What is GPT-3?
GPT-3, also known as the Generative Pre-trained Transformer 3, is a neural network machine learning model developed by OpenAI to generate text. Launched in 2020, uses of GPT-3 have disrupted the chatbot industry – it has been trained on internet data with 175 billion parameters, resulting in a deep learning neural network that can produce vast amounts of output texts based on a minimal input text. So, how do you use GPT-3 for an enterprise?
GPT-3 is trained to generate text that is realistic and closer to the text generated by humans themselves. For example, GPT-3 generates articles, poetry, dialogues, news stories, et cetera. It can even summarize large texts and produce codes. This means that it can do any text-related task.
Moreover, GPT-3 is also used for conversational chatbot applications that respond to questions typed in by a user. ChatGPT is a recent example of uses of the GPT-3 application. It has gained immense popularity among the masses for its ability to produce concise and relevant human-like realistic text while answering questions asked by people. Even though it is still in the research phase, this and other applications of GPT-3 have varying use cases for the corporate world.
Enterprise Use Cases of GPT-3
Here are some of the ways enterprises can use GPT-3:
Training New Hires
GPT-3 makes it easier to train new hires as resources. You can prepare notes on the topics you are training them for using the neural network. Other than content, trainees can ask GPT-3 questions regarding their training, customizing the training period to their own queries. This makes the training period more efficient and interactive.
GPT-3 also reduces your dependence on human trainers required during training as it guides them through the process. Therefore, you need fewer human trainers when training with a GPT-3 application.
It makes the recruitment process more manageable as you can use GPT-3 to shortlist candidates and ask them preliminary questions through its question-answering application. It also makes the process smoother, automatic, and streamlined.
GPT-3 is more efficient than most search engines currently being used. This is because it has been primed to retrieve the most relevant information regarding a question. It makes GPT-3 a critical research tool used in the enterprise world for researching new topics, techniques, etc.
GPT-3 has the ability to not only code for you but also read code for you. An example is Code Oracle, the uses of GPT-3 code editor and an in-console tool designed on the Eclipse Theia framework for efficient source code editing. This makes it an essential tool in the enterprise world for developing new software.
Through its chatbot application, GPT-3 can be utilized in the enterprise world to provide customer support to clients without requiring extra human resources. This capability makes a GPT-3 application ideal for customer service functions as the neural network will help answer client queries and resolve or log data regarding their problems efficiently.
You can also use GPT-3 for writing articles, blogs, and general content generation. It can write quality content, similar to humans, due to being trained on internet data regarding varying topics. This is another feature that makes GPT-3 a critical tool for the enterprise world, where companies will no longer have to hire content writers to manage their websites and blogs. You can simply use GPT-3 to come up with top-trending engaging content loved by your users!
GPT-3 is also used to read large amounts of data and generate insights and descriptions about the data that may not be apparent to the human eye. This enables enterprises to evaluate their data and how to use it to grow their business and develop new products.
In our excitement for AI-enabled technologies, we often forget that neural networks like GPT-3 and other such technologies also have limitations.
The most significant limitation is that it suffers from a machine-learning bias. This is because it has been pre-trained on internet data so it can imitate the biases present on the internet in the form of white supremacy, racism, or Islamophobia. It can also pick fake news and regenerate it as a form of accurate information.
Moreover, the use of the GPT-3 neural network is a pre-trained one. This means that learning does not happen dynamically. In case of errors, the neural network does not have long-term memory to learn from. Furthermore, suppose a GPT-3 application does not know the answer to a query. In that case, it will give whatever else it wants as the answer, as opposed to informing you that it doesn’t have the relevant information to answer the question. Thus, it becomes very challenging to control the output.
Given these limitations, one must note that the future depends on learning where to find relevant information that can benefit enterprises rather than rote memorization.
Despite some limitations, GPT-3 has great potential in the enterprise world. You can use it to reduce costs, scale workflows, and automate day-to-day text-related tasks. Moreover, you can employ GPT-3 to enable rapid software delivery by automating the coding process, solving customer problems, and enhancing customer support.
If you need any assistance with developing a GPT-3 application, contact us at [email protected].