Voyager
dreamGPT
Voyager | dreamGPT | |
---|---|---|
53 | 11 | |
5,184 | 543 | |
2.1% | 0.4% | |
4.7 | 1.0 | |
about 1 month ago | 10 days ago | |
JavaScript | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
dreamGPT
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Hallucination Is Inevitable: An Innate Limitation of Large Language Models
Hallucinations are essential for divergent thinking. Not everything is solved following goal driven approaches. Check out DreamGPT: https://github.com/DivergentAI/dreamGPT
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AI tests into top 1% for original creative thinking
Hallucinations are a feature, not a bug: dreamGPT: Leverage hallucinations from Large Language Models (LLMs) for novelty-driven explorations.
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I think generative AI is like man discovering fire but not knowing that they can make steam engines with it.
I agree that most people are focusing on the "surface" of what this new generation of AIs can do. Take for instance AI hallucinations. Everyone is avoiding them. What if they were actually a feature that could unlock a whole new set of possibilities? Check out: https://github.com/DivergentAI/dreamGPT
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AI Alignment explained by our favorite Sarcastic Programmer
Same as GPT hallucinations... "It's a feature, not a bug" https://github.com/DivergentAI/dreamGPT
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People who call GPT-4 a stochastic parrot and deny any kind of consciousness from current AIs, what feature of a future AI would convince you of consciousness?
Autonomous intent. All AI models today are directed by human defined intents. DreamGPT can give us a glimpse of this https://github.com/DivergentAI/dreamGPT
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What if LLM Hallucinations Were A Feature And Not A Bug? Meet dreamGPT: An Open-Source GPT-Based Solution That Uses Hallucinations From Large Language Models (LLMs) As A Feature
Github: https://github.com/DivergentAI/dreamGPT
- [Project] What if LLM hallucinations were a feature and not a bug?
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dreamGPT: AI-driven innovation
I highly recommend that you give it a try. You should be able to run it on any PC/Mac. No GPU is required. It's fascinating the quality of the ideas that it generates. You can see a sample of what you get just on the first step ("dream" phase) here: https://github.com/DivergentAI/dreamGPT/blob/main/docs/img/output.jpg
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Show HN: dreamGPT: What if LLM hallucinations were a feature and not a bug?
Yes, you can find a screenshot here (first "dream" iteration): https://github.com/DivergentAI/dreamGPT/blob/main/docs/img/o...
What are some alternatives?
GITM - Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory
tree-of-thought-llm - [NeurIPS 2023] Tree of Thoughts: Deliberate Problem Solving with Large Language Models
mineflayer - Create Minecraft bots with a powerful, stable, and high level JavaScript API.
llm-awq - [MLSys 2024] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
gorilla - Gorilla: An API store for LLMs
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
qlora - QLoRA: Efficient Finetuning of Quantized LLMs
prm800k - 800,000 step-level correctness labels on LLM solutions to MATH problems
craftassist - A virtual assistant bot in Minecraft
ChatDev - Create Customized Software using Natural Language Idea (through LLM-powered Multi-Agent Collaboration)
tidybot - TidyBot: Personalized Robot Assistance with Large Language Models