What Are GPT-3 Chatbots?
GPT-3 chatbots are programmable artificial intelligence applications built on development work by OpenAPI and powered by the GPT-3 language model. Also known as “Generative Pretrained Transformer 3,” the trained language processing software that powers these bots includes more than 175 billion machine learning parameters. The parameters help the GPT-3 bot analyze a communication input (such as a customer support request) and generate an appropriate response.
While building GPT-3 chatbots using a platform like OpenAI’s GPT-3 engine, companies can train the program to engage in human-like written or spoken communication. The advanced application relies on deep learning, NLP, operator tutorials, and a vast knowledge base sourced from an online training data set to generate natural conversation with customers. Python and Twilio’s SMS are common languages and platforms that use GPT-3 technology.
Unlike other simpler bots, GPT-3 bot messaging services can provide an actually helpful response to a customer query. Training the complex language model technology is relatively simple, thanks to its user-friendly application programming interface (API). Setting up the bot to serve a specific purpose (such as customer service) is usually done by the vendor, while the end-user helps with the fine-tuning required for their specific application or business needs.
To train the GPT-3 bot and account for certain “gotchas,” companies can input text into an API tutorial tool. Then, the software will work to create a response based on the information. After a few rounds of training, the GPT-3 bot’s algorithm will use the style, tone, and content of the provided information to generate future responses.
Note that the GPT-3 datasets aren’t updated real-time and can be several years old, so any new developments in a specific industry such as certain phrases or jargon may not be able to be integrated into your workflow unless they are custom coded in.
How Do GPT-3 Chatbots Impact Customer Service?
GPT-3 chatbots can generate conversation that is almost impossible to differentiate from that of live customer service agents (though sometimes it can output some hilarious or scary content). This AI system can, in best cases, resolve support requests without the need for a live customer service agent or other variables.
Additional benefits of incorporating GPT-3 technology into customer service bots include:
1. Improved Communication
GPT-3 chatbots use deep learning to consume nearly 500 billion words and numbers. Companies can then tailor the bots’ responses using GPT-3’s streamlined API. The language model can analyze and respond to customer questions, use predictive technology to anticipate client needs, and provide self-service resources that suit the context of the conversation.
In addition, GPT-3-powered instant messaging apps allow users to connect instantly with “someone,” reducing lag time and theoretically improving customer satisfaction. The bots can also gather pertinent information before escalating concerns to live agents, allowing customer service associates to prioritize requests and reducing support costs by 30% or more.
2. Enhanced Support for Customer Service Agents (the preferred option)
Programmable GPT-3 chatbots can help answer customer questions and direct clients toward helpful resources. However, live agents are still a necessary aspect of most company’s customer service departments and not even the best chatbots can prevent it.
GPT-3 bots can help support customer service departments by clarifying customer requests, escalating issues to a suitable channel, querying CRM libraries and product listing databases and presenting relevant solutions for the customer service agent to relay, and storing past interactions to ensure personalized assistance.
3. Increased Customer Satisfaction
In a study conducted by Uberall, 80% of customers admitted that they have had a positive experience with AI-powered bots. The technology works on several layers to increase user satisfaction. From instant responses to more efficient solutions, the increasingly popular virtual technology is becoming key in certain areas for Internet-based customer service departments worldwide.
How Do GPT-3 Chatbots Work?
Enhancing automated instant messaging services with GPT-3 technology provides the tools to analyze and understand customer queries and carry on a human-like conversation. GPT-3 adds an instant boost of contextual understanding and pattern recognition to scripted bots. Because of this, bots can instantly identify a change in conversational context and access new information to generate a response.
The actions that power the GPT-3 language model can be found in the software package’s name: Generative Pretrained Tranformer. Generative language models use statistics to predict — or generate — an output based on a specific digital input, such as a user’s question.
The pre-trained technology makes it easy for customer service departments to launch it quickly without needing their own AI and ML resources. The transformational aspects of the application can identify a keyword in a phrase, determine how often the words occur together, and then use the prediction to generate an appropriate, human-like answer.
Perhaps most importantly, GPT-3 technology can determine context and meaning from both structured and unstructured interactions. As a result, it can create knowledge graphs that improve chatbot responses, and it can then expand the knowledge graphs.
GPT-3 Chatbots for Customer Service
While GPT-3 technology has yet to become as widely adopted as the regular chatbot that’s commonly seen on websites, smartphones and computers, the flexible language model and user-friendly API have the potential to revolutionize AI-powered customer support. GPT-3 bots can analyze, understand, and respond to customer questions; predict needs based on a single word; and enhance their human-like responses with every interaction. And it’s only getting better as time goes on. By leveraging the advanced power of GPT-3, companies can improve customer support while reducing costs.