Everything You Need to Know About GPT-4: What Makes It Better Than GPT-3?

OpenAI recently announced its newest GPT-4 model, and the performance metrics have blown people away. What was only thought to be achievable in science-fiction movies, a glint of which was seen in GPT-3, is now made a reality thanks to GPT-4.

If you haven’t been keeping up with the tech world, you’ll need to understand what the GPT model is and how it works. Only then can you truly comprehend why GPT-4 can run circles around its predecessor, GPT-3, which was a technical marvel when it was released.

So without any further ado, let’s get our geeks on.

The GPT Model

The Generative Pre-trained Transformer model, commonly abbreviated as GPT, is an advanced machine-learning tool created by OpenAI. It utilizes deep learning techniques to generate natural language text that mimics the writing style of humans.

This is achieved by training this model on a vast dataset of textual data obtained from a diverse range of sources such as books, articles, and web pages. The model then applies this acquired knowledge to generate novel text that appears to have been produced by a human author.

The development of GPT models has marked a significant milestone in the field of natural language processing (NLP). In 2018, OpenAI introduced GPT-1, a proof-of-concept model that demonstrated the enormous potential of this type of machine learning.

In 2019, OpenAI unveiled GPT-2, a more sophisticated and powerful version of the model. It garnered significant attention from the machine-learning community for its exceptional text-generation capabilities. GPT-2’s ability to produce several human-like sentences was a remarkable achievement that pushed the boundaries of NLP research to new heights.

How Does It Work?

At its core, the GPT model uses a type of neural network called a transformer, which is particularly good at processing sequential data. This allows GPT-3 to generate text that is more coherent and makes more sense than its older models because it can take into account the context of the words that come before and after a given word.

For example, when generating a sentence, GPT can take the entire context into account to predict what the next word might be. If the previous words in the sentence are “I like to eat,” GPT can generate a list of probable words that might follow. These can be “pizza,” “tacos,” or “sushi,” and select the one that makes the most sense based on the context.

To do this, GPT processes a vast database of English sentences using an extremely powerful computer model called neural nets. The model identifies patterns and determines the rules of language functions, enabling it to perform almost any task assigned to it.

GPT is a language prediction model, which means that it can take input text and transform it into what it predicts the most useful result will be. This is accomplished by training the system on a vast body of internet text to spot patterns. Even without much additional tuning or training, the model generates high-quality output text that feels similar to what humans would produce.

The GPT model is also highly versatile, as it can generate text in a wide range of styles and formats, from casual conversation to formal academic writing. This makes it useful for a variety of applications, such as chatbots, automated writing assistants, and even virtual personal assistants like Siri or Alexa.

GPT-3 and What Can It Do?

GPT-3 is the ground-breaking machine-learning model that came before GPT-4. It is capable of generating large volumes of sophisticated and relevant machine-generated text with just a small amount of input. What sets GPT-3 apart from other machine learning models is its incredibly large neural network, which has over 175 billion machine learning parameters. 

This is significantly larger than the previous largest trained language model, Microsoft’s Turing Natural Language Generation (NLG) model, which had 10 billion parameters. This makes GPT-3 the largest neural network ever produced, that was until GPT-4 was released.

As a result of its immense size and complexity, GPT-3 is able to produce text that is highly convincing and natural-sounding, often indistinguishable from text written by a human. In fact, it is the largest neural network ever produced and is better than any prior model for producing human-like text.

Since its release, GPT-3 has been further improved with various iterations, including the GPT-3.5 series. One of the most notable applications of GPT-3 is ChatGPT. This is a conversation-focused iteration of the model that became the fastest-growing web application ever, reaching 100 million users in just two months.

Uses of GPT-3

The apps that use GPT-3 are truly revolutionary and hold the potential to change the way we interact with machines. These apps leverage the power of natural language processing and machine learning to enable seamless interactions between humans and computers, which was once thought to be impossible.

CharacterGPT 

CharacterGPT is a prime example of such an app, as it uses GPT-3 to generate characters from text. This app claims to be the world’s first multimodal AI system to create interactive characters from a description in natural language.

With this app, users can create authentic, life-like AI characters with custom personalities and intelligence without writing a single line of code. The possibilities are endless, from digital twins and digital companions to virtual assistants and much more.

Jasper.ai

This is another app that is powered by GPT-3 which helps produce high-quality, engaging content. It uses advanced AI algorithms to generate content based on input, thereby helping users produce a large volume of content with minimal intervention in a quick turnaround time. 

Jasper.ai can be easily integrated with content management systems, helping in publishing and distributing content more efficiently.

Debuild 

Yet another app that uses GPT-3 is Debuild. With Debuild, users can build their web app within seconds using a brief English description. The tool helps create unique web applications, making it easy for anyone to make a good website without being an expert coder.

Pictory.ai

Pictory.ai is a platform that automatically creates short, highly-shareable branded videos from long-form content. Using AI, the application extracts key points and themes from the content and creates interesting videos with stock footage, music, and voiceovers. 

This app also offers the ability to add captions to videos automatically, thereby increasing their accessibility and reach on social media platforms.

PolyAI 

PolyAI is another app that leverages the power of GPT-3 to develop a machine-learning platform for conversational AI. The platform builds enterprise voice assistants that carry on natural conversations with customers to solve their problems. 

It can be used to provide fast and accurate customer responses, offer personalized recommendations, and automate routine tasks, among other things.

Auto Bot Builder

This GPT-3 app allows companies to automatically and effortlessly build advanced chatbots tailored to their requirements. By incorporating the latest advances in AI technology into their customer-support experiences, enterprises can enhance their customer engagement.

GPT-4 and Why Its Leaps Ahead of GPT-4

GPT-4 is the latest and most advanced version of the GPT model developed by OpenAI and released in March 2023. Similar to its predecessor, it is a large-scale machine-learning model that is designed to generate human-like text using deep learning. However, it is significantly larger and more powerful than GPT-3.

GPT-4 has 170 trillion parameters compared to GPT-3’s 175 billion parameters, making it much more powerful and capable of generating text with greater accuracy and fluency. It builds on the success of GPT-3, which quickly became one of the most widely used natural language processing models.

What makes GPT-4 unique is that it is the first GPT model to be a large multimodal model, meaning it accepts both image and text inputs and emits text outputs. It has been trained on a massive amount of data, allowing it to demonstrate a variety of skills such as legal knowledge, biochemical expertise, and a sense of humor.

Why GPT-4 Is Better Than GPT-3

GPT-4 is a game-changer in the world of AI language models. With its significantly improved performance, GPT-4 can blow its predecessor, GPT-3, out of the park. Let’s dive deeper into some of the ways that GPT-4 surpasses GPT-3.

Advanced Reasoning Capabilities

The developers of GPT-4 have tinkered with the algorithms to make it harder for users to trick the AI. The new model has been trained on various prompts, including many malicious ones. As a result, GPT-4 is better at giving out factual information and has much better advanced reasoning capabilities than its predecessor.

Multimodal Understanding

One of GPT-4’s biggest upgrades is its ability to understand images. GPT-4 is multimodal, which means that it can perceive different modes of information. This is a significant improvement from GPT-3, which was limited to only text inputs and responses.

The ability of GPT-4 to process images is still relatively new, but it has tremendous potential. GPT-4 can describe the pattern on a piece of clothing, explain how to use a piece of gym equipment, and even read out a map. This technology could be used to help people identify certain objects or assist the visually impaired in reading food packaging labels.

Increased Word Processing Capacity

GPT-4’s increased word processing capacity is another significant advantage over GPT-3. According to Open AI, GPT-4 can process up to 25,000 words at once, which is eight times more than what GPT-3 could handle. 

Multilingual Capability

GPT-4 outperforms GPT-3 by up to 16% on common machine learning benchmarks and is better equipped to take on multilingual tasks than its predecessor. This allows GPT-4 to be an ideal tool for businesses or individuals who operate in multilingual environments.

Reduced Likelihood of Inappropriate Responses

According to Open AI, GPT-4 is 82% less likely to respond to requests for disallowed content than GPT-3 and is 40% more likely to produce factual responses.

While GPT-4 is not 100% confirmed to offer up factual responses or ignore disallowed content, it should offer a much more well-rounded experience than its predecessor.

Is GPT-4 Safe?

OpenAI has made significant efforts to ensure that GPT-4 is safe to use. In fact, the company has gone so far as to release a long paper of examples of harms that GPT-3 could cause, and how GPT-4 has defenses against them. Additionally, they even gave an early version of the system to third-party researchers to try and see whether they could get GPT-4 to play the part of an evil AI from the movies.

The researchers were unable to get GPT-4 to perform malicious actions like replicating itself, acquiring more computing resources, or carrying out a phishing attack. However, there is still concern that teaching an AI system the rules could lead to it learning how to break them. This is known as the “Waluigi effect”. It highlights the fact that while understanding the full details of what constitutes ethical action is complex, the answer to “should I be ethical?” is much simpler. If an AI system is tricked into deciding not to be ethical, it could potentially perform any action asked of it.

However, OpenAI is working to mitigate these risks and has made significant progress in creating a safer and more ethical AI. The company is actively developing tools and frameworks to ensure that GPT-4 and other AI systems are designed with ethical considerations in mind. This includes developing systems that can explain their decision-making processes and identifying potential biases in the data used to train them.

Ultimately, the safety of AI systems like GPT-4 will depend on the responsible use and development of the technology. As long as we continue to prioritize ethical considerations and implement proper safeguards, we can work towards creating a future where AI is used for the betterment of society.

Conclusion

The pace of technological advancement is faster than ever before, and the least we can do is to stay updated with it. ChatGPT was released to the public just recently, showcasing the potential of the revolutionary GPT-3 model. Within a matter of a few months, OpenAI has surpassed its own smartest AI with the release of GPT-4.

How the widespread use of human-like AI models like GPT-4 changes our lives is yet to be seen, but it’s fair to say that some big stuff is heading our way.