Introduction to AI

Unit 1

Lesson 3: Growth of generative AI

The explosive growth of AI in the last 2-3 years has been exciting and overwhelming for many. It may seem that it happened all at once and came out of nowhere, but as we’ve seen, the field has been advancing for many decades to get to this stage. The tipping point that created impressive demonstrations was a result of many factors coming together. These factors have created the field of Generative AI. These are AI programs that create new data or content, such as images, text, or music, using patterns and structures from existing datasets.

EXAMPLE

Here is an example of how sophisticated AI image generation programs have become over time: https://ourworldindata.org/brief-history-of-ai

DEMONSTRATION

Open this website and test yourselves on which images are real and which are AI here:

https://www.cnet.com/pictures/ai-or-not-ai-can-you-spot-the-real-photos/6/

Some of the contributing factors for the recent explosive growth of AI are:

Deep learning programs have become very complex, which means that they can represent data in complex ways. They can create models of hierarchical data, giving some information more importance than others and creating an understanding of how the information is linked.
The creation of very powerful computer chips. These include GPUs - graphics chips, the sort that are used to display complex graphics in video games. With the huge amount of data to process, these chips can run programs faster and better.
Using models that are pre-trained. These pre-trained models are ready to be applied to new tasks, without the need for a long computation to organise the data.
Collaboration between teams of scientists. Many different research groups, non-profit organisations and private companies have shared their data and techniques for AI.
Investment and interest. The applications of generative AI in many different industries has become more obvious as its use increases. This snowball effect creates more opportunities for funding, which creates more research and more applications.

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