That’s a clever implementation. I can see the same method used to generate the optimum prompt based on results.
Show HN: Microagents: Agents capable of self-editing their prompts / Python code
21–30 of 82 posts
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#22Earlier quoted context omitted.
Google and many people will tell you the same thing. So you must have a lot of lol moments in a day. Gpt4 is quite good (better than most humans I ever met) at php, but bad at facts; don’t ask it facts, ask it to write code. That’s what you would ask a human (outside interviews). Disclaimer; I am formally trained with proofs and proof assistants and I hate the current timeline where we ask ai to drivel up code, but I…
When saying LLMs are "good at writing code" there's a distinction between "good at taking high-level English-language solutions to programming problems and translating them into low-level implementations via a specific language / design patterns / etc" versus "good at finding solutions to programming problems." GPT-4 is indeed quite good at the former - and the former is what most enterprise programming work actually…
You are right, hence my disclaimer. For paid work, it works fine and that is indeed enterprise kind of mindnumbing plumbing. For other work, I do not use it (but will try every few months if anything changed of course).
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#23Add replication and you get virus like behavior. Not sure if this a good idea.
That's a separate project called ReplicatorAgent. Unfortunately the Stargate program has had a number of run ins with them and the Air Force is merciless in shutting those kinds of projects down.
Why the Air Force specifically?
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#24These and similar attempts are like those "perpetual motion machines" that captivated people's imagination for a long time. That the machine will generate energy and that would consume energy and thus will keep moving forever. Similar hopes here and everywhere. A model will generate its own input and will watch it's own output and in process, will become more intelligent than it really is.
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.…
We also have proven self improving AIs - GANs. Or even evolutionary algorithms.
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#25These and similar attempts are like those "perpetual motion machines" that captivated people's imagination for a long time. That the machine will generate energy and that would consume energy and thus will keep moving forever. Similar hopes here and everywhere. A model will generate its own input and will watch it's own output and in process, will become more intelligent than it really is.
I see the resemblance, but for perpetual motion machines, we have an actual physical law, the 2nd law of thermodynamics, that makes it impossible. As far as I know, we can't yet disprove that a self-improving AI will become more intelligent than it starts as. I'm not trying to say that it is likely or that I believe it will happen. Just that we can't disprove it yet, unlike perpetual motion devices. EDIT: corrected f…
Small nitpick: I think you mean the second law of thermodynamics.
Also the second law of thermodynamics is an empirical law. It is based on observations and not proven. To say, that a perpetual motion machine can't exist because of the 2nd law, is circular logic, since the 2nd law was established precisely because a perpetual motion machine was never observed.
That's from the POV of thermodynamics, though, you can show with statistical mechanics, that the probability for a process that defies this laws goes to zero.
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#26I made a system that dynamically generates agents. This looks similar, so I will take a look into it! Great work :)
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#27These and similar attempts are like those "perpetual motion machines" that captivated people's imagination for a long time. That the machine will generate energy and that would consume energy and thus will keep moving forever. Similar hopes here and everywhere. A model will generate its own input and will watch it's own output and in process, will become more intelligent than it really is.
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Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#28These and similar attempts are like those "perpetual motion machines" that captivated people's imagination for a long time. That the machine will generate energy and that would consume energy and thus will keep moving forever. Similar hopes here and everywhere. A model will generate its own input and will watch it's own output and in process, will become more intelligent than it really is.
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 exponentially. One can mitigate the problem by making e smaller (through training) but one simply cannot eliminate the problem entirely. A solution would require to make LLMs non auto-regressive while preserving their fluency.
Moreover, I think the human analogy doesn’t quite fit here. 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.
1: https://www.linkedin.com/posts/yann-lecun_i-have-claimed-tha...
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#29Earlier quoted context omitted.
That's a separate project called ReplicatorAgent. Unfortunately the Stargate program has had a number of run ins with them and the Air Force is merciless in shutting those kinds of projects down.
Why the Air Force specifically?
They are the ones that run the stargate program out of Cheyenne.
Re: Show HN: Microagents: Agents capable of self-editing their prompts / Python code
#30I 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 realized I could collapse all of my "agents" into one dynamic prompt that tracks state in a stupid simple text region. Passing messages around was playing in very expensive traffic at the end of the day.
This is ultimately about information and spinning up an entire matrix of "agents" to process stream of info from A to B seems quite wasteful when many clear alternatives exist.
If we are seeking emergence, then perhaps this mental model still fits better. But, for practical targeted solutions, I think it's a huge distraction.