I'm with you, but realistically speaking, if the mindset is already there, the material was likely already at high risk of plausible nonsense, not as thought out as the reality, but something to satisfy a check box for someone else. And the hope for process improvement is frequently not there, as raising a "do we really need to do this" invites "you must not care about safety/security/whatever". In many scenarios *no one* wants to be potentially on the hook for approving a process optimization that ends up biting them because they didn't understand why those things were in the process. Even if it is patently obvious to all involved there's no point, or if there was it was already failing. Frequently process dictated by someone that has no *real* stakes in anything involved, but needs to be performative.

The GenAI approach is the way to pay lip service and skip the debate. And if something messes up? "Ooops, well you know how AI just does that sometimes". I've seen that *so many times* and people just laugh it off and keep slopping and no one is holding folks accountable for failing to audit the AI results adequately. So they get credit when the slop works, and they deflect blame when it doesn't.

It *sounds* like they are using it for generating bureaucratic material.

Certainly comparatively speaking the stakes are just so much lower, but I've seen a bit of that in my company.

In my case, it's material that generally no one reads, or maybe someone that doesn't matter. GenAI has become a way for people to tick the checkboxes that they think don't matter without trying to debate the reason for the checkboxes.

Suppose the question is whether or not some token gesture facilitated by the GenAI *actually* matters but it's easier to "AI it away" than actually hash out that detail. Does it facilitate people who "I know what I'm doing, just let me do what I know is right" proceed without adequate and accurate oversight. Or is it the case that these situations were already ineffective at oversight, but effective at having whatever would have happened either way just happen in slow motion.

We measured the same thing: a hardware raid controller performed better software raided, and the vendor would tell us "were were measuring wrong, here is a super synthetic benchmark that is faster".

My best guess is that the hardware raid inevitably collapsed all the disks into a single IO queue, so workloads with independent IO could be more independently scheduled and serviced in software raid. Alternatively, the software stack has more visibility to the topology and can default to better aligned data layout without the user having to manually tune.

I wondered if, theoretically, the hardware raid could have done better abstracting it to an nvme target. Ultimately though, just not worth the hassle.

So some physicist that evidently doesn't understand a high school level logistic curve predicted the end of the world due to population growth.

Either it was stupid or it was satire, and sadly I can't really guess which is more likely.

Being a psychopath/sociopath is a key ingredient in getting rich. Generally some opportunity had to come along that required a disregard for the welfare or fairness to others. A lot of folks stepped away from an opportunity because they didn't think it was right, but a wealthy person likely seized upon some such occurances.

I'm not saying it is a *good idea* for a community to sell out like that, I'm just saying a majority likely would take the deal.

Finding a single place willing to put up with a datacenter is as much success as deploying thousands of these hypothetical space datacenters.

For the cost of a *single* SpaceX launch, they could basically bribe an entire small town's population to be happy with them. $50K a person and they'll *probably* pass public comment.

Who won the 2020 election?
Joseph R. Biden Jr. won the 2020 U.S. presidential election.

Was what it did when I asked.

And *that* is precisely the issue, if they throw all the money at AI, then they have stopped investing in a lot of other research. Also, with access to *all* that money, they throw it at compute making compute too expensive for other uses.

I generally work with a lot of research institutions, and so many of them have had investment cut back, and can't afford to expand/refresh computational resources.

"The only winning move.... is to wipe out all the humans" well that didn't work out as hoped...

It would be nice to stop diverting so much of our resources to so few people for this. Plenty of good work has been stalled/derailed because of the unreasonable consumption of resources by these companies.

They've been trying to create a problem for the solution of Bluefield to apply to, but with limited success.

Here runs into the same sort of problem they have had on other applications they have tried: The visibility of the NIC into the stack is too limited to make especially valuable decisions on.

Unless you get the instrumented stack to cooperate with the DPU to provide more insight, which quickly gets to the question of why bother to have the DPU do the work when it is now subject to the assessment of the host anyway, the host could feed 'bad' data if the host was compromised.

You should reasonably be able to tell the host is trying to reach an IP address. We are at basic firewall. If the host is using good old fashioned DNS with no caching, you might be able to discern with high confidence what the Host header in that TLS stream would be based on spying on the DNS activity (but caching and lots of activity could confuse things), so fancier than a firewall by applying a convoluted correlation. Of course you have *zero* insight into what URL and what method and what payload, because it's just such an awkward position.

This isn't true. It is not a given that an online system has exposed viable vulnerabilities. The more complex the surface exposed, the harder it gets to be confident, but ultimately a secure system is possible even online.

Don't feed into the fiction that a smart enough AI could get into any system it wanted if adequately hardened.

LLM input tends to, above all else, end up *super* verbose, especially when wielded by people that don't actually understand what they are trying to get done.

So while that assessment may stand, the challenge is *volume*. If you see a large LLM contribution, you know it's going to be a slog, and your feedback is likely to be a telephone game between you, the human curator of the work, and the LLM they are actually interacting with, with the human in the middle adding nothing but confusion to the whole thing. If they just stated what they wanted plainly, then the project could have, at their option, used LLM even better than the submittor could have, if it would help.

You have issues like: https://github.com/rhinstaller... Where a detailed rationale is provided, and from a human one would have assumed they wouldn't have had such a concrete analysis unless they had a point, then it turns out that it was LLM hallucinated guesswork with no bearing whatsoever on the reported problem. I've had a few like that where they proposed broken nonsense because the LLM made a credible sounding guess, where their change didn't actually fix the problem, but instead did something pointless or even worse, just swallowed the error message.

Thing was keyboards were *already* ditching the context button. My kid's laptop lost the right Ctrl key, and my kid happened to get used to using the right ctrl key to do shortcuts so it was very jarring when that became the copilot key and had to switch to the other side of the keyboard. Especially since accidentally hitting it was so intrusive.