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Show HN: Microagents: Agents capable of self-editing their prompts / Python code
41–50 of 82 posts
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#42Earlier quoted context omitted.
That's not a fitting analogy because there is no equivalent to the laws of thermodynamics that says a system can't be self improving. You're dismissing a technological possibility without much reason. We are extremely similar genetically to our ancestors of 100k years ago. The big difference is cultural inheritance. We come up with ideas and objects and pass them down. Humans have improved the capabilities of humans.…
It’s not that straightforward. Quoting Yann LeCun from a LinkedIn post [1]: > I have claimed that Auto-Regressive LLMs are exponentially diverging diffusion processes. Here is the argument: Let e be the probability that any generated token exits the tree of "correct" answers. Then the probability that an answer of length n is correct is (1-e)^n. > Errors accumulate. The probability of correctness decreases exponentia…
> There’s no evidence that today’s human is cognitively more capable than their human ancestors. It’s a conflation of technology and transference of knowledge with intelligence.
That was their point. See here:
> We are extremely similar genetically to our ancestors of 100k years ago. The big difference is cultural inheritance. We come up with ideas and objects and pass them down.
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#43I built a few multi agent systems and went down a rabbit hole where I reached an important conclusion - From the perspective of the LLM, the prompt/context is the only thing that ever matters. Everything about how your agent will behave ultimately boils down to this. I had a bunch of fancy stuff like agents collaborating by passing messages and interpreting them with their own prompts and function calls. Then I reali…
Interested in connecting. I have been creating a DSL for LLMs/agents inspired by Forth/Prolog.
Feel free to e-mail me at joshcho@stanford.edu
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#44[deleted]
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#45Any recent book recommendations on developing agent based systems?
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#46Awesome to see. We are productionizing a variant of this in louie.ai and it's the biggest step function in system quality we've seen in ~months. This kind of thing enables continuous learning & user-directed learning without having to formally fine-tune a model - magically instant from the user perspective -- and fits cleanly within a RAG system in general.
Of course, once you rephrase this as a learning problem, a lot of new questions pop up on what it means to do it right :)
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#47We do something similar with Magic Loops[0], but within the context of generating a single "loop" (automation). We've found that LLMs are pretty bad at prompting other LLMs, unless the problem at hand is very limited in scope. It's too easy to get incorrect/expensive behavior otherwise (e.g. starts building a framework against an imaginary API, instead of using an existing tool). Our approach looks more like a state…
> starts building a framework against an imaginary API, instead of using an existing tool
If you swap “API” for “business need” you’ve got a basic software developer. Most of the time those imaginary business needs are a waste of time, but every once in a while the solution is pure genius to a problem no one realised they had. Mostly the first though.
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#48Is this anywhere close to create microagent that takes you (the author, "aymenfurter") out of the equation for this repo itself? Like to make yourself redundant and let the bot be in charge of this repo and all that entails? How far in time?
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#49I built a few multi agent systems and went down a rabbit hole where I reached an important conclusion - From the perspective of the LLM, the prompt/context is the only thing that ever matters. Everything about how your agent will behave ultimately boils down to this. I had a bunch of fancy stuff like agents collaborating by passing messages and interpreting them with their own prompts and function calls. Then I reali…
The best analogy I can think of is that if you want your agent to accomplish something without persisting a long chat history, but instead use the agent to reorganize and change the prompt, you would choose to use the method Leonard uses in the film "Memento". Due to his condition, Leonard cannot form new memories and struggles to recall events that occur after his injury. Leonard knows his condition and uses tattoos to record facts "between sessions". Each chat completion of the LLM is similar to "each session" Leonard experiences. The prompt, with the help of the agent, can persist across LLM chat completions, which is similar to the tattoos, and various notes and photos he has.
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#50Earlier quoted context omitted.
It’s not that straightforward. Quoting Yann LeCun from a LinkedIn post [1]: > I have claimed that Auto-Regressive LLMs are exponentially diverging diffusion processes. Here is the argument: Let e be the probability that any generated token exits the tree of "correct" answers. Then the probability that an answer of length n is correct is (1-e)^n. > Errors accumulate. The probability of correctness decreases exponentia…
> There’s no evidence that today’s human is cognitively more capable than their human ancestors. It’s a conflation of technology and transference of knowledge with intelligence. That was their point. See here: > We are extremely similar genetically to our ancestors of 100k years ago. The big difference is cultural inheritance. We come up with ideas and objects and pass them down.
Yup, hence the “unfit” analogy. It doesn’t correspond well with LLMs getting more intelligent in the same way, which I believe, is intended by having a “self editing agent”.