empirical-philosophy
transynthetical-engine
empirical-philosophy | transynthetical-engine | |
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9 | 6 | |
141 | 26 | |
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2.5 | 6.2 | |
about 1 year ago | about 1 year ago | |
TypeScript | TypeScript | |
- | MIT License |
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empirical-philosophy
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Google “We Have No Moat, and Neither Does OpenAI”
One way that I've been framing this in my head (and in an application I'm building) is that gpt-3 will be useful for analytic tasks where as gpt-4 will be required for synthetic tasks. I'm using "analytic" and "synthetic" in the same way as in this writeup https://github.com/williamcotton/empirical-philosophy/blob/m...
- How ReAct Prompting Works in Detail
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Ask HN: People who were laid off or quit recently, how are you doing?
Hey Simon! I've been digging your writings on LLMs lately.
I've been having some decent luck with some of the approaches that I've discussed in the following articles and projects:
From Prompt Alchemy to Prompt Engineering: An Introduction to Analytic Augmentation: https://github.com/williamcotton/empirical-philosophy/blob/m...
https://www.williamcotton.com/articles/writing-web-applicati...
https://github.com/williamcotton/transynthetical-engine
I'd love to hear your thoughts on the matter!
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We need to tell people ChatGPT will lie to them, not debate linguistics
You’re not actually doing any research.
Here is my research: https://github.com/williamcotton/empirical-philosophy/blob/m...
It is clear that analytic augmentations will result in more factual information.
Your claims are unfounded and untested.
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ChatGPT and Wolfram Is Insane
Take a look at
https://github.com/williamcotton/empirical-philosophy/blob/m...
https://langchain.readthedocs.io/en/latest/
They can be taught!
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Prompt Engineering Guide: Guides, papers, and resources for prompt engineering
I've been developing a methodology around prompt engineering that I have found very useful:
https://github.com/williamcotton/empirical-philosophy/blob/m...
A few more edits and it's ready for me to submit to HN and then get literally no further attention!
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Professor writes history essays with ChatGPT and has students correct them
That's not a rebuttable of a claim that Bing is more accurate.
A proper rebuttable would involve empirical evidence that Bing is no more accurate than other LLM tools that do not add analytical augmentations such as search results to their prompts.
Based on empirical evidence, I find that analytical augmentations do indeed result in more accurate results:
https://github.com/williamcotton/empirical-philosophy/blob/m...
transynthetical-engine
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Native JSON Output from GPT-4
Here’s an approach to return just JavaScript:
https://github.com/williamcotton/transynthetical-engine
The key is the addition of few-shot exemplars.
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The Dual LLM pattern for building AI assistants that can resist prompt injection
I think the two-layer approach is worthwhile if only for limiting tokens!
Here’s an example of what I mean:
https://github.com/williamcotton/transynthetical-engine#brow...
By keeping the main discourse between the user and the LLM from containing all of the generated code and instead just using that main “thread” to orchestrate instructions to write code it allows for more back-and-forth.
It’s a good technique in general!
I’m still too paranoid to execute instructions via email without a very limited set of abilities!
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Prompt Engineering vs. Blind Prompting
Here is an example of some prompt engineering in order to build augmentations for factual question-and-answer as well as building web applications:
https://github.com/williamcotton/transynthetical-engine
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Ask HN: People who were laid off or quit recently, how are you doing?
Hey Simon! I've been digging your writings on LLMs lately.
I've been having some decent luck with some of the approaches that I've discussed in the following articles and projects:
From Prompt Alchemy to Prompt Engineering: An Introduction to Analytic Augmentation: https://github.com/williamcotton/empirical-philosophy/blob/m...
https://www.williamcotton.com/articles/writing-web-applicati...
https://github.com/williamcotton/transynthetical-engine
I'd love to hear your thoughts on the matter!
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We need to tell people ChatGPT will lie to them, not debate linguistics
Sure you can. The easiest way is to go to https://chat.openai.com/chat and paste in a Wikipedia article.
There are more involved manners like this: https://github.com/williamcotton/transynthetical-engine/blob...
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ChatGPT-Linux-Assistant
Parsel : A (De-)compositional Framework for Algorithmic Reasoning with Language Models
https://arxiv.org/abs/2212.10561
Here's a notebook with an introduction:
https://github.com/ezelikman/parsel/blob/main/parsel.ipynb
And here's a GUI interface the author has been developing:
http://zelikman.me/parsel/interface.html
I've been working on an augmented large language model that given these few-shot exemplars can build the below fully-functional ToDo App: ==
https://github.com/williamcotton/transynthetical-engine/tree...
https://www.williamcotton.com/articles/junie-browser-builder...
All of this is still very rough around the edges, prone to errors of various kinds, and generally not ready for prime time, but anyone is welcome to play around with what is there!
What are some alternatives?
magma-chat - Ruby on Rails 7-based ChatGPT Bot Platform
simpleaichat - Python package for easily interfacing with chat apps, with robust features and minimal code complexity.
pal - PaL: Program-Aided Language Models (ICML 2023)
NeMo-Guardrails - NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
guardrails - Adding guardrails to large language models.
chrono - A natural language date parser in Javascript
datasette-chatgpt-plugin - A Datasette plugin that turns a Datasette instance into a ChatGPT plugin
chatgpt-linux-assistant - An ai assistant in your CLI. But it knows what's on your system and can help you get things done.
stable-diffusion-webui - Stable Diffusion web UI
geppetto - Your personal assistant with ChatGPT and Linux superpowers, ready for any task!
serge - A web interface for chatting with Alpaca through llama.cpp. Fully dockerized, with an easy to use API.
openai-cookbook - Examples and guides for using the OpenAI API