We live in a world of no regulation (or, to be precise, no enforcement on regulations) but…

Holy shit? Stopping is the one time you actually SHOULD look at your infotainment screen to futz with climate control or check how many minutes until the next exit and so forth.

Tumblr was already in a bad place and was further cannibalized by instagram (and reddit).

Reddit still has no meaningful alternatives. Yes, we like lemmy. Most people don’t and won’t. They want corporate social media. Just look at how long it took people to leave twitter. And they only did once BlueSky had open sign ups.

My money is on a bunch of “protest” posts and subreddits to track this and people mostly just sit around and not care. With a lot saying “I don’t need porn on reddit, I have the internet” while completely ignoring things like trans erasure.

Its annoying as hell but I guess I don’t really see a meaningful impact. Yes, not everyone has a cell phone. But… I would say anyone who is flying doesn’t have an excuse of poverty.

And basically every single airport has “free” wifi these days. So either install the app or open the web page to get up to date info. Because there are countless stories of people who missed their flights because they were waiting at the original gate and somehow ignored everyone around them getting up and walking away when the gate changed.

Also: My excuse with departure boards has always been that EVERYONE crowds in front of it to have long conversations or “just stand there” and it is a shitshow anyway.

So yeah. Would REALLY prefer it to not be just even more ads being shoved down our throats. But this very much feels more like phasing out phone booths than anything else.

…

Excusing what? Someone called out the “free speech absolutist” hypocrisy. You assumed they were talking about Github or Microsoft for some reason. I corrected you.

Maybe learn how to contribute to a conversation?

This is being done by trump and musk.

Microsoft just own the company where this is being discussed because the people actually doing the work are treating it like any other software project.

I know it is applying logic to where there is none but…

In what world does it benefit trump, project 2025, and putin for Canada to have 10k more troops on the border?

Yeah. This is totally getting nuked by the admins. Also, Gritty don’t need a guillotine: he got feet.

And the security in DC and on the capitol building is very much going to be the “shoot first, plant antifa flags later” variety the moment there is a sign of ANY mass protesting. And considering there are semi-credible theories that the Fifth is a trap to begin with…

That is the beautiful part of it. It is a fundamental brain block in like 99.999999% of “The Children”.

In an old life I had to deal with this. Maybe one in every hundred interns we had realized how similar matlab and fortran were. The rest just immediately locked down because it wasn’t python or, in rare cases, C++.

AI mostly lies to us because it is trained on data containing lies, misinformation, and nonsense.

I have no idea why that would feel like a pertinent thing to say. Hmm.

The greatest and most vital of government secrets are safe. Because no chance any of those kids understand fortran or cobol.

They’ll just delete it rather than try to understand or modify it. But small victories.

Ah, but you see, he was a genius who was saving the world through EVs and space travel.

I do think a lot of it was based on sock puppets on social media. But I also think it is just an inherent side effect of all of us defaulting to being in content bubbles and many people going farther to outright block “political” content.

And then you just have the ongoing, and successful, efforts to vilify journalism and news media.

musk, at the height of his popularity, made it a significant part of his life to insist that a hero who rescued people trapped in a cave was a pedophile because they turned down his robot that wouldn’t even fit in the tunnels.

This is the kind of shit that he does notice. And it destroys him.

What “point”?

Your “point” was “Well I don’t need it” while ignoring that I was referring to the market as a whole. And then you went on some Team Red rant because apparently AMD is YOUR friend or whatever.

Ah. Apologies for trying to have a technical conversation with you.

And you are basically a single consumer with a personal car relative to those data centers and cloud computing providers.

YOUR workload works well with an FPGA. Good for you, take advantage of that to the best degree you can.

People;/companies who want to run newer models that haven’t been optimized for/don’t support FPGAs? You get back to the case of “Well… I can run a 25% cheaper node for twice as long?”. That isn’t to say that people shouldn’t be running these numbers (most companies WOULD benefit from the cheaper nodes for 24/7 jobs and the like). But your use case is not everyone’s use case.

And, it once again, boils down to: If people are going to require the latest and greatest nvidia, what incentive is there in spending significant amounts of money getting it to work on a five year old AMD? Which is where smaller businesses and researchers looking for a buyout come into play.

At the end of the day, every company will choose to do it faster and cheaper, and nothing about Nvidia hardware fits into either of those categories unless you’re talking about milliseconds of timing, which THEN only fits into a mold of OpenAI’s definition.

Faster is almost always cheaper. There have been decades of research into this and it almost always boils down to it being cheaper to just run at full speed (if you have the ability to) and then turn it off rather than run it longer but at a lower clock speed or with fewer transistors.

And nVidia wouldn’t even let the word “cheaper” see the glory that is Jensen’s latest jacket that costs more than my car does. But if you are somehow claiming that “faster” doesn’t apply to that company then… you know nothing (… Jon Snow).

unless you’re talking about milliseconds of timing

So… its not faster unless you are talking about time?

Also, milliseconds really DO matter when you are trying to make something responsive and already dealing with round trip times with a client. And they add up quite a bit when you are trying to lower your overall footprint so that you only need 4 notes instead of 5.

They don’t ALWAYS add up, depending on your use case. But for the data centers that are selling computers by time? Yeah,. time matters.

So I will just repeat this: Your use case is not everyone’s use case.

Your assessment is missing the simple fact that FPGA can do things a GPU cannot faster

Yes, there are corner cases (many of which no longer exist because of software/compiler enhancements but…). But there is always the argument of “Okay. So we run at 40% efficiency but our GPU is 500% faster so…”

Nvidia is the Ford F-150 of the data center world, sure. It’s stupidly huge, ridiculously expensive, and generally not needed unless it’s being used at full utilization all the time. That’s like the only time it makes sense.

You are thinking of this like a consumer where those thoughts are completely valid (just look at how often I pack my hatchback dangerously full on the way to and from Lowes…). But also… everyone should have that one friend with a pickup truck for when they need to move or take a load of stuff down to the dump or whatever. Owning a truck yourself is stupid but knowing someone who does…

Which gets to the idea of having a fleet of work vehicles versus a personal vehicle. There is a reason so many companies have pickup trucks (maybe not an f150 but something actually practical). Because, yeah, the gas consumption when you are just driving to the office is expensive. But when you don’t have to drive back to headquarters to swap out vehicles when you realize you need to go buy some pipe and get all the fun tools? It pays off pretty fast and the question stops becoming “Are we wasting gas money?” and more “Why do we have a car that we just use for giving quotes on jobs once a month?”

Which gets back to the data center issue. The vast majority DO have a good range of cards either due to outright buying AMD/Intel or just having older generations of cards that are still in use. And, as a consumer, you can save a lot of money by using a cheaper node. But… they are going to still need the big chonky boys which means they are still going to be paying for Jensen’s new jacket. At which point… how many of the older cards do they REALLY need to keep in service?

Which gets back down to “is it actually cost effective?” when you likely need

Not small but… smaller than you would expect.

Most companies aren’t, and shouldn’t be, training their own models. Especially with stuff like RAG where you can use the highly trained model with your proprietary offline data with only a minimal performance hit.

What matters is inference and accuracy/validity. Inference being ridiculously cheap (the reason why AI/ML got so popular) and the latter being a whole different can of worms that industry and researchers don’t want you to think about (in part because “correct” might still be blatant lies because it is based on human data which is often blatant lies but…).

And for the companies that ARE going to train their own models? They make enough bank that ordering the latest Box from Jensen is a drop in the bucket.

That said, this DOES open the door back up for tiered training and the like where someone might use a cheaper commodity GPU to enhance an off the shelf model with local data or preferences. But it is unclear how much industry cares about that.

Prices rarely, if ever, go down and there is a push across the board to offload things “to the cloud” for a range of reasons.

That said: If your focus is on gaming, AMD is REAL good these days and, if you can get past their completely nonsensical naming scheme, you can often get a really good GPU using “last year’s” technology for 500-800 USD (discounted to 400-600 or so).

From a “compute” perspective (so not consumer graphics), power… doesn’t really matter. There have been decades of research on the topic and it almost always boils down to “Run it at full bore for a shorter period of time” being better (outside of the kinds of corner cases that make for “top tier” thesis work).

AMD (and Intel) are very popular for their cost to performance ratios. Jensen is the big dog and he prices accordingly. But… while there is a lot of money in adapting models and middleware to AMD, the problem is still that not ALL models and middleware are ported. So it becomes a question of whether it is worth buying AMD when you’ll still want/need nVidia for the latest and greatest. Which tends to be why those orgs tend to be closer to an Azure or AWS where they are selling tiered hardware.

Which… is the same issue for FPGAs. There is a reason that EVERYBODY did their best to vilify and kill opencl and it is not just because most code was thousands of lines of boilerplate and tens of lines of kernels. Which gets back to “Well. I can run this older model cheap but I still want nvidia for the new stuff…”

Which is why I think nvidia’s stock dropping is likely more about traders gaming the system than anything else. Because the work to use older models more efficiently and cheaply has already been a thing. And for the new stuff? You still want all the chooch.

It was a combined effort to suppress voter turnout. Provide every possible reason to tap into that bernie bro “the democrats deserve to lose because they betrayed me” mindset.