GPT-3 has taken the world by storm, you see it on the news, social media, Google search trends and out of every other person’s mouth. It is an AI tool capable of doing anything with the help of just a little hint. We have seen the big names in tech appreciating it – The Verge called GPT-3 “an invention that could end up defining the decade to come.” W. D. Heaven wrote in an article in MIT Technology Review that GPT-3 is “shockingly good — and completely mindless.”
The kind of hype created by all this urges everyone to learn more about GPT-3 and you’re here because of curiosity too. So let’s get started with the intro of the company that created GPT-3 and then dive into the details of what this tool actually is and what it means for the world.
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What is OpenAI?
Before learning about GPT-3, let us dig a little into the world of Open AI. Open AI is an artificial intelligence research company, having Open AI Inc. as its parent company. It was initiated by a group of founders like Elon Musk, but he left the company a few years ago.
The company claims to develop and promote artificial intelligence in such a way that it proves beneficial for humanity. They work with the aim of producing human-like powerful reasoning capabilities in machines. They consider the future goals of this venture to be uncertain but the objective behind it to be right and promising.
The company is considered as one of the leading competitors to DeepMind. Open AI is the parent of amazing artificial intelligence projects like DALL.E – creating images from texts, CLIP – connecting text and images, Jukebox – a neural network generating music, Image GPT – transformer like model, trained on pixel sequences that generates image samples etc.
What is GPT-3?
Moving on to GPT-3, what it is and what it entails for the future of artificial intelligence development. GPT-3 is a continuation of GPT and GPT2 language models from Open AI. It stands for generative pre-trained transformer 3 and like other transformers, it is a language model deploying deep neural networking techniques for text generation.
But the special thing about this model is what is special about every other project of Open AI. They have developed this model to be able to generate human-like text. GPT-3 is accessed through the Open AI API and within a year of its release, is in use by around 300 applications with many more developers currently using it for building modern AI applications.
How does GPT-3 work?
GPT-3 works when we provide the transformer with a sentence or phrase as a prompt and it generates its output in the form of text completion in natural language. GPT-3 is a language model with highly efficient training where the developers need no more than just a few prompts to make it learn what they want. Moreover, it is easy to use and work with due to its simplistic API which is at the same time very flexible to be used in different ways by the developers.
GPT-3 tool is considered the next generation of language generating models with billions of parameters that are during training of the model. It can go as far as writing stories, song lyrics and even web page layout code for you on describing look and functionality. GPT-3 is considered as a significant step forward in excellent human-like text outputs and amazing versatility with which it generates its results.
We do not exactly know the inner workings and patterns GPT-3 runs on but what it seems from the outside is a language model bringing you a response formed by joining together thousands of text segments and trying to make sense of it for us in some way.
Why should developers be interested in GPT-3?
Systems like GPT-3 are as good as the application using them and they can be best appreciated when put into the hands of end users and customers. This is why developers have been going crazy to develop applications that use the excellent capabilities of GPT-3. Following improvements and features are provided by the GPT-3 platform to introduce new features for developers:
Answer Endpoints:
GPT-3 can be used for building applications working on feedback systems as relevant context is provided to be added to complete the prompts.
Enhanced Search Endpoints:
It provides a huge back support for the answers as well as classifications based upon a vast number of documents while it is also extremely cheap.
Classification endpoints:
GTP-3 searches the optimum output from among a large dataset related to that of the input query and gives the performance of a high-end machine learning fine-tuned model without any explicit need for fine-tuning.
Safety:
GTP3 developers are compelled to ensure safety measures while developing like user verification and testing, humans in the loop verification, rate limits etc. before their applications get approval for production. Only those applications pass the reviews and get production approved which use the transformer in a responsible way. The indications for misuse of the platform are also actively monitored and necessary actions are taken accordingly. A content filter has also been made part of the transformer for sensitive text classification which ultimately leads to a higher rate of false positives.
So, this was all about GPT-3, its developers, its working, and its awesomeness. The real question is, what are you going to do with GPT-3 now? Tell us in the comments!
