What is Generative AI?

Generative AI (GenAI) is a type of Artificial Intelligence that can create a wide variety of data, such as images, videos, audio, text, and 3D models. It does this by learning patterns from existing data, then using this knowledge to generate new and unique outputs. GenAI is capable of producing highly realistic and complex content that mimics human creativity, making it a valuable tool for many industries such as gaming, entertainment, and product design. Recent breakthroughs in the field, such as GPT (Generative Pre-trained Transformer) and Midjourney, have significantly advanced the capabilities of GenAI. These advancements have opened up new possibilities for using GenAI to solve complex problems, create art, and even assist in scientific research.

The future of generative AI

The incredible depth and ease of ChatGPT spurred widespread adoption of generative AI. To be sure, the speedy adoption of generative AI applications has also demonstrated some of the difficulties in rolling out this technology safely and responsibly. But these early implementation issues have inspired research into better tools for detecting AI-generated text, images and video.

Indeed, the popularity of generative AI tools such as ChatGPT, Midjourney, Stable Diffusion and Bard has also fueled an endless variety of training courses at all levels of expertise. Many are aimed at helping developers create AI applications. Others focus more on business users looking to apply the new technology across the enterprise. At some point, industry and society will also build better tools for tracking the provenance of information to create more trustworthy AI.

Generative AI will continue to evolve, making advancements in translation, drug discovery, anomaly detection and the generation of new content, from text and video to fashion design and music. As good as these new one-off tools are, the most significant impact of generative AI in the future will come from integrating these capabilities directly into the tools we already use.

Grammar checkers, for example, will get better. Design tools will seamlessly embed more useful recommendations directly into our workflows. Training tools will be able to automatically identify best practices in one part of an organization to help train other employees more efficiently. These are just a fraction of the ways generative AI will change what we do in the near-term.

What the impact of generative AI will be in the future is hard to say. But as we continue to harness these tools to automate and augment human tasks, we will inevitably find ourselves having to reevaluate the nature and value of human expertise.