Tootfinder

California Towhee emerging from the bath. LA Arboretum, Arcadia, California, USA. April, 2026. OM System OM-1 M.Zuiko 300mm F4 MC14 #laarboretum #towhee #bird

This film has finally come out. I recommend you see it, not because I did some strange pop/noise music for it, but because it is one of the strangest films I've ever seen.

Early Week 1 bets and futures to target following ... https://www.espn.com/espn/betting/story/_/id/48432437/2026-nfl-schedule-release-week-1-odds-lines-spreads-sports-betting-futures

Doin' US taxes again. Super blah without a donut!!
Last year my personal filing was about 200 pages long. (We also do a separate corporate filing.)
And once again my taxes will far, far, far exceed the actual disposable income I have received.
Yes, this is an upper-middle-class, first world problem.. But I do hate paying what amounts to big wads of $$ to pay for El Cheato's destruction of the US.

Geologists on the silver screen—the sequel: #movies, too ...

Fleet of ‘Flying Ferries’ Will Provide Zero-Emission, Silent EV Boats for Commuters and Tourists Along Norway’s Coast https://www.goodnewsnetwork.org/fleet-of-flying-ferries-will-provide-zero-emissio…

Fleet of ‘Flying Ferries’ Will Provide Zero-Emission, Silent EV Boats for Commuters and Tourists Along Norway’s Coast
Tourists and commuters along Norway’s coast will soon travel aboard “flying” electric ferries—quietly whizzing above the water from Candela.

BOFH excuse #431:
Borg implants are failing

And once again with #AltText4You.
Why is that one simple link so hard to click?

So to follow up on this, I've caught it in action. Models, when quantized a bit, just do a bit more poorly with short contexts. Even going from f32 (as trained) to bf16 (as usually run) to q8 tends to do okay for "normal" context windows. And q4 you start feeling like "this model is a little stupid and gets stuck sometimes” (it is! It's just that it's still mostly careening about in the space of "plausible" most of the time. Not good guesswork, but still in the zone). With long contexts, the probability of parameters collapsing to zero are higher, so the more context the more likelihood you are to see brokenness.
And then at Q2 (2 bits per parameter) or Q1, the model falls apart completely. Parameters collapse to zero easily. You start seeing "all work and no play makes jack a dull boy” sorts of behavior, with intense and unscrutinized repetition, followed by a hard stop when it just stops working.
And quantization is a parameter that a model vendor can turn relatively easily. (they have to regenerate the model from the base with more quantization, but it's a data transformation on the order of running a terabyte through a straightforward and fast process, not like training).
If you have 1000 customers and enough equipment to handle the requests of 700, going from bf16 to q8 is a no-brainer. Suddenly you can handle the load and have a little spare capacity. They get worse results, probably pay the same per token (or they're on a subscription that hides the cost anyway so you are even freer to make trade-offs. There's a reason that subscription products are kinda poorly described.)
It's also possible for them to vary this across a day: use models during quieter periods? Maybe you get an instance running a bf16 quantization. If you use it during a high use period? You get a Q4 model.
Or intelligent routing is possible. No idea if anyone is doing this, but if they monitor what you send a bit, and you generally shoot for an expensive model for simple requests? They could totally substitute a highly quantized version of the model to answer the question.
There are •so many tricks• that can be pulled here. Some of them very reasonable to make, some of them treading into outright misleading or fraudulent, and it's weirdly hard to draw the line between them.

General query: are you anticipating the return of 1974 gas lines and perhaps even/odd gasoline filling days?
(I am.)
By-the-way, when that was happening I would go fill my car at midnight - a time when it was ambiguous whether the day was an even one or an odd one.