GPT stands for Generative Pre-Training Transformer. It is a neural network machine learning model that is trained using data from the Internet to generate any type of text. This complex neural network is used to train large language models (LLMs) to simulate human communication.
The model tracks words sequentially, allowing it to learn the context and meaning of the language. The GPT model focuses on plain text, allowing it to use artificial intelligence to analyze user queries and generate text efficiently.
It has taken the artificial intelligence world by storm with its conversational capabilities, contextual information, and more. The model can handle tasks such as text summarization, code generation, and more and provide valuable insights in seconds.
GPT-3 is an autoregressive language model that is trained by predicting the next token . The model will need an initial prompt text and can use that initial prompt to continue generating text.
Reinforcement Learning with Human Feedback (RLHF) is used to help the model achieve conversational dialogue with the user. GPT-3 is a 175 billion parameter language model with the following use cases:
If you want to learn more about ChatGPT-3, read: ChatGPT: Everything You Need to Know. https://www.kdnuggets.com/2023/01/chatgpt-everything-need-know.html
When Microsoft Germany CTO Andreas Braun announced that GPT-4 was scheduled to go offline in the third week of March, there was a lot of speculation. Dr. Andreas Braun said in AI in Focus: Digital Kickoff: "We will launch GPT-4 next week, where we will have multi-modal models that offer completely different possibilities - such as video"
At this time, it was not until March 14, 2023 that OpenAI itself made a clear announcement. So what should we expect from GPT-4? GPT-4 is OpenAI’s new technology that delivers state-of-the-art systems that produce safer, more useful responses.
OpenAI president and co-founder Greg Brockman said in the GPT-4 Developer Livestream that OpenAI has been building GPT-4 since the company was founded, and has focused on perfecting the new technology for the past 2 years. They had to rebuild the entire train stack and train the model to see what it was capable of.
ChatGPT-4 is multi-modal, meaning it can use multiple data types such as images, text, speech and numeric data as well as multiple intelligent processing algorithms to produce accurate, high-performance output. It is no longer limited to being a language model.
Explanation of the role of ChatGPT-4
For example:
'You are ChatGPT, a large language model. Follow the user's instructions carefully 'Summary the specifics
However, the assistant said the word "AI" and Greg Brockman responded "AI doesn't count!" That's cheating! '. The assistant happily responded with a word that replaced "AI" and started with the letter "G."
GPT-4 can specifically output what the user wants by giving requests to the assistant.
Combine ideas
If the ChatGPT-4 assistant's output doesn't quite meet your requirements or isn't in-depth enough, you can provide feedback, which will improve its response.
Using Generate and Build GPT-4
Depending on the role assigned to ChatGPT-4 in the system part, for example if an assistant is expected to build some code generation stuff - they will be assigned as an AI programming assistant. As prompted, this will successfully help the assistant output the requested content.
You can test the code block generated by the assistant to see if it works. If you do encounter an error, just send the error message to the assistant and provide the correct code block. You can continue doing this and coaching the assistant until the code runs successfully.
Being able to solve complex calculations such as tax and advanced calculation problems can be a challenge. ChatGPT-4 can now be used to help with these mathematical calculations. For example, if there is a tax problem that you want to calculate, you need to designate the ChatGPT-4 system as a TaxGPT so that it knows what its role is.
Provide context about the problem and the assistant will be able to perform mathematical calculations. Interestingly, the model is not connected to a calculator – impressive right?
The picture feature is not yet available - but it is in development! You can enter an image and ask the Assistant questions about the image. Currently, output does take a while, however, OpenAI is optimizing the model to make it faster.
You can take a snapshot of a handwritten text, and ChatGPT can read the handwritten content and convert it into text. Some even joked about how it could detect a doctor's handwriting - something that there were and still are efforts to understand.
It is already known that ChatGPT has no knowledge after September 2021. However, you can provide articles or information to ChatGPT as a prompt for what you want to ask the assistant. The assistant will use it as a learning resource to provide accurate output.
If you wish to contribute to ChatGPT, provide feedback and comments - you can use Evals to do so. Evals is a framework for evaluating an open source registry of OpenAI models and benchmarks.
Evals allows you to create and run evaluations:
This will help evaluate and examine the capabilities of the model and how OpenAI can improve it and take it to the next level.
Since the release of ChatGPT-3.5, we have seen many changes and advancements in ChatGPT-4. It's great to see people planning to make stuff using ChatGPT-4.
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