GPT-4: What is Truly at the Core of This Virtual God?

Over a million users embraced OpenAI's creation last year: ChatGPT, an AI chatbot that caught the attention of the world. Setting the record for fastest user growth, it’s no secret that ChatGPT is the world's most successful AI phenomenon of the decade to date. Even Instagram's astounding growth was eclipsed by ChatGPT's seemingly limitless capabilities.

The natural language processing tool is sweeping the globe, challenging human intelligence and assisting with everyday tedious tasks. Nevertheless, all innovations are subject to limitations and ethical concerns to some degree.

With the latest release of GPT-4 in March earlier this year, the AI landscape is constantly advancing and taking integration that bit further by employing sophisticated improvements to AI architecture. As a result of the latest improvements to artificial technology, GPT-4 can now accept both text and image inputs and produce human-like text outputs.

We worship it like a virtual god, but what is truly at the core of this artificial intelligence technology? 

What Do We Know About ChatGPT? 

ChatGPT is an AI-driven natural language processing tool that allows you to have human-like conversations with a chatbot that is comparable to the automated chat services often used on customer service websites. The AI tool processes requests and formulates responses using GPT, short for 'Generative Pre-trainer Transformer.’

ChatGPT’s Learning Process 

The whole process of training is made up of pre-training and fine-tuning. 

Based on the input, ChatGPT generates human-like responses based on a corpus of internet texts. The model learns from publicly available texts and predicts the next word in a sentence, considering the context of the other words during pre-training. Using this method, the model learns grammar, facts, reasoning abilities, and even some biases in the training data. By building a language model, it can generate coherent, contextually relevant responses.

Following the pre-training, the model is fine-tuned on specific datasets for optimum performance and safety. The fine-tuning is generated with the help of human reviewers that follow guidelines provided by OpenAI to review and analyze the possible outcomes of the model; Feedback is then incorporated to refine the model. The idea of this process is to align with human goals and values. 

By using supervised and reinforcement learning through human feedback and reward models, ChatGPT can rank and propose suitable responses to your input. The AI tool exercises machine learning, a type of AI that uses algorithms and statistical models to analyze and draw conclusions from the patterns found in data. It can generate and improve future responses. 

Supervised: During supervised learning, the AI network uses images labeled by humans to learn to identify objects proficiently. It's trained until it detects patterns between input data and output labels, which allows it to label new data accurately.

Consider it like a student learning new information under the supervision of a teacher, making mistakes to learn what’s wrong and how to fix them to achieve better results. Over time it becomes second nature to answer questions correctly and accordingly. 

The types of supervised machine learning algorithms consist of Regression and Classification. When the input and output variables are related, regression algorithms are used, so it can present a best-fit line, but when there is a categorical output variable, classification algorithms are used to identify the category of a given dataset. 

Reinforced Learning: This is a method of machine learning training based on rewarding desired behaviors and punishing undesirable ones.

Imagine if you were to ask a network to play chess when it has no knowledge of the game. Trial and error enable it to learn from the environment and construct better decisions. Machine learning networks can outperform a human grandmaster within just four hours!

It is very similar to the way children learn - by observing and imitating. Our parents model certain actions for us, and we learn to follow them. It's like our experience with tidying toys as a child, where we learn to put them away to prevent losing them. This is essentially the equivalent of neural networks when they use formulas to calculate output based on inputs.

To sum it up, the neural network responds to a question based on its programming. If the response is deemed good, the network stores the formula used. If there is criticism, the network analyses the errors and updates its formulas accordingly. 

GPT-4 

I’m sure you’ve heard about the latest launch of GPT-4 technology by OpenAI in March. It's creating quite a buzz as it's being touted as the most capable language model yet, which is impressive considering how popular the GPTs already are.

In spite of OpenAI's attempts to remain secretive about GPT-4's inner workings, we do know that it is a cutting-edge model that's capable of accepting both texts and image inputs and generates text that is said to sound like it’s coming straight from a human. 

What Are The Capabilities of GPT-4? 

As the first users get their hands on this new model, we are only starting to uncover what GPT-4 can really achieve. From the looks of it, creativity and collaboration are at the heart of the model. 

Open AI also declared that it can accurately solve difficult problems and take complex instructions from natural language prompts or questions. This model is targeted toward answering questions, making inferences, and solving troublesome mathematics problems. It’s now easier to summarise large chunks of content, which has the potential to help in the business and medical fields. 

Some examples of what it’s achieved for users so far are coding games in under sixty seconds, turning hand-drawn sketches into fully functioning websites, creating characters from scratch, and even transcribing calls into lawsuits for court! The opportunities are endless now; this model can accept texts and images. 

Challenging Human Intelligence

The question circulating in society is whether artificial intelligence is smarter than humans. It is a definite contender, as the options are endless when it comes to AI technology. Whether you want help with the explanation of complex topics, are in need of an original joke, require a cover letter, or are just looking for relationship advice from a bot, ChatGPT caters to all.

So, while it may outperform the average person in certain areas, ChatGPT is still a distance away from replicating human intelligence completely. Not only does ChatGPT have the inability to comprehend emotions and make the distinction between human communication, but it also often struggles to avoid errors when it comes to more complex questions. Even the latest model, GPT-4, has defects like social biases, hallucinations, and adversarial prompts’ according to OpenAI. 

Although neural networks can be comparable to the work we produce, it has to be said that it operates on a fundamentally different level to us. It's important to remind yourself that ChatGPT is simply a statistical model that lacks true understanding. It can be hard to remember this when interacting with the network, as it’s essentially like having a personal assistant, encyclopedia, and therapist right at your fingertips. 

OpenAI Funding 

Funding for OpenAI was initially provided by its co-founders and subsequently contributed by other sources. It was established in December 2015 as a non-profit research organization aimed at promoting safe and beneficial artificial general intelligence.

In its early stages, OpenAI relied heavily on its co-founders for funding, including Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever, and Wojciech Zaremba. The initial capital provided by these individuals helped OpenAI launch and get off the ground.

Through seven funding rounds, OpenAI raised an impressive US$11.3 billion from 2016 to April 2023. Thrive Capital, a renowned technology investment firm, was one of the primary investors, followed by Andreessen Horowitz and Founders Fund, both well-known venture capital firms.

Like other early investors, Dmitry Volkov, CEO and Founder of the Social Discovery Group, saw the potential of this artificial intelligence from the start and had the privilege of investing in it.

“I was fortunate to participate in the investment in one of the world’s most successful startups - OpenAI, at the very early stage. Now the company sets records for a fast-growing user base. ChatGPT reached over 100 million monthly active users in January, just two months after launch, making it the fastest-growing consumer application in history. And keeps growing.

The investment was made via Khosla Ventures VI Fund, which was the lead investor in the first round. The value of the startup is now around 29 billion. OpenAI anticipates steep growth in the coming years: by 2024, the company aims to reach $1 billion in revenue. I have always been amazed by the results of Vindod Khosla and his team. We are proud to support their vision as LP.” - Dmitry Volkov.

What’s The Future? 

The potential of ChatGPT is enormous, from facilitating more efficient communication to providing new opportunities for research and AI development. In spite of this, we must always remember that power comes with responsibility. 

Developers have produced this ground-breaking technology that can make a positive impact on businesses, individuals, and experts worldwide, but only if used appropriately. Some people even believe that machine intelligence is the last invention that humanity will ever need to make.  

As technology continues to rapidly evolve, it’s crucial we adapt to these changes in order to create a brighter future. Our ability to embrace and effectively utilize new technologies will determine our success in various fields, including business, healthcare, education, and beyond. By staying up to date with the latest advancements and implementing them in innovative ways, we can unlock new opportunities and drive progress toward a more prosperous future. Therefore, it is essential that we remain flexible and open-minded in our approach to technology and continuously seek out ways to leverage it for the betterment of society.

Also published here.