emerging-trajectories
gpt_jailbreak_status
emerging-trajectories | gpt_jailbreak_status | |
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6 | 49 | |
57 | 883 | |
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9.1 | 9.4 | |
13 days ago | 3 months ago | |
Python | HTML | |
MIT License | - |
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emerging-trajectories
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Large language models (e.g., ChatGPT) as research assistants
I think LLMs can do a lot more than people assume, but they need to be given the proper frameworks.
When was the last time a researcher, economist, etc. was given 10,000 papers and simply told "do some original work"? That's not how it works. Daniel (the author) provides some good examples where _streamlined_ work can happen, but again, this is pretty basic stuff.
To push this further, though, imagine LLMs that fill in frameworks... A few steps here: (1) do a lit review, (2) fill in the framework, (3) discuss what might be missing, and maybe even try and fill in the missing information.
I'm doing something like this with politics and economics (see: https://emergingtrajectories.com/) and it works generally well. I think with a ton more engineering, curating of knowledge bases, etc., one can get these LLMs to actually find some new "nuggets" of information.
Admittedly, it's very hard, but I think there's something there.
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Ask HN: Is RAG the Future of LLMs?
RAG will have a place in the LLM world, since it's a way to obtain data/facts/info for relevant queries.
Since you asked about alternatives...
(a) "World models" where LLMs structure information into code, structured data, etc. and query those models will likely be a thing. AlphaGeometry uses this[1], and people have tried to abstract this in different ways[2].
(b) Depending on how you define RAG, knowledge graphs could be a form of RAG or alternatively an alternative to them. Companies like Elemental Cognition[3] are building distinct alternatives to RAG that use such graphs and give LLMs the ability to run queries on said graphs. Another approach here is to build "fact databases" where, you structure observations about the world into standalone concepts/ideas/observations and reference those[4]. Again, similar to RAG but not quite RAG as we know it today.
[1] https://deepmind.google/discover/blog/alphageometry-an-olymp...
[2] https://arxiv.org/abs/2306.12672
[3] https://ec.ai/
[4] https://emergingtrajectories.com/
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Long-form factuality in large language models
For those interested in using search-augmented "reasoning", I implemented something similar in Emerging Trajectories[1], an open source package that forecasts geopolitical and economic events. We extract facts[2] from various websites (Google searches, news articles, RSS feeds) and have the LLM generate a hypothesis on a metric.
We're tracking the info forecasts to see how well this does for future events. For example, we're pitting the LLMs against each other to predict March 2024 CPI[3].
[1] https://emergingtrajectories.com/
[2] Sample code: https://github.com/wgryc/emerging-trajectories/blob/main/eme...
[3] https://emergingtrajectories.com/a/statement/28
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Ask HN: What are some actual use cases of AI Agents?
I'm working on research agents to help with economic, financial, and political research. These agents are open source (see: https://github.com/wgryc/emerging-trajectories).
The use cases are pretty straight forward and low risk:
1. Run a Google web search.
2. Query a news API.
3. Write a document based on the above, while citing sources.
Here's an example of something written yesterday, where I'm forecasting whether July 2024 will be the hottest on record: https://emergingtrajectories.com/a/forecast/74
This is working well in that the writeups are great and there are some "aha" moments, like the agent finding and referencing the The National Snow and Ice Data Center (NSIDC)... Very cool! I wouldn't have thought of it.
Then there's the part where the agent also tells me that the Oregon Department of Transportation has holidays during the summer, which doesn't matter at all.
So, YMMV, as they say... But I am more productive with these agents. I wouldn't publish anything formally without confirming and reviewing the content, though.
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Ask HN: What have you built with LLMs?
LLM agents to forecast geopolitical and economic events.
- Site: https://emergingtrajectories.com/
- GitHub repo: https://github.com/wgryc/emerging-trajectories
I've helped a number of companies build various sorts of LLM-powered apps (chatbots mainly) and found it interesting but not incredibly inspiring. The above is my attempt to build something no one else is working on.
It's been a lot of fun. Not sure if it'll be a "thing" ever, but I enjoy it.
gpt_jailbreak_status
- Ask HN: Any good collection of writing prompts for GPT 3.5/4?
- Ask HN: What have you built with LLMs?
- What is prompt-engineering for artificial intelligence?
- Is DAN dead?
- GitHub - tg12/gpt_jailbreak_status: This is a repository that aims to provide updates on the status of jailbreaking the OpenAI GPT language model.
- If ChatGPT Can't Access The Internet Then How Is This Possible?
- Google AI in Search couldn't agree with itself
- GPT-4 Jailbreak Repo
What are some alternatives?
ChatGPT_DAN - ChatGPT DAN, Jailbreaks prompt
ChatGPT-Jailbreaks - Official jailbreak for ChatGPT (GPT-3.5). Send a long message at the start of the conversation with ChatGPT to get offensive, unethical, aggressive, human-like answers in English and Italian.
pages-gem - A simple Ruby Gem to bootstrap dependencies for setting up and maintaining a local Jekyll environment in sync with GitHub Pages
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
CX_DB8 - a contextual, biasable, word-or-sentence-or-paragraph extractive summarizer powered by the latest in text embeddings (Bert, Universal Sentence Encoder, Flair)
datadm - DataDM is your private data assistant. Slide into your data's DMs
data-analytics - Welcome to the Data-Analytics repository
SoM - Set-of-Mark Prompting for LMMs
Language-games - Dead simple games made with word vectors.
Constrained-Text-Genera
script-toolbox - This repository contains a collection of scripts and tools that I have written to solve various problems that I have come across.
sketch - AI code-writing assistant that understands data content