What is GPT? 7 interesting things about GPT3 and GPT4 you need to know

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What does GPT stand for?

Generative: Generative AI is a technology that can generate content such as text and images.

Pre-trained: A pre-trained model is a saved network that has already been trained to solve a problem or perform a specific task using a large data set.

Transformer: Transformer is a deep learning architecture that transforms one input into another type of output.

Breaking down the acronyms above will help you remember what GPT does and how it works. GPT is a generative AI technique that is pre-trained to transform an input into another type of output.

What is GPT?

The GPT model is a general-purpose language prediction model. In other words, it is a computer program that can analyze, extract, summarize, and otherwise use information to generate content. One of the most well-known use cases for GPT is chat-gpt. It is an artificial intelligence (AI) chatbot app based on the GPT 3.5 model that mimics natural conversations to answer questions and respond to prompts. GPT was developed by the AI research institute OpenAI in 2018. Since then, Open AI has officially released three versions of the GPT model: GPT2, GPT3, and GPT4.

GPT is a family of AI models created by OpenAI. This stands for Generative Pre-trained Transformer and basically explains what the AI model does and how it works (more on this later).

Although the latest GPT model, GPT, is in its fourth generation, various versions of GPT3 are still widely used.

Although this article often uses Chat GPT as an example, it is important to remember that GPT is not just ChatGPT but an entire family of large-scale language models (LLMs).

GPT-1

GPT-1 is the first version of OpenAI’s language model. This was followed by Google’s 2017 paper, “Attending Is All You Need”, in which researchers introduced the first general transformer model. Google’s innovative Transformer model serves as the framework for Google Search, Google Translate, autocomplete, and all large-scale language models (LLMs), including BARD and Chat-GPT.

GPT-2

GPT-2 is Open AI’s second transformer-based language model. It is open source, unsupervised and trained on over 1.5 billion parameters. GPT-2 is specifically designed to predict and generate the next text sequence after a given sentence.

GPT-3

The third version of Open AI’s GPT model has been trained with 175 billion parameters, a significant improvement over its predecessor. This includes Open AI text such as Wikipedia entries and the open source data set Common Crawl. Specifically, GPT-3 can generate computer code to improve performance in specific areas of content creation, such as storytelling.

GPT-3 is a language prediction model. This means it has a neural network machine learning model that can take input text and transform it into something that predicts the most useful outcome. This is achieved by training the system on large amounts of Internet text to find patterns in a process called generative pre-training. GPT-3 was trained on multiple datasets, each with different weights, including Common Crawl, WebText2, and Wikipedia.

GPT-3 is trained first through a supervised testing phase and then through a enrichment phase. When training ChatGPT, a team of trainers ask questions of the language model with the correct output in mind. If the model gives the wrong answer, the instructor makes changes to the model to teach the correct answer. The model can also provide several answers that the instructor ranks from best to worst.

GPT-3 has over 175 billion machine learning parameters, which is significantly larger than its predecessors (previous large language models such as Bidirectional Encoder Representations in Transformers (BERT) and Turing NLG). Parameters are part of a larger language model that defines skills for problems such as text generation. In general, the performance of large language models increases with the amount of data and parameters added to the model.

GPT-4

GPT-4 is the latest model from Open AI. It is a large-scale multimodal model (LMM), which means it can analyze not only text but also image inputs. This iteration is the most advanced GPT model and demonstrates human-level performance in a variety of benchmarks in professional and academic domains. For comparison, the GPT-3.5 scored in the bottom 10 percent of test takers on the mock bar exam. GPT-4 scored in the top 10%.

What can ChatGPT-4 do?

A more advanced version of ChatGPT called ChatGPT-4 is now available for paid subscribers ($20/£16/month).
Here are some of the tasks you can do with the latest versions of AI models.
• learn a language. Chat with Chat GPT in 26 languages
• Create a recipe. ChatGPT-4 can recognize images. You can send pictures of ingredients to ChatGPT and ask the AI to create a recipe for you.
• Explain pictures to blind people

What is ChatGPT?

Chat GPT soon became the golden child of artificial intelligence. Used by millions of users, AI chatbots can answer questions, tell stories, write web code, and even conceptualize incredibly complex topics.

This AI tool developed by Open AI has gone through several changes since it was first announced. A free version exists, but there is also a paid version known as Chat GPT Plus and Chat GPT Enterprise.

The free version of Chat GPT (GPT-3.5) is available for anyone to use on the Chat GPT website. Simply sign up, login and start exploring the depths of your AI models in just seconds. Chat GPT is also available for Android and Apple devices

A more advanced version of Chat GPT known as ChatGPT-4 is also currently available, but only for paid subscribers.

AI has achieved a lot since its introduction, being adopted by large corporations, rejected by schools, and used by millions of users every day. Controversial and celebrated in equal measure, it is a truly divisive tool.

There are currently many competitors (such as Google Bard), so Chat GPT has to constantly improve and introduce new features. The latest of these is the introduction of the Dall-E 3. Dall-E 3 works together with Chat GPT to make your vision a reality.

So how does this device work? Why is it so controversial? So how does Chat GPT actually work? With the help of AI researchers and experts, we’ve answered these and other questions in this detailed guide to Open AI’s most popular tools.

Learn more interesting about Chat GPT

What does GPT do?

GPT models are designed to generate human-like text in response to prompts. Originally, these prompts were supposed to be text-based, but recent versions of GPT also allow images.

This allows GPT-based tools to do the following:

Answer the questions conversationally.
Create blog posts and other types of short and long content.
Edit the tone, style and grammar of your content.
Summarize long texts
Translate text into another language
brainstorm ideas

You can use ChatGPT-3.5 to:

Write essays
Write excel formulas
Write poems and movie scripts
Research topics and summarise content
Help you build a cover letter or CV
Write code
Plan a holiday

Chat GPT has a wide range of abilities, including writing sentimental farts and poems about cliched romances in other worlds, explaining quantum mechanics in simple terms, or writing long research papers.

It can be fun to use Open AI’s years of research to help AI write a bad stand-up comedy script or answer questions about your favorite celebrity, but its power lies in its speed and complexity.

Where you can spend hours researching, understanding, and writing about quantum mechanics, Chat GPT lets you create well-written options in seconds.

It has its limitations, and its software can easily become confusing if the prompts get too complex or you go down a path that’s a little too specific.

Similarly, you cannot handle concepts that are too new. Global events that have occurred in the past year are addressed with limited knowledge, and the model may sometimes generate inaccurate or confusing information.

Open AI is also well aware of the Internet and AI’s interest in generating dark, harmful or biased content. Like previous Dall-E image generators, Chat GPT prevents you from asking more inappropriate questions or asking for support for dangerous requests.

How does GPT work?

“Creating Pre-trained Transformer Models” explains exactly what the GPT family of models does, how they are designed, and how they work.

We’ll use GPT-3 as an example, the model we have the most information about. (Unfortunately, Open AI has become more secretive about its processes over the years.)

GPT-3 was pre-trained on large amounts of unlabeled data. It’s basically fed by the entire open Internet, and then it continues processing and draws its own connections. This technique, called deep learning, is a fundamental part of machine learning, through which most modern AI tools are developed.

It’s important to note that GPT doesn’t understand text exactly like humans do. AI models break text into tokens instead of words. Many words map to a single token, but longer or more complex words are often split into multiple tokens. GPT-3 was trained with approximately 500 billion tokens.

All of this training is used to create complex, multilayered, weighted algorithms modeled after the human brain, called deep learning neural networks. This gives GPT-3 the ability to understand patterns and relationships within text data and create human-like responses. GPT-3’s neural network has 175 billion parameters (or variables), and it takes inputs (signals) and outputs anything based on the values and weights you give to various parameters (and a small amount of randomness). . I think it is best suited for your request.

GPT’s network uses a transformer architecture. This is the “T” in GPT. At the core of Transformers is a process called “self-attention”. Older recurrent neural networks (RNNs) read text from left to right. Transformer-based networks, on the other hand, read all the tokens in a sentence together and compare each token with all the other tokens. This allows you to direct your “attention” to the most relevant tokens, no matter where they are in the text.

Of course, this is a huge simplification of all things. GPT doesn’t really understand anything. Instead, all tokens are encoded as vectors (numbers containing position and orientation). The closer the two token vectors are, the more closely GPT thinks they are related. That’s how we can handle the differences between grizzly bears, the right to bear arms, and ball bearings. All use the string “bear”, which is encoded in such a way that the neural network can determine which meaning is likely to be most relevant given the context.

GPT-3 is trained first through a supervised testing phase and then through a enrichment phase. When training Chat GPT, a team of trainers ask questions of the language model with the correct output in mind. If the model gives the wrong answer, the instructor makes changes to the model to teach the correct answer. The model can also provide several answers that the instructor ranks from best to worst.

Frequently Ask Question (FAQs)

What is the difference between GPT-4 and GPT-3.5?

The main difference between the models is that GPT-4 is multimodal, so it can use image inputs in addition to text, while GPT-3.5 can only process text inputs.

According to Open AI, the differences between GPT-3.5 and GPT-4 in casual conversation can be “subtle”. However, the new model will perform better in terms of reliability, creativity, and even intelligence, as shown by the better performance in the benchmark tests above.

What model does Chat GPT currently use?

Chat GPT is powered by GPT-3.5, which limits the chatbot to text input and output.

What is Microsoft Copilot?

Copilot is Microsoft’s AI chatbot, formerly known as Bing Chat. Powered by Open AI’s most advanced LLM, GPT-4. It can be accessed from a standalone website or from within the Bing web browser. The popularity of the chatbot lies in the fact that it has many of the same features as Chat GPT Plus, which includes Internet access, multimodal prompts, and sources without the $20 monthly subscription

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