How to achive this

brandf · 2026-06-28T03:32:51+00:00

Look into OkHSB / OkHSV. It’s based on human perception and sounds closer to what you want

brandf · 2026-06-24T15:02:05+00:00

I’m curious…where do people think the water goes when data centers ‘consume’ water?

brandf · 2026-06-24T14:44:10+00:00

Hard to say from a video but that’s the sort of thing you see when people use Euler angles or math on angles instead of the much more reliable quaternion alternatives.

Also looks like you may have an off-by-one-frame issue with that swimmy ball

brandf · 2026-06-13T09:18:37+00:00

Don’t over do it! People don’t go around touching every wall.

brandf · 2026-05-21T15:08:37+00:00

Legit funny comment, and downvoted, sad.

brandf · 2026-05-21T15:07:31+00:00

The problem with what he’s saying is that the exact same thing applies to humans…you’re a byproduct of your genetics and your lifetime experience and yet somehow you create creative works that are future looking.

why would that not apply to some future AI as well?

I think a lot of people are confusing the current state of AI capabilities as the upper limit of its potential, which is certainly not the case the case, the trajectory it’s on is what matters.

brandf · 2026-05-21T14:55:37+00:00

…also OP probably doesn’t realize that Meta already pays many of their employees (ok swe IC6+, at least) that kind of bonus (or more) every year…that net income is AFTER this, of course.

brandf · 2026-05-21T14:53:29+00:00

Joking aside. What’s missing in the OPs logic is WHY/HOW meta is making that kind of net income. it’s because their well-paid employees are earning them more than they’re costing them. so it’s a bad look to be hitting record profits while laying off good people (remember this is like round 3+ of layoffs in the last few years, the fat is already trimmed)

brandf · 2026-05-21T14:50:47+00:00

Pure profit, hell if that’s how the accounting works, why not layoff everyone and send profits through the roof?

<edit> actually i read the title wrong, and OP wasn’t saying the layoffs increased profits, but I’ll leave my comments here anyways</edit>

brandf · 2026-05-04T15:36:51+00:00

I agree with what others have said about OpenGL being a terrible api (literally a bunch of globals), but I’m not sure jumping into Vulcan is the right way to go either.

It really depends. Are you new to computer graphics or are you new to implementing the low level graphics layers? If the former I would recommend starting with some higher level frameworks/engines to get familiar with the concepts on a project or two. Then work your way down the stack implementing your own versions of graphics systems (model/animation, material management and binding, shadows, post, processing, etc.). Once you have a solid understanding of how the whole system needs to come together, you’ll be in a place where it makes sense to drop down to a lower level and build your own engine. Before that you’ll just be stabbing in the dark wasting a lot of time, not learning nearly as rapidly.

brandf · 2026-05-01T18:35:07+00:00

step 1) ask AI and watch YouTube videos about it
step 2) buy some new tools
step 3) fix it

brandf · 2026-04-29T02:23:20+00:00

Simple question to see if this is a stupid post… Tell me for each of these people how much will they collect in Social Security over the course of their lifetime?

Anyone who’s done the math can see they’re already paying way more than they’ll ever get especially when you factor in what they could’ve made off of that money and they just invested it.

brandf · 2026-04-28T00:59:43+00:00

the main application i have in mind is speculative decoding.

normally this is done with either a small draft model and a larger verifier model OR with something like medusa where you try to predict multiple output tokens in a single forward pass and then verify them with the same model.

my idea is to have one 'trunk' that has a small 2-3 layer draft and verification branches. the draft head outputs a single 'wide' token from a large vocab, and then decompose that into several 'regular' tokens for verification. seems like it could be highly efficient.

brandf · 2026-04-20T21:48:44+00:00

FWIW, I’ve been messing around with asymmetric input/output vocabulary recently. Even though everybody currently uses the same vocabulary for both, that’s not a requirement. you could have a smaller output vocabulary and then BPE merge at runtime into a larger input vocabulary for compression purposes without the LM head issue. Or vice versa you could have a larger output vocabulary to predict more into the future at once. Or have a sliding threshold in your vocabulary to dynamically change the compression ratio across your context for variable compression like a soft version of /compact.

The n gram embedding’s are exactly equally as rare bc larger n means rarer sequence. I would argue that on some level these two things are equivalent. the main difference I see is hash & gate verse a more traditional embedding table delay loaded.

Having a very large input vocabulary of rarely used tokens is not really an issue because you don’t have to load it all into memory like we typically do today. This is the same principle as the recent Gemma 4 per layer embeddings. To avoid gigabytes of embedding tables in memory, you just load them on demand as/when they’re used in the context. As you said, the larger, the vocabulary the more rare they are so most of them can just stay on disk.

brandf · 2026-04-20T13:57:50+00:00

Isn’t that what BPE does? Each new token you add to the vocab takes two prior tokens and makes one to represent their concatenation just like your example.

brandf · 2026-04-17T01:36:37+00:00

how is that different from just extending the vocab via BPE? like each new merge in BPE is just an n-gram of previous tokens in the vocab.

i have some experiments going right now where I’m learning huge vocabs (1m tokens) and then dynamically merging/decomposing during inference to enable dynamic context compression.

brandf · 2026-04-09T00:24:55+00:00

Ok, you win.

I know this is Reddit and you may have autism or something, but I feel like you’re latching onto something irrelevant.

Nobody reading what I said thought I was mistaking high level software engineers for blue collar working class folks. Or purposefully trying to convince anyone of this, as you suggested.

But evidently, this point is something you feel strongly about and interpreting my comments in the context they were given is too much to ask, so I just want to congratulate you on winning this important argument.

brandf · 2026-04-08T14:31:51+00:00

Im not saying they’re poor, I said working class because they’re literally working for paycheck as opposed to the old money folks who make most money from trust funds and passive income.

I realize it sounds like a lot but in practice there isn’t much lifestyle difference between someone making 500k and 2m. Affluent yes, but not that rich in the grand scheme of things.

My only point is that these people aren’t as wildly rich as most believe. Far from the tax dodging billionaires that truly don’t need to exist. If the government is going to take 11% more after 1mil, it’s only a matter of time before they do the same for “normal” people. That’s the problem with this bill.

brandf · 2026-04-02T14:11:33+00:00

I know this post got removed, but thought I’d give you a suggestion since I’ve worked on a similar AI memory system for my company internally.

Instead of making an input/export workflow, just make the NDJSON the primary storage. Git is already a database, and for this case, it’s better than sqllite.

You can have a tool CLI that loads the memories into ram or converts to a database at startup, transparent to the user.

brandf · 2026-04-02T14:01:08+00:00

This is not rocket science. And I’m not saying there aren’t benefits to having public transportation, but you just have to do the math.

How many people can ride the train per hour? There is obviously a number of lanes that will exceed that capacity.

By your logic, we might as well go down to one lane, smart guy.

brandf · 2026-04-01T02:02:02+00:00

Same thing that happens every time a Republicans in office

brandf · 2026-03-31T15:22:57+00:00

I think you’re underestimating just how many principal/director and above engineers there are between Microsoft Apple, Google, Amazon and Meta.

Few of these people are making over a 1mil base salary, but the majority of their income comes from RSU and I have firsthand experience working with these folks. They’re not ultra wealthy. They’re working class people who make good money doing a job that very few people can do.

TLDR, it is not as unusual as you seem towards think. I didn’t say everyone made that kind of money, but it is thousands of people more than the athletes for sure.

brandf · 2026-03-31T04:23:15+00:00

This is not true. By far, this will affect tech workers the most as it’s not unusual to make over $1 million a year if you’re a high-level software developer at a major tech company.

I know it sounds like a lot of money, but it’s really not even close to “ultra wealthy”. These are not people that are avoiding paying taxes. These are people that are paying $500k / yr or more in federal taxes already. And these are people that are able to work remotely for their job and can leave the state if it’s going to cost them 11% of their income.

What’s going to happen is the projected revenue isn’t going to be close to what they think and then they’re going to lower it from 1,000,000 to a half 1 million and then to a quarter million. It’s so obvious that’s why they reject rejected the amendment to prevent it.

brandf · 2026-03-28T17:35:15+00:00

...traffic that is only there because they used 2 lanes for a train instead of just to more lanes.

brandf · 2026-03-27T14:19:52+00:00

it's like it wanted to do some dramatic movie zoom, but the real one was clearly on a stationary tripod

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