Thanks for replying! That's a good reason. Reporting is always hard, and of course, many things appear obvious in hindsight!
13,551 karma · joined May 15, 2013
Same thing the large transfer tax changes, vacancy taxes, etc. The inflation adjusted budget is definitely higher.
I never know what business codes / job codes get included in "Professional, scientific, and management, and administrative and waste management" but there's an explicit separate one for Information that is only 6.3% (https://data.census.gov/vizwidget?g=050XX00US06075&infoSecti...)
People write about tech jobs because they're highly paid (on average) and highly visible. But it's not the case that the city is entirely dependent on technology. You wouldn't say the same thing about the equally large segment of "Finance and insurance, and real estate and rental and leasing".
We did pass gross receipts taxes and do tax payroll for larger businesses. So yes, companies pay more taxes than 2015 (though they didn't choose to) and our budget per person in inflation adjusted terms is up:
A $16 billion question: How did San Francisco’s budget get so huge?
A lot of that is from "self-supporting" segments including SFO.
> Finally, Spark contacted Murray Close, the photographer who took the picture of Jack Nicholson that was inserted into the original image.
> The photographer revealed that "there was no such thing as the Warner Brothers photo archive [and] that was a complete mistake."
> Instead, Close had sourced the original photo from the BBC Hulton Photo Library in London, now part of Getty Images.
> The photo, it turns out, was taken at a Valentine's Day dance on February 14, 1921, in the Empress Ballroom at the Royal Palace Hotel in London.
https://waymo.com/blog/2024/09/waymo-and-uber-expand-partner...
Also to Belize and other parts of Central and South America. They don't all stop in Mexico.
> Do we really need 106 different rate plans in California? Why don’t utilities automatically put people on the cheapest rate plan for them, and reevaluate monthly based on usage?
And I think it makes sense to simplify, but I would bet that the old plans are required to persist for existing customers. That's how the NEM 2 folks are sticking with their previous contracts. It would be more efficient for everyone if PG&E could rationalize these various plans, but to do so, they'd also need to forcibly migrate people to other plans.
cloud.google.com/about/locations lists all the locations that GCE offers service, which is a super set of the large facilities that someone would call a "Google Datacenter". I liked to mostly refer to the distinction as Google concrete (we built the building) or not. Ultimately, even in locations that are shared colo spaces, or rented, it's still Google putting custom racks there, integrating into the network and services, etc. So from a customer perspective, you should pick the right location for you. If that happens to be in a facility where Google poured the concrete, great! If not, it's not the end of the world.
P.S., I swear the certification PDFs used to include this information (e.g., https://cloud.google.com/security/compliance/iso-27018?hl=en) but now these are all behind "Contact Sales" and some new Certification Manager page in the console.
Edit: Yes! https://cloud.google.com/docs/geography-and-regions still says:
> These data centers might be owned by Google and listed on the Google Cloud locations page, or they might be leased from third-party data center providers. For the full list of data center locations for Google Cloud, see our ISO/IEC 27001 certificate. Regardless of whether the data center is owned or leased, Google Cloud selects data centers and designs its infrastructure to provide a uniform level of performance, security, and reliability.
So someone can probably use web.archive.org to get the ISO-27001 certificate PDF from whenever the last time it was still up.
> evaluate relative brightnesses between art assets, and improve overall game readability
The method in Color2Gray is trying to enhance salience, but the paper does a good job of comparing the problems (including red / blue examples in particular).
Like other commenters, I think oklab would look better than CIELAB on the example given in the OP. https://bottosson.github.io/posts/oklab/#comparison-with-oth... and the Munsell data below it show it to be a lot more uniform than either CIELAB or CIELUV.
As https://www.microsoft.com/en-us/research/blog/meteoric-rise-... reminded me, they were on like 20% of the SIGGRAPH papers in 1996. And several have stood the test of time, like Hugues's Progressive Meshes paper (https://dl.acm.org/doi/10.1145/237170.237216). A little later, the spherical harmonics paper (https://dl.acm.org/doi/10.1145/566570.566612) was basically all MSR (I think Jan maybe interned there while at MPI? It's been a long time...).
That isn't to defend anything in AI, but it's not the case that they had no impact. The oral history thing there claims that the first grammar checking in Office 97 came from their NLP work.
https://waymo.com/blog/2024/11/waymo-one-open-to-all-in-los-...
You need to remember that was during the financial crisis, and the first chips were going to be laughably bad and uncompetitive. From the quote in that article:
> Justin Rattner (Intel Senior Fellow) demonstrated Larrabee hitting one teraflop, which is great but you could walk across the street and buy an ATI graphics board for a few hundred dollars that would do five teraflops.
Intel had no chance for v0 to do anything but lose money. They were way off track, and spent most of the time trying to get to a software rasterizer plus hardware that could work for some games.
They did pivot Larrabee into the various Knight chips (Knights Corner, Landing and whatever else) since the "it's just x86" was a pretty compelling story in the 2009 era. But ultimately, HPC wasn't that great a market in the early 2010s for accelerators yet and NVIDIA ended up totally eating their lunch over time.
I think Intel could have stuck with the HPC market and gotten lucky once ML exploded, but realistically until about 5 years ago there wasn't that much ML spending yet either. 10 years of last place discrete GPU work would have been difficult to invest in.
tl;dr: the business case for Larrabee hinged on having a successful gaming business and it wasn't even close.
On the flip side, until somewhat recently, NVIDIA GPUs didn't have the kind of hardware protections you'd want to build a modern multitenant OS (e.g., hardware page table and TLB support).
In the actual tweet (https://x.com/ID_AA_Carmack/status/1865127952712905197) he mostly seems to be talking about RLO style diagnostics with busybox on the device much like Dell servers with fancy BMCs:
> I still think today’s GPUs should be able to operate without host CPUs if they have a private link. Chains of accelerators are a legitimate use, but it would just be fun if GPUs made their own video signal with diagnostic information when you apply power outside of a host system. You could go farther and put a tiny linux system running busybox on your command processor, and backchannel keyboard input through the display port if you don’t have a USB port.
That said, I feel like writeback caching is a bit ... risky? That is, you aren't treating the object store as the source of truth. If your caching layer goes down after a write is ack'ed but before it's "replicated" to S3, people lose their data, right?
I think you'll end up wanting to offer customers the ability to do strongly-consistent writes (and cache invalidation). You'll also likely end up wanting to add operator control for "oh and don't cache these, just pass through to the backing store" (e.g., some final output that isn't intended to get reused anytime soon).
Finally, don't sleep on NFSv4.1! It ticks a bunch of compliance boxes for various industries, and then they will pay you :). Supporting FUSE is great for folks who can do it, but you'd want them to start by just pointing their NFS client at you, then "upgrading" to FUSE for better performance.
It's easier for most building blocks (like transcendental functions) to be discussed in terms of worst case ULP error (e.g., <= 1 everywhere, <= 3, etc.). For example, SPIR-V / OpenCL has this section on the requirements to meet the OpenCL 3.0 spec (https://registry.khronos.org/OpenCL/specs/3.0-unified/html/O...). NVIDIA includes per-PTX-revision ULP information in their docs (e.g., https://docs.nvidia.com/cuda/parallel-thread-execution/#floa... for Divide and https://docs.nvidia.com/cuda/parallel-thread-execution/#floa... more broadly).
They don't have the full suite of GCS's capabilities (https://cloud.google.com/storage/docs/request-preconditions#...) but it's something.