The release of GPT-3 was a huge milestone that led to a change in how most people perform daily tasks, there's no doubt it's one of the most important language prediction models!
In fact, GPT3's Neural Networks have remarkable problem-solving capabilities, and the way it understands human language has far exceeded our wildest dreams, greatly impacting areas like UI/UX Design, Software Development, and Content Creation.
So, without further ado, let's explore how GPT-3 has revolutionized AI!
What is a Large Language Model?
AI involves a wide range of tools and methods used to build advanced systems that can complete tasks that typically require human intervention. Some AI models can even work autonomously and learn from past interactions!
For years, AI systems focused on simple tasks with high levels of human supervision, until Machine Learning (ML) and Deep Learning (DL) allowed Data Scientists to develop Natural Language Processing (NLP) Models.
These models later evolved to become the Large Language Models (LLMs) that have revolutionized the world, including GPT-3 and its predecessors, GPT-1 and GPT-2.
Why were they such game-changers? NLP models rose to fame because they can comprehend and generate human-like text with impressive coherence.
This scope made users feel they were interacting with an actual person, and some even believed these models were sentient!
Modern versions can summarize text and answer complex questions on a variety of topics, from physics and math to Product Development, UI/UX Design, and Code Writing in multiple programming languages.
What is GPT3?
Also known as GPT3 or GPT 3, and one of the largest and most influential language models ever created, GPT is an acronym for Generative Pre-Trained Transformer.
Besides it working on already given data (which makes it Pre-Trained), it has two other main components. The Generative edge describes its primary goal, and the keyword Transformer means that it uses a Transformer Architecture.
Lastly, the 3 in the end clarifies that the model is on its third version. Since its launch, the model helped businesses reach never-before-seen efficiency and productivity levels, with ChatGPT as its most used application.
One of the reasons GPT-3-powered apps became so popular was their chatting capabilities. These apps offered users the possibility of talking with platforms and applications to ask questions in plain English.
While it's worth noticing that it can give nonsensical content from time to time, truth be told, GPT3 became a go-to platform for several companies at all market levels. Further, the Neural Networks used in the Transformer Architecture opened the door to more stellar AI tools, with Midjourney as probably the best example. Similar to ChatGPT, it allows users to interact with it using English prompts to create high-quality images.
GPT3 Evolution
When Google researchers published the paper "Attention is All You Need," they introduced the famous Transformer Architecture that quickly became one of the most important leaps in Natural Language Processing.
This architecture analyzes sequences of tokens in human text to make impressive predictions, allowing LLMs to understand complex relationships between distant words in long pieces of text.
That was the base OpenAI used for its GPT1 and its updated versions, GPT2 and GPT3. Thanks to Transformers, GPT-3 can write poetry, make jokes, and even make hard translations.
Its latest version, GPT-3.5, received around 175 billion parameters in training data that helped it achieve unprecedented levels of accuracy and coherence. But how has GPT evolved, and what are GPT3's limits?
GPT3 and Dall-E
OpenAI entered the world of art generators with DallE, its T2I (Text-To-Image) product. The popularity of this Generative AI tool skyrocketed in the blink of an eye, allowing tons of businesses to optimize processes.
With ChatGPT and Dall-E 3, OpenAI recasted several fields, such as UI/UX Design and Product Development, allowing smart professional to harvest ideas while reserving their human-based intuition for more complex parts of the lifecycle.
GPT4 and Sora
Once again, OpenAI knocked it out of the park when it released its GPT4 model, considered by many as the greatest Neural Network created to this date. In the product's preview, we watched how GPT-4 built a Discord bot in a few minutes and even debugged its code.
OpenAI's presenter also showed us how GPT4 could process images as input and turn them into HTML and CSS code. It was absolutely mind-blowing!
More recently, OpenAI announced its latest AI tool for video generation, Sora, which, just like Midjourney, can generate stunning, hyper-realistic images in seconds. Like with most Generative AI tools, users can use text instructions (T2V) in plain English to create beautiful scenes up to 60 seconds.
With this fantastic product, OpenAI aims to help users solve problems requiring real-world interactions. Tools like this can surely have countless applications for most users, team members, and businesses in sectors like Software and Product Development.
GPT3 Limits and Controversy
While Machine Learning models are great, they're not flawless. They still make "hallucinations" or invent responses on occasion.
Even the data used to train the most modern models like GPT-4 is not fully updated! In fields like Software Development, it may provide code snippets from outdated documentation. That's why you should be careful about how you use the given information.
Unfortunately, people can also attempt to GPT creation tools with wrong intentions. Since Generative AI tools have access to hundreds of billions of words, it's fairly hard to prevent things like bigotry, bias, sexism, and hateful content.
OpenAI has implemented robust safety measures in all its AI models, and, even though safety has improved a lot, AI models might still produce harmful content.
On the other hand, Artificial Intelligence in general has brought ethical concerns in industries like fashion, art, and entertainment. Plenty of artists are pretty unhappy about AI-produced art, and actors are concerned about how AI will impact their sector in the near future.
In 2023, the Writers Guild of America (WGA) went on strike, and while motives were much larger, AI as also part of the discussion. The WGA raised concerns over the use oF Artificial Intelligence to create scripts and automate content creation, fearing it compromises artistic integrity while also leading to unemployment.
While at the moment of publishing this article AI doesn't seem to be taking people's jobs, it's important to balance human minds with technology to achieve successful, user-centered outcomes!
Conclusion
GPT3 is one of the most influential and largest models ever created! Its language understanding capabilities made it incredibly useful for many businesses, optimizing operational costs and providing improved customer experiences. OpenAI tools have been able to see, hear, and speak for a few months, and we cannot wait to see what it does next!
