Recent submissions

Comment · 6 days ago
I'm fine with using AI for code, where the quality will likely be better than those of academics.

But writing.. FFS everything I see is just AI slop. And I only realize when I start wondering why the paper is going and going and saying nothing, and then pangram tells me that everything past the intro is just AI. :/

Comment · 11 days ago
Out of curiosity, which harness do you use? Hermes, ..?
Comment · 16 days ago
I used private torrents for the best part of 10 years but life got in the way, and when I tried to go back after my last Pvt torrent closed (Morethan..) I realized the bar was much higher than before. I only managed to get into MAM and perhaps and some point that would open more doors and so on, but it's anything but trivial lol (unless you never lost access to Pvt torrents or maybe if your friends do)
Comment · 1 month ago
A bit tired of spending $200 out-of-pocket for openai. What do you use as harness? (for me the harness if half of the benefit... controlling my PC, working from phone, etc.)
Comment · 1 month ago
Far left? Most economists consider it center-right, and it has been like that for more than 100 years.
Comment · 1 month ago
I thought that was a joke.. Like how I used "delve into" back in 2024 or so lol
Comment · 1 month ago
Honestly, it's a bit of a disappointment

- Many more mediocre papers written (mediocre ideas, implementation, claude-isms everywhere)

- Much easier to try every possible combination of a regression in order to show the result you want (same for theorists).

The one thing I'm happy about is it's now much easier to extract historical data from old documents from Google Books. Still not perfect, but takes you 95% there. And creating plots and datavis just for quick exploration is super fast.

Comment · 1 month ago
Also very puzzling to me. And the jargon-speak, albeit is more of an issue for Claude, is still puzzling. Wonder what part of RL led to this.
Comment · 1 month ago
Comment · 1 month ago
Sure, why not: https://github.com/sergiocorreia/overengineered-rand-mcnally

The original script was mostly very simple python:

1. Download some public PDFs. 2. Have a double for-loop (over PDFs and pages within PDF), 3. Use a library to call gemini-3.7-flash and ask it to run some OCR 4. Save JSON outputs, save a csv with results, validate with some Stata code

New code folder was 189 files. Just the PDF download folder is now 7 files involving an adapter, a source manager, an acquisition manager, etc.

Every instance of saving a file involves saving a temporary copy and then moving it, so e.g. I lose power, we minimize the risk of corrupted files.

And so on!

Comment · 1 month ago
I wonder if I would need a non-openai agent to enforce it.. I have tried so far with skills and agents.md and code stills end up over engineered to the moon.

Will ask OpenAI to write me that agent! Hope the agent is not over engineered or else unsure how to solve the bootstrap puzzle :D

Comment · 1 month ago
noted, thanks dang!
Comment · 1 month ago
(cross posted from the other announcment thread)

A big problem I have with OpenAI's models (and of course Claude) is that they tend to write the most over-engineered pieces of code, beyond the imagination of any architecture's astronaut.

Just this week I asked 5.6-sol-ultra to update a 1000 LOC python script I had, to "incorporate the key lessons learned when using it for another project".

I left it overnight and went to sleep. In the morning I realized it had created a monstruosity of 180 PYTHON SCRIPTS, with maybe 100,000 lines of code, each more crazy than the other. It took me minutes even to track where a single action took place, due to all the crazy imports, defensive coding, and premature optimization.

Similarly, anything they write is riddled with jargon that almost feel like they want me to give up trying to understand. Made up phrases that ended up with me having no idea of what was going on.

So now to my assessment: The reason why " Nobody Has Actually Built a Software Factory" [1], and why even SOTA LLMs struggle so much with open-ended unsupervised tasks is precisely this. They somehow let complexity explode, and unless it's also accompanied with an explosion in e.g. the number of agents, the amount of processing time, etc. then projects become broken/unmanageable.

Sure, LLMs are great at producing code that can be thrown out, so they are amazing when searching for exploits, for instance. But as of 5.6 they still lack either a better harness that encourages KISS principles, or a better RL step.

(And not sure why, but doubt Astra will fix this.. they seem to be aiming for AGI and for beating crazy benchmarks, which is not very aligned with KISS)

[1] https://news.ycombinator.com/item?id=49510843

Comment · 1 month ago
(Posting partly so I can revisit my predictions when they open access more widely)

A big problem I have with OpenAI's models (and of course Claude) is that they tend to write the most over-engineered pieces of code, beyond the imagination of any architecture's astronaut.

Just this week I asked 5.6-sol-ultra to update a 1000 LOC python script I had, to "incorporate the key lessons learned when using it for another project".

I left it overnight and went to sleep. In the morning I realized it had created a monstruosity of 180 PYTHON SCRIPTS, with maybe 100,000 lines of code, each more crazy than the other. It took me minutes even to track where a single action took place, due to all the crazy imports, defensive coding, and premature optimization.

Similarly, anything they write is riddled with jargon that almost feel like they want me to give up trying to understand. Made up phrases that ended up with me having no idea of what was going on.

So now to my assessment: The reason why " Nobody Has Actually Built a Software Factory" [1], and why even SOTA LLMs struggle so much with open-ended unsupervised tasks is precisely this. They somehow let complexity explode, and unless it's also accompanied with an explosion in e.g. the number of agents, the amount of processing time, etc. then projects become broken/unmanageable.

Sure, LLMs are great at producing code that can be thrown out, so they are amazing when searching for exploits, for instance. But as of 5.6 they still lack either a better harness that encourages KISS principles, or a better RL step.

(And not sure why, but doubt Astra will fix this.. they seem to be aiming for AGI and for beating crazy benchmarks, which is not very aligned with KISS)

[1] https://news.ycombinator.com/item?id=49510843

Comment · 2 months ago

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