00:00Generative AI models refer to artificial intelligence that can autonomously create
00:05or generate new content. In my previous course about developing an AI-first mindset,
00:11we discussed how AI is used for analysis, classification, optimization, and recommendation.
00:18Now, these new advanced AI models can understand patterns and relationships in data,
00:24and then use that understanding to comprehend and then produce or synthesize new information.
00:32This massive advancement in AI was made possible due to a number of factors, but arguably the three
00:38most important ones were the development of innovative deep learning architectures,
00:43such as transformers and diffusions, which are facilitating more complex and efficient AI models.
00:49Number two is the rapid expansion and access to computing power,
00:54especially cloud computing, which has made compute more accessible and cost-effective
00:58for AI researchers and companies, like OpenAI, who rely on it for developing and training their
01:03models. And number three is the ability to learn and train on an unprecedented data scale,
01:11essentially the entire internet. Take, for example, an AI model that's trained on thousands
01:17of paintings from famous artists. The AI model will learn the style, the patterns, and techniques
01:23from these paintings, and then utilize this knowledge to create new and sometimes unique
01:28works of art. Check out, for example, a photo I took of the sky of New York and how I recreated
01:35it in the style of a Renaissance painter while adding some science fiction elements to it.
01:40That's pretty cool, right? Art is just one example. Let's talk about customer support.
01:48The latest AI models are already trained on customer support best practices from every
01:54knowledge base available. Applying it within the setting of your own business can already
02:01enhance your customer experience materially. And if you're using a conversational AI model,
02:07customers might not even realize that they're talking to a machine unless you tell them. Now,
02:12imagine you can fine-tune it with your own data and include the uniqueness of each customer,
02:18your business model, your desired operating system, and your principles. You can then utilize
02:24this knowledge and establish a deeper connection with your customers and help provide the best
02:29service that matches your brand. Imagine building unique customer support models for healthcare or
02:35travel or government or utility companies. It's astonishing how extensible this technology can be.
02:42AI can be used to create new products or designs. It could be used to reimagine user experiences,
02:47to reinvent workflows, and to improve decision making. The list is endless. And as a result,
02:53AI has the potential to significantly benefit and disrupt businesses across a wide range of sectors.
03:00Now, the disruption part might sound concerning, but the more you know, the better position you'll
03:06be in to leverage this technology positively for your business and for your customers.
03:11If you do have concerns or reservations, write them down, and hopefully we'll be able to address
03:16them by the end of this course. In the next few sections, I'll share several key components that
03:21are typically involved in every AI project. I cover some of them in more depth in my previous
03:26course in case you want to check it out. But for the purposes of this course,
03:31you only need to know the components mentioned in this section. So let's get started.
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