GPT-4 vs. GPT-3.5: Unveiling the Evolution of AI-Language Model

In our in-depth comparison, discover the differences between GPT-4 and GPT -3.5. Explore how GPT-4's enhanced features are transforming the world of artificial intelligence.

GPT-3.5 has been upgraded to GPT-4 with a host of new features including the capability to understand images, which wasn't possible with the previous version.

Phewww! We were just getting off the hangover from ChatGPT and exploring its endless possibilities, and now GPT-4 is here. Yes, OpenAI has announced the arrival of its next-generation AI language model, an upgrade from GPT-3.5 and the rest of its predecessors.

ChatGPT which was launched in November 2022, was based on OpenAI's GPT-3.5 big language model family and had been fine-tuned (a transfer learning method) using both supervised and reinforcement learning techniques. It had been creating quite a buzz in multiple domains including but not limited to software development, digital marketing, business analysis, and so on.

And now, GPT-3.5 has been upgraded to GPT-4 with a host of new features including the capability to understand images, which was not possible with GPT-3.5. This newest Artificial Intelligence model was launched and integrated into ChatGPT on March 14th, 2023 and since then people are going gaga over the large language model.

And so we decided to explore what’s new in GPT-4 and what makes it different from its previous versions and put all of that information in this article for you.

Stay tuned till the end to know how GPT-4 can take you to the next level.

Introduction to GPT-4

It is the fourth generation of OpenAI's GPT (Generative Pre-trained Transformer) series of language models. In terms of capabilities and features, it is intended to outperform its predecessors, GPT-3 and GPT-3.5

GPT-4's increased size and power is one of its most notable advancements. This means it will be able to generate more logical and nuanced responses, better understand context and nuances in language, and execute a broader range of language-related tasks with greater accuracy. (evident by the fact that it passes a simulated bar exam with a score in the top 10% of test takers, whereas GPT-3.5 scored in the bottom 10%.)

GPT-4's capacity to reason and absorb knowledge better is another new feature, with the ability to accomplish common sense activities, answer questions, and even produce code.

Yes, it does have a similar limitation as GPT-3.5 for it has only been trained on datasets up till September 2021, and it doesn’t learn from experience either.

In summary, GPT-4 can be seen as the next big step in natural language processing and AI, delivering increased power, accuracy, and understanding of language and information, and paving the way for new and exciting applications in a variety of sectors.

With that being said, let’s delve deeper into the different features and factors that make GPT-4 different from its ancestors:

#1 - GPT-4 can process visual data/images

This is truly pathbreaking.

Because of its excellent multi-modal learning capabilities, GPT-4 is predicted to be able to interpret both text and images. This means that the model will be able to generate text descriptions of images, analyze their content, and generate images based on those written descriptions.

It will accomplish this by combining advanced machine learning algorithms capable of learning from both text and picture data sources at the same time. It will be able to discern patterns and correlations between the two modalities after training on large-scale datasets of images and text.

Case in point: The New York Times mentions one demonstration in which GPT-4 is shown the inside of a refrigerator and asked what meals may be made with the supplies. It generates a few examples, both savoury and sweet, based on the image. But, one of these choices — a wrap — calls for a component that doesn't seem to be present: a tortilla.

In another demo streamed by OpenAI, they showed how GPT-4 can create the code for a website off of a hand-drawn sketch. (Watch the video below for reference). Though, this sort of functionality isn’t entirely unique (many other apps do offer basic object recognition like Apple’s magnifier app), the parent company OpenAI claims GPT-4 to “generate the same level of context and understanding as a human volunteer”.

Where you can access GPT-4’s text input capability via ChatGPT and the API, OpenAI is collaborating with the startup Be My Eyes to prepare the image input capability on a wider scale. The startup uses object recognition and human volunteers to assist patients with visual impairment.

#2- GPT-4 has an improved performance

The distinction between GPT-3.5 and GPT-4 can be slight in conversational discourse. But, as the task's complexity reaches a certain level, GPT-4 becomes more trustworthy, innovative, and capable of handling far more sophisticated instructions than GPT-3.5.

GPT-4 models, as expected, outperform GPT-3.5 models in terms of factual correctness of answers. GPT-4 scored 40% higher than GPT-3.5 on OpenAI's internal factual performance benchmark, reducing the amount of "hallucinations" in which the model produces factual or logical errors.

In addition to its superior factual correctness, GPT-4's enhanced ability to minimise "hallucinations" significantly reduces response errors and inaccuracies. This improved accuracy makes GPT-4 a more reliable choice for various applications that require precise information.

#3- Steerability

The capacity of an AI language model, such as GPT, to control or affect its output depending on user-specified inputs or prompts is referred to as steerability. This means that the model can be directed to produce output that matches a specific style, tone, or topic.

Steerability in AI language models like GPT is an essential feature that empowers users to customise the model's responses to suit various applications. It allows for a tailored interaction experience by controlling the model's tone, style, and behaviour. This feature is particularly valuable for developers and businesses creating conversational agents with specific personalities and communication styles.

If a user wanted to generate text with a positive attitude, they may supply a positive word or phrase as a prompt, and the model would generate text with a more likely positive tone.

OpenAI claims that they have been working on defining AI behavior, including steerability.

Instead of the traditional ChatGPT personality with a defined verbosity, tone, and style, developers can now specify their AI's style and task by specifying such directions in the "system" message.

Try prompts like “You are a talkative DSA expert” or “You are an incisive DSA expert” in the system message and see how it explains DSA differently to you.

Further information on creating amazing prompts for GPT models may be found here.

“We will continue to enhance this (we know that system messages are the easiest method to "jailbreak" the current model, i.e., adherence to the boundaries is not flawless), but we invite you to try it out and let us know what you think.”

Here’s one sample:

#4- It's better at playing with language

OpenAI co-founder Greg Brockman asked GPT-4 to summarise a part of a blog article using just words beginning with "g" during a company demo. (He later requested that it does the same with "a" and "q.")

"We had success with 4, but never really got there with 3.5," Brockman explained before beginning the demo.

In the video, GPT-4 responds with a relatively intelligible statement that contains only one word that does not begin with the letter "g" — and gets it totally correct after Brockman instructs it to correct itself. Meanwhile, GPT-3.5 did not appear to try to follow the prompt.

#5- GPT-4 can ace tests

One of the most notable metrics in OpenAI's technical report on GPT-4 was its performance on a variety of standardized tests, including BAR, LSAT, GRE, a number of AP modules, and — for some inexplicable but amusing reason — the Introductory, Certified, and Advanced Sommelier courses offered by the Court of Master Sommeliers (theory only).

Chat GPT-4 showcased its capacity to excel in tasks requiring critical thinking and domain-specific knowledge in these tests. Its impressive performance across various assessments underscores its potential utility in educational and professional settings.

This is a comparison of GPT-4 and GPT-3.5 scores on some of these tests. It should be noted that GPT-4 is now quite consistent in acing many AP modules, but suffers with ones that need more creativity(i.e., English Language and English Literature exams).

It's an outstanding performance, especially when compared to previous AI systems, but understanding it also needs some context.

On Twitter, programmer and writer Joshua Levy described the logical error that many fall into when looking at these results: “That software can pass a test designed for humans does not imply it has the same abilities as humans who pass the same test.”

#6- It can process more text

The quantity of text AI language models can maintain in their short-term memory (that is, the text included in both a user's question and the system's answer) has always been a limitation. But, OpenAI has significantly improved these capabilities for GPT-4. The system can now process entire scientific articles and novels in a single pass, enabling it to answer more complex questions and connect more details in every given inquiry.

It's worth mentioning that GPT-4 does not have a character or word count per se, but instead measures input and output in "tokens." This tokenization procedure is somewhat difficult, but you should know that a token is typically four characters long and that 75 words generally take up 100 tokens.

GPT-3.5-turbo can employ a maximum of 4,000 tokens in every given query, which corresponds to little more than 3,000 words. In comparison, GPT-4 can analyze approximately 32,000 tokens, which equates to approximately 25,000 words, according to OpenAI.

The business claims it's "currently tuning" for longer contexts, but the higher limit means the model should open up previously inaccessible use cases.

Early adopters of GPT-4

Since the new AI language model has been launched, there’s seemingly a race going on between several businesses to adopt and better leverage it.

With its advanced capabilities and the ability to process images, Chat GPT-4 has sparked significant interest among businesses seeking to enhance their communication and problem-solving capabilities. This competition underscores the growing importance of AI language models in various industries.

• Microsoft has confirmed that Bing Talk, their co-developed chatbot platform with OpenAI, is running on GPT-4.
  
• Other early adopters of GPT-4 include Stripe, which is using it to scan business websites and send a summary to customer care workers.
  
• Duolingo has created a new language learning membership tier called GPT-4.
  
• Morgan Stanley is developing a GPT-4-powered system that retrieves data from corporate papers and provides it to financial analysts.
  
• In addition, Khan Academy is using GPT-4 to create an automated tutor.

If these companies are ready to rely on the GPT model, does that mean it’s perfect?

While Chat GPT-4 brings significant advancements to the field of language models, it's essential to acknowledge its limitations. OpenAI CEO Greg Brockman emphasises that Chat GPT-4, like its predecessors, can still generate errors, make reasoning mistakes, and provide inaccurate information. Therefore, while it offers impressive capabilities, users should exercise caution and not consider it infallible.

Limitations of GPT-4

Well, not really. We have already talked about the mistakes in the earlier ChatGPT version in our previous blog here. It’s also important to note that even GPT-4 isn’t absolutely free from errors.

GPT-4 can also be confidently incorrect in its predictions, failing to double-check work when it is likely to make an error.

As seen in the case of Microsoft Bing Chat, the bot tried to gaslight people and made silly mistakes.  

For example, Bing tried to gaslight one user like this when asked about the release dates for Avatar 2. It clearly didn’t have the updated data but it wasn’t ready to admit it and even went to the extent of calling the user stubborn. Now, that’s something funny and problematic at the same time, isn’t it?

Some of this may be due to how Microsoft implemented GPT-4, but these experiences provide insight into how chatbots built on these language models might make errors.

When asked about the capabilities of the then-unannounced GPT-4 in January, OpenAI CEO Sam Altman stated: “People are begging to be disappointed and they will be. The hype is just like... We don’t have an actual AGI and that’s sort of what’s expected of us.”

How to access GPT-4?

Despite all its flaws and drawbacks, GPT-4 can still turn out to be a pretty useful tool for most professionals including software developers. But here’s the deal- You can’t access GPT-4 for free as of now.

However, the significant improvements in GPT-4, such as its enhanced linguistic finesse, information synthesis capabilities, and advanced problem-solving skills, make it a valuable resource for those willing to invest in its usage.

Introducing dialect recognition, image analysis, and better content coherence can greatly benefit businesses and individuals seeking to improve project communication and creativity.

You’ll need to subscribe to the ChatGPT+ paid plan($20) in order to integrate GPT-4 into your ChatGPT account. Or if you’re a new user, visit chat.openai.com and subscribe for the same. There is now a usage cap in effect, which means you will be limited to 100 messages per four hours, which is appropriate for personal use.

If you’re willing to use GPT-4 for commercial purposes, you need to put your name down on the API waitlist where you’ll be required to fill in your organization ID and other details.

OpenAI has indicated that they hope to someday offer access to everyone, although there is a silent stipulation stating the following:

“During the gradual rollout of GPT-4, we’re prioritizing API access to developers that contribute exceptional model evaluations to OpenAI Evals to learn how we can improve the model for everyone. We are processing requests for the 8K and 32K engines at different rates based on capacity, so you may receive access to them at different times. Researchers studying the societal impact of AI or AI alignment issues can also apply for subsidized access via our Researcher Access Program.”

Wrap Up

That brings us to the end of this article. GPT-4 is a significant leap forward in natural language processing and artificial intelligence. Its enhanced architecture and increased capacity for training have resulted in even more impressive capabilities, including the ability to generate more accurate and human-like responses.

With GPT-4, we can expect to see even more advanced language models, leading to exciting new possibilities for applications in fields like healthcare, finance, and education. The future of AI and natural language processing is bright, and GPT-4 is sure to be at the forefront of these exciting developments.

Cheers!

FAQs

What sets GPT-4 apart from GPT - 3.5 regarding AI language models?

GPT-4 is the latest generation AI language model developed by OpenAI, succeeding GPT-3.5. It distinguishes itself through enhanced image processing capabilities, a larger token limit, improved response accuracy, and the introduction of variants like Chat GPT-4-8K and Chat GPT-4-32K. These improvements make GPT-4 more versatile and powerful compared to its predecessor.

What are the limitations of Chat GPT-4?

Despite its advancements, Chat GPT-4 is not infallible. It can still generate errors, make reasoning mistakes, and provide inaccurate information. Users should exercise caution and verify information when using Chat GPT-4 for critical tasks.