Generative AI (GenAI) is a subset of artificial intelligence that can generate content including text, images, video and audio in response to user prompts. It’s powerful because of the scale of the data sets on which it’s trained. Tools such as OpenAI’s ChatGPT and Midjourney have made the technology mainstream; it’s now possible for almost anyone to ‘create’ something using generative AI.
For businesses, GenAI can help wherever teams need support in content creation or ideation. This includes creating ideas and content for marketing campaigns or even strategy development. It can also be used in the software development process, helping developers do everything from writing code and testing to understanding legacy codebases.
Generative AI is a type of artificial intelligence that creates ‘new’ content in response to a particular user prompt.
It makes it cheaper and faster to develop ideas and generate new content.
Generative AI gets things wrong. Its response to a prompt may well be false or inaccurate, so it requires human oversight.
Although still a very new technology, it’s being used in software development, design and marketing.
What is it?
Generative AI is a type of artificial intelligence that can, as its name indicates, generate new content. The technology has emerged from innovations in machine learning over the last decade: it has moved mainstream thanks to a number of high-profile and widely-available products. These products are capable of generating visual or text-based outputs (DALL-E and Stable Diffusion are examples of the former, while GPT-4 and ChatGPT the latter).
What’s in it for you?
Generative AI can save you time and money when used effectively. It can also help people become more productive, removing some of the heavy lifting of certain tasks. Trying to come up with new campaign and content ideas for a marketing campaign? Generative AI can generate ideas for you. Want to explore new perspectives on a strategic problem? Generative AI might be the sparring partner you need.
The technology can also enable conversational interfaces that are far more convincing than the chatbots we’ve experienced in the past. This can greatly help in areas like customer support. It also has the potential to change the way internal knowledge is discovered: trained on internal documents and data, GenAI can provide a new way for employees to discover the information they need to do their jobs.
What are the trade offs?
There’s a lot of hype around generative AI right now: it’s important not to get carried away. Don’t waste time and money on GenAI products and initiatives that consumers don’t really want or makes employees’ work more difficult.
It’s also important to note that generative AI can get information wrong (these are what are usually described as ‘hallucinations’). A number of lawyers have found themselves in trouble because the GenAI tools they used generated fake and non-existent cases. They assumed these tools are like search engines — which they aren’t.
There are also important privacy considerations when using generative AI. Many of the tools offering generative AI capabilities are cloud-based — sharing user’s personal information with third parties can be risky.
How is it being used?
Generative AI is being used in a range of areas. This includes software development, where it’s helping engineering teams write code, test more effectively, produce documentation and devise architectural solutions. As mentioned above, it’s also being used by marketers to rapidly generate ideas and copy for campaigns.
One of the most impressive applications of generative AI is in conversational interfaces; the technology can extend their sophistication beyond the chatbots we’ve seen over the last decade. A team of Thoughtworkers, for instance, has used the technology to develop a tool that provides voice-to-voice interaction with government services in India in 11 different languages.
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