What is generative AI?

- Generally, AI models refer to artificial intelligence that can autonomously create or generate new content. In my previous course about developing an AI first mindset, we discussed how AI is used for analysis, classification, optimization, and recommendation. Now, these new advanced AI models can understand patterns, and relationships, and data and then use that understanding to comprehend and then produce or synthesize new information. This massive advancement in AI was made possible due to a number of factors, but arguably the three most important ones were the development of innovative deep learning architectures, such as transformers and diffusions, which are facilitating more complex and efficient AI models. Number two is the rapid expansion and access to computing power, especially cloud computing, which has made compute more accessible and cost effective for AI researchers and companies like OpenAI who rely on it for developing and training their models. And number three is the ability to learn and train on an unprecedented data scale. Essentially, the entire internet, take for example, an AI model that's trained on thousands of paintings from famous artists. The AI model will learn the style, the patterns, and techniques from these paintings and then utilize this knowledge to create new and sometimes unique works of art. Check out, for example, a photo I took of the sky of New York and how I recreated it in the style of a Renaissance painter while adding some science fiction elements to it. That's pretty cool, right? Art is just one example. Let's talk about customer support. The latest AI models are already trained on customer support best practices, from every product knowledge base available. Applying it within the setting of your own business can already enhance your customer experienced materially. And if you're using a conversational AI model, customers might not even realize that they're talking to a machine, unless you tell them. Now, imagine you can fine tune it with your own data and include the uniqueness of each customer, your business model, your desired operating system, and your principles. You can then utilize this knowledge and establish a deeper connection with your customers and help provide the best service that matches your brand. Imagine building unique customer support models for healthcare, or travel, or government, or utility companies. It's astonishing how extensible this technology can be. AI can be used to create new products or designs. It could be used to reimagine user experiences, to reinvent workflows, and to improve decision making. The list is endless, and as a result, AI has the potential to significantly benefit and disrupt businesses across a wide range of sectors. Now, the disruption part might sound concerning but the more you know, the better position you'll be in to leverage this technology positively for your business and for your customers. If you do have concerns or reservations, write them down and hopefully we'll be able to address them by the end of this course. In the next few sections I'll share several key components that are typically involved in every AI project. I cover some of them in more depth in my previous course in case you want to check it out. But for the purposes of this course, you only need to know the components mentioned in this section. So let's get started.