The Future of AI: GPT-3 Vs. GPT-4: A Comparative Analysis
In this era, the pace of technological advancement is faster than ever. From Sophia, Alexa, and SIRI to autonomous vehicles and alpha zero, artificial intelligence is making progress by leaps and bounds. The story has not ended here; in science fiction movies, we usually see AI-generated human-like robots, but things have come to reality now there are robots that perform tasks with greater efficiency compared to humans. A simple example is the Alpha zero program that can beat humans in a variety of games, Chess being #1.
In this article, we will explore the world of Artificial Intelligence and closely examine two of the most advanced AI technologies – GPT-3 and GPT-4, which have created a buzz in the tech industry. We will discuss the future of AI as a result of these advancements and conduct a comparative analysis between Generative Pre-Trained Transformer-3 (GPT-3) and Generative Pre-Trained Transformer-4 (GPT-4) to gain a better understanding of their unique features and whether they are truly deserving of the hype. If you’re a tech enthusiast or any person who wants to explore these 2, this post is only for you to provide you with valuable insights about the future of AI. So, let’s dive right in!
Artificial Intelligence
Artificial Intelligence (AI) refers to a field within computer science that focuses on developing machines capable of emulating human-like intelligence, behavior, and responses. Artificial intelligence is actually the intelligence demonstrated by machines (computers). Obviously, computers perform tasks faster than humans, but it’s a fact computers can’t make decisions on their own. These can only do the task they are trained for.
Explore artificial intelligence on the world’s top platform pic.twitter.com/oKPb9E5OD6
— PlayGPT (@PlayGPT888) March 10, 2023
However, empowering computers to make a decision on their own is Artificial Intelligence. Its examples include search engines like Google, generative and creative tools such as Chat GPT, AI art, etc., voice recognition tools, and more. The applications of AI can be seen in every field of life that may have some positive as well as negative impacts (i.e. replacing human jobs, thus leaving a large number of people jobless). However, experts predict that the rise in AI will ultimately benefit most people over the next few years.
The Emergence of GPT and its Implications for the Future of AI
The emerging technology of GPT has the potential to revolutionize the machine learning and artificial intelligence field. GPT, developed by OpenAI, actually stands for Generative Pre-Trained Transformer, which is a neural network machine learning model trained on the basis of billions of data points. The most famous models of GPT are GPT-3, the 3rd iteration of the model, which was released in may-jun 2020, and GPT-4, the much more advanced model that is going to be released in mid of march 2023. These algorithms work far beyond one’s expectations.
Sam Altman, chief executive at OpenAI, perceives the future of AI and states that the world will change due to these models. He expects further advances in AI research till the 2030s and says that there is about a 50% chance that Artificial intelligence will take over numerous human tasks in the near future (by 2035). He further says that explosive AI development is possible.
GPT-3 Vs. GPT-4: A Comparative Analysis
Undoubtedly, with the advent of GPT-3 and GPT-4, the future of AI looks even brighter. Belo, we’ll conduct a comparative analysis between GPT-3 Vs. GPT-4 is based on a few factors to give in-depth insights about these 2.
Parameters:
A parameter is a configuration variable in an AI model that determine the metric of performance. All AI models use these variables when making decisions and predictions. The 3rd iteration of GPT is trained on 175 billion parameters, which is a lot compared to most of the other natural language models of today that don’t even have half of this number.
OpenAI follows the rule “the bigger, the better” and claims that the upcoming 4th generation of GPT, the GPT-4, is trained on the basis of about 100 Trillion parameters making it significantly larger and better than its counterpart. To understand just how big this value is, let’s compare it with the human brain, which has around 80-100 billion neurons consisting of 100 trillion synapses. It means the number of parameters in GPT-4 is the same as the number of synapses in the human brain, indicating that this AI model is ore closer to actual human thinking compared to its previous generation model.
Performance:
GPT-3 is widely regarded as one of the top-performing natural language processing models available in the market today. This sophisticated model is capable of generating text that closely resembles human writing, effortlessly producing summaries, complete codes, articles, poems, and stories with minimal prompts. Despite its impressive capabilities, it has been observed that GPT-3 may encounter challenges when attempting to interpret certain idiomatic expressions.
However, with the upcoming release of GPT-4, which boasts a substantially greater number of parameters, there is a strong expectation that this model will outperform its predecessor. GPT-4 is anticipated to exhibit faster task completion and greater ease in comprehending complex subject matter, positioning it as a significant contender in the field of natural language processing.
Accuracy:
The accuracy of an AI model is fundamentally determined by the number of parameters it possesses. With a greater number of parameters, GPT 4th generation is anticipated to provide faster and more precise outcomes. Such models are capable of effectively emulating human behavior and speech patterns in response to input prompts.
Capabilities:
GPT-3 is capable of performing a wide range of natural language processing tasks such as summarization, question answering, language translation, declining inappropriate requests, permitting users to provide follow-up corrections and more. It can efficiently generate natural language and coherent responses indistinguishable from human-generated content.
GPT-4, on the other hand, is still in the development process, but it’s claimed by the developers that it’s multimodal learning capabilities, which means it can understand text, images, videos, and audio inputs, thus enabling users to create audiovisual content, movie characters and more. The 4th model of GPT can also create a whole 200 pages book from scratch in just a few minutes.
Potential Applications:
When it comes to potential applications, GPT-3 is widely used in a number of industries, including customer services, chatbots, content generation, virtual assistants and more. It’s also been used in the research field for machine learning and natural language processing. While GPT-4 is expected to have even more applications, specifically in music creation, movie character development, creative writing and art.
Dependence on Prompt:
Those individuals who work with GPT-3 are well aware that prompting plays a crucial role in producing satisfactory results. In instances where users do not utilize the appropriate prompt, they will not achieve optimal outcomes. This indicates that the model is heavily dependent on prompts. However, such limitations may not apply to GPT-4, which will comprehend the user’s intent and provide them with greater flexibility in formulating their intentions, enabling them to feel more confident that the system will understand them.
Susceptibility to Misinformation:
OpenAI trains its models based on learning from human feedback. For every answer it generates, it asks users to give their feedback, thus fine-tuning the algorithm and reducing the susceptibility to misinformation or generating biased or toxic text.
Comparison Table GPT-3 Vs. GPT-4
| FEATURES | GPT-3 | GPT-4 |
| Release | June 2020 | Expected to Release in 2nd Week of March 2023 |
| Machine Learning Parameters | 175 BILLION | 100 TRILLION |
| Training Data | 17 gigabytes | 45 gigabytes |
| Capabilities | Understand different languages, can translate text, summarize data and provide an answer to questions. | Can create video scripts, Videos, AI-generated Movie actors, Code generation, and the list goes on. |
| Model | Text Only | Multimodel |
| Performance | Write human-like text with a combination of idiomatic text and slags within seconds. | 500 times more powerful than GPT-3 |
| Potential Applications | Chatbots, generate Emails, write blog posts, virtual assistant, coding. | Language translation, grammar correction, chatbots, Essay and book writing (can write a fully optimized 200 pages book from scratch in minutes). |
| Limitations | Trained on facts of 2021, can’t provide the latest knowledge. | After all, it’s dependent on the parameters it’s trained on. Can’t go beyond that limit. |
FAQS
Final Words
We’ve tried our best to provide a comprehensive analysis of GPT-3 vs. GPT-4 to help you understand the main differences and explain how these have revolutionized the world. No doubt, these models are crucial advancements in the field of natural language models. Now creating human-like text, movie scripts, chatbots and music is a breeze. Unless you live under a rock, you may already be familiar with GPT progress and the variety of tasks it can perform. In a nutshell, humanity has stepped at the doors of singularity, and the technology world will change dramatically due to OpenAI.
