AI Demystified: How It Works and Why It Matters for the Future
The topic of Artificial Intelligence (AI) has seeped into our everyday conversations with relatives, friends, and co-workers. Despite being around for decades, it’s only recently with the release of ChatGPT has the sheer potential of AI become so apparent and accessible to the general public. It’s shaping up to be the next big global revolution in technology, much like the internet or the smartphone before it.
Funnily enough, similar to the internet or the smartphone, much of the general public doesn’t understand how an AI actually works - we just simply accept that it does! Let’s dive into demystifying AI in this blog.
What is AI?
Artificial Intelligence, or AI, is a branch of computer science that focuses on creating machines that can mimic human intelligence. These machines are designed to think, learn, and make decisions in ways that are similar to how humans do. From virtual assistants like Siri to chatbots we can talk to like ChatGPT!
How do machines learn with AI?
The learning process in AI is quite similar to how humans learn from experience. For example, in order to teach a child to recognse different animals. You show them pictures of cats, dogs, and birds, and tell them what each one is. Over time, the child learns to identify each animal based on its features (fur, size, beak, etc.). Similarly, an AI system is trained with large datasets containing many examples of the task it needs to learn.
This is done through a process called Machine Learning which is commonly split into three variations.
Supervised learning is like teaching AI by example. We show it thousands of pictures of apples and tell it, "This is an apple." The AI learns to notice the common traits of apples, like their colors, shapes, and sizes. Eventually, it can tell that something is an apple from any picture.
Unsupervised learning means we give the AI completely unlabeled data. Without telling the AI what anything is, it has to find patterns and relationships between the data on its own and sort them into categories. This can be used to train AI to detect spam emails or fraudulent activity on your bank account.
Reinforcement Learning (RL) is a type of machine learning where an AI learns to make decisions by performing actions in an environment to achieve some goal. Every decision will have a positive or negative value attached to it meaning we can let the AI know which behaviors we want or not. For example, we can train an AI to win a game of chess by letting it know which moves are good or bad!
AI models are trained with billions of data sourced all across the internet. Pictures, videos, essays, websites… By taking in all this data and processing it using extremely complex algorithms, it is able to use mathematical probability to mimic the way a human writes, draws, and speaks! Incredible - but also a bit scary.
So what does this mean for the future?
With the rise of AI use in workplaces everywhere, there are plenty of big, important discussions to be had on its usage. For instance, its undeniable impact on the labor market. Would corporations still be willing to spend thousands hiring creative people like writers or graphic designers when AI can do it for free? Would teachers be necessary in developing appropriate curriculum for schools when AI can explain things in a way specific to an audience’s age?
Being able to type on a typewriter used to be an employment-worthy, sought-after skill back in the 20th century. Today, it definitely isn’t seen as an impressive skill anymore. The only way to stay relevant back then was to pick up more current skills to keep up with the times. Similarly, while AI may make some jobs irrelevant in the future, we can future-proof our children by equipping them with knowledge that can prepare them for new careers in a world of advanced AI.
At Coding Lab, we understand the importance of preparing the next generation for these changes. Our AI classes for kids are designed to equip them with the skills they need to thrive in a world where AI plays a central role. We have our Young Computer Scientists - Cognitive Artificial Intelligence as well as AI and Machine Learning modules (Ages 7-9), Advanced Computer Scientists - Machine Learning and Image Classification (Ages 10-12), and Advanced Electives - AI and Machine Learning elective. Do note that these classes are only available when they’ve mastered the basics of computing by completing our prerequisite courses or placement tests!
By enrolling your child in our AI classes, you’re not just teaching them about technology; you’re empowering them to become innovators and leaders in an evolving job market. Let's embrace the future together and give our children the tools they need to succeed!