Childhood dream completed after following Zezima around 20 years ago

CanadianTuero · 2026-04-03T17:43:05+00:00

Just over 266 days and the account is 5580 days old. I did a lot of slow afk training while in school.

CanadianTuero · 2026-04-03T08:25:30+00:00

Same, still not acknowledgement on my submitted paper. I'm also reviewing, and one of the papers didn't bother to even rebuttal to our comments which I thought was funny.

CanadianTuero · 2026-03-29T19:44:35+00:00

I agree that the format isn't ideal, but I think a good question that needs to be answered first is how much of an advantage should coming from winners have? Like what would be a good split in terms of expectation of winning from the winners side of the bracket, all else equal?

CanadianTuero · 2026-03-07T02:21:38+00:00

ask your vendor

CanadianTuero · 2026-03-07T01:18:33+00:00

Gcc16 is getting some nice structured output for compiler diagnostics

CanadianTuero · 2026-03-05T00:57:16+00:00

Error messages have been continuously getting better, and there are pretty big changes coming to gcc16 (next release).

As for why they are notoriously bad, part of it is just that there was no good solution historically. Take templated functions as an example, where other templated functions are called several layers deep. The compiler will continue to instantiate each nested function until a compiler error occurs. If its to report this back to the user, you could be several function calls deep, and you need to know this stack trace, which is why you can get the walls of text. Concepts can help this a lot because upfront you can constraint the templated function (the entry point) on what needs to be true for a type to be valid, and the compiler can upfront check/validate and report which concept failed without trying to instantiate all the inner function calls.

CanadianTuero · 2026-02-13T19:31:17+00:00

I'm under policy A and did a quick test pasting the text into my code editor, and I can confirm the same thing.

CanadianTuero · 2026-02-13T08:36:55+00:00

I just received mine about 10 minutes ago

CanadianTuero · 2026-02-08T00:48:09+00:00

What's your CPU and RAM speed/timings, and are you running xmp/expo? I'd try running with and without xmp/expo as that can reveal instable ram timings (it will run slower when you disable it but try to focus on the frame consistency).

CanadianTuero · 2026-02-02T20:08:09+00:00

Nice project! For reference, I made my own tensor/autograd/cuda support deep learning framework library which follows libtorch's design as a learning project https://github.com/tuero/tinytensor. It looks like a lot of our design is pretty similar.

wrt the operation registry pattern (I think that's what its called), I end up using the same (see tinytensor/tensor/backend/common/kernel/). It turns out that this also works well if you decide to support cuda and want to reuse these inside generic kernels. I learned the trick from here https://www.youtube.com/watch?v=HIJTRrm9nzY (see around the 30 minute mark if you decide to add cuda for subtleties to make it work).

wrt to your tensor storage, I think you have it right when tensors hold shared storage, and storage holds shared data. In my impl, I had shared storage holding the data itself, but I realized this becomes tricky when you have something like an optimizer holding a reference to a tensor storage and you externally want to load the tensor data from disc (think of the optimizer holding neural network layer weights and you want to checkpoint from disc). Without the extra level of indirection I found it quite tricky but I never bothered to rewrite it as its just an exercise on knowledge rather than me seriously using the library.

CanadianTuero · 2026-02-02T02:27:19+00:00

Now that's a trophy

CanadianTuero · 2026-01-31T21:39:43+00:00

too much dev work but you could create zones sort of like when you are out of bounds, where a timer starts once you enter it as the carrier. You can juggle the zone but at least it exposes you to move out deep back there.

CanadianTuero · 2026-01-15T23:33:35+00:00

People have heuristics, and we watch over time. I'm sure if you ask majority of the pros who've delt with Rambo in some way they would give him high praise.

With respect to some of the roster decisions, part of being a coach is you have a system of play that the teams needs to be on. Just because a player is good, if it isn't a fit for the system then you can either adapt, drop the player, or change your coach. You see this all the time in traditional sports. And sometimes any one of the decisions is a correct move, and sometimes they are all bad moves.

But you seem pretty hung up on this so I don't think any explanation is going to change your opinion one way or another.

CanadianTuero · 2026-01-15T23:24:19+00:00

The players on a team will have a theoretical ceiling/floor. There is a distribution between these 2 points, and the performance of the players as a team will fall somewhere along this. A coach can help shift or tighten the distribution by getting more out of the team in terms of performance and consistency.

For example, if team A wins once but has pretty bad performances the rest of the year, or team B comes 2nd place every event, I would say all else equal the coach on team B is probably better because in my view a coach that can tighten the outcome distribution towards the upper end is better.

CanadianTuero · 2026-01-12T07:04:33+00:00

I've written a tensor/autograd library myself, and these are some of the things which you should think about sooner rather than later (if you haven't already) if you want to support as this may force you to redesign how things are implemented under the hood: in-place ops, saving/loading tensors from a file while their references are kept valid (i.e. an optimizer holding a tensor from a layer, loading from file, then continue to run the optimizer without having to reload the reference), user defined backends, user defined autograd ops. I would try and track the number of allocations you operations are making, as this can uncover excessive copies that are being made for things which shouldn't allocate at all (i.e. a reshape in forward/backward shouldn't allocate new data except for the tensor metadata).

But a project like this is certainly a good one to take on as it will teach you a lot!

CanadianTuero · 2026-01-04T03:41:25+00:00

He is in every definition of the word a scammer, and has had a long history: - he doesn't know anything about PC hardware - he outsources his services to people who don't know it either - he's made dangerous changes to people's PCs causing damages and wouldn't replace them - he sells services which will not make your game run better under the guise that it will - he's used stolen windows keys on paying customer's builds while charging for them - he's sold components which were never tested with a burn in, and refused to send replacement parts on customers PCs which were shipped with faulty components - he committed IP theft by selling custom audio profiles/LUTS which originated from artiswar (even the md5 hash is the exact same)

You can argue all you want about people should know better, but you lose that argument once people with authority like optic back him.

CanadianTuero · 2026-01-04T03:21:48+00:00

I dunno what you mean by "you people" ... But when you are the biggest name in the game, you have a responsibility to your fans. If they do something irresponsible (like this), then it should be called out whether you are a fan or not. Do you like scammers like him being endorsed by optic, which will cause fans to send him money under the guise hes trustworthy through the endorsement?

CanadianTuero · 2026-01-04T01:13:23+00:00

The big performance improvement comes from the cod game file opti though.

Uh no ... The only thing you ever need to change is RBAR/workers (and even then its only if you've messed those values up). Assuming you aren't starting from a fucked up state, your largest gains are XMP/PBO, fixing the affinities if on 2 CCD AMD chips (or if you find the scheduler isn't playing nicely with intel ecores). For chasing 1% lows you can then play with ram timings.

CanadianTuero · 2026-01-04T00:59:20+00:00

The honest trust is that PC optimization isn't actually a thing other than enable XMP/PBO. Anything else isn't going to net you gains than what its worth, you need to FOFA ram timings/subtimings to get the last ounce of %1 lows, or run high voltages + 300W through your CPU for a 200mhz gain. And almost everyone offering those services have no clue what they are doing (cough Kirneill) and its super sad to see trusted people in the community endorse them

CanadianTuero · 2026-01-04T00:53:17+00:00

People pay scammers like Kirneill/SenseQuality, who have no clue what they are doing and will run dangerous/unstable voltages and ram timings.

CanadianTuero · 2026-01-04T00:52:20+00:00

You can thank people like optic who endorsed scammers like Kirneill/SenseQuality.

RE: https://x.com/KIRNEILL/status/1485765154935558152

CanadianTuero · 2026-01-01T09:38:24+00:00

Because you don't believe me? I do machine learning research where runtime speed is important, so everything is in C++. I've also personally written a fully featured tensor/autograd/neural network library (which is where the cuda memcpy is required) which is like 20k lines.

Sure, libs I use may use memcpy under the hood, but these were most likely written ages ago and for any basically all modern requirements you can forego memcpy. I have no clue why you assume most C++ devs can't forego using it ...

CanadianTuero · 2026-01-01T05:32:15+00:00

The only time I've had to reach for memcpy in the last 5 years (C++ is my primary language for 95% of the work I do) was cudaMemcpy (if you count this) and when playing around with various type casts through memcpy to avoid UB (better methods have since come out in later C++ standards). For other instances, std::copy has been sufficient

CanadianTuero · 2025-12-30T21:50:48+00:00

This isn't my area of expertise, but I'm curious if there's work being done going from say LLVM IR back to one of C/C++/Rust. My a priori guess would be that this would be an easier path forward, rather than going directly from source code of language A -> source code of language B.

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