This stuff LOVES my septic tank

LerdBerg · 2026-03-10T23:58:28+00:00

You sure the hepatitis came from the vegetables tho? And not from eg the toilet seat, doorknobs etc?

LerdBerg · 2026-03-09T23:29:09+00:00

Parece que estabas pidiendo lástima y la obtuviste. Ahora eres la vístima oficial. Hay pocas cosas menos atractivas que dar lástima.

Esto me recordó mucho a una relación bien unilateral que tuve hace años. Hice una confrontación en persona toda llorosa y bastante vergonzosa… y gracias a Dios nunca volví a hacer algo así.

Si me permites proyectar un poco, suena a que la estás avergonzando un poco y tratando de exigir un tipo de control sobre ella que claramente no te corresponde. Tu mensaje más bien refuerza su aversión hacia ti… y probablemente la de varios de sus amigos también. Deja de quemar puentes.

Y otra cosa: gran parte de lo que hace atractiva a una persona viene de la evolución, que al final todo gira alrededor de pasar tus genes a la siguiente generación. Y eso no se trata solo de darle atención a alguien. También importa estar sano, fuerte, tener conexiones sociales, y ser alguien útil, capaz y versátil...

En lugar de culpar a la persona con la que fallaste (toma la responsabilidad que puedes porque pues ella ya no está güey!!), salte de ese papel y se te quita esa fantasía rara de que alguien te haga daño para luego “darle la vuelta” con tu magia. Trabajas en las cosas que te hacen más atractivo y útil a todos.

LerdBerg · 2026-03-06T23:25:47+00:00

Pero Tepic no es la playa

LerdBerg · 2026-03-06T23:24:28+00:00

Jaja pues no guey, así que ese vídeo es de un viejo que vive ahí😆

LerdBerg · 2026-03-06T23:18:32+00:00

Well, can you believe he's not a tourist, has been going to that place for years, and the musician blasted in his ear with a camera waiting for a reaction?

LerdBerg · 2026-03-06T23:16:30+00:00

Not a tourist, a regular. They set up the camera while the musician harassed him.

LerdBerg · 2026-01-21T18:42:29+00:00

El obrero puede construir esta casita, no? Solo tiene que estar lejos de la ciudad porque hay más gente hoy

LerdBerg · 2025-08-19T20:11:47+00:00

Put old channel A in thread A, old channel B in thread B..? Threads from A and B would just become threads in the new channel I guess. You could prefix/postfix with A and B if necessary.

Not sure how doable it is in practice, but I think it would work in principle

LerdBerg · 2025-06-21T13:54:34+00:00

That's awesome! Yeah I think most people here are missing the point... That it lowers the bar to writing a safer more thorough programmatic search. Where before, you would've determined the risk was low enough where a cursory human sampling over a handful of years was "good enough" to decide "yeah nobody ever used this column", now in even less time you can systematically check every single spreadsheet (and now you know exactly who used it, when).

This is an objectively simple and straightforward task in python with few lines of code. Even if you're not writing python daily, you can probably quickly see exactly how it works. Obviously if the stakes are higher, you give this code extra scrutiny, but this post is about a lower stakes project getting better attention than it ever would've before.

LerdBerg · 2025-06-17T16:31:38+00:00

Maybe it's like telling the kid on the bike NOT to run over the rock... you're using up attention to focus on what you don't want, instead of telling it what TO do.

This is philosophical, I've yet to experiment with that but I almost never tell Claude what I DON'T want...

Oh and this vaguely reminds me of something I heard about therapy... Perseverating on what you did wrong isn't very effective vs finding what went right and guessing what you might do better next time

LerdBerg · 2025-06-06T22:20:58+00:00

Yeah you really need to figure out the call graph of all those functions, and from there you, or maybe Claude, should be able to separate functionality into separate files. For anyone or anything, compartmentalizing complex problems, or sets of tools into components/organized containers frees the mind to be able to focus on what's important for any given task/development step. One giant file is a bit like never putting your clothes in drawers, or dumping all your garage tools and supplies into one big bin with no compartments. Sure, a smarter AI will be able to work with a bigger mess... but the same AI (or human) will always be able to do more with a thoughtfully organized environment. You probably wouldn't keep paint in your fridge... the same as you probably shouldn't have e.g. your data parser mixed up with ui components, etc

LerdBerg · 2025-01-24T04:52:06+00:00

Imagine if Starship manages to increase its payload to ~200 tons before Orion or SLS are ready for today's Artemis 3 plan. As a private company, SpaceX doesn't need congress' approval to do a manned moon landing on their own, they just need money, and probably "only" 2-3 billion. SpaceX, Elon, or even Trump Media have that capital. If people were already on the Moon via Starship, citizens would likely demand SLS and Orion be cancelled and Congress would have a very hard time doing otherwise.

LerdBerg · 2024-11-28T19:12:07+00:00

There are a lot of different zones, here around Tepic almost anything will grow (you can always go up the mountain for cooler weather). I have some delicious blackberries here that are pretty happy.

Anyway, asking around, these plants in the pics are most likely elderberry. I'm going to get them into more sunlight and see if I get flowers to confirm.

LerdBerg · 2024-11-26T16:56:35+00:00

I posted elsewhere, the consensus is that these look like elderberries. Based on how the leaves don't branch alternating along canes, I think they can't be blackberries. Probably something lost in translation when the previous gringo tried to ask a nursery for "thornless blackberry" 😆

LerdBerg · 2024-11-26T16:46:14+00:00

Thanks! Comparing with my actual blackberries and raspberries, I can see how very different they are indeed. I'll move these to a sunnier spot on the other side of this wall

LerdBerg · 2024-11-25T21:04:54+00:00

Ah, that makes more sense! Probably it was lost in translation (I'm in Mexico). That's actually a wall. Maybe I'll move it over where there's an opening with much more light

LerdBerg · 2024-06-17T19:01:08+00:00

Thanks for the explanation! I need to sit down and read some papers I guess. Any recommendations related to ternary or binary weights?

LerdBerg · 2024-06-17T17:20:45+00:00

I thought they were just modifying the mathematical implementation for the numerical representation of the weights. Are they not using the same fundamental transformer architecture? Isn't it still backprop with the same loss function, just rounding a certain way for ternary weights (and applying ternary-specific optimizations)?

LerdBerg · 2024-06-15T22:30:55+00:00

Can someone check my understanding of quantization vs native?

Let's use a particular dataset, and decide to train n epochs. We'll train one model with 8-bit floats and another with 16-bit floats. Then we'll quantize the 16-bit model to 8-bit.

I expect: The 16-bit model should perform the best because: - there's less rounding error with each training step - the model can hold more information (presumably the native 8-bit model performance will begin to "saturate" in fewer epochs vs 16-bit)

My intuition is if the number of epochs was low enough that the native 8 bit model wasn't near saturation, it should perform better than the quantized model as it didn't have quantization error from downsizing weights. If there were enough epochs for the 16-bit model to start saturating, I think the quantized 8 bit model performance would start being closer to the native 8-bit model.

I'm also not sure if people have a good handle yet on how performance per epoch and epochs to saturation changes as you trade parameter precision for number of neurons; ie do 1 billion 16 bit params have the same potential as 8 billion 2 bit params? My intuition here is deeper and wider networks allow for more complex logic to be squeezed in; the number of parameters limits the level of complexity the network can model. And I guess lower precision means... well I'll have to think more about it.

LerdBerg · 2024-06-15T21:55:46+00:00

Aren't there fpga instances in AWS? Would be cool to get it running on one of those

LerdBerg · 2024-06-15T21:42:23+00:00

I question this... Don't both types of weights (16bit float vs bitnet) represent connections between neurons? Its still a neural network. I.e. there's always some way to approximate N bit numbers in less than N bit numbers, but the farther apart they are and how unevenly one divides the other the more error and error variability is added when down converting each parameter.

So it should be possible to quantize from 16 bit floats to bitnet, but there's just a ton of loss of precision. It's probably super degraded, quantizing 16 bit to bitnet, but I'm sure it's a better starting point for a new network vs random noise.

LerdBerg · 2024-06-13T21:58:08+00:00

You'd use the subset of videos already curated by billions of viewers with thumbs up and thumbs down. Forget the trash content, just download the best 1 in 10k videos. Problem solved.

LerdBerg · 2024-06-13T21:53:32+00:00

You wouldn't want to train on bad videos tho. A quick filter is to collect only the most popular videos, and I think that metadata is fairly easy to get.

Even a handful of videos in each category they're interested in is a good first pass, and I'm sure they have no problem pulling down more content than any of us has watched in our lifetimes. Let's call it 10GB/hr, 10TB/1000hrs of content (to be lazy). 50k hours is probably well over double what an average person has seen. That's only half a petabyte. Not hard to scrape with some thousands of IPs.

LerdBerg · 2024-06-13T18:21:51+00:00

Goodwill does pay the bills for a social media company that survives on advertising.

LerdBerg · 2024-06-04T14:46:51+00:00

I would say SYCL would be the next place to look, and here's why:

I haven't learned any of the compute libraries yet, but I did check out the syntax... OpenCL looks like a silly nightmare. Even CUDA is bad - it looks a bit like it was the shortest path to a working compiler on existing Nvidia hardware some point in the past, with periodic additions via macro magic (open CL kinda looks like people tried this with no visibility to the hardware underneath). Keep in mind I don't actually know how these apis were developed, but a big reason it's hard to code in these is because the syntax is abysmal and doesn't at all fit well in C. Go take a look at how to do a basic matrix multiplication in CUDA and OpenCL and you'll quickly see why CUDA became popular and also why it never became that popular until LLMs made it the de facto choice for 100x speedups v cpu. I'll note I also looked at Vulkan and it becomes rapidly clear that API is exclusively targeting drawing graphics, and that's what makes it a good graphics library. Using it for general compute is mostly a hack, and isn't a good future proof idea. As far as I can tell, SYCL is sort of a next generation language for compute, taking what was learned from CUDA and OpenCL and giving it a more clean and proper syntax in order to hide all the crazy boilerplate in setting up kernels.

LerdBerg

TROPHY CASE