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A Basic Understanding of Generative AI: ChatGPT, DALL-E, & More

In late 2022, OpenAI, an American artificial intelligence research laboratory, unleashed a revolutionary Generative AI language model upon the world: ChatGPT. This digital beast took the world by storm. Soon enough, every other newsfeed headline began mentioning other Generative AI tools such as DALL-E, Midjourney, Synthesia, Stable Diffusion, and more.

These tools grew in popularity due to their accessibility, as users can access them for research purposes at no cost. In a flash, our world transformed right before our eyes. From music to literature, art to coding, Generative AI is disrupting the digital landscape, and we’re just beginning to scratch the surface of its potential.
What is Generative AI, anyway?

Generative artificial intelligence refers to algorithms that can produce unique and original content, as opposed to examining pre-existing data.

Although traditional AI is frequently used to build machines capable of performing tasks that normally require human intelligence, Generative AI goes a step further by enabling machines to create innovative content based on what they have learned. This type of AI can produce a wide variety of content types, such as images, text, music, computer code, and visual models.

How does Generative AI work?

It’s simple, really. Generative AI tools utilize a technique called “deep learning” to recognize patterns in data, which is essentially equivalent to “trial and error.”

Here’s an example:

Let’s say you are a highly experienced graphic designer with a distinct design style that you have developed over the course of 10 years, and you want to utilize Generative AI to create five graphic designs that match your unique style.

The process would be broken down into four steps:

Step 1: You, as the graphic designer, feed the computer your previous work that encapsulates your distinctive style. This work will serve as training data for the computer.

Step 2: The computer starts learning and recognizing your design style, including how you use lines, shapes, colors, textures, typography, space, and images. Then, the computer begins to identify and categorize the patterns of your work.

Step 3: The computer then familiarizes itself with the common features of your graphic design style and trains its “brain” to better recognize those features.

Step 4: In a quick and iterative process, the computer analyzes and learns every aspect of your design work. From there, the computer is able to produce designs that mimic your previous work in the same distinctive style.

Embracing the Power of Generative AI

The emergence of Generative AI is poised to transform our world and unlock a plethora of new capabilities. With this technological breakthrough on the horizon, now is an incredibly thrilling time to delve into its potential.

At eClerx, our objective is to support clients in navigating this new terrain and exploiting the potential of Generative AI to enhance business performance and achieve a competitive advantage. Let’s embark on this journey toward the future together and discover all that it has to offer.

To better understand Generative AI, its implementation, and how it can provide a competitive advantage for your business, we invite you to read our white paper Navigating the Age of ChatGPT & Generative Artificial Intelligence: A Definitive Guide to Thriving with AI in Business & Life.

You can access the white paper here.

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