AI: A mind blowing puzzle!
Have you ever tried solving a jigsaw puzzle? Well that’s what artificial intelligence(AI) is! Except it’s much more complicated... In a puzzle there are multiple pieces that you must put together in order to end up with a complete picture, and in AI there are many components that work together to create an outcome. Puzzles focus on developing and growing the human brain. Similarly AI aims to help computers learn how to perform intellectual tasks.
“Predicting the future isn’t magic, its artificial intelligence.” — Dave Waters
Hello! My name is Sara AlSalloum, I’m a 14 year old girl from Saudi Arabia who has a passion for AI. I always loved problem solving, whether it was jigsaw puzzles or simple word riddles, as long as there was a solution I would find it. Every once in a while I challenge myself to a riddle, or a 1,000 piece jigsaw puzzle. The journeys I go through in solving riddles greatly challenged my patience and critical thinking skills. I realized that I have the need to test myself in new concepts no matter the difficulty. These traits flourished my passion for AI. I like how I can create modern solutions to issues the world is facing. After an email from my college counselor, it led me to the AI Fluency Course.
Before I started this course I saw AI as bits and pieces of metal and wires, but I was proved wrong. It is much more than a physical body; it includes a LOT of programming. You wouldn’t believe me if I told you the base of an AI’s mind is basically a bunch of math. It’s true math really is everywhere. But it creates crazy projects! For example, during the reinforcement learning class, I was introduced to an AI technology which was able to solve a Rubik’s cube. This AI was structured as a hand so that it can move the cube placed in its palm. The AI explored how the cube was structured and had to find different ways to solve the puzzle. The robot was shown many variations so that it can randomly solve the cube. It made me ask many questions like: “How does it know what its next move should be?” and “How does the AI know what the cube looks like after every move?”.
This technology helped me know more about reinforcement learning. Reinforcement learning is when an agent explores its environment for decision making. It uses the reward & punishment policy to make decisions in problems. As stated before there is the agent; the model that is trained to make decisions, and an environment; where the agent interacts. Basically the reinforcement learning agent perceives its environment then takes actions. The agent will reinforce decisions that were rewarded and will penalize actions that lead to errors so in the same situation it will act differently.
It’s interesting how machine learning can create advanced cutting edge technology but can also use more simpler algorithms in complicated tasks. It’s common to see rookie data scientists/machine learning engineers using the latest algorithms when there are more simpler and efficient ways that can suit the task. K-nearest neighbors (KNN) is a simple machine learning algorithm that can be used to solve complicated regression or classification problems like classifying the species of a penguin based on its bill and flipper size. KNN identifies the closest data points in the training dataset — it’s “nearest neighbors” — to create a forecast for a new data point. This prediction becomes the main output for the training point.
These examples are a visual representation of the algorithm. It shows that when the nearest neighbor was k=10 the data points were in smoother location boundaries than when k=1; where the boundaries were more specific.
With everything I learned so far and all the different documentaries I’ve watched, it surprises me that the human race is still at the beginning of the AI revolution. This AI fluency course has really opened my eyes towards AI and given me information I can use for future projects and courses. It has helped me start my journey already by teaching me the basics of machine learning. Not only that but it has given me a sense of responsibility in organizing my time in learning and other personal activities. I also feel much more confident in this subject. Before I took this course I knew nothing about AI but knew I had a strong passion. Now, I feel confident in learning more about AI and hope to use this information in future projects. I am in MYP5, meaning that I’m currently working on my personal project. This course has positively influenced my idea in the personal project.
I know for a fact that if I didn’t have my instructor helping me throughout this journey I wouldn’t have been as confident as I am today. There is so much information used in this study, and I believe that the way he was able to present the information made it less complicated. Especially with the notebooks and videos that were provided, his way of interpreting the information in different ways made it easy for everyone to learn. I appreciate how he was able to create a positive environment for learning. He had us share screens, ask and answer questions so that we can all cooperate during the learning journey. He also gave us examples and asked us to give ideas on certain topics.
AI is the foundation of a better future, and it brings me joy to know that I have started my AI journey aiming to impact humanity through technology, for good.
