Within weeks of its launch, OpenAI‘s ChatGPT triggered a new global race in artificial intelligence. The chatbot is part of a fresh wave of so-called generative AI—sophisticated systems that produce content from text to images—that is set to be one of the most disruptive forces in a decade to Big Tech, industries and the future of work.

Microsoft Corp. has added the technology to its products, including search engine Bing, while competitors Google and Baidu are pushing to launch similar tools. Despite its sudden burst in popularity, the technology currently has serious limitations and potential risks that include spewing misinformation and infringing on intellectual property.

Here’s what to know.

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ChatGPT is an artificial-intelligence chatbot developed by San Francisco-based AI research company OpenAI. Released in November 2022, it can have conversations on topics from history to philosophy, generate lyrics in the style of Taylor Swift or Billy Joel, and suggest edits to computer programming code.

ChatGPT is trained on a vast compilation of articles, websites and social-media posts scraped from the internet as well as real-time conversations—primarily in English—with human contractors hired by OpenAI. It learns to mimic the grammar and structure of the writing and reflects frequently-used phrases.

The chatbot isn’t always accurate: its sources aren’t fact-checked, and it relies on human feedback to improve its accuracy.

OpenAI developed ChatGPT as part of a strategy to build AI software that will help the company turn a profit. In January, Microsoft, its strategic partner, unveiled a fresh multibillion-dollar investment in OpenAI and said it plans to infuse ChatGPT into its Bing search app and other products.

The technology that underlies ChatGPT is referenced in the second half of its name, GPT, which stands for Generative Pre-trained Transformer. Transformers are specialized algorithms for finding long-range patterns in sequences of data. A transformer learns to predict not just the next word in a sentence but also the next sentence in a paragraph and the next paragraph in an essay. This is what allows it to stay on topic for long stretches of text.

Because a transformer requires a massive amount of data, it is trained in two stages: first, it is pretrained on generic data, which is easier to gather in large volumes, and then it is fine-tuned on tailored data for the specific task it is meant to perform. ChatGPT was pretrained on a vast repository of online text to learn the rules and structure of language; it was fine-tuned on dialogue transcripts to learn the characteristics of a conversation.

Developed by researchers at Alphabet Inc.’s Google in 2017, transformers have since become pervasive across dozens of technologies. Google uses them in its new experimental service Bard, which gives users conversational answers to their search queries. Chinese tech giant Baidu is using them to develop its own ChatGPT to integrate into its search engine by March.

Transformers, which can be trained on images or images and captions simultaneously, are also the basis of image-generation software systems such as OpenAI’s Dall-E 2 and Stability.ai‘s Stable Diffusion.

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The message "at capacity" means OpenAI’s servers are overwhelmed with requests and can’t handle new ones right now. Try again later. An OpenAI spokesperson said the company has been working to expand server capacity to meet the unexpected demand.

ChatGPT is free. OpenAI released the chatbot as a research preview and users can try it through a dedicated website. On Feb. 1, OpenAI also launched a premium version for $20 a month, starting in the U.S., that will give subscribers priority access.

Both Microsoft and OpenAI plan to release an API, or application programming interface, allowing companies to integrate the technology into their products or back-end solutions. Microsoft’s API will be available through its Azure cloud-computing platform. Both companies already offer OpenAI’s earlier AI technologies.

Media companies including BuzzFeed and the publisher of Sports Illustrated have announced plans to generate content such as quizzes and articles with ChatGPT. Some schools have blocked access to the service on their networks to stave off cheating, while others are actively encouraging students to use the tools ethically.

Keep in mind that OpenAI has access to your inputs and outputs for ChatGPT and its employees and contractors may read them as part of improving the service. Avoid providing private data or sensitive company information.

Other generative AI technologies such as Dall-E 2 and avatar-generator Lensa have become popular with internet users for producing fantastical images and illustrations, and are finding use among independent writers to create artwork for their articles.

AI chatbots and other generative AI programs are mirrors to the data they consume. They regurgitate and remix what they are fed to both great effect and great failure. Transformer-based AI program failures are particularly difficult to predict and control because the programs rely on such vast quantities of data that it is almost impossible for the developers to grasp what that data contains.

ChatGPT, for example, will sometimes answer prompts correctly on topics where it ingested high-quality sources and frequently conversed with its human trainers. It will spew nonsense on topics that contain a lot of misinformation on the internet, such as conspiracy theories, and in non-English languages, such as Chinese.

Some artists have also said that AI image generators plagiarize their artwork and threaten their livelihoods, while software engineers have said that code generators rip large chunks of their code.

For the same reasons, ChatGPT and other text generators can spit out racist and sexist outputs. OpenAI says it uses humans to continually refine the chatbot’s outputs to limit these mishaps. It also uses content-moderation filters to restrict ChatGPT’s responses and avoid politically controversial or unsavory topics.

Ridding the underlying technology of bias—which has for years been a recurring problem, including for an infamous Microsoft chatbot in 2016 known as Tay—remains an unsolved problem and a hot area of research.

"ChatGPT is incredibly limited, but good enough at some things to create a misleading impression of greatness," tweeted OpenAI Chief Executive Sam Altman shortly after the chatbot’s release, adding that it is "a mistake to be relying on it for anything important right now."

Microsoft is OpenAI’s largest investor and exclusively licenses its technologies. The tech giant invested $1 billion into the AI startup in 2019, an undisclosed amount in 2021 and an additional amount of up to $10 billion in January, according to people familiar with the latest deal. Under the agreement, Microsoft can use OpenAI’s research advancements, including GPT-3 and ChatGPT, to create new or enhance existing products. It is the only company outside of OpenAI that can provide an API for these technologies.

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As with every wave of automation technologies, the latest will likely have a significant impact on jobs and the future of work. Whereas blue-collar workers bore the brunt of earlier waves, generative AI will likely have a greater effect on white-collar professions. A 2019 study from the Brookings Institution found that AI would most affect jobs such as marketing specialists, financial advisers and computer programmers.

Those effects will be mixed. Economists who study automation have found that three things tend to happen: some workers improve their productivity, some jobs are automated or consolidated, and new jobs that didn’t previously exist are also created.

The final scorecard is difficult to predict. In company-level studies of automation, researchers have found that some companies that adopt automation may increase their productivity and ultimately hire more workers over time. But those workers can experience wage deflation and fewer career growth opportunities.

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Newly created jobs often go one of two ways: they either require more skill, or a lot less, than the work that was automated. Self-driving cars, for example, create new demand for highly skilled engineers but also for low-skilled safety drivers, who sit in the driver’s seat to babysit the vehicle.