The potential enterprise uses for GPT-3 range from summarising common complaints in customer service logs to helping developers code faster.
Since the GPT-3 natural language model platform was launched last year, it has shown many things it can do. Built by OpenAI, it is part of a new class of models that can be customised to handle a wide variety of use cases — from converting natural language to software code to summarising large amounts of text.
Recently, a sports website enlisted GPT-3 to see if AI could emulate a head coach. The study prompted GPT-3 to generate motivational speeches, handle in-game scenarios, and promote team building. This summer, a theatre production was based on a play written by GPT-3 at the Young Vic theatre in London.
Even the marketing team could use GPT-3’s capability to generate original content for social media or blog posts and engage with fans.
In November, Microsoft announced it will help its customers, which is currently only by-invitation, uncover the capabilities of GPT-3 with the new Azure OpenAI Service.
The public release of GPT-3 comes after one year of limited trials through OpenAI’s API service and specialised integrations with Microsoft’s software development products.
It is the latest offering from its partnership with OpenAI that aims to accelerate breakthroughs in AI, and Microsoft to offer GPT-3 at an affordable price to businesses of different sizes.
Microsoft will also offer Azure OpenAI Service customers new tools to help ensure outputs that the model returns are appropriate for their businesses, and this is expected to expand the market for Microsoft by reducing the technical burden of product teams, especially for small startups.
“We are just in the beginning stages of figuring out what the power and potential of GPT-3 are, which is what makes it so interesting,” said Eric Boyd, Microsoft corporate vice president for Azure AI. “Now we are taking what OpenAI has released and making it available with all the enterprise promises that businesses need to move into production.”
The availability of GPT-3 gives the software giant an opportunity to strengthen its hold on the new business applications in natural language processing.
Although GPT-3 has been publicly available through an API managed by OpenAI, now, through Microsoft Azure, enterprises will be able to run solutions to meet their production needs, including critical security, compliance, performance, reliability and scale requirements, while Microsoft will take care of security, access management, private networking, and data handling protections.
Users can also teach the models to meet specific business needs using their own data. In a process known as “few shot learning,” users only need to show the models a few examples of the kinds of outputs or responses or code they want it to generate.
The potential enterprise uses for GPT-3 range from email composition to text summary, website design, and even software code generation. GPT-3 can also help in summarising common complaints in customer service logs to help developers code faster and generate new content for blog posts.
Meanwhile, OpenAI has removed the waitlist to access its GPT-3 API which means any developer can get started. OpenAI says “tens of thousands” of developers are already taking advantage of powerful AI models through its platform.
However, OpenAI has also been building a number of “safeguards” that have made the company feel comfortable removing the waitlist.
“To ensure API-backed applications are built responsibly, we provide tools and help developers use best practices, so they can bring their applications to production quickly and safely,” wrote OpenAI in a blog post.
“As our systems evolve and we work to improve the capabilities of our safeguards, we expect to continue streamlining the process for developers, refining our usage guidelines, and allowing even more use cases over time.”
OpenAI has improved ‘Playground’ to make it even simpler for researchers to prototype with its models.
The company has also added an example library with dozens of prompts to get developers started. Codex, OpenAI’s new model for translating natural language into code, also makes an appearance.
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