Large language models (LLMs) like GPT-3.5 and GPT-4 were both made by OpenAI. The GPT-3.5 came out in 2021, and the GPT 4 in 2022. Both models are taught on vast amounts of text and code, and they can be used for many different jobs, like making new text, translating it, and asking questions.
GPT 4 was learned on a set of data collected after GPT 3.5. This means that GPT 4 can better keep up with current events and trends and adjust to them. For example, GPT 4 can make more correct recaps of news articles and give more complete and valuable answers to questions about current events.
GPT 4 can understand and take pictures. This makes GPT-4 a more helpful tool than GPT-3.5 because it can be used for more things. For instance, GPT-4 can label pictures or new pictures based on a description.
Here we discuss GPT 3.5 and GPT 4 in detail.
What is chat GPT 3.5?
OpenAI developed the massive large language model GPT 3.5 in 2022. It is the improved version of the GPT 3 language model, and it was created using a text and code training set that is better than GPT 3. As a result, GPT 3.5 is now better able to comprehend and produce both code and normal language.
Additionally, GPT 3.5 can better recognize and react to the emotions portrayed in the text. For instance, GPT-3.5 may detect and sensitively react to a user expressing melancholy or annoyance, improving the interaction’s personal and sincere feel.
Although GPT 3.5 is still in development, a lot of unique applications have already been made using it, such as:
- A chatbot that can have genuine discussions with people
- It can produce original material, such as tales, poetry, and essays,
- A program that generates code in several different programming languages
GPT 3.5 is a fantastic innovation that has the potential to improve computer-human interaction drastically. It is still in its early stages of development, but its promise is clear.
Some prominent features of GPT 3.5 include:
- Since it is a large language model, it has been trained on a massive collection of text and code.
- It can read and write in both binary and natural language.
- It can read and respond more accurately to written expressions of emotion.
- GPT 3.5 is a fantastic technology that has the potential to improve computer-human interaction drastically. It is still in its early stages of development, but its promise is clear.
What can be achieved with GPT4
The GPT 4 language model is better and more potent than the GPT 3.5 model. GPT-4 can be used for a wider variety of jobs than GPT-3.5. Some of the specific things we can do with GPT-4 that we can’t do with GPT-3.5 are:
Improved accuracy: GPT-4 is better than GPT-3.5 at some jobs, such as making text, translating it, and answering questions.
Better ability to understand pictures: GPT-4 can understand pictures and write down their appearance. Because of this, it is a vital tool for adding captions to pictures and searching for pictures.
Increased speed: When making text, GPT-4 is faster than GPT-3.5. This makes it better for real-time uses like robots and customer service.
Generate more accurate and original text: GPT-4 can do this better than GPT-3.5 because it has a bigger language and can learn more complex relationships between words.
Translate languages more accurately: GPT-4 can translate languages more accurately than GPT-3.5 because it has a larger model size and can learn more complex word relationships.
When Should You Use GPT 3.5 or GPT 4?
Both GPT-3.5 and GPT-4 are large language models, but their strengths and flaws are different. GPT-3.5 is faster and can handle more extended questions, while GPT-4 is more accurate and can understand pictures.
Here is a more thorough look at how GPT-3.5 and GPT-4 are different:
GPT-3.5
Pros:
Faster
Can deal with longer questions
less likely to make mistakes with facts
Cons
GPT-4 isn’t as exact.
Can’t understand pictures
GPT-4
Pros:
More exactly, pictures can be understood
Cons:
Slower
Can’t handle as many long questions and are more likely to get the facts wrong
Here are some examples of jobs that fit each model better:
GPT-3.5
Quickly making text, like for robots or customer service apps. Processing a lot of information, such as for jobs that involve natural language processing
GPT-4
Creating correct writing, such as for news stories or product descriptions. Understanding pictures, for things like image labeling or image search
You should think about your own needs to decide which type to use. GPT-3.5 is a good choice if you need a fast model that can handle a lot of text. GPT-4 is a better choice if you need a correct model that can understand pictures.
Difference Between GPT 3.5 And Chat GPT 4
However, GPT-3.5 and its predecessors are significantly outperformed by the most current model. Where does GPT-4 diverge from its predecessor, GPT-3.5? Here, we’ll compare and contrast GPT-4 with its predecessor, version 3.5.
Differences | GPT-3.5 | GPT-4 |
| Creativity | GPT-3.5’s answer alternates between the two languages, with each line utilising one language before switching to another. Every line of the answer from GPT-4 would be in both languages. | The GPT-4 model performs better when given a creative assignment, such as producing a poem in which each line alternates between English and French. |
| Cost | Less expensive | More expensive |
| Image vs. Visual Inputs | The GPT-3.5 only takes text-based questions. | GPT-4 is capable of receiving both textual and visual inputs. |
| Safer Responses | While GPT-4 isn’t perfect, the model’s improved safety features over GPT-3.5 are much appreciated. | GPT-3.5, which produced harmful reactions 6.48% of the time. replies less improved over the GPT-4 model. |
| Response Factuality | Hallucinations are still a concern in GPT-4. According to the GPT-4 technical study, the new model has a 19%-29% lower chance of experiencing hallucinations than the GPT-3.5 model. | One of GPT-3.5’s shortcomings is its propensity to generate illogical and false information confidently. This is referred described as a “AI hallucination” in the language of AI and might cause people to doubt the accuracy of data generated by AI. |
| Context Window | GPT-4’s context size and window are notably superior than those of its prior model. | GPT-3.5 is not an improvement over GPT 4 with respect to context size and window. |
OpenAI’s long-awaited GPT update, GPT-4, is now available. A number of potent new capabilities and features that the Large Language Model (LLM) has have astounded users all around the world.
Similarities between ChatGPT 3.5 with GPT 4
GPT-4 is a considerable improvement over ChatGPT 3.5, as stated by the developers. However, did you realize that they are more alike than different?
Although an improvement over the earlier generation, the GPT-4 has many features, functions, and data training in common with the previous device.
Detail of similarities between GPT-4 and ChatGPT 3.5.
| Similarities | Detail |
| Transformational Architecture | Each layer of the transformer network used in GPT models employs self-attention processes to choose which elements of the input sequence to concentrate on. When you ask a question using self-attention processes, both transformer networks capture the input sequence and give a secret picture of the message or symbols. |
| Comparable Training Model | The ChatGPT 3.5 and GPT 4 models, which differ from the earlier GPT-2 and GPT-3 models, were developed using comparable deep-learning approaches. They are improved using RLHF (Reinforcement Learning from Human Feedback), and they are trained using data that is available to the general public. Both GPT models include recurrent neural networks (RNNs), which are often used in natural language processing, despite this not being explicitly stated. |
| Competencies and Results | GPT-4 may converse with the user like its predecessor. When the task’s complexity exceeds a certain level, they may both provide the same answer similarly, but it may differ somewhat. |
| Useful Implementations | Despite improvements to the model, training data, and response speed, the only function of both GPTs is to react to user inquiries. |
| Language Generation | They produce well-crafted, logical, and appropriately contextualized statements. |
| Translation | Both GPT models are remarkably accurate and fluid when translating text across different languages. |
| Text Completion | Based on the context given, they finish phrases and paragraphs, finishing unfinished articles, documents, programming functions, etc. |
| Question-Answering | Both have received instruction on responding to various questions, from simple factual inquiries to more difficult cognitive exercises. |
Why is GPT-4 superior to GPT-3.5?
Compared to GPT-3.5, the current LLM powering OpenAI’s popular chatbot ChatGPT, chatGPT4 is a significant upgrade in many ways. Not only does it have a far higher character input limit and the ability to detect inputs with more complicated patterns, but it also seems to be safer to use.
Comprehend more complicated inputs
The capacity to comprehend nuances and complexities in stimuli is one of GPT-4’s most impressive new features. OpenAI claims that GPT-4 “exhibits human-level performance on various professional and academic benchmarks.”
GPT-4’s much greater word limit also makes it simpler to understand input prompts with more intricate language.
The new model can process input prompts up to 25,000 words long (for comparison, GPT-3.5 had a word limit of 8,000). This directly affects how much information users may include in their prompts, giving the model considerably more data to work with and resulting in longer results.
Multimodal Competencies
ChatGPT’s earlier iteration only supported text prompts. The multimodal capabilities of GPT-4, however, are among its most recent characteristics. The model may accept both text and picture instructions.
Image reading capabilities of GPT-4 go beyond simple interpretation. This was shown by OpenAI in the developer stream (above) when they gave GPT-4 a hand-drawn prototype of a satirical website. To turn the mockup into a website and replace the jokes with actual ones, the model was charged with coding HTML and JavaScript code.
Greater Steadiness
In addition, I assert that GPT-4 is steerable. Additionally, it has made it harder for the AI to stray from the character, decreasing the likelihood that it would fail when employed in an app to depict a certain character.
Developers may decide on the look and function of their AI by specifying the direction in the “system” message. These messages enable API users to significantly personalize the user experience, subject to certain limitations. Since they are the simplest way to “jailbreak” the model, they are also working to make them more secure. The GPT-4 demo emphasized this point by asking a user to try to prevent GPT-4 from functioning as a Socratic teacher and answer their query. But the model persisted in keeping up her façade.
Security and safety
Over the course of six months, OpenAI improved and made GPT-4r. This, compared to GPT-3, shows that it is 82% less likely to respond to requests for offensive or otherwise prohibited content, 29% more likely to respond to sensitive questions in accordance with OpenAI’s standards, and 40% more likely to provide honest answers.5. Because it isn’t perfect, it sometimes could “hallucinate” and forecast things that don’t happen. Even if GPT-4 has more precise perception and prediction skills, you should only have a limited amount of confidence in AI.
Performance Improvements
OpenAI configured the bot using common benchmarks designed for machine learning models in addition to evaluating the model’s performance on tests given to humans.
The statement claims that GPT-4 “considerably outperforms” both existing LLMs and “most state-of-the-art models.” The MMLU, which was already mentioned, the AI2 Reasoning Challenge (ARC), WinoGrande, HumanEval, and Drop are just a few examples of benchmarks that assess various abilities.
You’ll find equivalent results when comparing performance on academic vision criteria. All tests, including VQAv2, TextVQA, ChartQA, AI2 Diagram (AI2D), DocVQA, Infographic VQA, TVQA, and LSMDC, are performed best by GPT-4. According to OpenAI, the results of these tests for GPT-4 “do not fully represent the extent of its capabilities” since researchers are still finding new and complicated issues the model can resolve.
Final Verdict
GPT-4 will definitely provide more relevant replies than its predecessors, but its forecasts may also need to be more accurate. Above all, to prevent errors, double-check the replies before adopting them. To access the GPT-4 Beta version, join up or download the API services.
