ChatGPT has been a game-changing tool in the world of natural language processing since its first version. Active users of ChatGPT have reached to million in just a few days. It has improved its ability to understand and respond to human language with every update, and ChatGPT 4 is no exception.
Building on the success of its predecessor, ChatGPT 3, this new version represents a significant advancement in natural language processing (NLP) technology. With an impressive 6 billion parameters, ChatGPT 4 has even more capacity for understanding and generating human-like language than its predecessor.
In this article, we will explore some of the key advancements in ChatGPT 4 and how they differ from ChatGPT 3. Those interested in natural language processing, researchers, and developers will benefit from this article.
ChatGPT 4 vs. ChatGPT 3: what’s new?
Open AI has now launched the fourth version of ChatGPT. Let’s discover some upgraded features and comparison for Chat gpt 4 vs Chat gpt 3, what’s better and why?
1.Image recognition
Chat GPT-4 includes an image recognition feature that is one of the biggest differences between Chat GPT-3 and Chat GPT-4. This is because Chat GPT-4 is multimodal, which means it can understand a variety of modes of information, including words and images. In contrast, Chat GPT-3 was limited to text inputs and responses, which limited its application.
Chat GPT-4’s image recognition system is still relatively new, but it can describe what’s going on in an image and can help people suffering from vision problems. As part of Open AI, Chat GPT-4 described a clothing pattern, explained how to use gym equipment, and read out a map.
A label’s information can only be read out by the AI if it is prompted in the right way, so what you ask it will determine its answer. Rather than Chat GPT-3, this technology could help people identify certain objects or assist the visually impaired with food packaging labels.
2.Factual Information
As Chat GPT-4 is the latest version of the software, the developers have spent more time tweaking algorithms to prevent users from fooling the AI.
Many types of prompts Chat GPT-4 has been trained on, many of which are malicious. Thus, the newest model provides more factual information and has better reasoning capabilities than its predecessor.
3.Optimized for the future
One of the biggest problems with language models has been their training resources. Often, companies sacrifice accuracy for lower prices, leading to under-optimized AI.
Model performance was thought to be mainly affected by model size for a very long time. Many large companies, such as Google, Microsoft, and Facebook, have spent large sums building the biggest systems. However, this method ignored the amount of data fed to the models.
In recent years, hyperparameter tuning has been shown to significantly improve performance. For larger models, however, this is not something that can be achieved. Parameterization models can be trained on a smaller scale for a fraction of the cost to then be transferred to a larger system for virtually no cost.
The result is that GPT-4 can be more powerful with a smaller size than GPT-3. The model size is not the only variable it optimizes for – quality data also counts. GPT-4 is capable of incredible developments when fine-tuned with the correct hyperparameters, model sizes, and parameters.
4.Steerability
The concept of steerability in AI is an intriguing one because it refers to being able to change one’s behavior as a reaction to changing circumstances. Unlike GPT-3, GPT-4 integrates steerability natively, and users can customize the classic ChatGPT personality to suit their preferences.
It is now possible for developers to provide instructions to their AI models using the ‘system’ message to describe the desired style and task that they want them to perform. API users can customize the experience for their users according to their preferences within a certain range of restrictions.
5.Enhanced memory
There is a limit to how much information language models can retain when conversing with users; they are trained on millions of web pages, books, and other texts.
Earlier ChatGPT versions equated to about 7,000 words or three to four pages. As details recede further into the attention function, the model may lose track of them.
However, GPT-4 offers a staggering 32,768 maximum token count. In essence, the model can store up to 50 pages of text or 64,000 words.
As a result, it can recall discussions from 20 pages ago. Despite this explanation being a rough approximation, GPT-4 is equipped with an extended memory capacity with its corresponding capabilities.
6.More safety
For over six months, Open AI has been improving its monitoring framework and collaborating with experts in sensitive fields such as medicine and geopolitics to ensure an accurate and safe response to GPT-4.
Compared to GPT-3, OpenAI claimed that GPT-4 would produce 30 percent more factual responses and 75 percent fewer disallowed content responses.”
How Does Chatgpt Plus Work?
ChatGPT has now been upgraded to ChatGPT Plus with GPT-4, and can deliver faster response times, more parameters, and supports more parameters. Currently, ChatGPT Plus is only available to a limited number of users.
With the updated version, tough questions can be answered more accurately. Customers willing to pay $20 a month, including taxes, will be able to subscribe. OpenAI requires that you fill out a form to be able to use ChatGPT Plus.
Final Take
Both GPT-4 and GPT-3 have powerful AI-based text generation capabilities. Despite their similarities, the two applications have some significant differences.
Comparing the two models, each has advantages and disadvantages. Because GTP-3 has fewer parameters and fewer records, it can solve basic problems faster than GTP-4. For basic tasks, GTP-3 often makes more sense than GTP-4. GTP-4, however, provides greater accuracy for difficult tasks due to its larger parameter set and data set volume, which make it suitable for more demanding tasks.
For this reason, there is no universal consensus on which method is best: for simple tasks, GTP-3 might be useful, but for more challenging problems, GTP-4 may be a better choice, especially if accuracy is important.
In machine learning, both models have their place – but ultimately, the right approach always depends on your personal preferences!
