PentestGPT
JARVIS
PentestGPT | JARVIS | |
---|---|---|
18 | 52 | |
6,361 | 23,054 | |
- | 0.7% | |
8.2 | 7.2 | |
13 days ago | 9 days ago | |
Python | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
PentestGPT
- PentestGPT
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PentestGPT, a gpt-powered penetration testing tool, open source
👨💻 Source: https://github.com/GreyDGL/PentestGPT
- PentestGPT: GPT-Powered Penetration Testing
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April 2023
A GPT-empowered penetration testing tool (https://github.com/GreyDGL/PentestGPT)
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Fundamental LangChain Question
How you use it is up to you. There are hundreds of question answer clones with different data source adapters. Some projects that I found more interesting: https://github.com/GreyDGL/PentestGPT https://github.com/jina-ai/dev-gpt https://github.com/corca-ai/EVAL You can probably build something similar to smol developer with langchain too.
- Why are so many people vastly underestimating AI?
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Hackathon Ideas? Gen AI
Look up langchain. Some example projects. https://github.com/corca-ai/EVAL https://github.com/jina-ai/dev-gpt https://github.com/GreyDGL/PentestGPT https://blog.langchain.dev/origin-web-browser/
- GreyDGL/PentestGPT: A GPT-empowered penetration testing tool
JARVIS
- FLaNK Stack 26 February 2024
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Overview: AI Assembly Architectures
Jarvis: github.com/microsoft/JARVIS
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When will we get JARVIS?
You can build it yourself now. https://github.com/microsoft/JARVIS
- How to build the Geth (networked intelligence, decentralized AGI)
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Off-topic: What NVIDIA GPU do I need to run privateGPT or Alpaca-Lora for code translations, debugging, unit tests, etc?
https://github.com/microsoft/JARVIS (when ready says >=24GB VRAM)
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Apple announces Apple Silicon Mac Pro powered by M2 Ultra
Can be. There are projects that run fully locally like Microsoft’s Jarvis. https://github.com/microsoft/JARVIS
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April 2023
JARVIS, a system to connect LLMs with ML community (https://github.com/microsoft/JARVIS)
- Nvidia's GH200 AI supercomputers could build 'giant' AI models more powerful than GPT-4
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A Lightweight HuggingGPT Implementation w/ Langchain + Thoughts on Why JARVIS Fails to Deliver
HuggingGPT is a clever idea to boost the capabilities of LLM Agents, and enable them to solve “complicated AI tasks with different domains and modalities”. In short, it uses ChatGPT to plan tasks, select models from Hugging Face (HF), format inputs, execute each subtask via the HF Inference API, and summarise the results. JARVIS tries to generalise this idea, and create a framework to “connect LLMs with the ML community”, which Microsoft Research claims “paves a new way towards advanced artificial intelligence”.
- Edit videos through intuitive ChatGPT conversations
What are some alternatives?
llama.cpp - LLM inference in C/C++
AutoGPT - AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
ChatGLM2-6B - ChatGLM2-6B: An Open Bilingual Chat LLM | 开源双语对话语言模型
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/Auto-GPT]
deepdoctection - A Repo For Document AI
babyagi
langcorn - ⛓️ Serving LangChain LLM apps and agents automagically with FastApi. LLMops
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/AutoGPT]
developer - the first library to let you embed a developer agent in your own app!
visual-chatgpt - Official repo for the paper: Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models [Moved to: https://github.com/microsoft/TaskMatrix]
vocode-python - 🤖 Build voice-based LLM agents. Modular + open source.
dalai - The simplest way to run LLaMA on your local machine