Humans tend to make their life and work easy. From the invention of the wheel for easy transportation till now, we have found ways to get more with less effort. In the current golden age of technology, we have surpassed the past limits and ventured into the domain of Artificial Intelligence.
We are now out of the first steps of AI development and moving toward more powerful and useful AI implementations. Where Siri and Alexa are helping us get answers from the internet, and ChatGPT is providing us with solutions to our problems. We are currently in a constantly developing age where technology is evolving faster than our past expectations.
With this constant evolution and implementation of AI in many sectors of life, the future of AI looks brighter than ever. After the successful launch of ChatGPT, people are more excited to see how the Future of AI can benefit them.
Let’s quickly go over some basics before jumping into what the future of GPT beholds with GPT-4.
Table of Contents
- Definition of Artificial Intelligence (AI)
- Overview of Generative Pre-trained Transformer (GPT)
- What is GPT-3?
- What is GPT-4?
- Comparison of GPT-3 and GPT-4
- Future of AI with GPT-4
- Wrap Up
Definition of Artificial Intelligence (AI)
Artificial Intelligence is associated with creating a digital program or robot which can have the characteristics of human-level intelligence. This term is mostly used for projects which have intellectual characteristics, like reasoning, conversation, learning from past experiences, and understanding the context of a given situation.
We have seen AI advancing in many forms. For example, programmed AI that can play chess or checkers like a pro player, or AI which can interact and hold a conversation like Siri or Alexa.
Now we have more advanced AI in the form of the GPT family, which can understand the context and generate an appropriate reply.
Overview of Generative Pre-trained Transformer (GPT)
Generative Pre-trained Transformers are large language models which are trained on text data to generate Human-like responses. It is a neural network deep learning model based on the multiple-layer architecture of transformers.
These transformers are further fine-tuned for natural language processing and generate results like language translation, text generation, and text classification.
What is GPT-3?
GPT-3 is the 3rd generation in the family of Generative Pre-trained Transformers. It is more powerful than its predecessors, GPT-1 and GPT-2, which, even combined, are just 1% of GPT-3.
A Brief Overview of GPT-3
GPT-3 was introduced back in 2020 as the largest AI text generation model, with 175 billion parameters, and the ability to hold a conversation and generate continuous responses. GPT-3 can take 2024 tokens of input which is equal to 1500 words.
The training data of GPT-3 is also based on tokens, which include 410 billion tokens of common crawl data, 19 billion tokens of web text, 67 billion tokens from books, and 3 billion tokens from Wikipedia.
GPT-3 takes minimum input and generates longer relevant outputs with exact context according to the input. GPT-3 uses a Natural Language Process to add a human conversation layer. It uses both generative and processing layers of NLP. This gives it the capability to understand and generate human-level intellectual text.
Advantages of GPT-3
GPT-3 might feel like a chatbot to some, but it has a lot more potential than just a normal chatbot. The advantages of GPT-3 are as follows:
- Language Translation
- Writing Python or other language codes
- Write plagiarism-free articles, poems, stories, and blogs
- Automated conversations
- Takes written and voice inputs.
- Create game designs
- Build website designs
- Auto word completion
- Chatbot capabilities
Limitations of GPT-3
With many advantages, there are also a few limitations in GPT-3:
- It is a pre-trained model, so no new data can be added
- It has no training for audio or video data
- It cannot reason why certain outputs appeared
- Lack of common sense as it is trained on statistical language data
- Reaching its bottleneck as it can’t learn new stuff
- Lack of empathy and emotional intelligence
What is GPT-4?
GPT-4 is a combination of the multi-large language model. It’s the 4th generation of Generative Pre-trained Transformers upgraded from GPT-3.5. OpenAI has recently introduced GPT-4, and it will be available to ChatGPT premium customers. It is confirmed by Microsoft that they have been using the GPT-4 in Bing well before its release.
A Brief Overview of GPT-4
OpenAI has upgraded its GPT-3.5 and upscaled its model with a multimodal system. The GPT-4 is capable of taking inputs in the form of text, audio, and images. In the past two years, OpenAI has worked with Azure and re-developed its Transformer, and built a supercomputer to handle the workload of GPT-4.
Compared to GPT-3 145 billion parameters, GPT-4 has 100 trillion parameters which makes it the largest known trained AI model. Along with it, they have maximized their performance capabilities making it 82% more secure on disallowed content. It is also improved in giving factual answers compared to GPT-3, and it has improved by 40%.
GPT-4 is far more capable than GPT-3 or GPT-3.5 as it can handle far more complex tasks easily, and its reliability and creativity are on another level. It has also taken part in exams that were built for humans, and it has shown some amazing results in understanding the context and generating text according to it. Out of 26 test results, GPT-4 has dominated GPT-3 in almost all tests.
Advantages of GPT-4
GPT-4 is an improved and huge version of GPT-3, so it has more advantages over all other AI models available in the market:
- Less repetition of data and more creativity due to its large data set
- Text and image inputs to get more detailed answers
- A better understanding of context and emotional stuff
- More capable in customer support and management
- Adds more value to the marketing experience as it adds demographic and other dependencies to the marketing
- Far better at creating original art and music
- More languages are supported in translation, input, and outputs
- It is also likely to bottleneck as its pre-trained data is from 2021
Limitations of GPT-4
There are still a few disadvantages of using GPT-4:
- Available for premium customers only
- Its data is socially biased at some points
- It has data in the form of audio and video (training data mostly). However, it lacks audio or video generation in the output.
- It still hallucinates and provides fiction as facts.
Comparison of GPT-3 and GPT-4
While comparing both GPT-3 and GPT-4, we can see the whole picture of how changing the overall scale of data helped in improving the performance of GPT-4:
- GPT-3 can take text input, and this is improved in GPT-4, which can take text and visual input
- Output capabilities of both GPT-3 and GPT-4 are the same as they generate text data. However, the major difference is GPT-4 can generate 25000 words while GPT-3 can generate only 1500 words.
- GPT-4 is trained on trillions of parameters which include text, audio, and video data. On the other hand, GPT-3 is only trained on text data.
- The performance on OpenAI’s websites shows that GPT-4 produces 40% more fact-based data than GPT-3
Future of AI with GPT-4
With the rapid advancements in the GPT family and the introduction of GPT-4, the new largest pre-trained model. The future of AI will flourish, and more apps will be able to access the GPT-4 API to get better results for their business.
GPT-4 has raised the bar of AI performance and accuracy. GPT-4 also has multi-input formats, which makes it more usable in customer service and the shopping industry.
It has also overcome the problem of bottlenecking and repetitive parts of results from GPT-3.
However, it’s for the time being, as it is also the pre-trained dataset, and the same limitation exists as its predecessor.