If we’re listing out powerful, game-changing artificial intelligence tools, OpenAI’s GPT-3 certainly makes the list. Released in 2020, the language model became a near instant sensation by performing language tasks previously thought impossible for machines. Some of the most interesting GPT-3 use cases happen in the world of business, interacting every day with consumers whether they know it or not and behaving almost like another employee.
These are our top four most interesting business GPT-3 use cases and what makes them so revolutionary. But first, a quick reminder of just how fascinating the model actually is.
What makes GPT-3 special?
Language is notoriously tricky. Humans often say lots of things besides what they mean—sarcasm, irony, idiom, and slang. Languages can have hundreds, thousands of pitfalls and plenty of space for machines to get our meaning very, very wrong.
It also has a reputation for sounding, well, like a machine. In the tv series The Orville, for example, Isaac is a robotic super intelligence that can’t interpret simple human emotions like love or carry on a conversation comprised of small talk. That won’t work for businesses that need to perform customer service tasks or monitor social media and its language complexities for business mentions.
So far, GPT-3 is the largest trained language model in existence, with 175 billion parameters. As an unsupervised language model, it requires very little input from humans compared to any other model. At the moment, some demonstrably remarkable benchmarks include:
- Writing an entire article (well) from just a title.
- Story writing
- Predicting the last words of sentences using contextual clues
- Solving trivial puzzles
There are still some roadblocks to true understanding. However, it’s one of the closest attempts we’ve had to a truly human-like understanding of language.
GPT-3 use cases in the real world, aka in business
The online world is noisy. Customer service is overwhelmed. Consumers simultaneously want a thoughtful, personalized, white glove experience, and we want it fast. It’s a bit like demanding a five-star, 12-course meal at fast food speeds and convenience—something has to give.
AI can help us nudge closer to that impossible balance. Here’s how it’s already happening.
Relieving the technical debt of legacy code
Legacy code causes serious downtime for companies. A developer writes the code, documents it based on the developer’s own system, and then that developer leaves. Now, new employees have to figure out what’s going on first before they can update or make improvements.
San Francisco-based startup, Replit uses GPT-3 to analyze legacy code and quickly explain what it does in plain, understandable English. The language parameters provide explanations that are understandable and easy to read, reducing the time developers spend trying to sort out codes in the first place. Developers can spend more time creating dynamic online experiences and tools for consumers and less time figuring out what the previous developer meant.
Turning everyone into a writer
Content is another roadblock for many businesses. The speed at which online users consume content often means that companies struggle to produce what’s expected to keep their site at the top of the search. They may not have the team to write what’s necessary or have the time to vet freelancers to help out.
Enter GPT-3. Companies like OthersideAI are leveraging the natural language capabilities to help turn everyone into a writer. Their current product, HyperWrite, is a writing assistant that suggests ideas, words, and sentence completions to help speed up the writing process without sacrificing the quality or interest.
Even further, the company is developing an email generation tool that will write emails automatically. The basic idea—write down a few bullet points for what you want to say, and the model will generate a well-written, fluid email based only on that limited input. Once the tool is refined, businesses could respond to emails more quickly while retaining the polite, deferential tone of excellent customer service.
Improving search and product discovery
An age-old challenge with operating on the internet is helping customers find the products they’re looking for. Right now, search terms still need to hit on an exact match to find the product. GPT-3 is changing search by helping understand the intent of the search terms, not just the concrete meaning.
This could help businesses offer suggestions of real value and uncover what each individual is actually looking for. Instead of turning in hundreds of semi-related product images, for example, the results could narrow to just a handful that offer the most immediate value.
Handling more customer service conversations in real time
Customer service online can be challenging to manage. Agents can get overwhelmed quickly with many different channels, millions of users, and a global clock. Startups like ActiveChat are using GPT-3 to develop chatbots, live chat options, and other conversational AI services to help relieve the burden.
The principle is simple. Most customer service interactions are simple queries such as “what time do you open?” It also includes common problems many new customers might have with a product, onboarding, or easy-to-fix troubleshooting. AI can respond to queries no matter the time of day or night and in multiple target languages. Customers receive nearly instant answers and can more easily resolve challenges, mostly independently but with some assistance.
If a more challenging problem arises, AI can tag in a human agent to resolve the issue. Data gathered from previous interactions passes to the human agent, and they can spend more time with high-touch situations while the machine moves on to another simple inquiry for someone else.
GPT-3 isn’t perfect just yet, but it’s already astonishing
GPT-3 still carries some of the bias and pitfalls that other language and AI models carry, thanks to human inputs. Despite some high-profile test cases, it can still prove too unpredictable to remove humans from the equation entirely. However, it’s one of the most advanced language models available and could help reduce the amount of repetitive and mundane work humans need to do to succeed in business.
We are definitely watching how it unfolds. And we’re curious—have you tested the model yourself? Let us know if you have a GPT-3 use case we should know about.
How to learn more about GPT-3 use cases and business applications
At ODSC West 2022 this November 1st-3rd, we will have a special training session on how to build something cool with GPT-3, “Building a GPT-3 Powered Knowledge Base Bot for Discord” with Steve Tingiris, Managing Director at Dabble Lab. In this workshop, we’re going to build a simple Discord bot that leverages GPT-3 to answer user questions. Generative Pre-trained Transformer 3 (GPT-3) is a highly advanced language model from OpenAI that can generate written text that is virtually indistinguishable from text written by humans. Discord is a chat app, similar to programs like Facebook Messenger, Telegram, Skype, WhatsApp, or Slack. Register for ODSC West now while tickets are still 40% off!