The reference is an example of a flippant sort of response of answering the request, but with something lacking the depth the person was asking about.

He probably doesn’t mind talking about the game broadly, but it can be a bit much for someone to be annoying about saying it should have been a different genre that they would have enjoyed. I suppose your question could be flipped around, why attend a panel discussing doom if you don’t really care for doom?

Sounds like a couple of randos, no one significant. The perspective is the interesting part, not the person expressing the perspective.

So it eventually destroys the company.

So it is just as good as the typical CEO

This is part of why I’m so disappointed in the LLM craze, they basically sucked all attention including some promising uses of machine learning in medicine.

Instead now we put every last memory module towards generative AI…

It is a different substrate for reasoning, emergent, statistical, and language-based, and it can still yield coherent, goal-directed outcomes.

That’s some buzzword bingo there… A very long winded way of saying it isn’t human-like reasoning but you want to call it that anyway.

If you went accept that reasoning often fails to show continuity, well then there’s also the lying.

Examining a reasoning chain around generating code for an embedded control scenario. At one point it says the code may effect the behavior of how a motor is controlled, and so it will test if the motor operates.

Now the truth of the matter is that the model has no access to perform such a test, but the reasoning chain is just a fiction, so it described a result, asserting that it performed the test and it passed, or failed. Not based on a test, but by text prediction. So sometimes it says it failed, then carries on as if it passed, sometimes it decides to redo some code to address the error, but leaves it broken in real life. Of course it can claim it works when it didn’t at all. It can show how “reasoning” can help though. If the code is generated based on one application, but when applied to a motor control scenario, people had issues and so generating the extra text caused it to zero in on some stack overflow thread where someone made a similar mistake.

Oh phone trees are terrible, I refer exclusively to online self service. I suppose an LLM might be able to help a caller connect to the correct set of humans better than phone trees…

If I’m resorting to phone, it’s because I really really need a human. I know there still exist some very old people stuck calling… But if they can’t work your online portal, they won’t be able to work a phone tree either…

The robo-bullshit is great, if the thing has no nuance. Self checkout, paying bills, buying stuff online.

The things is those things are great because they are so predictable. LLM takes the predictability out. It’s also generally not allowed to do anything that the self service portal was not allowed to do, so you get stuck with a more imprecise interface instead of the nice, precise interface of a traditional portal, and no access to more nuanced help. It’s the worst of both worlds.

Yeah, have a new executive who managed a vaguely segment appropriate “hello world” with code gen and so regularly rants about why we should be paying human developers.

The biggest improvement on the user side was to stop trying to weigh the bagging area to prevent loss.

The newer machine vision based systems are less likely to screw up. “Unexpected item in bagging area” was an almost universal experience, nowadays I have only been flagged for human review once.

Also, one store I was at just lets you put your items under a camera without finding barcodes, and you just confirm the identified products.

Think the issue is either a self service portal that works in very predictable way (like the self checkout) or a human to deal with nuance.

To the extent an LLM might be useful, it’s likely blocked from doing so because the operator doesn’t trust it either.

The biggest annoyance is that the LLM support tends to more aggressively refuse to bring a human in.

When I went not long ago, the nearby desert had lots of solar. There was actually a fight about putting more solar, and the utility thought they compromised by putting it up on a mesa, but people griped that it would look bad for skydivers…

And we didn’t have CFC deniers with huge social media platform amplifying fringe conspiracy theories into big political platforms.

Of course, the dangerous CFCs weren’t as critical, if anything new formulations were easy business opportunities for established players. There’s no easy pivot from being a big fossil fuel company to a replacement, any attempt to do so comes with huge risk of being distributed by an unexpected competitor.

The “reasoning” models aren’t really reasoning, they are generating text that resembles “train of thought”. If you examine some of the reasoning chains with errors, you can see some errors are often completely isolated, with no lead up and then the chain carries on as if the mistake never happened. Errors that when they happen in an actual human reasoning chain propagate.

LLM reasoning chains are generating essentially fanfics of what reasoning would look like. It turns out that expending tokens to generate more text and discarding it does make the retained text more more likely to be consistent with desired output, but “reasoning” is more a marketing term than describing what is really happening.

Vegas is in decline not because of lack of pedestrian capability, is just kind of pointless.

Gambling? Well you can gamble much closer to home.

Shows? It’s kind of arbitrary that Vegas was the hotspot, but the residencies are pretty much the same ones they had twenty years ago, and everything else you can find essentially the same show on tour.

Accommodations once luxurious haven’t really kept up, again mostly monuments for how they were two decades ago. Preserving some of the ambition of back then but tossing a lot of it toward the end of saving money, and not really investing in keeping things as nice as you’d expect.

So what you have is the hubris of “look how far we pushed a city on the middle of the desert”.

So, Windows is harder to use you say. And “incompetent” users should stick to Linux?

That’s a take that would have been absurd many years ago. I personally am willing to do things the hard way for some benefit, so I have a Windows PC for gaming. But all my other systems are Linux systems, laptop, workstation, or embedded. However Windiws is supposed to be the easier choice.

I’ll even grant that Windows PITA is mostly not deliberate action by Microsoft. It’s mostly letting vendors be their crappy self and messing up the experience, with a bit of windows driver model incompatibilities breaking hardware support abandoned by vendor, but kept alive Linux side.

Main issue is the inconsistent drivers naturally included in Windows update and just how many things demand you install a weird vendor specific driver, with the steward of what should be a generic Winfows driver sometimes breaking things for other vendors, and/or neglecting the Windows update vintage of their driver.

Architecturally, the Windows driver model should be saner, but for most random devices I have better luck with Linux in how drivers are maintained and supported over time.

I found it relatable because just last night same thing happened in my windows boot, but all of a sudden it decided I had no wifi adapter, even though it worked fine in Linux and hadn’t broken in Windows before. I see it indicating an error in device manager, found a “guide” that specifically called out that device manager error that suggests rebooting the router, because people writing websites troubleshooting guides are morons. The driver model has some weird behaviors that make device behavior more convoluted.

In Linux, generally it either loads and works or it doesn’t and if it doesn’t, you absolutely need a fixed driver or the hardware has a problem. In Windows it can absolutely not work and you go through some weird things, end up with exact same driver and version as before but suddenly it actually works…

The things to remember is that these CEOs have made a whole living out of not knowing what they are doing, but being insufferably confident in whatever vomit of words they spew, whether they know anything or not, while ultimately just saying the most milquetoast blatantly obvious stuff and pretending it’s very insightful. All this while they believe and the money proves that are the most important people in the world.

So naturally it’s easy for them to believe LLM can take all the jobs, because it can easily take theirs.

I just don’t get how so many people just start by it. Every time I set my expectations lower for what it can be useful at, it proceeds to prove itself likely to fail at that when I actually have a use case that I think one of the LLMs could tackle. Every step of the way. Being told by people that the LLMs are amazing, and that I only had a bad experience because I hadn’t used the very specific model and version they love, and every time I try to verify their feedback (my work is so die-hard they pay for access to every popular model and tool), it does roughly the same stuff, ever so slightly shuffling what they get right and wrong.

I feel gaslit as it keeps on being uselessly unreliable for any task that I would conceivably find it theoretically useful for.

And what’s your point?