What is ChatGPT?
It is a trained model which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.
ChatGPT is a tool in the GPT Tools category of a tech stack.
Who uses ChatGPT?
10 companies reportedly use ChatGPT in their tech stacks, including GO2, 4RWeb Interactive, and Papumba.
96 developers on StackShare have stated that they use ChatGPT.
ChatGPT for Google, ChatGPT Desktop, Sidekick AI, Haystack NLP Framework, and SupportGPT are some of the popular tools that integrate with ChatGPT. Here's a list of all 20 tools that integrate with ChatGPT.
Decisions about ChatGPT
Here are some stack decisions, common use cases and reviews by companies and developers who chose ChatGPT in their tech stack.
Shared a protip
New versions of ChatGPT work well with the open internet. The New Plugin Marketplace helps us consume data from third-party sources that site back to that source. In addition, ChatGPT has plugins for core Microsoft Stack products, such as Microsoft Teams & Microsoft Excel
- Interacts in a conversational way
- Answers follow-up questions
- Admits its mistakes
- Challenges incorrect premises
- Rejects inappropriate requests
ChatGPT Alternatives & Comparisons
What are some alternatives to ChatGPT?
See all alternatives
It is an experimental open-source application showcasing the capabilities of the GPT-4 language model. This program, driven by GPT-4, chains together LLM "thoughts", to autonomously achieve whatever goal you set.
It is an open-source project designed to make the process of creating charts easy. You can use this tool to generate charts based on your data.
It is a Slack and Discord bot that provides developer support, using the GPT API. It scales very well with documentation. It is also open source.
Create an AI-generated backend with just a few sentences. Every query generates a functioning API server with a descriptive documentation site. Everything -- including server code, persistent storage, docs request/response schemas, etc -- is generated on the fly.
It gives a large language model (LLM) control of a Linux machine. Each time it runs a command the result of this command gets sent to OpenAI and asks for a summary of what happened, then uses this summary as part of the next prompt.
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