questions. Earlier, I mentioned that AI will enable computers to simulate human learning, comprehension, etc.. Everything, meaning any capability that a machine or application may have will be based on computer code. Algorithms will be the result of computer code. At this point in time only humans can generate computer code. Will it be possible for computers to generate code in the future? Your guess is as good as mine, but let me say this. If such does become reality (and it probably will...) it can only be because humans made it possible. It's really no different than guns, computers, nuclear weapons, automobiles, and so on. All wonderful products of human curiosity and innovation. But in the hands of those with less than good intentions, all can be evil, powerful and destructive. As we continue to invent implementations for the betterment of the human condition, there continues to be those who'll hijack great inventions to inflict pain and suffering. Such has been the history of mankind...
No comments:
Post a Comment