In March, to be precise, on the 14th, the release of the flagship fourth iteration of GPT was announced. The AI capabilities impressed users just after viewing the release. The platform became faster, smarter, and more user-friendly.
How ChatGPT Works
The bot is a Large Language Model with a transformer architecture that has been trained on a vast array of data. To put it very simply, the essence of its operation is somewhat as follows:
- Breaking down the phrase-query into words and correlating how each is used in context;
- Identifying the topic of discussion;
- Merging and aligning data.
Simpler still, the program looks for word combinations in the context of the topic. It then runs each word through layers of neuron network and composes a correct phrase.
For instance, if you give an AI the word “dog,” it will most likely associate it with the verbs “bark,” “bite,” “run,” or “walk”. In other words, it will construct a meaningful sentence. It does this after analyzing a vast amount of data and running information through layers numerous times to ensure the correctness of its response. This is because the bot was “taught” by people. It knows Wikipedia data (up to the year 2021), and millions of articles and scientific papers have been uploaded into it.
OpenAI, the developer, used several training technologies to improve the AI’s skills:
- Supervised Fine Tuning Model – people wrote questions and themselves provided answers, creating a knowledge base for artificial intelligence;
- Reward Model – based on input data, AI generated several texts, and users rated them;
- Reinforcement Learning Model – here, the neural network produced one solution and got feedback from a person.
All these technologies allowed the chatbot to “understand” how human speech is constructed, to give meaningful natural answers, and even to maintain a conversation with the user.
Differences Between GPT 3.5 and 4
Speaking of the differences between ChatGPT 3.5 and 4, the latter is better at reading the emotional coloring of the text, expressing empathy or joy. Therefore, the dialogue with AI resembles a live human conversation.
GPT-4 works with dialects, which are usually difficult for language models to understand. The previous version could not handle this task.
GPT 3.5 can be creative, but the result of the artificial intelligence’s creativity is unstable because it struggles to maintain narrative consistency. In contrast, GPT 4 will write poetry, essays, or stories according to all the rules of literary genres.
Comparing ChatGPT 3.5 and 4 in terms of information synthesis capacity and abilities to solve complex problems also favors the latter. For example, when asked about the impact of the declining bee population on agriculture, ChatGPT 4 produces a logically structured text with references to scientific research and thematic articles.
Here, however, not everything is smooth, as the neural network periodically makes mistakes by referring to non-existent sources or confusing the titles of scientific books.
As far as complex tasks go, the enhanced fourth technology solves complicated problems in mathematics, physics, and astronomy. It is capable of analyzing data, making forecasts, and finding information quickly.
Compared to ChatGPT 3.5, artificial intelligence skills in programming have also improved. The system will find errors in existing code and write a simple algorithm itself.
Additionally, GPT 4 is more ethical – the likelihood of it generating biased or offensive content (based on race, sex, gender) is not excluded but is much less probable.
What’s New in Version 4
If we talk about how to differentiate ChatGPT 3.5 from 4, the answer will be straightforward – the fourth iteration has received new skills:
- The addition of a second type of data processing – AI will now link the image with the words in the request (several pictures can be uploaded). There’s no talk of generating images or drawing (like Kandinsky) yet; the bot will still answer in text format, but this is already a big step in the development of neural networks.
For example, one can ask the neural network to take an IQ test or analyze an image graph and check how logically artificial intelligence will perform the task.
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AI can explain memes – this is if there’s nothing else to do and you want to see if the system has a sense of humor.
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Creating websites – at the presentation of GPT-4, it wrote the code itself according to the input from a photograph (from an ordinary notepad page) and launched the website in the browser.
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Improved programming skills – the bot can write code quickly, and if there are errors during compilation, you can simply copy the wrong part of the code and ask the AI to correct it.
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The addition of new languages, dialects – in this parameter, the fourth iteration beats the competition. Yes, sometimes the AI during translations may not convey the essence of the question accurately or miss important words, rendering the text meaningless. But this is a problem with translation models.
Now the bot can be personalized and humanized by changing scenarios and manners of communication with AI. Just let the neural networks know in what tone you want to maintain the dialogue. Or, if it’s about content generation - what emotional shading your story or essay will have.
In general, the capabilities of the new version are truly astounding and even a bit frightening. The model surpasses its competitors and confidently beats them in all parameters. Perhaps that’s why the developer declined (for the first time) to publish a report, stating the decision was because revealing information about such a powerful technology was considered a “bad idea.”
