Unless you just arrived from Mars, you must have heard or seen how OpenAI’s latest innovation ChatGPT has taken the world by storm. The conversational AI chatbot can do almost anything from writing essays, conversing in human-like tones, and even writing code.
But what makes it tick? How is it even possible for it to do what it does? And what does its emergence mean for natural language processing and other industries?
Let’s look into all of that.
What Is ChatGPT?
ChatGPT (Generative Pretrained Transformer), or simply ChatGPT, is a language model developed by OpenAI that uses deep learning algorithms to generate text.
ChatGPT was trained on a large corpus of text data and can generate text in response to prompts, complete text snippets, or answer questions. You can also fine-tune it for specific use cases, such as customer service or content creation, by training it on a smaller, specialized dataset.
The language model is designed for natural language processing tasks, such as text generation, language translation, and question answering. It has widespread use in chatbots, virtual assistants, and other AI-powered applications.
So how does it work?
How Does ChatGPT Work?
ChatGPT, being an AI, means it has to work with data. And large amounts of data. The model is trained with large text datasets that allow it to learn patterns and relationships between words and phrases.
It consists of a transformer architecture and a neural network that processes sequential data, such as text.
The transformer takes in a sequence of words as input. It uses self-attention mechanisms to weigh the importance of each word in the series when making predictions.
During training, trainers feed ChatGPT a massive amount of text data and adjust its weights to predict the next word in a sequence with high accuracy. Once trained, the model is helpful for various natural language processing tasks, such as text generation, language translation, and answering questions.
When a user inputs a text prompt into ChatGPT, the model uses its understanding of the relationships between words to generate a response. The model uses the self-attention mechanism to weigh the words in the input and generate a text output that is contextually relevant and coherent.
Here is an example: Let’s ask ChatGPT to define a language model:
The model scrapes the internet for information on the topic and offers a relevant answer.
How Does ChatGPT Fare vs. Other Language Models?
As an AI language model, ChatGPT is a state-of-the-art natural language processing (NLP) model. It is a transformer-based model trained on a large corpus of text data, making it one of the most advanced language models available.
ChatGPT is part of the GPT family of models, which includes GPT-1, GPT-2, and GPT-3, each with increasing size and complexity. GPT-3, the largest model in the series, is one of the most advanced language models available today, capable of generating human-like text and performing a wide range of NLP tasks.
While there are other advanced language models, ChatGPT has performed well on various NLP tasks, including language generation, question answering, and sentiment analysis. The ability to generate high-quality text has made ChatGPT a popular choice for chatbots, virtual assistants, and other conversational interfaces.
However, it’s worth noting that different language models are better suited for different tasks. Also, many factors can affect performance, including the training data’s size and quality, the model architecture’s complexity, and the specific task. So, while ChatGPT is a powerful and versatile language model, it may not always be the best choice for every NLP task.
ChatGPT vs. Google Bard
Such was the popularity of ChatGPT that Google, the search market leader, had to respond with Bard. Bard is supposed to be Google’s answer to Open AI’s sensational ChatGPT.
How do they compare, though? Both are highly advanced language models, but they have some essential differences.
Bard is a language model Google developed and designed specifically for creative writing. Unlike other language models trained on large, diverse text datasets, Bard has received training on a narrower data set. Such data includes poetry, scripts, and other forms of creative writing.
In contrast, ChatGPT is a general-purpose language model. It grew on a much larger and more diverse text corpus, including everything from news articles to social media posts and scientific papers.
Because of its focus on creative writing, Bard may be better for tasks such as generating poetry or writing scripts. ChatGPT may work best for tasks requiring more general knowledge or conversational ability. An example of such is answering questions or carrying on a conversation.
The specific architectures and training techniques used to develop these models will also likely differ. That can affect their performance on different tasks. Both models are state-of-the-art and can generate high-quality text. However, their training data and design differences mean they will likely excel in different areas.
What Are the Limitations of ChatGPT Technology?
As everything technology gives, ChatGPT isn’t without its limitations. Some might only because the technology is in its nascent stages. Teething problems are a must with any technology, as you might remember.
Here are the main sticking points when using ChatGPT:
ChatGPT Shows a Gripping Lack of Common Sense
ChatGPT does not have common sense. It may generate responses that seem illogical or irrelevant in specific contexts. For instance, it may not understand jokes or sarcasm, leading to inaccurate or inappropriate responses.
Check this out:
One day, a hen and an elephant were having a chat. The hen said, “I can lay an egg every day, but you can’t do that!” The elephant replied, “That’s true, but I can produce a poop the size of your egg every day!” The hen thought for a moment and said, “Well, I guess you’ve got me there.”
While ChatGPT got the elephant and pooping context right, it was wrong regarding the size. An elephant’s poop is about 18kg. The largest eggs only range between 63 and 72.99 grams!
Inability to Grasp Context
While ChatGPT can understand the words and grammar of a sentence, it may struggle to understand its context. This can result in inaccurate or misleading responses, especially when the context is critical to understanding the meaning of a statement.
ChatGPT Has a Limited Reasoning Ability
Though ChatGPT can recognize patterns in large amounts of data, it lacks the reasoning ability of humans. It may struggle to solve complex problems requiring high logical thinking or creativity.
Here is an example:
ChatGPT Can Produce Biased Output
This is a potential concern for all AI language models. The data each of them receives in training determine their output. If the data is biased, the responses ChatGPT generates may also be biased.
That can lead to unfair or discriminatory responses, especially in sensitive areas such as gender, race, and religion.
Little Emotional Connection
ChatGPT is incapable of forming emotional connections with humans as it is an artificial system. ChatGPT technology cannot empathize or build rapport with users in the same way as a human could.
Some people will say it tries its best. But some responses are robotic and less likely to help form emotional connections with humans. Ultimately, it’s only a robot. You don’t expect it to be as emotionally dynamic as a human would in a conversation.
Despite these limitations, ChatGPT and other language models have made significant progress in recent years and are becoming more advanced daily. Many of these limitations will likely reduce as researchers continue improving the technology.
That will make language models even more valuable tools for various applications.
What ChatGPT Means for Search Engines
If you’ve been keeping up with ChatGPT news, you know Microsoft integrated the technology into its search engine, Bing. That integration forced Goggle to fast-track its AI development and come up with Bard.
The introduction of Bard had ramifications on Alphabet Inc’s value, wiping off nearly $100 billion on the market cap of Google’s parent company. That was after Google showed an error Google Bard made. The AI wars have sparked fears it could end content marketing as we know it. If Bard and ChatGPT can give precise answers, traffic for informational topics on different websites will suffer.
Search engines will become better at answering user queries. It could even elevate the quality of the content on blogs.
However, since it’s only early days, the extent to which these changes will take hold is anyone’s guess. However, with more improvements to ChatGPT technology, you bet more things will change.
This is the AI revolution. We will either have to accept it or ship it out.