What is Generative AI?

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Generative AI has become one of the hottest topics of 2023 to date – dominating headlines and sparking debate. While it has been around for years now, the latest and impressive capabilities are taking the world of AI by storm, with ChatGPT, DALL-E and Stable Diffusion taking center stage. 

Last year alone, investors bet over $1.37 billion on generative AI through 78 deals. So, what is generative AI? Let’s deep dive into what it is and the impact it is set to have.

Analyzing Generative AI

Generative AI uses Large Language Models (LLMs) and advanced machine learning to create human-like text or imagery, pulling from existing data and experiences to generate new content. As technology’s next big wave, it has the potential to drastically change the way humans perform daily tasks and work across industries, spanning from education, to marketing, journalism and more. 

In particular, Open AI’s ChatGPT release has significantly impacted the world by showing the possibilities of AI through a simple to use prompt-based interface. Within two months of launching, ChatGPT surpassed 100 million users – growing faster than record setting TikTok. Many consumer-based applications have already propagated using ChatGPT and other large language models, causing significant disruption for creative industries. 

Utilizing in Regulated Industries

AI technologies, particularly generative AI, are rapidly changing the way we accelerate design in a variety of fields. It’s hard to predict exactly what’s to come, but we must try to understand these models and the potential challenges that can be associated with implementing them, as they continue to evolve and become further mainstream. 

While tools like ChatGPT are groundbreaking, their outputs are often misleading. When it comes to more regulated sectors, AI-powered tools need to go beyond what existing probabilistic models are capable of. As life sciences and finance companies show more interest in leveraging components of LLMs into their workflows, it’s critical they collaborate with a vendor that takes a data and human-centric approach to implementation. 

Existing LLMs, while causing quite a stir across a variety of industries, are only a precursor of what’s to come.

“Early foundation models like ChatGPT focus on the ability of generative AI to augment creative work, but by 2025, we expect more than 30% — up from zero today — of new drugs and materials to be systematically discovered using generative AI techniquesand that is just one of numerous industry use cases.”

Brian Burke, Research VP for Technology Innovation at Gartner

Yseop’s sole focus is using generative AI for content creation in regulated industries. The automation of content in any regulated document is complex. Yseop is using a combination of generation technologies, called hybrid generation, to deliver the greatest automation value for our customers. Leveraging LLMs in our platform has already started and is proving to be a great technology asset. 

This is the first part of a series of blogs relating to generative AI. In our next article, we will further discuss the use case in regulated industries. To learn more about how Yseop’s AI technologies can help your organization, please contact

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