Have you heard of ChatGPT? It’s making a lot of waves. People are equal parts scared and excited, and it’s because this represents one of the most obvious advances in artificial intelligence (AI) and language models so far in human history.
What you might not know is that ChatGPT is powered by GPT-3. That’s the sophisticated machine learning tool that runs under the hood, and it’s even more versatile and impressive than GPT, the popular topic of discussion today.
Take a deep dive and see what GPT-3 is all about. You’ll be impressed, and it might be the start of a journey that is empowering to you and your business.
What is GPT-3?
On the surface, there are a few simple ways to think about GPT-3 that can paint a useful picture. GPT-3 is an artificial intelligence that aims to understand and interact with human language. GPT-3 is a natural language processing model that simulates human conversation. GPT-3 is the foundational model that runs Chat-GPT. GPT-3 is an experiment in neural networks and how they can be applied to human languages.
All of these are true, and yet none of them are complete—mostly because GPT-3 is a large, complicated project.
If we want to dive a little deeper into what it really is, GPT stands for Generative Pre-trained Transformer 3. The “3” is there because it’s the third major iteration of the project. Everything else in the name explains that GPT-3 is designed to generate language responses to language prompts based on machine learning.
We’ll get more into how this works in the next section, but a good way to think about it is that GPT-3 is just a very, very intricately designed word generator. A simplistic word generator would either show you the same words every time regardless of your inputs, or it would only be able to string together random words in response to your prompts.
Because GPT-3 has such sophisticated programming running (and access to a vast store of data), it can produce sophisticated responses that really are custom-tailored to whatever you can provide to it with your interactions. As a result, it’s one of the most powerful AI tools in the world right now, especially in terms of language processing AI.
How GPT-3 works
GPT-3 might make more sense if we talk about how it works.
To begin with, it’s an artificial intelligence that runs on neural network designs. Such designs are potentially complicated, but they boil down to a simple enough concept. Any task the AI is supposed to accomplish is broken down into smaller pieces. Each piece can be adjusted up or down, and the AI follows a mathematical formula to figure out the optimal way to operate based on how the task is broken down.
We’ll get into how this specifically works with language in a bit, but there’s another component to neural networks that we should talk about first.
Neural networks can self-adjust based on input and feedback. As a result, they can be trained. If you give such a network enough data, the programming can “learn” a lot and become very effective.
With GPT-3, the AI was more or less tasked with reading the entire internet a few years ago. That’s a simplification of how the data was really inputted and processed, but the point is that GPT-3 was given access to a vast body of information that boggles the human mind. As a result, the neural network is extremely capable.
But, how does a neural network break language into chunks that can then be adjusted according to math? That’s a weird concept to even try to say aloud.
Again, it’s very complicated, but the crux of it is found in what is called natural language processing (NLP). Specifically, many generative text models are transformer-based models.
What does that mean?
The transformer model is able to take any sample of text and break it into parts to try to analyze it. It can look at individual words, phrases, and the entire text as a whole. It puts all of that analysis through the neural network. That’s a network with tons of different individual nodes that compare the text, deconstruct, reconstruct it, and really try to express it in as many different analytical terms and concepts as possible.
Remember, this is all done by a computer (or group of computers), so it's really doing this in terms of 1s and 0s. In other words, the neural network is finding countless different ways to break the text into 1s and 0s, all from the perspective of understanding the language itself.
By breaking language down so completely, the transformer model is genuinely able to reduce talking to mathematical formulas. Those formulas were developed and refined by the massive training that GPT-3 received, and the final result is a model that is able to interact with human language in a way that is adaptive, original, insightful, and broadly useful.
Applications of GPT-3
With all of that technical information covered, let’s explore what this powerful AI can really do.
The most famous application of GPT-3 is Chat-GPT. It’s a specific language AI built out of GPT-3 that tries to provide human-like responses to any prompt. As a result, it’s something that you can actually use to bounce ideas around, explore concepts, shore up your own writing, and more.
Whether using GPT-3 or Chat-GPT, here are just a handful of interesting applications that have already emerged from people interacting with the tools:
- Writing YouTube scripts. Vlog Brothers is a popular YouTube channel, and they posted a video that was written entirely by ChatGPT. The video is interesting and compelling, and unless you’re an avid fan of the YouTube channel, you might not realize that the video was written by AI.
- Creating content. Another YouTube channel, Forever Adventures Library, has spent hours of live-streaming sessions with ChatGPT. In those sessions, the host plays games of DND, creates living, active stories, and a whole lot more.
- Support. GPT-3 is being used to power AI tools that help with customer service as the source of live chat software. Such tools can answer questions about healthcare, help you troubleshoot technical problems, order products, and much more. AI is essentially replacing help-desk employees for the easiest tasks.
There are countless other examples. It’s great at AI in marketing campaigns, business intelligence, CRM strategy, conversational marketing, sales automation, and even more. The real point here is that Generative AI is extremely versatile.
Limitations and concerns
For all that GPT-3 does and all of the ways that it is impressive, it has clear and notable limitations. It’s not perfect, and it’s important to understand the limitations before you lean on it too heavily.
First, the developers have acknowledged that the AI has biases. Not all of those biases are publicly listed, but since the AI was largely developed in Western countries, there are biases that reflect the perspective of the primary developers.
This isn’t to say that GPT-3 or the team was intentionally creating such biases, but the language tools are more adept at English than other languages, and conversations will reveal that the AI was trained more on Western schools of thought than those you might find in other parts of the world.
Acknowledging biases is important, but arguably more important is discussing the accuracy of GPT-3 responses. The language generator is designed to respond to your inputs and try to sound human. If you ask it a question, it will give you an answer (although some specific questions have canned answers). The problem is that it won’t ensure that you get the correct answer or that it is factual. Because of the data it was trained on, it can get answers wrong. This is referred to in the AI community as “Hallucinating”, and can be hard to spot if you don’t know the truth because GPT-3 states the inaccuracies as fact.
GPT-3 was trained by consuming internet content, and you can already see how this creates problems. GPT-3 will answer you with perfect confidence, whether it is right or not. In other words, you can’t trust the information that it gives you, and if you have any type of expertise, you can interact with the AI and quickly see its limitations.
On top of that, GPT-3 is not constantly updated with more information. If you’re probing it for current events or related uses, it will fail. It’s typically completely unaware of any events since 2021, since the model was trained in 2020.
The future of GPT-3
GPT-3 is powerful, but it also has its limits. Considering all of that, what can you expect?
Ultimately, it’s going to revolutionize how computers interact with language. Admittedly, there will be a GPT-4 down the road that does even more revolutionary work, but number 3 is already powerful enough to do so much.
It can help people who struggle with writing to communicate more clearly. It can take over mundane tasks that don’t really require a human touch. It can help spark or develop ideas, organize information, and rapidly speed up tasks that might involve writing, creativity, or typing.
In a few years, everyone reading this might be engaging with GPT-3 (or some comparable AI) on a daily basis.
GPT-3 is a big deal. It’s changing the world, and fast. If you want to jump on the bandwagon and start incorporating it into your own online efforts, you can. Contact Mailchimp today and see how to integrate GPT-3 and any other tools into websites, marketing campaigns, and more.