cgearhart

5 ms·

1.
by cgearhart 8d ago
Out of curiosity, do you have other ideas or things you want it to do? It just seems like they always converge on the same set of executive tasks because they’re a nail that is exceptionally well suited to this particular hammer.
2.
by cgearhart 24d ago
At least in the write up he talked about trying with 3 different models. He could look at the progress at each step and evaluate whether it was making progress or stuck. He was able to understand the partial and complete solutions. I think
3.
by cgearhart 24d ago
I understand why “prompt kiddie” feels accurate, but I don’t think it is. Expertise is _amplified_ with LLM agents. The same $300 of tokens given to my plumber—who is an _excellent_ plumber—is unlikely to produce the same outcome.
4.
by cgearhart 1mo ago
This is the exact opposite of what I’ve been dealing with for awhile. LLMs absolute cannot work on something without an understanding unless they can outsource the understanding to a verifier. If you’ve got an easy to check function to me
5.
by cgearhart 2mo ago
Zero dependencies should not be the goal. It’s just a modern retelling of “not invented here” syndrome. It’s an anti-pattern because now you own maintenance on something that is not your core problem. In every case I’ve seen so far, the pro
6.
by cgearhart 2mo ago
This is exactly what I’m talking about. I’m seeing the same pattern. And the most useful proxy I’ve found so far for “we don’t understand the problem” is taking zero dependencies. It means that you haven’t bothered to understand what the li
7.
by cgearhart 2mo ago
I’m seeing kinda the opposite. At some point it becomes obvious what to build and there’s no friction to building it anymore. So you get a flood of low effort copies of the same thing and no one wants to depend on anyone else, and the old v
8.
by cgearhart 2mo ago
This seems very related to a trend I’m seeing as my company goes all in on AI: everyone thinks that every problem is “a couple hours” with AI now, and they all want zero external dependencies because they can move faster alone. As a result,
9.
by cgearhart 2mo ago
I like my steam deck and got tired of waiting for the steam machine. I asked one of the AIs for something similar and it told me to install Bazzite. Took me an hour and I got the Steam-like UI that I wanted. I did not explore other options
10.
by cgearhart 2mo ago
A few months ago I got tired of waiting for the steam machine and built my own. Geekom box on sale (note: would NOT buy from them again) and then a quick hour or so to get Bazzite running. The hardest part was purchasing a thumb drive (had
11.
by cgearhart 2mo ago
We used to use this, but it was a broader conversation around tradeoffs to meet different constraints. If the expected array is small, then sort + index is probably fine. If it’s big (bigger than main memory?) and latency is the most import
12.
by cgearhart 2mo ago
My read has been that a lot of leaders were trying to drive “being early” as the catalyst for future success. At the complexity scale of big orgs you’re mostly fiddling with the incentives that the system self-aligns toward. Firing a bunch
13.
by cgearhart 2mo ago
Yes, that’s what I think at this point. There is no effect of the study group except as a support group. (That’s all it was for me when I was a student and joined the self-organized study group.)
14.
by cgearhart 2mo ago
I used to TA a graduate level CS math class at Georgia Tech. We regularly saw that the students who self-organized study groups did dramatically better in the course than average. One semester they told us to put everyone in study groups
15.
by cgearhart 3mo ago
I’m starting to realize that LLMs are really good at building low-stakes projects. Your questions mostly presume that the stakes are higher. The software will last a long time; the requirements will evolve; we can’t tolerate mistakes; etc.
16.
by cgearhart 3mo ago
I just tested this myself. I wrote “flip the reduce white point toggle accessibility option in the settings app” and it worked perfectly. Run once to set it and run again to disable it.
17.
by cgearhart 5mo ago
Spreading out the refusal encoding shouldn’t be effective as a countermeasure. Even if it were smeared across the vector space, as long as it’s in a subspace that doesn’t span the entire domain then you should be able to either null out the
18.
by cgearhart 5mo ago
A much earlier major win for deep learning was AlexNet for image recognition in 2012. It dominated the competition and within a couple years it was effectively the only way to do image tasks. I think it was Jeremy Howard who wrote a paper a
19.
by cgearhart 5mo ago
I agree, it would be nice if we could prioritize basic human needs rather than treating them like burdens caused by bad luck or poor choices.
20.
by cgearhart 6mo ago
Slightly unrelated to this story, but I’m curious if anyone has good resources for learning FreeCAD. I have quite a lot of experience with SolidWorks, AutoCAD, OnShape, and similar software, but FreeCAD has always been hard for me to pick u
21.
by cgearhart 6mo ago
Eh. I think my point is that the OP is presented as a “how to” (literally: “how to do important research”) and then it immediately dodges the question by saying “have good taste”. That does not help anyone do important research or improve t
22.
by cgearhart 6mo ago
That seems even less actionable, and somewhat misaligned with the OP article. “Taste” implies an ability to distinguish between a good example and a bad one. If it’s only recognizable in retrospect then it’s just another name for survivorsh
23.
by cgearhart 6mo ago
I often find this kind of advice too vague to really be useful. “Have taste” in the problems you work on isn’t very actionable. (Unless perhaps you list examples of good and bad taste.) I’ll admit that I may just be immature at research as
24.
by cgearhart 8mo ago
Any notes on the problems with MLX caching? I’ve experimented with local models on my MacBook and there’s usually a good speedup from MLX, but I wasn’t aware there’s an issue with prompt caching. Is it from MLX itself or LMstudio/mlx-l
25.
by cgearhart 8mo ago
I think this is the actual “bitter lesson”—the scalable solution (letting LLMs bang against the problem nonstop) will eventually far outperform human effort. There will come a point—whether sooner or later—where this’ll be the expected norm
26.
by cgearhart 9mo ago
So…great for prototyping (where velocity rules) but somewhere between mixed to negative for critical projects. Seems like this just puts some mildly quantitative numbers behind the consensus & trends I see emerging.
27.
by cgearhart 9mo ago
“Better than me” != “good” I know approximately nothing about approximately everything. Claude seems pretty good at those things. But in every case I’ve used Claude Code for something I do know about it’s been unsatisfactory as a solo ope
28.
by cgearhart 9mo ago
I love the way you phrased this.
29.
by cgearhart 9mo ago
Best of luck! I hope it’s as amazing for you as it was for me.
30.
by cgearhart 9mo ago
I had been working in civil service for the US Navy for about 10 years in operations research & systems engineering. It was very hard to break out of that role to any private industry—especially for the ML roles I wanted, which I thin

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