21st-century humans are incredible. We're empowering artificial intelligence and machine learning and stretching its functional, predictable, and understanding power to a new level of efficiency with every coming day.
The past two decades have truly shown how far humans can take technology, and fortunately, we were able to perpetuate the growth of artificial intelligence and its products. However, who knew that one day AI would be smart enough that it would generate computer code just by giving a few input instructions?
Among many great OpenAI ideas is the GPT-3 model.
GPT-3 is OpenAI's greatest third-generation language prediction model (and the successor to GPT-2), which OpenAI introduced in 2020. And the model is the current sensation on the internet as people around the globe are mesmerized by it.
Logically, while GPT-3 has the spotlight currently, some say the introduction of GPT-4 in the tech market will steal GPT -3's place.
A game-changing revolution in AI is drastically changing the technological world!
AI-based software models are trained to learn through the deep learning model transformer's neural network architecture to understand and generate text of any sort. However, GPT-3 works more efficiently than GTP-2, which is obvious. It has an increased capacity and considerably more parameters and was trained on unlimited words while it can also code in CSS, Python, and many other languages.
OpenAI creates it, and it only needs a brief description of your requirements in text form and produces detailed machine-generated content with accuracy.
With over 175 billion ML parameters, OpenAI's GPT-3 model is currently the largest trained language model, and, therefore, is considered efficient in terms of producing text that appears to be produced by a person.
What are the Parameters?
An AI-based model parameter is a configuration variable whose value may be calculated from other estimated data. They're needed by the model when making predictions. Their values define the intelligence of a model when you ask a question or find a solution to your problem. Parameters are crucial to machine learning algorithms to predict new data.
Popular GPT-3 OpenAI Use Cases
AI is going above expectation and beyond imagination. Here's why!
The GPT-3 can answer users' questions with mind-blowing accuracy. And certainly, with the smart-human-like-intelligent AI technology, organizations and developers are admiring its wonders in their digital work procedures.
Tech-savvies have made the best use of the offerings the world's largest AI-based language model has to offer. To that end, let's briefly discuss some best GPT-3 OpenAI use cases.
The integration of GPT-3 and Figma plugins has enabled us to create stunning customized website layouts and designs. The designer will describe the template in textual form, and GPT-3 will assist in automatically creating an attractive application.
The app is trained to create exceptional user-friendly UI layouts, all thanks to GPT-3 intelligence.
The Resume Creator
Job seekers face a significant issue when it comes to writing an effective and brief CV for job interviews. GPT-3 can assist in creating resumes that stand out. Simply write your description, and it will provide you with the best suggestions to strengthen your CV and get your interview calls within a short time.
The AI recursion
You might not even imagine that machine learning models could write different potent machine learning models. It may sound impossible, but GPT-3 can already create ML models tailored to specific tasks and datasets. The user specifies the dataset and the desired output, and GPT-3 assists in producing code for an ML model.
GPT-3 can be used for effective code generation comprehension as well as code comprehension. GPT-3 can fully understand Python code.
In general, other uses of GPT-3 show that it can generate:
OpenAI GPT-3 – An Assistant with Incredible Capabilities
GPT-3 can code
GPT-3 can write functional code that can be executed without error with just a defined text line of the required functionality. Additionally, GPT-3 has been effectively applied to create website mockups.
Developers are smartly using GPT-3 in a variety of ways – from utilizing it in excel functions, plots, and charts to generating code and snippets to implementing GPT-3 in other development applications.
In the gaming industry, GPT-3 is also used to generate realistic chat dialogue, quizzes, images, and other graphics from text suggestions. In addition, GPT-3 can also produce comic strips, recipes, and memes.
GPT-3 can do a wide range of language tasks like translations, answering questions, and providing other work-related solutions.
GPT-3 can Answer Your Questions
With the help of the new prompt self-ask method, GPT-3 model asks itself intermediate questions to answer a complex question. With this method, GPT-3 is able to provide accurate, reasonable, and reliable answers to your queries – be they simple or multi-stepped complex questions. Moreover, to gain more accurate results from GPT-3, combining the self-ask method with Google search results in precise answers.
The language model searches Google to answer an intermediate question and feeds it into the self-ask method. Once all the questions are answered, the model decides on the final answer to the question.
However, when the test was conducted by asking multi-level questions, both self-ask and self-ask with Google search results were considerably more accurate than direct prompts, chain-of-thought prompts, and direct Google searches.
Moreover, the self-ask doesn't work depending on the size of the language model, which means large language models might have more knowledge or data, but it's possible that they could not reason your answers with accuracy.
GPT-3 can Write
GPT-3 is trained smart enough that it can change plain text into different writing styles. So, for example, you can provide a normal text like "artificial intelligence is taking the world to the next level," and you can ask the model to change it into other writing forms.
To that end, you can best utilize the GPT-3 intelligence for producing emails, changing the content tone, writing essays or letters, or even obtaining content based on described writing types such as persuasive, narrative, descriptive, etc.
GPT-3 has a wide range of applications because of its potent text generation capabilities. For example, GPT-3 is used to generate creative writing that imitates the writing styles of Shakespeare, and other well-known authors, including blog posts, advertising copies, and even poetry.
Will there be GPT4?
As GPT-3 is a successor to GPT-2, we can expect GPT-4 to be unveiled in the near future. However, whenever GPT-4 arrives, it might not need a huge number of parameters, but some have to say that GPT-4 will have 100 trillion parameters, and it would be 500x the size of GPT-3, mind-blowing!
But we can't validate our conclusions over predictions about the GPT-4 until it gets released.
What to expect from GPT-4?
It is most likely that GPT-4 will be a text-only model (not multimodal). OpenAI is trying to use language models to their best before jumping to multimodal models like DALL·E. GPT-4 is going to be larger than GPT-3. However not as large as compared to the present largest models.
It is said that following the trends from GPT-2 and GPT-3, GPT-4 will be a dense model (a dense layer of neurons where each neuron gets input from all other neurons of the previous layer). Therefore all parameters will be in use to respond to any given input.
Therefore, sparsity might be dominant as it maintains the accuracy of approaches using dense math on AI tasks such as image classification, language translation, and object detection. Moreover, sparsity can yield statistical benefits.
Moreover, it's possible that GPT-4 can use more processing power than GPT-3. Moreover, it'll implement optimality insights on parameterization and scaling laws. In addition, GPT-4 is going to be more aligned than GPT-3 as it would be designed to implement learnings from InstructGPT (that was trained with human feedback). However, AI alignment requires more human effort and should be carefully tackled.
Is there anything more that you should know about?
After the rapid popularity of OpenAI's ChatGPT, Google has decided to issue a "code red" as GPT-3 has raised serious concerns over the future of Google's search engine, as The New York Times reported.
The debate about the ChatGPT will be able to replace the search engine and affect Google's ad revenue business model has been a hot trend in the market lately. It is being said that GPT-3 could prevent users from clicking on Google links with ads, generating a huge revenue of $208 billion, equal to more than 80% of Alphabet (Google's parent company).
Keeping upfront search engine issues that Google has been focusing on, it is clearly observed that users have been asking chatbots to write and code, which could disrupt Google's business model and traditional internet searches.
However, as per AI experts, GPT-3 could not verify facts, and the results were based on misinformation. Moreover, a high rate of errors, misleading results, and vulnerabilities are why Google hesitates to launch its AI chatbot LaMDA (language model for Dialogue applications).
According to Zoubin Ghahramani, lead at Google's AI lab Google Brain, "Chatbots are not something that people can use reliably on a daily basis."
However, despite all the facts, Google continues to improve its search engine, which could align with modern-day needs.
Undoubtedly, GPT-3 is the greatest AI-based upgradation of all time. Its outputs, unquestionably, are what drive the world to move even faster and smarter. The GPT-3 technology has a wide range of applications and uses cases.
Since artificial intelligence and Machine learning has taken hold of the tech world, the future opportunities look endless. Therefore, we must keep up our skills and knowledge that best fits the wonderful aspects of the AI-based and close-to-magic tools/products/offerings that add significant value to our day-to-day work life.
To put the upfront OpenAI ideas, who knows what the future holds in the tech realm, especially regarding artificial intelligence and machine learning?
With the rapid change and challenges that OpenAI has brought front with OpenAI use cases, we can assume that many more wonders are yet to happen.
If you want to gain a new perspective on your project based on AI and want to integrate openAI API into your project, get in touch with us today!