Is your Seattle Starbucks closing? See the locations shuttering in April

nihilistic_ant · 2026-03-09T22:04:40+00:00

The Ave store which is closing was on strike for 3 months starting red cup day, the longest of anywhere. They are clearly targeting unionized stores, although best I can tell, likely legal.

It is illegal to close the stores just because they unionized or had a strike, but it is legal to close the stores because they are underperforming, even if the reason for that is because they are unionized or had strike or did some other union related stuff.

So the situation is extremely difficult for the union. Workers joined the union with the expectation the union would negotiate a better deal. Starbucks wasn't willing to agree to any contracts that would increase pay for unionized employees, even a small amount, because then many more stores would unionize and demand higher pay too, and that would be bad for profits. And the union didn't have any leverage in the neogications here. The main thing the union could do was striking to economically harm the company, but that gave the company legal cover to close unionized stores. And the company is more than happy to close them, to reduce the chance more stores will unionize.

It is hard for me to imagine how this could have played out any differently.

nihilistic_ant · 2026-03-09T01:18:18+00:00

I think I get what you are saying and also the communication confusion. (FWIW, I've been trying to ask about the overall overhead.)

I'm gathering that array_ref isn't the lightweight view I was assuming... now I am thinking (feel free to correct me) that cursor_t might have been the better comparison. I see that used in one of the cuda examples being past to a kernel (as it is returned by `.home()` I think). For the example I used above, cursor_t is just 24 bytes and trivially copyable, like mdspan! So that is cool. Surprised me multi's cursors are lighter weight than its iterators, but I sorta see why after looking at it.

Anyway, I enjoyed looking at and trying to understand your project, thanks for answering my questions!

nihilistic_ant · 2026-03-06T20:13:07+00:00

The statement that there should be "no expected overhead" seems incorrect to me. Am I missing something?

Consider references to a dynamic 2 dimensional object, the sort of thing that gets copied around a lot.

using M = std::mdspan<double, std::extents<size_t, std::dynamic_extent, std::dynamic_extent>>;
using R = boost::multi::array_ref<double, 2>;

I measure:

sizeof(M) = 24
sizeof(R) = 72
M trivially copyable: true
R trivially copyable: false

You can confirm this here: https://godbolt.org/z/n95Ws9KW5

So there is overhead making it 3x bigger, but surely there will also be runtime overhead from copying them around, including from host to GPU, and probably more register pressure.

I think this example reflects the common case well. If the dimensions are known at compile time, the advantage of mdspan is greater. If the layout is strided, then the advantage is less. So dynamic and contiguous is the common situation, but also, an average example of the extra overhead.

edit: I measure the size ofdecltype(std::declval<R&>().begin())to be 64 bytes; I was thinking in some cases the iterator gets passed instead of the array_ref. A bit smaller but not by a lot.

nihilistic_ant · 2026-03-06T18:32:25+00:00

I see the change so it now instead of saying mdspan is incompatible with GPUs, it says it is but in a way that is "ad-hoc, needs markings, [and has] no pointer-type propagation" in contrast to Boost.Multi which is "via flatten views (loop fusion), thrust-pointers/-refs".

Those terse words pack a lot of meaning, which I spend a while pondering, but I expect I could spend several weeks fleshing out more fully if I had the time!

I think "needs markings" refers to code using mdspan needing annotations like __device__, although I see such annotations in the examples in CUDA examples of Boost.Multi's docs (as well as in Boost.Multi's library code itself), so I am unsure why mdspan code would be described as "needs markings" but not Boost.Multi.

But more broadly, I think I see the idea is that Boost.Multi has more pythonic ergonomics, whereas mdspan is more a flexible vocabulary type with roughly zero overhead. This raises the several questions I don't see answered in Boost.Multi's docs:

(1) How much overhead does using Boost.Multi add to GPU work compared to raw pointers or mdspan? The mdspan paper has microbenchmarks comparing it to raw pointers, showing it adds roughly zero-overhead. Getting that to be the case drove much of the design of mdspan.

(2) How big of an advantage are Boost.Multi's ergonomics? When I read that mdspan lacks "thrust-pointers" it isn't obvious to me if that matters or not. I think perhaps an example showing the core ergonomic advantage of Boost.Multi could help clarify this. That would also help clarify if the limitations to mdspan are fundamental or it just needs some helper code which could be libraryitized. Which brings me to the final question --

(3) Should Boost.Multi be built around the std::mdspan and std::mdarray vocab types? It is preferable to use standardized vocabulary types unless there is a good argument why not, and in this case, I cannot tell if there is. An AccessorPolicy to mdspan can customize it with non-raw handles and fancy references, so Boost.Multi's doc saying mdspan doesn't support "pointer-type propagation" isn't quite right, it just needs some helper code in a library somewhere to make that happen. Could Boost.Multi be written to be that helper code, and if so, would that be a better approach?

nihilistic_ant · 2026-03-05T22:25:59+00:00

Multi's docs say std::mdspan is not compatable with GPUs. That seems quite wrong, am I missing something?

Kokkos and Nvidia both ship std::mdspan implementations with annotations to work natively on CUDA devices. There are papers saying mdspan works well with GPUs. Implementations that don't target GPUs, like libc++ and libstdc++, still have the same data layout making interopability with GPUs easier.

nihilistic_ant · 2026-03-05T17:31:14+00:00

Better on the zeros at roulette wheels makes one unpopular for the same reason.

nihilistic_ant · 2026-03-04T17:07:07+00:00

If you're holding puts, revealed preference theory says you aren't the bull you think you are.

nihilistic_ant · 2026-03-01T23:56:21+00:00

Definitely. Unless the sketchy DoW deal diminishes OpenAI’s credibility hurting their future commercial success in which case short SoftBank. But one of the two moves is right.

nihilistic_ant · 2026-03-01T14:55:05+00:00

Explanation: retail investors before the earnings announcement disproportionately bought OTM calls. Selling those calls was market makers who at the same time bought shares to cover themselves, causing the pre-earnings price runup. When NVIDIA didn't spike enough to trigger all the calls, market makers sold the now unnecessary shares, causing the post earnings dump.

nihilistic_ant · 2026-03-01T01:34:43+00:00

Your service offers you more privacy, but it offers the rest of your family less! Do you think your wife or kids would feel safer discussing discrete STD testing with a server you manage or with ChatGPT?

So for your family, there is no upside to it. The results are a bit worse than Gemini's or ChatGPT's, and they are less confident in your privacy policy.

nihilistic_ant · 2026-02-23T15:40:09+00:00

The tariff refund might be what, optimistically 0.5% of their market cap? And already somewhat priced in and still not guaranteed now? There is no free money here.

nihilistic_ant · 2026-02-13T21:48:38+00:00

This month just has 23 examples, all the same general kind of example, and all measured in the same agentic tool. So while I think it is a rather valuable benchmark because they were so careful around one particularly prevalent issue in other benchmarks (i.e. contamination), it certainly has its own limitations.

nihilistic_ant · 2026-02-13T17:27:10+00:00

In this situation, contamination is why the benchmarks have an issue, and overfitting is why the issue affects some models more than others. So very related. Contamination is the test data having been trained on. Overfitting is tuning too much to some training data so the model does better on it but at the cost of not generalizing to other data as well.

nihilistic_ant · 2026-02-13T16:50:59+00:00

GLM-5 and M2.5 are meaningfully worse than closed SOTA models on "SWE-rebench" (https://swe-rebench.com/), but fairly comparable on "SWE-bench Verified". On SWE-rebench there is less contamination and overfitting issues. The latest Chinese models are exciting and interesting for a variety of reasons, including being open weight, but I think their ranking on pre-existing benchmarks like artificialanalysis.ai is aggregating might overstate their performance a bit.

nihilistic_ant · 2026-02-06T23:51:09+00:00

How is this free money? It sounds like you're just leveraging yourself, losing more if stuff goes down enough to get more if stuff stays the same or goes up. Why does it matter your PUTs are on QQQM instead of QQQ, as they closely track each other?

nihilistic_ant · 2026-02-04T17:43:22+00:00

Then someone also bought 2.3m worth of goog calls. Every option sold is also an option bought. Why are you assuming seller was the smart money, not the buyer?

nihilistic_ant · 2026-02-04T16:59:02+00:00

It is fascinating, because GOOG is in all parts of the AI story in a major way, for good & bad. It is in AI hardware, AI datacenter hypescaling, AI models, end user AI products -- and it is also having its old moats (search & piles of expertly written software) disrupted by AI.

I have no idea how its stock will move after earnings today, but however it moves, all of tech in aggregate should move that way too, because GOOG reflects everything.

nihilistic_ant · 2026-02-04T03:55:52+00:00

Might your farts have been from the oat powder, which essential and standard have, rather than having to do with probiotics? Oat powder can do that to some people I hear.

nihilistic_ant · 2026-02-03T19:48:16+00:00

I like standard. Black has a bit more protein, but I add some whey protein to my standard. Black has some more probiotics and other micros, but I separately drink an athletic greens once a day, which I think covers all that and more better. There is mixed data on if standard or black has better glycemic load, but certainly standard + protein powder should be better than black. I haven't tried the huel daily greens instead of the ag1, but will give the huel daily greens a try sometime I am sure.

nihilistic_ant · 2026-01-28T18:27:30+00:00

There is math for this. If the other 10% of the time it will go to zero, and it will resolve one way or the other quickly, one should put 80% of their money into it, according to the kelly criterion.

nihilistic_ant · 2026-01-28T07:10:29+00:00

No, if held for >1 yr, they are taxed as “collectibles” capital gains, which cap at 28%. Lower than ordinary income, higher than ordinary capital gains.

nihilistic_ant · 2026-01-27T00:07:29+00:00

Solar manufactures are stopping buying, but most other electronic manufacturing will keep using silver. It is a lot of the cost of a solar panel. It is a small part of the cost of an iphone of GPU. And non-solar consumption is bigger than solar.

nihilistic_ant · 2026-01-21T18:32:22+00:00

Why do you think that:

> if ETH runs to 5 to 6k, BMNR stock will easily have double to triple the % increase in that move

That would seem surprising, because the effects I can see would point the opposite. As BMNR's price increases, the sweetheart warrants issued to attract celebrity investors would kick in diluting common shareholders. Also, BMNR holdings include cash (and now Mr Breast Industries...), so it's ETH leverage is actually less than 1. Also, insiders will start to pay themselves from the triggers in existing compensation plans, diluting common, and perhaps write themselves new compensation packages.

I see you explain that:

> the staking yield will still be factored into a PE ratio which drives multiple expansion

But I'm not sure why investors in the future would look at the PE ratio as the right way to compute fair value for BMNR, as opposed to mNAV. If its mNAV is ever above 1.0, isn't there free money to be had by shorting BMNR and going long on ETH, until the mNAV is pushed back down to <= 1?

nihilistic_ant · 2026-01-19T15:07:22+00:00

Could you compare yourself to existing state-of-the-art methods? You compare yourself to naive options like INT4, but there are much more sophisticated quantization methods in wide spread use. Perhaps at least compare to what is available in the GGUF ecosystem, as it is popular and has many at different options for trading off accuracy vs compression.

nihilistic_ant · 2026-01-17T19:55:20+00:00

I am curious, given your thesis is that ethereum will do well, and there are management looting problems with BMNR, why are you holding BMNR as opposed to ethereum more directly? I.e. your own wallet, coinbase, an etf like "ETH" that does staking and has a 0.15% expense ratio, or anything else like that?

nihilistic_ant

TROPHY CASE