vibe42

7 ms·

1.
by vibe42 25d ago
"Almost every model finds the same winning ideas. What separates the best traces is what an experiment leaves behind. They preserve weak signals long enough to validate them, but they also have a better understanding of the results.&qu
2.
by vibe42 1mo ago
Meta released their own 4-bit quant of this model for devices with 24GB VRAM. That's a modern gaming laptop; cheapest I see in the US with 24GB is $3.5k. Should be quite a bit faster than the new M5 MacBook Pro, and you can run Linux o
3.
by vibe42 4mo ago
I'm using the pi-mono coding agent (open source, free) without any extensions and very simple prompts. The 3.6 27B model (BF16, 250k context) uses 67GB VRAM on an RTX PRO 9000. It's very capable on almost any coding task I've
4.
by vibe42 4mo ago
It can indeed cause some models to try too hard to come up stuff, but the next verification prompt does counteract it. E.g. some findings first classified as moderate priority often get reclassified as low priority even if the finding itsel
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by vibe42 4mo ago
Something I've had good progress with using local models and simple open-source harnesses is to repeat, in a new context, simple verification prompts. I'd run the following 5-10 times with one model, then again with a 2nd model. &
6.
by vibe42 4mo ago
Many crypto wallets use a key derivation function (KDF) to add an amount of computation (and memory usage) per password tried - to mitigate brute force of weak passwords. The increase in compute (decrease in brute-force cost) combined with
7.
by vibe42 5mo ago
I run both MoE and dense models on laptops. One set of models run on 8GB VRAM / 16GB RAM and another set runs on 24GB VRAM / 64GB RAM. Both are very useful for easy and easy-to-moderate complex code, respectively. The latest open
8.
by vibe42 5mo ago
https://old.reddit.com/r/LocalLLaMA/ Bit of a hype madhouse whenever a new model is released, but it's pretty easy to filter out simple hype from people showing reproducible experiments, specific configs for
9.
Whitehouse memo on Adversarial Distillation [pdf](whitehouse.gov)
2 points by vibe42 5mo ago|0 comments
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by vibe42 5mo ago
Outside Trading.
11.
by vibe42 5mo ago
This. And when possible, first asking the AI to add more granular logging around the code where the problem is - then re-run the code and feed the new log in a new context. I've used this to debug some moderately complex bugs in golang
12.
by vibe42 5mo ago
Keep it simple and run a fresh, new context for each prompt. I use the pi-mono coding agent with several different new open models running locally. The simpler and more precise the prompt the better it works. Some examples: "Review all
13.
by vibe42 5mo ago
With the pi-mono coding agent (running local, open models) this works very well: "Do not modify any code; only describe potential changes." I often add it to the end when prompting to e.g. review code for potential optimizations o
14.
by vibe42 5mo ago
Q4-Q5 quants of this model runs well on gaming laptops with 24GB VRAM and 64GB RAM. Can get one of those for around $3,500. Interesting pros/cons vs the new Macbook Pros depending on your prefs. And Linux runs better than ever on such
15.
by vibe42 5mo ago
Both are possible; increasing demand and bubble collapse. The way this could happen is if model commoditization increases - e.g. some AI labs keep publishing large open models that increasingly close the gap to the closed frontier models. A
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by vibe42 5mo ago
That's a very good point! And an opportunity for game worlds; extrapolate those blind spots by assuming small planets and planets further out from their stars are more common than what's been confirmed so far.
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by vibe42 5mo ago
Thanks for the link! Looks like pretty useful tools. I'm playing with a space game idea of physics simulation somewhere between the fidelity of KSP and Eve Online. More robust ships and easier gameplay than KSP, but much more in-dept
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by vibe42 5mo ago
Their latest open models are pretty competitive with other open models, and some innovation around the smaller sizes (2-4 GB). They're helping close to the distance to realistic quality inference on phones and other smaller devices.
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by vibe42 5mo ago
The pics of the cooling system is pretty good sci-fi / cyberpunk / steampunk inspo. If the whole AI bubble spectularly collapes, at least we got a lot of cool pics of custom hardware!
20.
by vibe42 5mo ago
Training their own, closed, internal models on their own data sets? Probably a good way to squeeze out some market trading signals.
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by vibe42 5mo ago
Something related and fun is parsing a simple CSV file of exoplanets. https://exoplanetarchive.ipac.caltech.edu/cgi-bin/TblView/np... Download Table -> All Columns, All Rows. Tried a few new, open, local AI mod
22.
by vibe42 5mo ago
A parcel of land. A few robot legs and arms, big battery, off-the-shelf GPU. Solar panels. Prompt: "Take care of all this land within its limits and grow some veggies."
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by vibe42 5mo ago
If Starship puts some kind of fully-fueled, modular stage in LEO, and Orion docks with it, how fast could Orion then fly to and from Mars?
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by vibe42 5mo ago
Space Weather still looks calm: https://www.swpc.noaa.gov/
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by vibe42 6mo ago
NASA's rendering of the flyby: https://svs.gsfc.nasa.gov/vis/a000000/a005500/a005536/a2_fly... Hope we get to see something like this in 4K !
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by vibe42 6mo ago
Mild Space Weather: https://www.swpc.noaa.gov/ Moderate geomagnetic storm watch until April 2.
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by vibe42 6mo ago
They can move around after they switch from launch to spaceflight config. Apparently they also have some exercise gear for the journey.
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by vibe42 6mo ago
Here's a habitable zone in a different star system: https://en.wikipedia.org/wiki/TRAPPIST-1#Habitable_zone
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by vibe42 6mo ago
How does this compare to the pi-mono coding agent? https://github.com/badlogic/pi-mono/tree/main/packages/codin...
30.
by vibe42 6mo ago
With 16 GB VRAM one can run a decent quant (Q4-Q8) of newer, smaller dense models. This leaves room for e.g. 32-256k context size. This might not be enough to chew through a large code base but for smaller projects it can easily fit enough

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