It’s a wave of sewage, few users want to ride it in the first place
It’s like they created a very good phone tree and are trying to shove it into everything that never had or needed a phone tree in the first place.
The fuck is a phone tree? Pardon my language, sir.
“for financial services, press one. for technical support, press two. for goblins, press three. for repairs, press four.”
Thanks! I just thought that’s some non-existent thing, which Microsoft invented and nobody needs it ever. Well, that’s not far from your point, I guess. But still. Didn’t know that’s called a phone tree!
I know them as IVR https://en.wikipedia.org/wiki/Interactive_voice_response
i thought that was specifically for the voice recognition ones but apparently not.
“three”
#beep#
dispatching goblins. good luck!
*click*
funny you should use that example in particular because i recently had the displeasure of using microsoft’s phone tree. i was trying to close a dead relative’s account and the info on the website was wrong.
they built a phone tree that remembers you. if you try to call in multiple times during some time period (at least several hours) it will just assume you have the same question and skip to your last choice.
it’s a tsunami. uncontrollable, started far away from any normal humans, sweeps up everyone in its wake, and will cause massive damage when it inevitably crashes into a place with lots of people.
Spend imaginary tokens to send an email
Yay
They didn’t miss the “wave”, they discovered it’s just hype and a bubble. They spent a fortune and damaged their core products to try and get in on AI, and have realised it was fools gold that their actual paying customers don’t want. This really sums the problem up well:
According to Velloso, less than 3% of paying users actively use Copilot, even though Microsoft has pre-deployed it directly into the Windows 11 taskbar and across the Office suite.
Out of Microsoft’s 450 million Microsoft 365 user base, the company has only managed to convert roughly 15 million paid Copilot seats. This means a staggering 96.7% of users are rejecting the premium AI features, yielding just a 3.3% paid adoption rate. When viewed against Microsoft’s estimated $37.5 billion quarterly AI spending, this is an alarmingly low adoption rate.
I’m sure I’m like many people - I tried Copilot a couple of times; it’s ok to make an email or even document text a bit more concise, but that’s really it. I don’t find it useful; I do all the actual work and then occasionally get an AI to help make it a bit easier to read very similar to a spell check and grammar check. It’s not good enough to do anything else; it bullshits and is error ridden and like all the AI I’ve tried it’s really plateaued. I just really don’t see where the value in that $37.5bn spent by Microsoft is.
I certainly wouldn’t pay for copilot myself. Instead I object to it being rammed down my throat at work, and Windows 11 just being generally awful but not improved. Microsoft are finally making the right noises but the damage is already done.
No one wants copilot because it’s highly unpleasant hot garbage. There is definitely a market for AI for the competent providers.
Yeah the vast majority of AI “offerings” from most of these huge companies and/or websites is just bolting a chatbot to something and then wondering why people don’t want it. I tried copilot in excel and it couldn’t access the document I was working on, it was an absolute useless mess.
They didn’t miss the wave they just failed to surf it. Anthropic can’t stop making more money, microsoft competed and lost.
You didn’t miss the “mobile wave”. You purposely gave up. Idiots.
True. As much as I hate to admit it, the Windows phones were actually pretty good.
Had they not botched app adoption and then immediately given up, they could have done fairly well.
They were not good, they were dogshit. I had one and it was like a decade behind android.
Agreed I have been a Linux Stan since the 90s and even I thought windows phone was pretty good.
We were lucky and dodged that future enshitification bullet.
The more logical explanation is that AI is not a wave like the Internet and Mobile, but it is instead a wave like cryptocurrencies, NFTs and tulip bulbs.
If there’s one thing that almost 3 decades at or near the forefront of Tech has taught me is that “novel” is not the same as “better”, and that of all the times a novel technology was pushed by insane amounts of hype, only a handful turned out to match the hype and the ratio of good-ones to bullshit has become much worse in the last 2 decades as the Tech Startup sector fully morphed from Techie-driven to Financeer-driven.
On hype alone “AI” (as in, what’s called now AI for the public, rather than the ML domain) stinks of greed-driven bullshit and the more one analyses the Technical details of LLMs and the Mathematics of it as well as of the improvements over time, the more painfully obvious it becomes that it’s not at all AGI or a path to it, rather it’s an overhyped attempt at it that turned out to be the wrong path. (All of which would’ve been absolutelly fine and a big Scientific step forward if it weren’t for the greedy financeer class and grifters pushing, purelly for their own personal enrichment, for people and companies to adopted it for doing things it’s not suitable for)
AI has an interesting economic trait in that it’s very, very expensive to deploy, and made very fast progress from 2022 to 2024. That caused investors with money to believe that:
- Pushing the frontier was going to cost a lot of money. More than any other purported revolutionary tech.
- Extrapolation of past improvement meant that whoever was on the cutting edge may end up with a product with a huge paying market.
- So whoever wins this race would be rich, and the investment would have been worth it for them.
But since 2024, we’ve seen that the cutting edge got even more expensive much faster than expected, and much of the improvements in performance now come from inference rather than training, which represents a high ongoing cost.
Now, if we extrapolate from that trend line, we’ll see that the market will be much smaller for AI services at the cost it takes to provide that service, and the question then becomes whether the industry can make its operations cheaper, fast enough to profitably provide a service people will pay for.
I have my doubts they’ll succeed, and we might just be looking at the industry like supersonic flight: conceptually interesting, technically feasible, but just a commercial dead end because it’s too expensive.
The economics of it don’t add up and the growth rate of the curve of improvement over time has already significativelly fallen which looking at the historical curves for other technologies is a very strong indication that it’s approaching the limits of how far it will go even though it’s nowhere close to the hype.
So at both levels it all looks like a massive bet in the wrong horse that’s turning out not to be a winner but it keeps getting pushed by those who bet on it in the hope of making enough people and companies dependent that its sustained by nothing more than the unacceptable cost of it failing.
(In terms of strategy, it’s similar to how Uber started by using loopholes in the regulations for taxis, investing heavilly in becoming so big and established fast that when Authorities around the world got around to address those loopholes, they ended up accepting Uber and the like as something that could not be reversed and instead of regulating it out of existence, legitimized it. A very similar strategy was used by AirBNB: make the facts on the ground so big and reverting them so damaging that their low-value-adding business model with massive negative externalities and collateral damage ends up protected rather than made to pay for the societal costs of said collateral damage and negative externalities - essentially at some level Uber and especially AirBNB are being heavilly subsidized by society by being allowed to “polute” at will without paying for it).
So as I see it, the way Microsoft and other AI investors are going at it is to try and create a beachhead for it via hype, branding and lock-in in the expectation that something will come along at some point from the companies they invested in that is actually a genuine breakthrough that uses all the computing capacity created with their investment money.
I think that the reason why from the point of view of the public the AI adoption feels wrong is because it’s almost entirelly top-down, driven by marketing techniques and against the natural desires of people - it’s a novel form of entertainment being shoved down people’s throats as suitable for important responsabilities.
From my own experience, this feel a lot like the hype part of the cycle for the Segway, only with 100x or 1000x more investment money behind it.
The economics of it don’t add up and the growth rate of the curve of improvement over time has already significativelly fallen which looking at the historical curves for other technologies is a very strong indication that it’s approaching the limits of how far it will go even though it’s nowhere close to the hype.
Yeah, I’m convinced that they’ve maintained the illusion of continued exponential improvement from 2024-2026 by sneaking in exponential increase in resources (hardware complexity, power consumption), to prop things up past what should have been a plateau.
The way GDP is calculated you can in the short term create GDP “growth” by using debt to invest in things whose eventual return on investment is less than 1.
My only complaint here is that there is a lot of very, very valid use cases for “AI” specifically “Agentic AI”.
We (including myself) may not like a lot of those uses because it devalues my fellow workers but it does not change the fact that it works.
The problem is everyone needs to be so goddamn polarizing and god forbid we have a mature honest discussion about the tools being built and how they are changing society as we know it.
We should be discussing and pushing for UBI across the world for decades now as youth unemployment is already at dangerous levels in continents like Africa (lol of course we don’t care because black people) but no instead we have asshats pushing a narrative of “AI bad”. It’s not. It has many purposes. Smarter people know this and it’s why it isn’t going away and the train is not going to stop if you don’t pull your head out of your ass.
/rant
I can’t wait to dip out of society and find somewhere in the middle of nowhere to live a quiet life with minimal technology in my life. I’m done with all of you. I stand by what I’ve said to my mum many times over the years. I hate people. I love persons.
The list of valid use cases for AI is bound by “what is the worst possible consequence of a mistake done here”, because the statistical distribution of mistakes in terms of severity of consequences of things like Agentic AI is uniform (meaning, they’re just as likely to do the worst mistakes with the nastiest consequences as they are doing the smallest mistakes), which it is not the case with humans who make more of an effort and give more attention to avoiding catastrophic mistakes and also have a “this is stupid” (i.e. don’t put glue in pizza, don’t tell a suicidal person to kill themselves) recognition capability which also stops a lot of the nastiest mistakes.
This is something which is not noticeable to most people because most people don’t have deep enough process experience in at least one expert domain and process analysis experience, to upfront recognized anything beyond the “in your face” elements of using AI (or using anything, really) in a process.
Very few people would think “what’s the risk profile for this business of giving this thing these responsabilities”.
So they seriously overestimate what are valid use cases for AI, something that the hype around it also pushes for: not a single AI vendor will ever mention just “error distribution” or anything close to it.
Obviously, when the thing blows up catastrophically by doing something which for a human is “obviously a bad idea”, THEN people recognized that AI is unsuitable for that, but by then its often too late.
(Easy example: lawyers using AI to make submissions to the Court and ending up disbarred because those submissions “quoted” invented case law).
So I don’t expect Agentic AI to fuck society up by taking a large fraction of the jobs, I expect Agentic AI to fuck society up by an accumulation over time of random catastrophic mistakes that kill people and collapse otherwise stable companies, mistakes that humans in such positions would never do or at least be way less likely to do.
It’s going to be akin to death by cummulative poisoning.
It’s going to be akin to death by cummulative poisoning.
Agree and despite what it may seem like it really is gradual right now. What people are avoiding (god the C level discussions I have been witness to is mindblowing) is the long term damage of their choices today.
The amount of times I have heard executive talks with “you know we both have kids around the same age what do you see this doing?” And they always wrap it with something positive. These fuckers most likely have their kids in private schools, not to mention their kids have all the connections these fucking parents can afford them.
In short the execs making the decisions have their heads equally shoved so far up their own asses they are ignoring the problems on the horizon.
The list of valid use cases for AI is bound by “what is the worst possible consequence of a mistake done here”
Its not because humans make those mistakes all the time. It doesn’t need to be %100, it just needs to be like 95% to be better than humans.
My point is that for Agentic AI mistakes with catastrophic consequences are just as likelly as minor mistakes, which is not the case for people because humans can spot the “obviously stupid” or “obviously dangerous”, plus they make more of an effort to avoid mistakes that can have very bad consequences, so they tend to make catastrophic mistakes will less probability than minor mistakes.
People giving psychological advice are incredibly unlikely to tell suicidal people to “kill yourself”, those giving food recipes are incredibly unlikely to say that pizza should have glue on top or those deploying software in Production are incredibly unlikely to delete the whole fucking Production environment including backups.
So even if the total rate of mistakes of an an Agentic AI was less than a human, its rate of catastropic mistakes would still be much higher than a human.
This is however not obvious unless one actually analises the risk profile of using Agentic AI in a specific place in a specific process, a skill very few people have plus it requires information about and/or understanding of Agentic AI which itself very few people have and the AI vendors activelly do not want people to have.
So you end up with an e-mail fluffing and defluffing machine being used to summarize and store medical info about patients and then down the line somebody gets given something that kills them because the data on file had a critical mistake.
This is why I said that its “the worst possible consequence of a mistake done here” that limit Agentic AI suitability: because generally you’re going to have way more catastrophic mistakes with an AI that you will even with even an human with no domain experience.
generally you’re going to have way more catastrophic mistakes with an AI that you will even with even an human with no domain experience.
That’s just not even true. People with no experience are going to fuck shit up completely. We have a human president and look where that’s getting us.
Even people with zero experience in counseling don’t tell a person who is thinking of committing suicide to “kill themselves” and even those with zero culinary experience don’t tell others they’re supposed to put glue on top pizza when you’re making it.
To do that a human needs not just have zero experience but actually have no common sense whatsoever.
Further, even with such people, it’s only if they’ve been given the tools to do things with a huge impact that it becomes a problem: that’s pretty much “child with a loaded gun” situations.
The number of humans that inept given such power is minuscule (pretty much just children given loaded guns), whilst every single Agentic AI out there is that stupid and they’re currently being given “loaded guns” all the time.
The problem is exactly that Agentic AIs are being given adult responsibilities and have the capacity for complex operations whilst having the common sense and reasoning abilities equivalent to those of a small child.
Maybe AI is a particle?
Maybe it only behaves as a particle when it’s being observed?
The “AI wave” is a scam. Everyone missed the AI wave because it sucks at everything except making slop.
That’s why I embraced the Dagothwave.
Context for all you n’wahs - https://www.youtube.com/watch?v=iR-K2rUP86M
this is a decent read. theres honest criticism and not a “m$ sux lol” rant. a someone who can agnostically enjpy tech history, i would like to see how this plays out.
Yeah good read. I don’t agree that Microsoft isn’t dying though. They are, because people and companies alike are tired of other corporations throwing them under the bus. So many people are realizing that the companies don’t want what they want, and it kills their business or happiness.
They are dying because they have horrible leadership. They are solely focused on subscription revenue now, and everything else is just left to rot. They’ve pretty much lost any urge to do anything creative with their money and manpower.
Wave? This is like being sad you did not get in on the housing crisis, or the dot com bubble, or any other clearly labeled landmine.
I know right. They dodged the AI bullet would be a more accurate headline.
I don’t think they dodged it
Prolly not eh
There is no “AI wave”. Machine learning can he incredibly powerful when used properly, and is being used to process scientific and medical data in pursuit of improving humanity’s understanding of reality around us.
But that is not what Microslop is pushing. LLMs that exist to chew up RAM, water, and electricity to shit out slop and generate suicidal tendencies in children.
They aren’t trying to make copilot useful, they are trying and failing to make it profitable, just like every other LLM.
The " AI Wave" is just a fiction. The whole idea is just an attempt to get investments for companies that don’t and cant really produce any value. I’ve tried many of these “AI” tools and none of them can really do anything useful.
From what I’ve seen programmers are using Claude a lot. It may still cause problems in the medium to long term by squeezing out junior developers or atrophying the skills of senior developers, but in the meantime it is speeding up production of code.
It’s also making scams a lot easier by simulating real human communication, up to and including video chat.
I’m not sure what will cool down the hype. It’s almost exclusively driven by c-suite morons who find AI very useful for writing unclear emails and inaccurate notes. The sort of things they’d do themselves before. Even programmer who adopt it are mostly quietly muddling along.
They didn’t miss shit, they just competed and lost to like the four other AI companies that executed much better than them.
First off, copilot is just ChatGPT.
Second off, their implantation of ChatGPT is so bad it actually makes the original look good. And that is a damn low bar to reach for and miss.
Are you really being “left behind” when everyone else is going the wrong way?
I’m really baffled because this is super easy to fix.
Step 1. Pull all the AI bloat out of Windows 11. Make a clean, compatible, and user friendly OS out of the Windows brand.
Step 2. Spin CoPilot into it’s own OS. Go crazy with your “Every app is just a different AI presentation of your data.” Make the AI in there all powerful. Allow users to remote to the OS and run the same AI regardless of the platform.
Step 3. Print money
The problem isnt co pilot. Its co pilot being rammed in incredibly stupid ways into every possible product.
More importantly, its cramming it in everywhere when basis windows 11 sucks. Explorer sucks, search sucks, performance sucks, Updates suck.
The problem isnt co pilot
I will stop you there because Copilot is downright horrible compared to other LLMs lol
You’re saying they’re going “the wrong way”, but from the standpoint of a publicly traded company it’s literally the best way possible.
You promise to give $1million to Nvidia, Nvidia promises to give $1million to you - wam, bam, suddenly your stock market valuation’s up, people are throwing their money at you, and you didn’t even have to call your bank to make any transfers.
They’re literally printing money out of thin air.
That it will all crash and burn at some point? Who cares? If everyone goes down, you can blame the market. If you’re not in on the bandwagon while everyone else is printing money, you get sacked by the board of directors.
That’s all there is to it.
Microslop was right there along with the rest of them. Idiots with more wealth/resources than they are actually capable of managing letting fear/fomo drive their decision making is going to bury us all.
What wave? None of it fucking works…
I think it is so strange people say stuff like this as though there aren’t objective metrics showing it does. We don’t have to like the billionaires using it to subjugate people, or the energy and water consumption, or the theft of copyrighted materials to be honest about the technology.
It does work. As far as ml models go, since backpropagation was implemented in training, transformers have become extremely capable.
Every actual objective metric shows that companies have been using the LLM craze to cover for their layoffs for other reasons. That the dumbasses who did pay for it are spending more than their developer salary budgets for lower quality shit that needs people to fix it anyway, and that employees fucking hate having to use it - because it’s shit. People wouldn’t be tolenmaxxing to waste their quotas if they thought it was working.
There is definitely some truth to what you’re saying, but my point is that those aren’t conflicting with the technology working. There are many scholarly refereed papers on transformer performance and generational improvement on standardized metrics. I don’t see the value in conflating something working with it being good or ethical. There is a gap between utility and hype, yes. That doesn’t mean it doesn’t work, and the inexorable negativity that comes invariably to comments recognizing this simple truth undercuts actual critical feedback.
LLMs work like LLMs. Sure, in that way they work.
LLMs are not Gen AI. Like they are being sold as. In that way they do NOT work.
If they hadn’t pitched these things as the singularity, people would be singing a different tune. But they’re at best, a usability interface layer for other things. Not something that needed to be shoved down everyone’s throats and spawn thousands of slapdash datacenters
I don’t care anymore. Haven’t used Windows in years.
