Table of contents
ChatGPT is having as big of a moment as when Netscape, iPhone, or AWS launched. It is setting a new paradigm and powering game-changing applications across industries. Some might even say it’s the biggest tech advance of the current generation.
But guess what? We’re still only witnessing the early iterations of ChatGPT!
ChatGPT is built on a large language model called GPT-3.5. It is a model fine-tuned from GPT-3 to create a general-purpose chatbot.
While the response of ChatGPT has been nothing short of sensational, with more than 100 million users in two months, some things could be improved in terms of optimization, accuracy, and safety alignment.
Learn more about how to use ChatGPT and check our 150 ChatGPT prompts that you can simply copy paste to generate crazy content.
This is where GPT-4 comes into play. In this blog, we’ll share what we can expect from GPT-4 and further explore its possible functionality and future direction.
Table Of Contents
What is GPT-4?
GPT-4 is the fourth version of the Generative Pre-trained Transformer or GPT tool. GPT-4 is expected to take a massive leap in capabilities by becoming a multi-modal that accepts both images and text as inputs.
OpenAI believes GPT-4 to be the most capable and aligned model they have trained so far. By training existing parameters extensively at almost the same size as GPT-3.5, OpenAI is expected to raise the bar with GPT-4 in terms of advanced reasoning and contextual response.
Why is GPT-4 a Game Changer
Every model in the GPT evolution has introduced something new, whether task conditioning in GPT-2 or in-context learning in GPT-3. See more about GPT-4 vs GPT-3.
With GPT-4, we’re going to see a whole new dimension of AI-human interaction with images. Plus, the chatbot is going to be incredibly reliable, accurate, and capable of handling hard tasks. And here’s how it’s being achieved:
Emphasis Shifts to Optimization
You might have seen the following image comparing the number of parameters of GPT-3 to the GPT-4 model. Recently, the CEO of OpenAI, Sam Altman, shut down this rumor in an interview with Strictly VC and called it “complete bullshit.”
The emphasis for GPT-4 is not how big the language model will become compared to GPT-3. But rather, the focus is shifted to optimizing the current. This is mainly because the GPT-3 has been only trained once with less precision.
So, for GPT-4, the training will be more extensive across many hyperparameters. As a result, GPT-4 will have more choices or inputs and can tackle complex tasks at scale.
New Visual Input Setting
GPT-4 will be a multi-modal that allows you to input images. Further, GPT-4 can analyze the text within the images and give you the necessary insights based on the prompt.
For example, you can input a sales report and ask for key takeaways. This also applies for programming code, medical records, and many other use-cases across industries.
When it comes to the outputs, GPT-4 will not have image generation capabilities. It will be text-only.
Better Alignment with Human Values
We’ve seen dozens of movies where an AI machine goes rogue and aims to take over the human world. In movies, heroes like Terminator can aid humans, and we’ll get a happy ending.
But, in reality, that’s not the case. As AI models are getting more advanced with them taking our decisions, it’s paramount to make AI safety a top priority. This means improving AI alignment with human values.
When an AI develops an emotional quotient, it can tell right from wrong and make decisions without biases. This is challenging because the training data may present a biased take, and the AI model simply maps its observations to an outcome.
With GPT-4, we will see improvements in AI alignment that will make the multi-modal chatbot better human judges. But it still will have a long way to go to reach true alignment.
Improved Self-Assessment of Prompts
When using ChatGPT, the results will vary vastly when your prompt lacks proper details. So it requires certain expertise for a user to engineer prompts in a way that helps them extract maximum value from the GPT model.
With GPT-4, it will be more robust in understanding prompts. Even if the prompts are not perfect or contain errors, the model can still accurately provide necessary outputs without much repetition.
Computing Costs Remain the Same
So far, OpenAI uses sparse models that allow it to scale large language models without drastically increasing computational requirements. As it won’t be adding more size to its model with GPT-4, it will no longer use sparse models.
Instead, GPT-4 will be based on denser language models. This means the answers from the chatbot will be more accurate. And it will have a better understanding of a user’s behavior and preference.
What Can GPT-4 Do?
The GPT-4 model can solve a plethora of Natural Language Processing (NLP) tasks at higher efficiency and accuracy than previous models. Some of them are given below:
One of the common applications of GPT-4 will be producing text that appears to be human-like. You can leverage it for various uses, like creating content for social media, blogs, and websites. This would be a game-changer for many businesses as scaling content is now a few sentences away. Learn more about how GPT-4 will revolutionize content creation industry.
Long-Form Text Summarization
Summarization is a basic NLP task. But it wasn’t done effectively by previous GPT models. It either used to miss out on important information by repeating the same sentences or produced completely inaccurate information. This is expected to improve with GPT-4 significantly. It is reported that GPT-4 can analyze and generate up to 25,000 words.
GPT-4 can be an excellent support system. It can act as a tutor for students to learn about a subject in a friendly manner. Or it can act as a chatbot designed to answer customer queries perfectly.
Other Potential Uses
GPT-4 can come in handy in many other tasks, such as text completion, text classification, and language translation. As the model becomes more advanced, we may see more advanced applications that leading businesses can widely adopt.
Check out all the use cases of ChatGPT and see how to access GPT-4.
The Potential Benefits of GPT-4
People who integrate GPT models into their daily work or study flow can expect to see massive changes. These changes will mainly translate to three things:
When engaging with a GPT model, you’re effectively automating a task or asking the AI to do the heavy lifting. If this is a repetitive task, you are adding a significant amount of time to your calendar. Some of these tasks can be writing emails, social media captions, and generating replies to comments.
Effective Allocation of Resources
If you’re running a business, you want to generate maximum return on investment. With GPT-4, you can create a situation where most of your resources are spent on high-ROI tasks. For the rest, you can incorporate GPT-4 for automation and have a few supervisors for final reviews. This saves you plenty of time and resources.
Improved User Experience
When searching for answers on the Internet, we usually check 3-4 pages until we find something accurate. With GPT-4, we get a direct answer. And we are not bombarded with ads all over the page. This is for a normal user. If it’s for a business, the response time of chatbots and engagement rate from content will help improve customer experience, resulting in better retention rates.
What Does the Future Hold for GPT-4?
GPT-4 will be another state-of-the-art large language model by OpenAI that will introduce new possibilities and make the entire industry more efficient.
When we look into the future era of GPT-4, we should focus on the near term of 2023 rather than the long term over the next 5-10 years. This is because things can quickly shift course in AI.
Predictions for GPT-4
- OpenAI will commercialize on a large scale: Many believe that OpenAI will make the majority of its revenue through licensing the underlying technology to other companies for creating their own custom chatbots than from the subscription model. Microsoft has already announced this in their plans to incorporate ChatGPT into their product lineup.
- A new race in search begins: Microsoft’s Bing is the first to integrate GPT models into search, initiating a new race in search that Google has dominated for over two decades. We will see Google aggressively build its version of ChatGPT called Bard and compete with Microsoft.
- Uncertainty for online creators skyrockets: With models like GPT-4, we’re essentially discussing disrupting the relationship between the Internet and the end user. So far, search engines have driven traffic to content, generative ad revenue, product sales, and much more. Now that could be significantly impacted as more users rely on GPT-4 models for search. So cracking revenue distribution for original content creators will be crucial moving forward.
- Regulators take notice: 2023 may finally be the year when regulators take notice of the AI disruption. We may see policies slowly forming that give a framework to establish safety and copyright laws for these AI models.
- AI alignment remains unsolved: We mentioned better alignment with human values would be seen in GPT-4 in earlier sections. But we don’t think it will completely solve the problem as we are nowhere close to an AGI.
- False news will be on the rise: One of the negative parts of the parabolic growth of GPT models is that bad actors can spread fake news much faster than before. As it almost speaks like a human, it will be hard to distinguish.
Preparing for GPT-4
AI is not going anywhere. Outside of ChatGPT, we already have many ChatGPT alternatives like ChatSonic, building amazing applications that profoundly impact many businesses. So going against this AI revolution is not wise. Instead, it is better to think of it as a tool that can make your life easier.
The next step would be to leverage the tool to gain a competitive advantage. In business, it can be used for many things beyond automation. The models must be trained to self-diagnose failures and adjust accordingly without delays. At first, the changes will only be incremental but will have a widespread impact on the entire business over time.
On an individual level, it is crucial to develop traits like adaptability and resilience to have a smoother transition to an AI-first world. Further, it is important to modify the way we learn new things. Before the Internet came along, we spent much of our time memorizing. But that disappeared when Google launched. With models like GPT-4, it will change again, and we must adapt.
Imagine if we fought against personal computers. Would we be where we are now? Probably not! AI is the same thing. Evolve with it, and you’ll not be displaced.
The AI revolution led by GPT models like GPT-4 draws attention from all corners of the world. It is the first time humans felt that a machine could replace them, given it’s far from being perfect. With more iterations, the language models will become more advanced and showcase more human-like tendencies.
In the case of GPT-4, we will see a jump in efficiency and performance while not changing the number of parameters in a big way. Understanding context will also vastly improve with GPT-4, making the model conversational for longer periods.
While the large-scale impact of GPT-4 is unknown, it is expected to power search engines like Bing and enable businesses to create custom chatbots. On the retail side, we can see more functionality to be added to paid plans. See more about how to use ChatGPT for business.
The upside of the GPT-4 model for users and businesses is that it saves time and money. For example, content publishers can adopt these GPT models into their tech stack to scale content in an efficient way. Learn more about how to use ChatGPT for content creation.
But, for some industries and professionals, it creates new problems. For example, teachers need tools to detect AI-written content from the original. This is a problem that needs an immediate solution.
Despite the shortcomings and negative impact of GPT models, the future of AI is looking bright. And, when we reach AGI status, we will look back at GPT-4 and say it’s one of the important moments that shaped the AI landscape.