The Race To AI

2019-08-15 18:15:17     Rohan Bhattarai, Student

“By far, the greatest danger of Artificial Intelligence is that people conclude too early that they understand it.” —Eliezer Yudkowsky

There is a lot of buzz around AI at the moment. And the term AI seems to be used a lot. So, what is Artificial Intelligence (AI)? To avoid confusion, we have to go the earliest and hence the purest definition of AI formed the time when it was first coined. So, here is what The First Definition of AI looked.

“Every aspect of learning or any feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.”
In simple words, it is just the capacity of a software or hardware to solve a problem that requires human-like intelligence. A computer would demonstrate a form of Intelligence when it learns how to improve itself at solving these problems. So, in definition you heard the word “Intelligence”. Ask yourself what is intelligence? If you summarize intelligence into different factors then it would go as:
1.Learning to perform better in situations not previously encountered.
2. Reason a conclusion appropriate to the situation in hand.
3. Solve problems with given data.
4. Analyzing features and relationships between objects.
5. Understand language by following syntax and other rules.

To bring the aforementioned points together a bit and solidify the concept in your mind of what an AI is, here are few examples of AI; Machine Learning, Computer Vision, Natural Language Processing, Robotics, Pattern Recognition and Knowledge Management.
By 2018, there have been thousands of companies working in this field, performing different experiments, writing thousands of lines of code to make their dream and thoughts turn into reality. Every company has its own start up idea for AI. But these concepts are not new. This industry is in the market from more than a half century. By now, you may be thinking that we may get to AI very soon. But what if I say that we are still far from it? From this the question arises, will we win this Race To AI?

So, let’s read about some new technologies in AI field. There is an AI technology developed that will look at a static image and predict that what would have happened in next few seconds. This may seem an easy task to an average human but it's not always the same for a computer. Making a computer able to do this was a science fiction until 2017. Similar work was done by another AI technology which guessed what was happening in the scene just by analyzing the audio and it is quite better than humans in this field. These types of AI technologies are not coded like other software. These use technology of Neural Networks which works on the same principal your brain works.

Do a thing --> If Make Mistake --> Learn From that Mistake and Prevent it in future.

There is another AI technology which takes input of an image and describes it for you in the text form. As humans learn from mistakes, so does the computer in Neural Network. It only gets better with training like humans. To make a program describe the image for you, it will take AI learn millions of other images at first and compare its output with the correct ones. It also classifies itself into different generations on the basis of its learning and accuracy. So, for example generation 99 will be better than generation 1 in a certain work.

Another example of Artificial Intelligence is Google’s New Feature in its virtual assistant. You will understand it with an example. If you need to fix an appointment with a doctor for your check-up, Google Assistant can do it for you. When said to do, Google Assistant will call the doctor by itself and talk to the doctor like a human and fix an appointment for you. This technology was being developed from many years and has been implemented now. This really makes you think that we are still in the phase of developing Artificial Intelligence. But in some field computers have outsmarted humans too.

Here is another example, Go is considered as the world's hardest game. It is an ancient board game. Go players in countries like Japan, South Korea take a separate learning course of Go from childhood. This means that they will not read other subjects. They go to school; practice Go every day. One thing about Go is that its possible moves' variation is almost infinite. Prediction of another few moves in this game is impossible. But Engineers at Google Deep Mind were working on the AlphaGo. It was an AI that could play the game of Go. It got better and better every time it was practicing. On March 23-2017, it defeated World Go champion.

There are many others form of AI that people are working on. Here is an AI that is near to you and that is Facebook. Facebook AI analyzes your chat and generate an applicable Ad beside you. For example, you are chatting about travelling with your friend. Then it is likely that you will get Ad about travelling too.

Technologies have gone very far in some areas and are still new in some areas. The methods engineers have used are for general purpose have created some sorts of anticipation in us that one day AI could be extended to help us address some of the society’s toughest and most pressing problems, from climate modelling to complex disease analysis. We are excited to see for what we can use this technology to tackle next. In conclusion, intelligence comes in many forms and has many aspects. At this time, we have many different types of AI technologies that are good at particular subsets of intelligence.

There is a possibility that AI could be the human’s greatest aid, fixing fundamental problems in our planet and allowing us to have technology and infrastructure that could have taken out centuries if we try to figure it out ourselves. All in all, we may be in a critical point in artificial intelligence, the future could see deep Neural learning and general-purpose AI in our smartphones and computers. Many decades of building smarter computers and algorithms, it turns out that the best blue print was in our heads the whole time ‘The Human Brain’. So, naturally our minds are capable of doing a vast range of things and all it depends upon how we use it.

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