When it comes to technologies of the future, Artificial Intelligence (AI) and Machine Learning are some of the most impressive ideas– how can you get a machine to learn? Despite being one of the most well-known current innovations, there are a lot of misconceptions about what exactly AI is, and how Machine Learning relates to it.
Broadly, Artificial Intelligence just refers to the ability of technology to act like humans, and Machine Learning is an application of Artificial Intelligence where a machine can learn and grow based on its experiences. In other words, Artificial Intelligence uses Machine Learning to accomplish tasks that a human could.
One way to learn about Machine Learning is to compare it to how populations expand and evolve over time. For instance, if we had a group of 100 animals competing in an environment, the animals with traits beneficial to their survival would live on and produce offspring. For instance, animals with good camouflage or speed would outlive those lacking these traits, as they could avoid predators. Then, these positive traits are passed to the next generation of animals: the offspring of the most fit members of the population.
Some types of Machine Learning work in a similar way. If we programmed a racetrack and let 100 racers randomly attempt the course, many would immediately fail, but a few may make a small amount of progress. Then, the program would take the most successful individuals, and use their settings (genes) for the next set of 100 racers, with each of the 100 racers having additional random mutations to prevent all 100 racers from doing the same thing. With this new, second generation, the program gains information about what worked and what did not and uses this information to make the algorithm slightly better.
After repeating hundreds of these generations, slowly learning over time, this Artificial Intelligence will eventually complete its goal, as slowly improving the algorithm by analyzing successful individuals will eventually lead to success. This is the general idea that Artificial Intelligence is based on– analyze patterns and variations in data to change the program’s behavior. AI isn’t something to be terrified about– while innovations in the field are being made every day, it’s a slow learning process that’s mostly still theoretical. Hopefully you learned some about AI and Machine Learning; if you’re interested in learning more, there are plenty of YouTube videos with interesting examples of each.