JARVIS VS babyagi

Jarvis: github.com/microsoft/JARVIS

You can build it yourself now. https://github.com/microsoft/JARVIS

https://github.com/microsoft/JARVIS (when ready says >=24GB VRAM)

Can be. There are projects that run fully locally like Microsoft’s Jarvis. https://github.com/microsoft/JARVIS

JARVIS, a system to connect LLMs with ML community (https://github.com/microsoft/JARVIS)

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”.

Define agency. Does AutoGPT or BabyAGI fit the definition?

BabyAGI: github.com/yoheinakajima/babyagi

In my opinion the most interesting Agents: Auto-GPT Github: https://github.com/Significant-Gravitas/Auto-GPT BabyAGI Github: https://github.com/yoheinakajima/babyagi Voyager Github: https://github.com/MineDojo/Voyager / Paper: https://arxiv.org/abs/2305.16291 I would also add: ChemCrow: Augmenting large-language models with chemistry tools Github: https://github.com/ur-whitelab/chemcrow-public/ Paper: https://arxiv.org/abs/2304.05376

People also have been trying to build multi-agent and task-planning systems. MS research in Asia seems to produce decent results with Task Matrix and HuggingGPT. Similar things have been tried in the form of Auto-GPT and BabyAGI , but both projects are setting their goal so high that they may not achieve the at all, and they are likely to see a complete rework when multi-modal solutions become widespread.

Joke's on you, /u/ILoveThisPlace is actually just a bot responding using the BabyAGI script, we've all been had!

BabyAGI AI-Powered Task Management for OpenAI + Pinecone or Llama.cpp

Yes, we haven't seen anything like that yet. But we do see the people trying to build these things (see AutoGPT, babyagi, ChaosGPT, etc) today, and with the last few years of advancement in LLMs they now have the fundamental building blocks to succeed in the near term (say the next 5 years) rather than in some imaginary far future.

You should check out some of the projects that combine LangChain with LLMs to automate this process like BabyAGI (https://github.com/yoheinakajima/babyagi) and AutoGPT (https://github.com/Significant-Gravitas/Auto-GPT). They were originally designed around ChatGPT models but have expanded to include llamacpp as an alternative. These provide your language models with the ability to save long term memory, a goal-oriented task list and extra functionality like surfing the web and, in some cases, creating and modifying files on disk.