Outlook not so good… nailed that one too.

Inspired by your comment, I polled ChatGPT 5 direct and Copilot itself, and ChatGPT was smarter than the executive by saying it was a bad idea, while Copilot itself said it might be a bad idea, but it’s aligned with Microsoft’s vision, which may be more important, but ultimately seemed to have no idea if it was a good idea or bad idea…

So I guess ChatGPT at least is smarter than the MS CEO. Of course Copilot seemed primed to try to favor and vindicate Microsoft’s decision. I tried a more aggressive statement that it was stupid to try to get that ‘I agree with you by default’ and it still tried to soften the perspective in favor of Microsoft.

As a bonus, I asked if it would be a good idea to rename LibreOffice to LibreSidekick. It looked more like the ChatGPT 5 answer for Office to Copilot, saying it’s a dumb idea, until the end when it said unless it has an AI assistant like Microsoft Copilot, then it would be a good idea…

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.

Considering a lot of the full YouTube videos are full of padding, taking over ten minutes to get to the point, I can understand why the shorts would have appeal.

Problem is one way or another people are being incentivized to target a specific runtime regardless of whether they have the material to fit.

Well yeah, I would assume Steam would be a big priority for this scenario…

Had a relative with a toddler that almost died due to his GCM overreporting his levels.

My mom had one and learned immediately not to trust it.

I’m shocked that both people I know personally had those devices turn out to be uselessly inaccurate…

Nah, AI code gen bugs are weird. As a person used to doing human review even from wildly incompetent people, AI messes up things that my mind never even thought needed to be double checked.

Oh man, I remember marveling at BeOS in the day and for a brief moment in time when SSDs first hit the scene you could have a credibly fast Windows boot… Nowadays it’s worse than ever despite super fast storage, fastest CPUs, and gobs of RAM…

There was a while back some Windows developer externally lamenting how ass-backwards they were and as a result their NT kernel was woefully under-featured compared to other contemporary OSes…

Then I think they forced him to take it back and say ‘um actually our kernel is actually super awesome, my mistake’.

They did not, they had some touch screen button.

They basically needlessly increased risk for the sake of avoiding optics of a safety driver with direct controls possible.

That’s a good point, also if you can compare like to like conditions and what the data does if you exclude teen drivers. Also if you can identify incidents related to bald tires and brake failures that wouldn’t apply.

Also would be interesting to compare human augmented driving miles to full autonomous miles. With the automated emergency braking/collision alert/lane centering assist. Anecdotally was teaching my teen to drive. Suddenly a car pulls out right in front of us, zero warning. If that happened to me, with experience on a formerly normal car, I’m pretty sure I would’ve wrecked. However my kids reflex to swerve triggered the cars “evasive steering assist” and did an action movie worthy maneuver, avoiding going off into the ditch and returning just right into the lane after getting around the other car.

Thing about autonomous driving is that it seems to get the stupid easy stuff wrong in dangerous ways, but if you have a demanding precise maneuver to make, it has a better chance once that maneuver is needed.

The challenge is one approach only needs to modify the transit infrastructure. The other means having to tear down and build new commercial and residential properties and force people and businesses to relocate in order to have a vaguely sane transit system. My area desperately wanted to do transit but even with rather significant hypothetical funding, they could only service about 10-15% of typical trips. They’ve settled on a plan that is much less money, but only serves like 5% of trips. To go with that plan, they are making restrictions around zoning to force mid density mixed use construction only, favoring one of the two chosen transit corridors.

They are trying but just people are distributed very awkwardly for mass transit.

Let’s put it this way. If you knew a person, and that person just had their fourth crash in 8 years having driven 160k miles, would you think “this person is a bad driver” or would you think “they only crashed 4 times, let’s see where this goes”.

Especially if you’ve seen this driver drive in the wrong lane, go straight in a turn only lane, and other dodgy maneuvers regularly.

A small sample size would just make the prediction highly uncertain, could be way better or way worse.

However others have made the observation that it’s reasonable to consider the miles driven as the sample size, and at over 300,000 miles, it is a bit more credible sounding.

Funny part was that tesla taxis also had a human attendant, but for the sake of appearance made them sit on the passenger side. They deliberately limited staff from being able to interact with steering and pedals.

They eventually moved those to the driver seat.

Going by inflation adjusted market cap values, it certainly looks like the financial facet of the AI companies alone are bigger than both those events… This is going to be beyond messy…