Yeah, at some point I gave up and asked AI to do patching for me. It was a good call because it found affected certificates in places where I wouldn't look (e.g. aws-cli or Libre Office).
> Asking for a second opinion sucks. A lot of us are preconditioned from birth to trust our clinicians.
I wonder if it's a cultural thing. I live in Poland, here we ask for second, third and sometimes more opinions in cases far more trivial then cancer. We do this before any kind of surgical procedure, painful treatment, anything that could be even unpleasant. I saved myself from a couple of root canal treatments just by consulting different dentists. We don't trust doctors at all.
These ones are from BYD, however Poland is constructing another, smaller BESS in parallel where the batteries will be supplied by LG Energy Solution and manufactured near Wrocław, Poland.
To be fair, in Europe, we largely rejected the russian COVID vaccine. In theory we had good reasons, the vaccine was a bit shady, but I always wondered how much geopolitics played the role and how much it was really the problem with russian manufacturing standards.
> in Europe, we largely rejected the russian COVID vaccine. In theory we had good reasons, the vaccine was a bit shady
That is an understantement. The Russians publicly acknowlaged the vaccine aproval had been rushed and international protocols hadn't been met. And that is what they said publicly.
Since more reputable vaccines were comming online from other sources, why take the risk?
I’m sure geopolitics had some effect, like it might have in China, but I think that just begs the question how serious the virus was for governments to say nah we will wait until we get our own vaccine from our trusted sources. Russia has vaccine skepticism too entirely if their own making.
In Europe’s defense, which is a very broad thing to speak of anyway, they had a vaccine either already there or close enough so why give Putin any credence when you could wait just a little bit longer?
> The project was met with significant legal challenges from authors and publishers which was eventually overcome
I don't think they were overcome. As far as I remember Google couldn't make the books available so they abandoned the project. They possess the scans (if they didn't delete them) but they won't be made public.
IIRC the courts ruled that because it would be implausibe for a person to use google books previews to read an entire work (you'd have to make a whole bunch of separate accounts to do so), it could not plausibly impact the market for that work.
The consensus among copyright lawyers is Google lost Authors Guild v Google, but for some reason the media and Wikipedia do not clearly report it that way.
In some countries they do, in some they don't, in others every PhD student even gets a scholarship. Every person I know who did the PhD did it because they loved the topics they were studying.
The author of the blogpost is from Russia, I bet he didn't have to pay for his PhD.
My uneducated guess says, not much. For running massive models you still need a ton of high-bandwidth interconnects between many individual chips/GPUs/etc since you need to do math across a few TB worth of weights. That's simply going to require more power (and more die area in I/O, and therefore more cost). Being able to run small models in tiny power envelopes is incredibly useful to people, but I believe it will be covering a different niche than what datacenters can provide. Likewise, you'll still need crazy amounts of high-end memory to populate whatever goes in these datacenters.
The only thing that will crash prices is reduced demand (duh) or, more interestingly, increased production. In particular, if CXMT is able to get their DDR5 fabs up to a reasonably high yield, that could add some downward price pressure (as could government subsidies). As well, if Micron/Kingston/Hynix think that CXMT is going to start cutting into their market share, they might be willing to either increases supply or drop prices. Unfortunately CXMT looks to be taking quite a while to get their new fab up to max capacity so that may take a year+ before anything manifests.
If you're interested in following the (publicly available) info on these sorts of things, check out what companies like Axelera, DeepX, and MemoryX are doing today and have on their roadmaps, as well as the sorts of chips/SoCs Qualcomm, Kinara (now NXP), and Ambarella currently have announced (or have on the market). And remember, that pretty much all of these chips on the market today were in initial development more or less when ChatGPT first launched. If you knew what you knew today (or a year ago) about what requirements current- and next-generation models would have (from a silicon perspective), what might you do differently? Think for instance, host system interconnects, amount and speed of on-package or on-die memory, image/video decode capabilities, int8 vs fp8 vs fp16 vs bf16 compute units, etc. And, consider that most "AI" stuff in development a few years ago was all 15nm or 12nm - because who was gonna pay big money to get fab capacity at 3nm to run some object detection models? So most of the stuff on the market today is on very old nodes and therefore not super power efficient.
Pretty well, to the point where the US administration complains that there's a trade imbalance. (which is true for manufactured goods, false when we count in services)
reply