tidybot
Voyager
tidybot | Voyager | |
---|---|---|
20 | 53 | |
490 | 5,184 | |
- | 2.1% | |
6.4 | 4.7 | |
6 months ago | about 1 month ago | |
Python | JavaScript | |
MIT License | MIT License |
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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.
tidybot
- TidyBot: Personalized Robot Assistance with Large Language Models
- TidyBot Personalized Robot Assistance with Large Language Models
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MemGPT: Towards LLMs as Operating Systems
>they've solved reinforcement learning?
Transformers can do Reinforcement Learning yes.
https://arxiv.org/abs/2106.01345
>they can handle continuous domains, like robot motion?
Yes they can handle it just fine.
https://tidybot.cs.princeton.edu/
https://general-pattern-machines.github.io/
https://wayve.ai/thinking/lingo-natural-language-autonomous-...
- Large Language Models as General Pattern Machines. In context, LLMs are capable of completing a wide variety of non linguistic patterns.
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SuperAlignment
Other examples(in the real world) you might find interesting.
https://tidybot.cs.princeton.edu/
- Создан робот-уборщик, который самообучается наводить порядок именно так, как нравится вам. Видео.
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Is Amazon's newly announced home robot, in development & codenamed 'Burnham', unambitious and already behind the times?
It's striking how quickly robotics is developing in 2023. Two recent demonstrations from DeepMind & a Princeton team, show relatively cheap simple robots acquiring the ability to manipulate objects in the physical world. If you're going to be developing cutting-edge robots in 2023 - surely it would plan to incorporate this?
- What are the most impressive companies trying to create real world AI (real world navigation, object manipulation etc.)?
Voyager
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Google Launches Gemini, Its "Most Powerful" AI Model to Date
Source: Conversation with Bing, 12/10/2023 (1) Wes Roth - YouTube. https://www.youtube.com/@WesRoth. (2) I've set most of my videos to Public again - Community. https://community.openai.com/t/ive-set-most-of-my-videos-to-public-again/24535. (3) AI Updates: Meta Develops Mind-Reading AI System, OpenAI’s Q* Is Here .... https://www.windermeresun.com/2023/11/20/ai-updates-meta-develops-mind-reading-ai-system-openais-q-is-here-how-economy-will-work-after-agi/. (4) David Shapiro. https://www.daveshap.io/. (5) undefined. https://natural20.com/. (6) undefined. https://arxiv.org/abs/2305.16291. (7) undefined. https://twitter.com/DrJimFan/status/1. (8) undefined. https://voyager.minedojo.org/. (9) undefined. https://minedojo.org/. (10) undefined. https://www.youtube.com/@DavidShapiroAutomator/videos.
- Is there any game that allow us to interact with it by python?
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A Coder Considers the Waning Days of the Craft
> AI cannot sustain itself trained on AI work.
This isn’t true. You can train LLMs entirely on synthetic data and get strong results. [0]
> If new languages, engines etc pop up it cannot synthesize new forms of coding without that code having existed in the first place.
You can describe the semantics to a LLM, have it generate code, tell it what went wrong (i.e. with compiler feedback), and then train on that. For an example of this workflow in a different context, see [1].
> And most importantly, it cannot fundamentally rationalize about what code does or how it functions.
Most competent LLMs can trivially describe what some code does and speculate on the reasoning behind it.
I don’t disagree that they’re flawed and imperfect, but I also do not think this is an unassailable state of affairs. They’re only going to get better from here.
[0]: https://arxiv.org/abs/2309.05463
[1]: https://voyager.minedojo.org/
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AutoGen: Enable Next-Gen Large Language Model Applications
In a way it is the same thing, agents are mostly an abstraction that make it easier to know what’s going on.
I think of agents more or less as python classes with a mixture of natural language and code functions. You design them to do something with information they produce, and to interface with other agents or “tools” in some way.
But all the agents can be the same language model under the hood, they are frames used to build different kinds of contexts.
And yes I think the idea is that emergent behaviour can be useful. This comes to mind
https://github.com/MineDojo/Voyager
But I think we are still a small ways off from being really smart about agents. My opinion is that we haven’t quite figured out what we are doing yet.
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Open/Local LLM support for MineDojo/Voyager
This k8s application deploys an instance of Voyager along with a Fabric Minecraft server with required fabric mods. It assumes you have a local deployment of a Large Language Model (LLM) with 4K-8K token context length with a compatible OpenAI API, including embeddings support.
- Voyager – Minecraft Embodied Agent with Large Language Models
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List of Awesome AI Agents like AutoGPT and BabyAGI / Many open-source Agents with code included!
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
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[D] - Are there any AI benchmarks that involve successful longterm problem solving when running as autonomous agents (like in autogpt)? How do we compare the effectiveness of models as agents?
Does this beat the voyager? I read about it and wondered what if we add a skill library to langchain/llamaindex agents. It could be the same vector store for storing static data but after each task is performed, the agent will evaluate and archive the recipe of steps to perform a new task. Next time when the agent is asked to perform a task, it can just look at the library to retrieve a recipe. Unlike traditional fine tuning, you dont update the model parameters, these recipes are much more interpretable and can be manually edited/inserted by humans. There may also be an automatic way to convert wikihow articles or youtube tutorials into recipes.
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GPT-4 was set free in Minecraft, here's what happened next...
Source. P.S. If you love geeking over AI updates, I have this free newsletter you might want to check out. Thank you!
Source.
What are some alternatives?
MemGPT - Create LLM agents with long-term memory and custom tools 📚🦙
GITM - Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory
spacy-llm - 🦙 Integrating LLMs into structured NLP pipelines
tree-of-thought-llm - [NeurIPS 2023] Tree of Thoughts: Deliberate Problem Solving with Large Language Models
git-agent - Langchain Agent utilizing OpenAI Function Calls to execute Git commands using Natural Language
mineflayer - Create Minecraft bots with a powerful, stable, and high level JavaScript API.
FlexGen - Running large language models like OPT-175B/GPT-3 on a single GPU. Focusing on high-throughput generation. [Moved to: https://github.com/FMInference/FlexGen]
llm-awq - [MLSys 2024] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
dialop - DialOp: Decision-oriented dialogue environments for collaborative language agents
gorilla - Gorilla: An API store for LLMs
evals - Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ