ChatGPT currently enjoys the status of being the latest buzz across the technology world, with the natural language processor garnering a lot of notice. The chatbot provides the ability to carry on a meaningful conversation by answering a host of complex questions. This tool boasts a lot of potential including the ability to generate articles, source code, poetry, and more.
Created by the AI technology research group, OpenAI, ChatGPT is part of a family of other similar generative AI applications. Some even have the capability to generate images, videos, and animation, as well as algorithmically composed music. If ChatGPT isn’t the dominant tool in this emerging generative AI sector, expect other alternatives to fill the void when it comes time to perform tasks. It almost seems like the initial internet search provider market in the 90s.
Needless to say, this area of technology innovation offers much promise for improving productivity in a variety of business sectors. So let’s take a high-level overview of the generative AI application landscape, ChatGPT, and the future of these advancements in the different types of artificial intelligence. In the end, everything from internet searches to automated customer service seems likely to become a lot more conversational. The future Gene Roddenberry and others dreamed about seems closer every day.
Ultimately, ChatGPT might end up being known as the tool that took generative AI from the research lab into the public consciousness. After all, the fact people from all walks of life can interact with the chatbot carries some weight. Like many other generative AI tools, it leverages the GPT machine learning model, however, its specific approach focuses more on powering a conversational chatbot.
Jeremy Roberts, research director at Info-Tech Research Group, commented on OpenAI’s strategy for training the underlying machine learning model used by ChatGPT:
"OpenAI trained its ChatGPT language model using supervised learning and reinforcement learning. This means that the language model was repeatedly trained by a human that demonstrates the desired behavior and then supervises the output produced by the model, reinforcing the learning by ranking outputs based on their quality.”
While a conversational chatbot serves to expose the public at large to the possibilities of generative AI, concrete business use cases are what eventually result in this technology innovation making a real impact in the world. So let’s take a closer look at what the potential future holds.
Not surprisingly, much of the mainstream press on ChatGPT and similar tools focus on a common theme: How robots and computers are going to replace humans while taking their jobs. The reality, however, seems much more nuanced. After all, generative AI offers the potential to serve as an automated assistant, letting humans focus on more value-added tasks or simply boost their productivity level.
For example, a generative AI tool might help developers understand how to properly use a function or object, even providing relevant code samples. This application of artificial intelligence actually makes human programmers more productive, allowing them to accomplish more in the same amount of time. This human element remains critical as it provides the context to recognize any errors in generative AI’s output.
Other intriguing use cases for ChatGPT and other generative AI capabilities also show promise. Many of the potential applications relate to providing some form of support. Let’s take a closer look at a few.
Enterprise Support: Chatbots currently see use in a variety of customer service roles in different business sectors, providing an automated approach that once again allows human representatives to concentrate on more complex tasks. However, these bots tend to be static and frustrating for the people actually needing help. ChatGPT and other generative AI options provide the additional conversational power to make these chatbots much more effective.
Intriguing applications along these lines include an enterprise help desk or other automated technical support functionality. In essence, they end up serving more as an information concierge, a use-case that offers potential in multiple business sectors.
Initial Interaction With Customers: Another potential application for generative AI involves answering questions about a product or service, essentially serving in a pre-sales role. If a potential customer needs more information, they simply speak with an actual sales representative. Similar functionality also makes sense in the staffing industry, as potential candidates can query a chatbot to find out more about a job opening and its requirements.
Other similar natural language use cases involve generating marketing copy for product development or other business functions needing content. Instead of replacing writers, they serve to make them more productive, again illustrating the common theme of generative AI serving as an assistant. Needless to say, the future for this technology remains bright, even when only considering its ability to generate natural language. Expect it to become the next big innovation at the forefront of the current digital transformation in business.
If generative AI provided an idea for a great business application, consider working with the experts at NineTwoThree to turn it into a reality. We boast extensive experience with machine learning and AI, with a robust track record of success partnering with businesses from startups to enterprises. Schedule some time with us to discuss your intriguing idea.
