Generative AI has quickly emerged as a leading trend – impacting the way humans perform tasks and work across industries. According to McKinsey & Company, generative AI’s impact on productivity has the potential to add trillions of dollars to the global economy. As generative AI technologies continue to evolve, it’s important to understand the best ways to implement these models. In this blog post, we’ll address a commonly asked question: how does generative AI work?
Background on Generative AI
While generative AI has been widely discussed recently, it is not necessarily new. It was first introduced in chatbots in the 1960s. In 2014, the introduction of generative adversarial networks (GANs) demonstrated generative AI’s ability to create images and videos. For additional context, generative AI is a type of technology that uses Large Language Models (LLMs) and advanced machine learning (ML) to create human-like text, audio or imagery. Further, generative AI pulls from existing data and experiences to generate new content. Benefits of generative AI include:
- Generating content at lightning speed
- Simplifying processes across industries
- Eliminating weeks of rigorous work
- Allocating time to focus on more strategic tasks
Additionally, a recent mainstream example of a generative AI interface is ChatGPT. While ChatGPT has gained traction for its innovative capabilities, its outputs are built on predictive engines and often produce false information due to lacking the ability to make sense of each word’s meaning. As it’s not a reliable or secure option, highly-regulated industries in particular should evaluate generative AI technologies carefully.
Implementing Generative AI in Regulated Sectors
When deploying generative AI technologies in regulated industries, a data and human-centric approach to amplify human abilities is key. With that, training models using LLM and symbolic AI is important to achieve reliable results.
Yseop is hyper focused on using generative AI for content creation in regulated industries. For instance, Yseop Copilot is a powerful automation tool that uses LLM for content generation hosted in a fully secure environment and is reimagining the future of work for regulated industries. Yseop leverages a variety of data-to-text (symbolic AI) and text-to-text (pre-trained open source LLM) techniques for cohesive and intelligent content automation processes.
Yseop’s products are designed to be copilots to not only increase efficiency, but make work more enjoyable and fair. To learn more about how Yseop’s generative AI solutions can accelerate your business, please contact email@example.com. If interested in further exploring Yseop Copilot, start your free automated content generation trial here.