Despite being a relatively young technology, there are already plenty generative AI examples making a significant difference to the way people live and work.
Generative AI, which can create new, original content has potential in a wide range of fields, although most people will have encountered online generative AI engines capable of creating text based or graphics based content. But generative AI doesn’t primarily exist for us to go and have fun. It has serious, significant and far-reaching uses across a wide range of industries.
Generative AI is lauded for its potential to help us get work done faster, and achieve more complex outcomes than we might be able to as ‘mere’ humans. But it is also the subject of much discussion around ‘existential threat’ – the potential for AI to go off and make decisions of its own, act on those decisions, and in doing so present a threat to humanity. The debate is exercising national governments, think tanks, international organizations and others.
In the meantime, there are many examples of generative AI finding a place in the world of work - and we have pulled together some of the more interesting use cases.
Generative AI examples
Video generation
Generative AI can be used to help create new videos using existing video content. This can be achieved by combining existing elements under direction from, for example, commands around using particular styles, or the selection of a specific image or set of images.
The speed at which videos can be produced means developers don’t have to concern themselves with the basic construction and can instead focus on tweaks. This also makes it easier to produce multiple examples to showcase options, or experiment with different tones without having to rebuild projects from the ground up.
This technique can be used in all manner of scenarios from computer games to pop videos, movie cartoons and more. Patrick Claire, a filmmaker who has won two Emmys, uses DALL-E 2 in his work.
Image generation
In a similar vein to video generation, generative AI can be used to create images from scratch. The technology is capable of producing sophisticated content that is incredibly useful to creative professions, such as advertising and magazine production, or artists using the technology in their work.
One example where generative AI is beginning to make its mark as an image generator is interior design. The tool InteriorAI has been endorsed by interior designer Isabella Penichet Orsi, who wrote on LinkedIn, “Generative A.I. seeping into interior design with www.interiorai.com. I would highly encourage interior designers to play around with this tool”.
Medicine and healthcare
AI already plays a part in many areas of medicine and healthcare. Examples include drug discovery, diagnosis, research, producing treatment plans, and much more. As generative AI matures and develops, it has the potential to extend the reach of AI across this industry even further.
In records creation, services like those developed by Abridge AI are utilising generative AI to help speed up the creation of medical notes. The company claims its system can save doctors up to two hours per day, on average. The service is being rolled out by the University of Kansas Health System and has the potential to serve over 1,500 physicians across more than 140 locations.
In the pharmaceutical industry, Insilico is one example of an organization using generative AI in the design of drugs. The company specializes in the study of rare diseases that affect small numbers of people, work that would otherwise be stymied by the high costs associated with traditional research and development methods.
Customer services
We are already used to chatbots on web sites, with their ability to answer simple queries like “how do I change my login” or “how do I return an item”.
However, Generative AI introduces a whole new set of use cases, and, importantly for customer-facing organizations, can answer more complex questions quickly without necessarily escalating to a human agent. The AI can search databases of information to produce bespoke responses, and have more conversational interactions with customers than earlier generations of chatbots. This kind of AI can also take a role behind the scenes, helping human customer service agents through its ability to access and synthesise information more quickly.
One of many companies active in the customer service field, Salesforce has outlined its plans for Generative AI, which are wide-ranging, and even include using it in Slack.
