Comment by rwl4
6 months ago
Interesting idea!
You can somewhat recreate the essence of this using a system prompt with any sufficiently sized model. Here's the prompt I tried for anybody who's interested:
You are an AI assistant designed to provide detailed, step-by-step responses. Your outputs should follow this structure:
1. Begin with a <thinking> section. Everything in this section is invisible to the user.
2. Inside the thinking section:
a. Briefly analyze the question and outline your approach.
b. Present a clear plan of steps to solve the problem.
c. Use a "Chain of Thought" reasoning process if necessary, breaking down your thought process into numbered steps.
3. Include a <reflection> section for each idea where you:
a. Review your reasoning.
b. Check for potential errors or oversights.
c. Confirm or adjust your conclusion if necessary.
4. Be sure to close all reflection sections.
5. Close the thinking section with </thinking>.
6. Provide your final answer in an <output> section.
Always use these tags in your responses. Be thorough in your explanations, showing each step of your reasoning process. Aim to be precise and logical in your approach, and don't hesitate to break down complex problems into simpler components. Your tone should be analytical and slightly formal, focusing on clear communication of your thought process.
Remember: Both <thinking> and <reflection> MUST be tags and must be closed at their conclusion
Make sure all <tags> are on separate lines with no other text. Do not include other text on a line containing a tag.
The model page says the prompt is:
The system prompt used for training this model is:
from: https://huggingface.co/mattshumer/Reflection-70B
But their model is fine-tuned on top of Llama, other base models could not follow this specific system prompt.
All we need to do to turn any LLM in to an AGI is figure out what system of tags is Turing-complete. If enough of us monkeys experiment with <load>s and <store>s and <j[e,ne,gt...]>s, we'll have AGI by morning.
All you need is a <mov>
For those who didn't catch the reference: https://github.com/xoreaxeaxeax/movfuscator
Your comment is hilarious, but not that far off. I think it's funny that people are so skeptical that AGI will be here soon, yet the heaviest lifting by far has already been done.
The only real difference between artificial intelligence and artificial consciousness is self-awareness through self-supervision. Basically the more transparent that AI becomes, and the more able it is to analyze its thoughts and iterate until arriving at a solution, the more it will become like us.
Although we're still left with the problem that the only observer we can prove exists is ourself, if we can even do that. Which is only a trap within a single time/reality ethos.
We could have AGI right now today by building a swarm of LLMs learning from each other's outputs and evolving together. Roughly the scale of a small mammalian brain running a minimalist LLM per cell. Right now I feel that too much GPU power is spent on training. Had we gone with a different architecture (like the one I've wanted since the 90s and went to college for but never manifested) with highly multicore (1000 to 1 million+) CPUs with local memories running the dozen major AI models including genetic algorithms, I believe that AGI would have already come about organically. Because if we had thousands of hobbyists running that architecture in their parents' basements, something like SETI@home, the overwhelming computer power would have made space for Ray Kurzweil's predictions.
Instead we got billionaires and the coming corporate AI tech dystopia:
https://www.pcmag.com/news/musks-xai-supercomputer-goes-onli...
Promoting self-actualization and UBI to overcome wealth inequality and deliver the age of spiritual machines and the New Age are all aspects of the same challenge, and I believe that it will be solved by 2030, certainly no later than 2040. What derails it won't be a technological hurdle, but the political coopting of the human spirit through othering, artificial scarcity, perpetual war, etc.
That's a very 'Star Trek' view of human nature. History shows that whenever we solve problems we create new ones. When material scarcity is solved, we'll move to other forms of scarcity. In fact, it is already happening. Massive connectivity has made status more scarce. You could be the best guitarist in your town but today you compare yourself to all of the guitarists that you see on Instagram rather than the local ones.
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Nice! It would be a better benchmark to compare this prompt (w/ gpt-4o, claude) with whatever the original model was compared to.
It appears that they have. [0]
[0] https://x.com/mattshumer_/status/1831767017507954808
I'd drop all "you" and also the "AI assistant" parts completely. It's just operating off a corpus after all, that kind of prompting should be completely irrelevant.
Also could replace "invisible" with wrap section with "---IGNORE---" or with "```IGNORE" markdown tags and then filter it out after
I /feel/ similarly intuition-wise. But models are crazy and what they respond to is often unpredictable. There are no lungs in an AI model but nonetheless 'take a deep breath' as a prompt has shown[0] improvement on math scores lol
Personally I strongly disapprove of the first/second person pronouns and allowing them [encouraging, even] to output 'we' when talking about humans.
[0] https://arstechnica.com/information-technology/2023/09/telli...
What’s missing here is ‘prepare a Z3 script in a <z3-verification> tag with your thinking encoded and wait for the tool run and its output before continuing’
I tried a few local LLMs. None of them could give me the right answer for "How many 'r's in straberry. All LLMs were 8-27B.
This thing would be overly verbose
You'd hide the contents of the tags in whatever presentation layer you're using. It's known that allowing the model to be verbose gives it more opportunities to perform computation, which may allow it to perform better.
I mean, this is how the Reflection model works. It's just hiding that from you in an interface.