My name is Chaudhry Talha and this is my declaration of the intentions, motives, or views behind Intuitive Artificial Intelligence or Intelligent Artificial Intelligence (IAI). his journal also works as a rough ideas board that I am doing ad might change later as the research progresses.

Below is a theory that I see when I look at the data being collected. It's not the final work but I'm sharing it here to deliver the idea.

The Theory of IAIA (Intuitive Artificial Intelligence Algorithm)

What if I tell you that every grid in this simulator is a point of life (a life scenario) or life itself and it all depends on the perspective you put it through. Have a look at the image below and read along:

In the above image, there are three games data translated to grids and a path is drawn to each of the grids that show the user journey.‌

Imagine each of these grids as a completely different scenario of the life of one person or they define a particular scenario in a person's life, for example, a life scenario could be going for a job interview, the user starts at 2(14) and went to 8(10) it was windy (meaning going bad) he took a small risk b opening 6(9) it was still windy this grows the user's fear that they are going to fail and hence they took a big jump to 5(3) and died. Maybe, an AI can learn that when things are going windy don't take big risks from this one. From the second grid, AI can learn when it starts to get wind go up. Remember the AI will never be able to know what the full grid was, it'll just know the path it has explored. Similarly in the third grid, an AI might learn that if you are on an unknown territory or a scenario where you don't know what to do go for a smaller or optional goal rather than running after something that you are not going to get or has greater risk.

It's all about from what perspective you are defining each element in this simulator. Any program can code an intuitive AI into their systems and if needed the AI can use intuitive AI when needed. There will be a control on how much the AI can ask its Intuitive Brain. For example, in an image recognization example if an AI is unable to identify that the animal is a dog three times it is allowed to use its intuitive brain. You can mold this example into anything to it this algorithm here is one o the many other scenarios this example can fit into a problem. Now the one intuitive AI perspective to define this image recognization example would be:

• Goal: Need an output string of the animal in the photo

• Optional Goal: Just to reverify use a different image recognization algorithm before presenting the result.

• Risk: Image recognization result is wrong

The AI will look into the millions of intuitive data points that we have collected using the simulator. It'll pick a starting point, let's say it's index 12. It'll sort millions to only select the grids that have an opened box at index 12 (I am defining it like that, you can use our own perspective to take all the failed ones as well and let AI decides if it wants to follow this path or not based on the hints it's getting). Then from this result, the next sort will be to get all the scenarios where the user has won or found gold. Now on index 12, it has an answer let's say it has detected the dog as some other animals say a cat which is wrong and we know the AI is going to fail and from the sorted out result it randomly picks a grid in which the user has found gold. Consider the path below:

AI has the answer say cat, it's going to move forward and found an optional goal which means it'll run a different algorithm just to reverify and that algorithm also detects wrong say it detected that it's a seal. The reason why it decided to move to 8 and not to any other index is because of the random selection of this gid. Here the task is complete but the risk is higher now as both answers don't match. Here the AI only knows that they don't match and also has no idea if any of them is correct but knows for sure that both are not correct.

• It's a cat(True) and not a seal(False)

• It's not a cat(False) but it's a seal(True)

• It's not a cat(False) and it's also not a seal(False)

Here the AI has to decide either to move forward or go back and for that, we need a zero (No, don't move forward) or a one (yes, move forward). If we take the above to NAND we end up with 1,1,1 and then pass these through an XNOR gate and you'll get 0 which means not to move forward.

You can completely change this output to make sure it continues the path. It's all based on the risk that you want the AI to take. As moving forward you're going to get wind and if you set its score to say -1 which means bad. If the hint is wind, glitter the score can be 0, and if it's smell and glitter the score can be 1. If it's all three it can be 0, and if it's X nothing it can be 2. Based on the next score that you get you can decide either to alter or not. Let's say we have this logic implemented and we ask for the next index to move to and we get 13 and the score as its wind is -1 so AI knows it's in a dangerous zone. Our logic says that if the risk is zero or greater then move forward otherwise choose another grid.

Let's say the AI selects the second one as a winner.

In this new scenario, the AI will start again with a totally different thought process it'll go to 15 get a score of 1. Which is good. The next index the user gets on is 14 and gets -1 so doing +1-1 we get zero and based on our logic zero is greater than -1 so we'll move forward. But what about the previous data i.e. -1? We'll also add it to this result so 0-1 is -1 and we can't move forward. So, we'll need another winner board that has 12 as the opened index. Also, note that the opened box also has a score. In the case of the second grid, the score at opened index is 1 as it has glitter and wind. So, let's say this time we have programmed to select the highest score grid with index 12 as the opened index. So we need the third grid. Its starting score is bad i.e. -1 but in the data, we only have this one left so we're forced to use this grid.

In this scenario, the AI will start and take the first move. Evaluate its score i.e. 1 which is good to move forward. Now next we go to index 6 which is -1 so here I have to re-evaluate. So, -1+0-1+1 = -1 and we know we have to change the grid. let's say we don't have any grid left and are forced to move forward. We'll go to index 3 and here we'll get 2, and then again we get 2, then we get 1, then we reevaluate the image lets say this time we get Dog. The next index would be 11 and that is to present the findings so we'll say that intuitively the AI thinks it's a dog which is correct. Here the output of the reevaluation can be wrong, there is a full chance of that and in this scenario, we can say that we have found a goal so the output will say it's a cat or a seal or some other animal. it'll decide based on the score of each grid i.e. -1, 0, 5 which means that the AI is less confident that it's a Cat and more confident that it's a seal and it's very confident that it's some other animal. This is still not correct but the computer thought about it. Maybe in a world where AI is dominant, dogs are called seals or some other name because of this intuitive decision. We can change this scenario to sort the grids that start at 12 and have all Gold and Monster found only. Depending on your scenarios you can code the risk. So, it has countless possibilities and you can reprogram it to work in the ways you want it to take the decisions, meaning you can control the intuitive amount of the AI. Too much intuition is bad and too little is also bad. Our goal should always be to take the best scenario.

So, this is just one example of how Intuitive AI will take a decision. This situation can be molded to a different logic but the point to take from this example is that there is no one type of programming scenario. You have to program it in a way that you take the best scenarios possible. That is why we used NAND & XNOR gate as they take the best scenarios. The goal of Intuitive AI is not to improve an algorithm but to add a brain that takes decisions where there are no other options left.

The Idea Behind

I read it somewhere that if we can define anything with a mathematical equation we can get the computer to do that. Because the computer is built on logic. That is why our brain is divided into two parts, anyone who sees a brain diagram can tell it's in two parts and it's only because our decision-making process consists of the logical and the hunch.

Time is very strange. It's a part of our daily life but yet if you do a little research of what time actually is you'll be blown away with what it is and to save you time, no one can tell what time actually is. The problem with the majority of us is that we are either living in the past or living in the future we just don't live in the present or we just don't live in the NOW.

A good example that I give to myself of why this concept of IntiutiveAI that what I'm presenting is worth exploring is if you go back to 1995 when Java was introduced. It was the first Object Oriented language and it was inspired by real-world concepts like objects, Inheritance, Abstraction, etc. Objects are all around us and a similar concept is used to define Java Objects though they are a bit different in nature they are not like the objects around us they act like that. Similar is going to be the situation here, the intuitive thinking of a computer will not be similar to what we have but it'll be something that only machines can do or in other words, it'll be machine intuition that is made for the machine.

“You are awareness, disguised as a person.” ― Eckhart Tolle, The Power of Now: A Guide to Spiritual Enlightenmen

Computers are different from humans so self-awareness or computers will be a bit different. Almost all machine learning relies on past data in order to make a decision in the present that is going to change the outcome o the future.

Can a computer ever achieve it? Intuition revolves around the psychology of humans and the simulator basically defines those psychological principles into a mathematical term. When I first designed the simulator I went to the one and only meeting I had with Dr. Vazeer and I was super hiked about this simulator that I got super excited telling him about it that sir it fulfills the aspects and I think we have something here that can revolutionize something if an algorithm is built around it and of course because of this excitement I got carried away and he got lost in the conversation. So, I opened the simulator and gave him the rules and that's it. He played about 5 games and he realized everything that I was trying to say and he said I know even if I play this game a million times I'll still not be able to improve and will always have to make decisions based on my intuition. The simulator was portraying the NOW factor. You have to focus on the now situation, you know you're about to open a random box which can have anything in it, and all the boxes look the same so the box you'll choose you'll explain your decisions to someone like "I just felt like opening this box so I opened it", that's intuition scaled on a different scale as I wanted to take the real world intuitive decision making into the computer.

Let's see how the simulator works and this time we'll see how every step is mimicking the real-world psychological principle.

When a new game is started the grid is randomized so the previous knowledge you had is useless because it's a totally new world with the same rules. Now one box is opened randomly, it just gives you a hint which basically portrays that you can start from here if you want, meaning you have been given a divine path but at the same time you have free will to open any box at any time, there is also no surety that if you follow the path you'll achieve your goal. This is life, God has given us free will but also at the same time all the religious books that are the way to live. We are free to follow them or make our own paths. People who follow religion in its true essence have fewer mental health issues. The new randomized game is your life. You have a hint which gives you a sense of some of the world but not all the details you have to make a choice and follow the journey to achieve your goal. There is a high chance of failure just like in real life. There are 4 pits and only 1 monster so your chance of failure is higher and this is exactly how it happens in real life. If achieving the goal of life was easy everyone would be rich and because the failure is high that is why we only have a few successful people in the world where we are billions in numbers.

Sometimes in life, you have some goals that you should do but if you don't do them there is no harm but if you do them you will get more than you were actually going to get when you achieve your goal. Think of it like people who pray 5 times a day which is a requirement you must follow, but with that, if they also feed the poor every day which is optional but encouraged they'll either stay wise and earn an extra reward in the after-life but there is also a chance that you start thinking yourself as God of those people and your path is totally ruined so basically, you have fallen into the pit. This optional but encouraged task is the gold in our simulator.

The boxes you open are either intuition-based or you know exactly what will happen when you open a box. This is how we make decisions in life, sometimes we make decisions based on carefully calculated decisions, and sometimes you have to make decisions solely based on your intuition, and sometimes you have to take a mix of both. For example, if you get a hint Wind now you know there is a pit in one or more of the adjacent boxes this is calculated then which boxes will have the pit from those adjacent boxes is something you don't know and you are now forced to make a decision based on your intuition, that's a mix of both calculated and intuition.

So, you see how life is scaled down to a 4x4 grid, and when people are playing it they don't realize it because their reality is on a much bigger scale. The rules are the same for everyone, i.e. you were born, you are going to get aged and one day you'll die. These three simple rules are for everyone, the world is different for everyone. Someone is religious, someone is atheist, someone loves to eat meat, someone is a vegan, and so on. Our decisions throughout our life shape how our life is going to be. Also, the simulator is designed by keeping an individual in mind, because my belief is that you are alone in the world. Your family, your wife, your kids are just other people you are an individual and you'll be answerable to your decisions only and no one can take your place no can you take someone else's place. That is why when you are playing the game you're all alone, all you have is a world that is changing with every decision you are making, either you'll succeed or just die.

The scoring in the game is also built on psychological principles. You can only get -1, 0, 1, or 2 in the game. Most people will strive for 1, this portrays the 80% of the world population that is middle class. Many people if they see a good calculated chance that they'll be able to get 2 only then they'll take it where some people will go out of the way to take the risk of getting the 2. These are people who are successful. The people which get 0 are the ones who were going good in life, but died early otherwise they would've done more great things but they left behind some sort of legacy, which saved the people after them something meaning they were saved from a total loss which is -1 in the game i.e. the smallest number. Now the people of -1 are the ones who get the lowest possible in this small 4x4 world. They can be people who try to work hard but failed even after taking a calculated risk or following their intuition. They can also be people who don't care and they are just making decisions randomly and ends up failing. In life, we have to be a bit careful and use both sides of our brain to make decisions. The risk of failure is still there but that's the life you do your best and let fate decide.

Now, if an AI is able to play through this world and improves its accuracy to an acceptable amount I can confidently say that it has achieved the intuition decision making and I'll not stop until I am able to solve this.

The 4x4 grid can make more than 16! = 20,922,789,888,000 (twenty trillion, nine hundred twenty-two billion, seven hundred eighty-nine million, eight hundred eighty-eight thousand) unique games. By more, I mean if we consider the one box that opens up randomly then the number of the unique pattern increases. The total the Population Reference Bureau estimates that about 107+ billion people have ever lived on this planet, according to https://www.bbc.com/news/magazine-16870579 so, if you give one unique grid to each of these humans they'll all have unique lives and we'll still have a lot more left fo the humans who'll be coming in the future.

I still remember when I was thinking of the logic of this simulator, I started around 11 PM at night and kept on working till 4 AM. I was working from a co-working space in Washington DC and they had a room that had a whiteboard on the three sides of the wall and one wall was the door. I brain-stormed the rules the logic, anything I could think of at the moment, kept on changing rules until I couldn't find anything that I could not fit in this 4x4 world. Then I sat down on the chair facing the three walls and coded the simulator which looking at the walls. Here is a picture that I took from the video that I made as I thought the board is not going to be enough. I don't have the video anymore but I have this photo taken out at that video.

This is just a brief of the thought process that was put in this small 4x4 world. I went through past simulations and saw what computers know, then I mixed concepts of those games ad simulators and generated rules and ran scenarios on them. I'm really proud of this idea as it's something that I don't even understand and my INTP-A personality is super excited about this.

In conclusion, this is how I was able to place some of the psychological principles of our life into a computer simulation and now using the data we'll build the algorithm that'll bring something big out on the table of machine learning.

Thank You & Yours Truly, Chaudhry Talha