Even before all this Blockchain Technology (GO HERE to learn about it) started to flood the internet. And all the new Digital currency started to take shape (you can GO HERE to learn how you can start mining your own FREE Bitcoins). Man was interested in Artificial Intelligence. With what it could possibly do and what it possibly could be used for.
What is Artificial Intelligence?
Most people when they think of Artificial Intelligence. They think of the Sci-Fi movies they have seen. Like I Robot where human-like robots do the menial tasks. Like cooking, cleaning, and dusting. Ones we humans don’t want to be bothered with. But AI is a whole lot more than just that.
The Dictionary defines artificial intelligence as. The theory and development of computer systems able to perform tasks that normally require human intelligence. Such as visual perception, speech recognition, decision-making, and translation between languages. Artificial intelligence (AI) makes it possible for machines to learn from experience. And adjust to new inputs and perform human-like tasks.
The History Of AI.
It was in 1956 when the term artificial intelligence was coined. Thanks to increased data volumes, algorithms, and computing power improvements. Along with storage, AI has become more popular today.
In the 1950’s early artificial intelligence research explored topics such as. Problem-solving and symbolic methods. Which In mathematics, the symbolic method in invariant theory is an algorithm developed by Cayley (1846), Siegfried Heinrich Aronhold (1858), Alfred Clebsch (1861), and Paul Gordan (1887). In the 19th century for computing invariants of algebraic forms.
In the 1960’s interest in this type of work was taken on by the U.S Department of Defense. When they began training computers to mimic basic human reasoning. For example, the Defense Advanced Research Projects Agency (DARPA) completed street mapping projects in the 1970s. And DARPA produced intelligent personal assistants in 2003, long before Siri, Alexa or Cortana were household names.
This early work paved the way for what we see in computers today. Automation and formal reasoning. Including decision support systems and smart search systems. That can be designed to complement and augment human abilities.
While today Movies and Sci-Fi Novels love to portray AI in the form of human-like robots. That only function is to take over the world. And make all us humans their slaves. But quite the contrary AI has evolved to provide many specific benefits in every industry.
Some of the AI uses we see every day.
Virtual Personal Assistants
Video Games
Another form of AI most people are probably familiar with are Video games. Ai has been used for awhile in video games. In fact, since the first ones have hit the market. But since then the AI has become more complex and effective. Most of this was during the past several decades. Because of this, you will see the characters that are able to. Learn your behaviors, respond to stimuli, and react in unpredictable ways.
Far Cry and Call of Duty make significant use of AI. In these First-person type shooting games. You will encounter enemies that can analyze the environment they are in. Find objects or actions that might be beneficial to their survival. You will see them take cover and perhaps flank you. Investigate sounds and communicate with other AI’s. In an attempt to increase their chances of victory.
As far as artificial intelligence goes, video games are somewhat simplistic. But because of the industry’s huge market. A great deal of effort and money are invested every year in perfecting this type of AI.
Purchase Prediction
When it comes to retailers, the big ones can make a lot of money if. If they can anticipate the consumer’s needs. Thou the technology isn’t in place yet Amazon is working on an anticipatory shopping project. They hope this will let them send you items before you need them. Thus eliminating the need for the last minute trip to the online store.
You might see some brick and mortar retailers doing something very similar to this new technology. By given you some coupons when you visit the store. These are selected by a predictive analytics algorithm.
This technology can be useful in many ways. Be it sending your coupons, offering discounts, targeting advertisements. Or even stocking warehouses by your home with the products you are likely to buy. You can see examples of the targeting advertisements every time you are surfing the web. Ever notice the ads you see are always related to what you have bought or searched?
Fraud Detection
I hope you never had. but most of us have probably gotten an email or call asking about a certain purchase made. More than likely on a credit card. I have had an issue when traveling for work once. I tried to use my credit card out of state to have it denied. After calling them they said it was denied due to the fact I was not even close to the state I lived in. And tried using the card to make a purchase. It was nice to know they were looking out for me. But this could really put you in a bind.
Most banks are using this artificial intelligence technology to monitor for this type of fraud. They use these kinds of communications if they think there is a chance that fraud may have been committed. This is for our benefit making sure we approved the purchase. Before any money is sent out to another company.
In many cases, computers are given a very large sample of fraudulent and non-fraudulent purchases and asked to learn to look for signs that a transaction falls into one category or another. After enough training, the system will be able to spot a fraudulent transaction based on the signs and indications that it learned through the training exercise.
Online Customer Support
You might have seen the little “Chat Now” window on a lot of websites these days. This allows you to chat with Customer support. Where you can ask questions or get assistance. But are you really chatting with a real person? In a lot of cases, you are talking to a primitive form of artificial intelligence. Most of these chat support amount to little more than automated responders. Some of these are able to find knowledge from the website. And they can present it to the customers when asked for.
The interesting part is that these chatbots need to be capable of understanding natural language. This can be a rather difficult proposition. Because the way in which customers talk. And the way in which computer talk. These are very different kinds of languages. And to teach a machine to translate between the two is no easy task. But with rapid advances in natural language processing (NLP), these bots are getting better all the time.
Security Surveillance
We have all seen movies where they will show a security guard. Sitting at a desk in front of a bunch of monitors reading a newspaper, watching TV, or even taking a nap. Granted it is a tough job for humans. They get bored and lose interest. Let alone the eye strain of trying to keep up with everything going on, on a bunch of monitors. That’s why this is an ideal situation of the use of artificial intelligence. With extensive training exercises, you can have security algorithms take input from security cameras. And with the information, it sees determine if a threat is present. Then be able to notify human security officers if it sees a “warning sign”.
The technology at the moment is pretty limited on what these computers can see. Flashes of lights and debris can appear to be an intruder. But exactly identifying a thief are likely beyond the current technological limitations. Don’t be surprised what these might be able to do in the near future.
Music and Movie Recommendation Services
Music and movie service also use a form of AI. Although a rather simple form of it. Services like Netflix, Pandora, and Google Play Music can recommend music and movies based on your interests. The ones you have expressed interest in, in the past. By monitoring the choices you make and inserting them into a learning algorithm, these apps make recommendations that you’re likely to be interested in.
Much of this functionality is dependent on human-assigned factors. For example, If you listen to Jazz, soft rock, or hip-hop. Or watch movies like action, comedy, or drama. It will base movies and music similar to these that you might also like. This is the basis of many recommendation services. While not technologically advanced if does do a decent job of letting you discover new music or movies.
Smart Home Devices
More and More these days you can find new smart homes on the market. These homes can make everyday life easier for us. Many of the new devices in the smart homes now have the ability to learn. These forms of artificial intelligence can learn from our behaviors. For example, your thermostat that knows when your home and adjust’s itself to your desired temperature. Not only is convenient. But can save you money by not heating or cooling your home when you are not there.
Lighting is another place where this form of AI is very useful for. These basic artificial intelligence systems can have default settings and preferences. For not only the lights inside the home. But outside as well. They might adjust themselves based on where you are and what you’re doing; dimmer for watching TV, brighter for cooking, and somewhere in the middle for eating, for example. The uses of AI in smart homes are limited only by our imagination.
Why is artificial intelligence important?
Repetitive learning and discovery through data are automated through artificial intelligence.
We all have seen the factories with rows of robotic arms doing what they have been programmed for. But AI is different from this hardware driven robotic automation. AI can perform frequent high-volume computerized tasks reliably. And can do them without fatigue like its human counterparts. But don’t worry we all will not lose our jobs. As humans are still needed for the essential setup and maintenance.
AI can add intelligence to products.
Artificial intelligence isn’t something you will see being sold on its own. But what AI will be used for is enhancing products that already exist. Like Siri was added to the new generation of Apple products. And when it comes to automation and conversational applications. Bots and smart devices or machines can be combined with large amounts of data. Which in turn can improve many technologies. Both at home and the workplace. From smart home devices to security surveillance.
AI adapts through progressive learning algorithms.
With AI applications the data will be able to do the programming. Artificial intelligence can find structure and regularities. Which will allow the algorithm to acquire a skill. This allows the algorithm to become a classifier or predictor. It then can teach itself things like what song you might like to listen to next. Or what products to advertise to you online. The model can also adapt when its given new data. There is an AI technique that allows the model to adjust. This through training and added data. When the first answer is not the correct one.
Artificial Intelligence can not just analyze more data but can analyze it deeper.
A few years ago, building a fraud detection system with multiple hidden layers was almost unattainable. But with using neural networks that have these hidden layers. All that has changed because of the unbelievable computing power and enormous data storage. Since these models learn directly from the data. You need a ton of data to train them. The more data you can input the more accurate they become.
AI has achieved amazing accuracy.
Just look at Alexa, Siri, and Google search have gotten more accurate because of deep learning. And the more we use them the more accurate they become. This is due in fact to the deep neural networks. Which a few years ago would have been impossible. The medical field is also benefiting from the deep learning of AI techniques. With image classification and object recognition. The medical field can utilize these to find cancer on MRI’s. That has the same accuracy as a highly trained radiologist.
Some of the challenges of using artificial intelligence
Artificial Intelligence has the ability and will be changing every industry. But what we have to remember is it does have its limits. And we have to understand this.
Perhaps the most pronounced limitation for artificial intelligence is that it has to learn from data. This is the only way in which knowledge can be incorporated. So if there are any inaccuracies in the data. This will then be reflected in the results. And any additional layers of prediction or analysis have to be added separately.
The AI systems of today are all designed and trained to do clearly defined jobs. The security surveillance system cannot detect fraud. As the system designed to drive a car cannot play solitaire. I am sure you get the idea so no need to elaborate more.
In a nutshell, these systems are very specialized in what they can and cannot do. They are focused on one task and one task only. I am sure you will see in the future that this will change. Maybe not in our lifetime but rest a sure they will.
What we see AI doing in movies is still pure science fiction. But computers that can probe complex data to learn and perform some specific task are becoming quite the norm.
How Artificial Intelligence Works
The principle way that AI works is by joining large amounts of data. With quick repetitive processing and intelligent algorithms. Thus enabling the software to automatically learn from patterns or features in the data. The field of AI is broad and includes many methods, theories, and technologies. As well as all these major subfields.
Machine learning
Using methods from neural networks, statics, operations research, and physics. This allows it to find hidden insights in data. Without particularly being programmed for where to look or what to conclude from it. This all for the automated analytical model building.
A neural network
You may ask what is a neural network. It a form of a learning machine made up of interconnected units (like neurons). That process information by responding to external inputs. Relaying that information between each unit. This process requires multiple passes at the data to find connections. And then derive meaning from the undefined data.
Deep learning
In order for AI to have deep learning. Huge neural networks. With many layers of processing units are used. This takes advantage of the all the recent advances. In both computing power and improved training techniques. They have to in order to learn difficult patterns in huge amounts of data. Some of the common applications include speech and image recognition.
Cognitive computing
In this subfield, AI has been reaching for the goal of natural. And human-like interactions with machines. They hope to achieve a machine that can simulate human processes. With the two abilities of speech and image interpretation. Then be able to respond with coherent speech. Like Data on Star Tech the Next Generation as an example.
Computerized vision
This form of computer vision relies heavily on pattern recognition and deep learning. This to accomplish the recognition of what is in a video or picture. When a machine can process, understand, and analyze images. They will then be able to capture videos or images as they occur. Then be able to interpret their surroundings.
Natural language processing
This can be an entire article in itself. As there is so much one can learn from it. The basics of NLP is the ability of computers to analyze. Understand and produce human language. This encluding coherent speech. The next milestone of NLP is interacting with natural language. Which means humans being able to communicate with computers. using normal everyday language to perform tasks. Although we already see some applications of this. Such as Alexia, Siri, and Cortana. This is yet far from being perfect.
Technologies that enable and support AI:
.There are quite a few technologies that enable and can support AI. Here are a few examples of them.
The Internet: Yes, the internet. The internet generates enormous amounts of data. From all the connected devices to it. The majority of it is unanalyzed. But with automated models of AI. We will be able to use more of it.
GPU’s: Graphic processing units are a key factor to AI. Because they can provide the necessary heavy computing power. That is needed for repetitive processing. Computing power and big data are necessary for training neural networks.
APIs: These application processing interfaces are nothing more than. Portable packages of code which make it possible. To add AI functionality to already existing products and software packages. Which can make it possible to add image recognition to devices. Like unlocking a device with your face.
Advanced algorithms: These algorithms are constantly being developed and combined. In new ways in order to make analyzing data. Faster and on multiple levels. Having intelligent process is key in order to. Identify and predicting rare events. And also understanding complex systems. And for optimizing very unique scenarios.
To recap the ultimate goal of AI is giving software the ability to reason on input. Then being able to explain it on the output. Enabling software to interact human-like with the user. Not to be a replacement for humans but aiding them to make things easier for them. This won’t be anytime soon but eventually, it will happen.
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