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One of the biggest trends in machine learning today is text generation. AI systems learn by absorbing billions of words from the internet and generate text in response to various prompts. It sounds simple, but these machines can be put to a wide range of tasks – from creating fiction, to writing bad code, to being able to chat with historical figures.
The best-known AI text generator is OpenAI’s GPT-3, which the company recently announced is now used in over 300 different applications, by “tens of thousands” of developers, and producing 4, 5 billion words a day. It’s a parcel robot verbiage. This may be an arbitrary milestone for OpenAI to celebrate, but it’s also a useful indicator of the increasing scale, impact, and business potential of AI text generation.
OpenAI started life as a nonprofit, but for the past few years has been trying to make money with GPT-3 as its first salable product. The company has an exclusive deal with Microsoft that gives the tech giant unique access to the underlying code of the program, but any company can request access to GPT-3’s general API and build services. more.
As OpenAI is keen to advertise, hundreds of companies are now doing it. A startup named Viable uses GPT-3 to analyze customer feedback, identifying “themes, emotions and sentiments from surveys, support tickets, live chat logs, reviews, etc.” “; Fable Studio uses the program to create dialogue for virtual reality experiences; and Algolia uses it to improve its web search products which in turn sells to other clients.
All of this is good news for OpenAI (and Microsoft, whose Azure cloud computing platform powers OpenAI’s technology), but not everyone in the startup arena is enthusiastic. Many analysts have noted the folly of starting a business on technology you don’t actually own. Using GPT-3 to create a startup is ridiculously easy, but it will also be ridiculously easy for your competition. And while there are ways to differentiate your GPT startup through branding and user interface, no business has more to gain from using technology than OpenAI itself.
Another concern with the rise of text generation systems relates to output quality issues. Like many algorithms, text generators have the ability to absorb and amplify harmful biases. They are also often incredibly stupid. When testing a medical chatbot built using GPT-3, the model responded to a “suicidal” patient by encouraging him to kill himself. These problems aren’t insurmountable, but they are certainly worth pointing out in a world where algorithms are already creating wrong arrests, unfair school grades, and skewed medical bills.
As OpenAI’s latest milestone suggests, GPT-3 will just keep talking, and we need to be ready for a world filled with bot-generated chatter.
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