Published 04/29/2024
AI For Everyone by DeepLearning.AI taught by Andrew Ng, Founder, DeepLearning.AI & Co-Founder, Coursera
What is this AI propaganda?! The cars are driving themselves! Social media is suggesting incredibly niche advertisements to me! The chatbots are taking over! I repeat, THE CHATBOTS ARE TAKING OVER!
Why are people up in arms about these recent developments, and what IS it? It’s none other than deep learning, a type of machine learning and artificial intelligence that imitates how humans gain information or certain types of knowledge.
Should you be scared of it? Not at all – you should welcome it with open arms like a long-lost pal because it’s here to make your life easier.
Deep learning models can be taught to perform tasks and recognize patterns in various data types like photos, text, audio, etc. Deep learning is used to automate tasks that humans usually do, freeing us up to take a vacation or a nap.
A great example of deep learning is its ability to predict housing prices by utilizing information like the house size, the number of bedrooms, the number of bathrooms, whether it is newly renovated, and more.
The most effective way to price a home would be to feed all this information into a neural network. This artificial intelligence method teaches computers to process data in a way that was inspired by the human brain. It uses interconnected neurons in a layered structure.
The general public’s concerns may be warranted by how new AI may be. We are always afraid of what we know little about, and any opportunity to find validation in our concerns is pursued – queue a Facebook post from your grandpa about AI coming from aliens, so it is evil and dangerous.
What IS dangerous is how we decide to use it and our ability to be critical, self-reflective, and willing to learn about it.
Luckily, engineers, data scientists, and AI teams are constantly learning more about potential flaws and biases while creating strategies to overcome them. As discussed in the previous episode, data science projects are helpful to all, even AI teams.
Every system learns from humans and is evaluated by other humans and a large group of humans, critiqued by other humans, and so on. The only thing to fear is misinformation that must constantly be checked and improved by large teams of people.