Generative AI Is A Hot Topic – Here’s Why

• Best-selling novels written without a human author
• Beautiful artwork generated in minutes
• Entire symphonies created without a composer

With AI becoming a reality and jumping into the mainstream, you won’t have to imagine for much longer.

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So, what is generative AI exactly? We can help you unpack this relatively new and complex topic with our short guide below.

What is generative AI? Until recently, artificial intelligence was based entirely on pre-programmed input. A computer or robot was programmed with an if-then-based algorithm (e.g., If A is input, then it should output B; if C is input, then it should output D) that allowed the device to output information based on the data.

It was often used to run massive simulations to help predict outcomes (e.g., Can we predict what will happen after running 10,000 simulations?). Generative AI, however, uses multiple systems to check and balance its output to create more dynamic and diverse end products.

When it comes to different types of generative AI, one of the most well-known right now is Generative Adversarial Networks (GANs). The system uses two neural networks, which are algorithms that extract and classify information before creating an output. The neural networks are referred to as a generator and a discriminator and work against one another to help create the final product. They do this as the generator creates content, then the discriminator evaluates the content to see if it’s real or not.

In other words, the two networks “push against” one another to create more realistic content through a process called deep learning. Through deep learning, AI systems can gain certain types of knowledge, including statistics, predictive modeling, pictures, sounds, and so much more.

Why is generative AI suddenly so popular? Generative AI has been around since 2014. Until the last two years, many companies didn’t have the processing power, storage, or bandwidth to run generative AI algorithms. But now, requests that would have taken hours to process and compute three years ago, now take only several minutes.

Websites running AI can take requests for information like writing an essay for a term paper or creating an image or another product similar to what a human can in a couple of minutes. This change happened slowly over time and has now reached a point where it’s useful.

How are people using generative AI? We see generative AI being used for all sorts of things across the internet these days. People are using it to make artistic profile pictures for social media, or to help with content creation ideation, build stock photos, make music, write, research and much more. One of the most popular ways the general public is using generative AI is to create art. TikTok has several filters built into the app where users can take a photo and then have it edited to a specific artistic style within seconds.

Chatbots like OpenAI ChatGPT can be used to spark ideation and do quick research for somebody writing a paper. Of course, there are practical applications in the real world. Pharma companies can use generative AI to simulate chemical compounds for drug development, while architectural firms could generate building mockups in a matter of seconds.

What are the limitations of generative AI? The widespread use of generative AI in recent months has shown the massive capabilities of the algorithms. However, it’s not without its limitations. Every database needs to be updated, and the source of information from which AI algorithms draw their information is not different. That being said, an AI server can only stay up to date to a certain point.

As of early 2023 ChatGPT, for instance, is limited to information from 2021 and earlier. AI isn’t infallible either, as chatbots can generate incorrect or biased information based on how the algorithm has been built. Because AI can be inaccurate, it’s important that whoever uses is aware of its limitations and thoroughly fact-checks the info.

Generative artificial intelligence has taken a strong hold in both the digital and real world in recent months because of its capabilities. Can generative AI help you break down complex ideas and create lifelike pictures in a matter of minutes? Yes, it can, and it’s a tremendous tool because of it. However, we all need to understand the lines that should be drawn and that there are limitations to what the tool can do.