AI, NLP, and the Evolution of Machines
AI, NLP, and the Evolution of Machines
Artificial intelligence has been getting a lot of attention in the business world lately. But what exactly is it? What’s it good for? And most importantly, what’s going to prevent it from overtaking humans in the business world?
Artificial intelligence is software that shows large amounts of potential – in contrast to human intelligence, which shows only limited potential. We humans can only think, reason and create relatively small amounts of things. Conversely, computers have the ability to solve extremely complex tasks like recognizing images, speech, text and web pages. With the help of sophisticated algorithms, these computers can now achieve these tasks with relative ease.
Why is artificial intelligence becoming so popular? Computers are now capable of doing a great deal of routine tasks that were once only left to the hands of human professionals. For example, a car last year beat out the most qualified human driver in a driver’s challenge by using computer assisted driving techniques. A major reason for this is that artificial intelligence has made the process of learning more effective, by allowing a machine to learn at an individual level from experience.
Another use of artificial intelligence comes from machine learning technologies. Machine learning techniques were originally developed to assist humans when they were unable to do certain tasks themselves. Now machine learning technologies are being used in education, corporate training and real-world business environments.
How does artificial intelligence replace humans in these tasks? Humans will still need to perform some tasks such as reading, writing and perhaps answering the phone – but a machine learning system will be able to take over these duties, making them unnecessary. As new technologies are created, a variety of these technologies will become available. In general, there are three categories that I would like to discuss.
There are two primary categories of artificial intelligence: Computer generated and Computer optimized artificial intelligence. In the previous article, we looked at how computer optimized artificial intelligence differs from computer generated artificial intelligence. Here, we’ll look at the first category:
In this case, the goal is to make decisions that are better than those that humans could make. In other words, this might mean giving an answer that is different than what a human would have done. In many cases, the distinction between these two types is purely symbolic. For example, humans can use facial recognition to identify a face. Computer AI systems can make decisions based on facts, rather than experience or emotions.
The final category is called Computer-assisted conversation or CAC. In short, conversational artificial intelligence is using automated systems to speak with people in the real world, rather than with text. The first applications of this technology was in the retail market, but it is now becoming more common in the business environment. Chat bots that are sent through email, IM, text and video are examples of CAC. The ultimate goal of these programs is to provide the customer support that is needed when a machine learning algorithms are making calls to a live agent.
As defined above, the term artificial intelligence covers three areas of research. It combines computer science with programming languages such as MLive, JAVA, and R programming. Another area is the study of how artificial intelligence is used in the marketplace. This encompasses both web services and the delivery of products and services to individuals.
Computers are beginning to replace people in many aspects of our lives. However, there will always be a need for humans because they are the ones that can reason, make decisions, communicate and learn. This is where the third area comes into play, machine learning algorithms. Rather than having to be concerned about being able to program the artificial intelligence system to do specific tasks, all you need to worry about is how you program the human brain of the bot to perform those tasks. Since the machine learning algorithms are designed to take the best information from a human brain and translate that into the most likely result in an artificial intelligence system, you don’t have to be an expert in software engineering to design an effective ai system.
The three areas of study that comprise artificial intelligence are NLP (neuro-linguistic programming), CMU (computer modeling and analysis), and ML (natural language processing). These subtopics have their own independent and unique contributions to making the field of AI much more interesting and successful. NLP focuses on how language and thought are intertwined; it uses tools like neuro-linguistic programming and other tools to help a person create programs that enhance their potential; it studies how we use logic to achieve objectives and solve problems; and it applies tools from traditional computer science to help us build artificial intelligence systems.
On one hand we have classical AI technologies like computer chess and self-driving cars… And then we have NLP, ML and other forms of artificially intelligent software that are being designed by people in every field imaginable. Will humans be able to design their own AIs or will they have to buy the technology from someone else? And how will this all play out for those of us in the so-called business community or those of us with a “cybernetic” bent? As you can see, these are very important questions and the answers may well change human evolution forever.