Asmongold TV - replacing people with AI is not going well | Asmongold TV

Episode Date: October 4, 2025

Replacing people with AI is not going well Asmongold podcast for all of his stream highlights, competitions, reactions & more. ------------------------------ --- Keywords: esports commentary, gaming takes, streaming highlights, world of warcraft, gaming news Learn more about your ad choices. Visit megaphone.fm/adchoices

Apparently people are replacing humans with AI a little bit too early. The fast food chain Taco Bell introduced artificial intelligence at over 500 locations in the United States. I fucking knew it. I knew it. Because they started getting my order right for the first time in 30 years. I'm like, how are they getting it right now, but they haven't been getting it right for 30 years? No, now I knew they were doing this. to reduce mistakes and speed up orders. They did.

But in some cases, AI delivered just the opposite. Like this frustrated customer, McDonald's drive-thrues. Nope, nope, I'm not going to do that. Because I'm telling you, people do that too. So I think that at every fast food restaurant, they have a competition.

Who can speak the worst English? And the person that wins that competition gets to take orders from the drive-thru. So really, when I see this, it's not a surprise at all. Also tried AI, but decided to scrap it because it was too unreliable. One person had bacon added to their ice cream in error, and another... No, that's just a fat person saying it was a mistake. They probably did that on purpose.

Hundreds of dollars' worth of chicken nuggets mistakenly added to their order. Ah, another fatty. As for Taco Bell, the fiasco has caused them to rethink their use of Yeah. Their chief technology officer, Dane Matthews, told the Wall Street Journal, in regards to deploying the voice AI system, quote, sometimes it lets me down, but sometimes it really surprises me, end quote. That's what people do.

He said is the very crux of consumer generative AI today. It works most of the time, but about a few percent of the time, it just gets things wrong. Yeah. But where does this all lead? A recent MIT report found that after surveying 150 business business, business leaders and 350 employees. Just 5% of integrated AI pilots are extracting millions in value, while the vast majority remains stuck with no measurable profit and loss impact.

In other words, it's probably true. AI implementation fails in 95% of the cases. Yeah, I wouldn't be surprised. The market was spooked by these findings and shares in NVIDIA, the $4 trillion company whose chips power the AI boom, dropped by 3.5% while Palantir fell by 9% off the back of the new. Damn, bro.

news. It all sounds pretty heavy, but this was just a reaction to the headline, because as you dig deeper into what was actually said in the report, the picture isn't as clear cut as AI simply failing everywhere. Yeah, obviously. A few episodes ago, I talked about the current crisis with new graduate jobs. A large part of that was the AI threat. Imagine going to school for four or six years, and then whenever you start school, you're going to get a job. and by the time that you finish your degree, your jobs been replaced by a robot. That would suck.

It's true and happening some entry-level jobs, especially in the creative fields. I'll be pissed. I did caveat in that episode that current AI system still get a lot wrong, but will improve in the future. But today, let's explore that fact a bit more deeply. What if generative consumer AI

continues to underperform in businesses for years to come? In this episode, we'll look at how AI is actually performing once put into the position of taking people's jobs. To summarize the sentiment of this episode, I think that AI will never completely replace a lot of jobs, but it will make one person able to do five jobs. I think it will act mainly as a force multiplier,

and then expecting it to completely replace people altogether, I think is, you know, you're just, you're jumping the gun way too much. And I think that's really where AI is going to come in clutch. AI is an extension rather than a replacer. Exactly. Now, does it replace people by abstraction? Because obviously if you have one person doing five people's jobs, well, you don't need the other four people, right?

Yes, but it's in the matter of the way that you frame it. Consumer Generative AI will revolutionize global productivity eventually, but as for now, it's possibly in a bubble. I don't know about that. You are watching told Fusion TV. We'll see. So first thing, let's lay it out straight. AI has some legitimate use cases and works well in non-critical areas that don't require 100% precision.

Robots, live translation, and even some prototype website builders like Loveable are some examples. But the sentiment is clear. Most people online find it annoying. But that aside, there's a fun... I think that there is a massive internet circle jerk of people that negatively talk about AI. And I think it's become kind of like that give me likes for saying that AI is bad type thing. I think a lot of AI hate is kind of like, I think it's very forced. And it's kind of like appealing to this group of people that I feel like are delusional.

Like a lot of the people that are talking about AI being bad are, you know, that are like content creators or artists or stuff like that. And I can get why people would complain about it. But you can't deny that this is going to have a very, very large effect on, you know, just business in general. Reddit hates AI. Yeah, a lot of platforms hate AI. The reason why people hate AI, I think one of the big reasons, is because it stands to take their jobs away. That's the reason why. I think that's the main thing.

Fundamental problem with current generative AI, let me explain. You see, everything we call artificial intelligence today was built on the findings of a 2017 paper from Good That paper provided a way for AI to focus on different parts of an input sequence simultaneously and determine the relevance of each word to every other word. This innovation called a Transformer Neural Network allowed researchers, computer scientists, and later companies, to change the world. But herein lies the fundamental problem. With this method of Transformer Neural Networks, it turns out by determining the relevance

of each word and predicting the next word, it just makes up stuff. it doesn't know what it's saying. We call this problem hallucinations, and it has real world consequences. I think the consequences are when people take AI and they don't actually filter it through a human expert. Because I feel like AI, this is what I was saying before, right? AI can do a lot of the groundwork and do some of the busy work,

and then it leaves that time open for the individual to make the actual crucial decisions. That's what I think. Picture this. You're a business that decided to replace its staff with AI to write up patient documents, fill in patient information, summarize meetings, or do some basic scheduling. But as time goes on, to your horror, you realize that the AI system makes up 10% of everything that it delivers. But the real problem is, you don't know what it's made up and you don't know what's accurate. That's why you need to have people that are experts and already trained in the field to where they can determine which part is inaccurate and which part isn't? All your staff manually have to go back and check everything. This ends up just being extra work for the remaining staff, and ultimately is a waste of time.

Yeah, code reviews, exactly. It sounds stupid, but this is exactly what's happening. Now, the following are read a comments taken from those in the workforce who had to take the brunt of upper management thinking that blindly implementing AI was a good idea. Quote, my company paid for some AI scheduling software a few months ago, thinking that it could free up the accounts team so that they could continue their hiring freeze in that department.

apartment. Now the accounts team is having to do extra work making sure the program isn't messing everything up. Not to mention our production team. This seems like just your traditional upper management making bad decisions because they don't really know what the people who they're managing's job is supposed to be. This doesn't really, I feel like this isn't really an innate problem with, uh, it's not an innate problem with AI. This is just a problem with management at a company. To worry about schedules. It's incredibly frustrating. Yeah. checking everything. They're finally scrapping it for some basic scheduling. I'm not surprised. And same experience here. Products sold and demonstrated to be a lifesaver. Ultimately, the staff

that used to do the work spend all their time making sure that AI doesn't screw up and help train it. Also, working in a medical slash clinical setting, we really don't trust the new file sorting and labelling system. Names, data birth, insurance data has to be perfect. AI is less than that. It fails at gathering proper demographic information and assigning relevant tasks. Sometimes it thinks the doctor is the patient or doesn't know where the document was faxed from, etc. And yet another user states that AI was good at taking notes from Zoom meetings but would make up 5 to 20% of the content

even when hand-fed the transcripts of the meeting. Those who looked over the AI-generator summary realized that some of what was written wasn't even said. All of these disasters make sense. LLMs predict the next word statistically, but they'll never tell you when it doesn't know the answer or if it can't understand something. Yeah, true.

There's many such stories of company regrets after rushing into half-baked AI solutions. A report suggests that 55% of companies regret replacing people with AI. I think that a lot of companies probably jump the gun on it too much because they could see the writing on the wall. It's very clear that this will happen

and it will be useful at some point. but is it useful yet? I don't know. Bank, for example, who fired staff to install an AI chat bot that was so bad, they begged for their old humans back. And take the example of Klanah.

Two years ago, they implemented a hiring freeze and began to replace their human staff with AI. By 2024... KORNA is the app that people use so they can finance a pizza. Their head count had fallen from 3,800, to 2000. But lo and behold, their customers wanted to speak to actual human.

humans. Klanar said that its AI chatbots perform the work of 800 employees, but the company admits that their service quality and customer satisfaction have dropped, and they lament that human interaction is still needed. Yeah, sure. That makes sense. On replacing people with AI, the publication Fortune notes, quote, not only is it short-sighted, it's fundamentally bad business.

The company's cutting people today in the name of AI will be the ones playing catch-up tomorrow. There's no doubt that AI is excellent at doing more with less. It speeds up processes, cuts down repetitive work, and buys back time. I think the cutting down repetitive work is the biggest value add that they can have. I, on its own, cannot create the next generation products and services. End quote. So on Cold Fusion, we tried to be thorough here. So it has to be said that all of these failures aren't the full story.

There are indeed companies that are extremely successful at using artificial. intelligence. Of course. Yeah, the ones that understand it and they don't just want to use it so they can not pay people. Now, even though the MIT paper said that 95% of companies who implemented generative AI failed in said implementation, the same MIT paper states, quote, some large companies, pilots, and younger startups are really excelling with generative AI. They mean startups led by 19 or 20 year olds. They, quote, have seen revenues jump from zero to 20 million in a year. Because the 19 and 20 year olds understand the product and the technology that they're using. This isn't anything new. This is the same with using the internet or using computers or any

type of technology. Is it when you have people that are using it because they think it's the cool thing to do and they don't actually understand it themselves? What the hell do you expect? It's because they pick one pain point, execute it well, and partner smartly with companies who use their tools, end quote. So how companies adopt AI is crucial. For example, purchasing AI tools from specialized vendors and building partnerships succeed 67% of the time, while internal builds succeed only one-third as often. Wow. This goes to show that you can't just slab AI everywhere and expect it to work.

It needs thought in its implementation and also to... Like anything else. It depends on the specificity of the AI tools in question. But in the grand scheme of things, it's still early days for AI, and it'll be naive to think that it'll stay the same forever. all it would take is another groundbreaking paper, a new underlying neural network architecture, and everything could change again. This could mean another giant leap forward that none of us are expecting.

But in the meantime, it's uncomfortable territory. So what happens? Dotcom bubble. I mean, I think that AI, there's definitely a lot of people that are like over-invested into AI, and it will probably take longer for certain things to happen. But I don't think it's going to be like a dot-com bubble burst. I don't think so. Maybe, but that's not what I would expect.

Like the steam engine, which sparked the industrial revolution of a late... Are you for or against implementing AI in the workforce in place of humans? I'm very much for it. My mindset is that I think a lot of jobs, if there's a job that can be replaced by a robot, I think that you should do that. I think really the problem isn't that AI is replacing people. It's that people need those jobs to make money. So the real core issue is that people rely on jobs in order to make income and you need to make income to live in society.

AI is not actually the problem. It's a symptom of a larger problem. And I think that as technology, automation, machines, AI get better, you're going to have more and more jobs that will be replaced by technology. And I think this is a general thing. It's not unique to AI. It's overall. And what's going to end up happening is that we will reach a point where employment is no longer an expectation in society. And I am a universal basic income person. I think this is an inevitability of time. And once enough jobs are replaced by technology, robotics, AI, and other forms of computers, how are somebody going to be able to make a living if there's no job for them to do? And so, like, farm equipment, yeah, sure, right? I mean, you've got a lot of examples of that.

So I think this is an inevitability. And I think also, even if you think that it's not an inevitability, other places in the world think that it is. And when other places in the world, here's a great example, Nike and Adidas are two of the biggest shoe companies and apparel companies in the world, right? And why are they so big? One of the big reasons why they're massive and hugely successful is because they utilize third world labor in order to make products. for cheaper than their competitors. So when American companies and Western companies choose to side in terms of ethics, what they end up doing is they end up effectively putting off different types of social

conversations because people don't want to have them. And also they end up outsourcing that exploitation to the third world. And I think that what's going to happen with AI is that if we have companies here that are using AI or are not using AI, but companies in China or the Middle East or Russia are using AI, and it's able to increase their productivity in a free global market, those companies will outcompete and beat American companies, which will put us at an economic disadvantage. So I think that you either take advantage of this and capitalize on it, or you lose to people that do.

In the 1800s, the internet is changing. everything it touches. That's what I think. And at the cutting edge of the revolution is Wall Street. In the dot-com bubble during the mid-90s, everyone who simply put a dot-com at the end of their company name saw massive valuations because investors who didn't understand the technology saw them as the future. In reality, these companies had no solid way of making a profit or didn't even have a business

plan. When the broader market realized that it was all a smokescreen, the sector crashed. stock companies went out of business and only a handful made it out and a giant today. So let's compare that to the AI wave of today. I do think that there will be a degree of AI companies that will fall off. I would assume probably half of them will fall off. And I think that AI will probably be kind of, I hope it's not like Google, I hope it's kind of like email, where there's like four or five big email services.

There's like a hot mail, gmail, there was AOL for a while, proton mail and maybe a couple of others. But other than that, you know, everything else is pretty much defined. And back in the day, a lot of them, 90% will fall off. Yeah, but I do hope that we're not using only one AI model in the future. I think that's very, very dangerous. Long-awaited release of chat GPT-5 was a disappointment. And many users even thought the previous version was better. And this caused...

No. Wait a second. Let's add some context to that. The people that were complaining about chat GPT-5 were people that were trying to have an emotional relationship with chat GPT-4. And chat GPT-5 didn't add as much flowery language and as much flirting in it that GPT-4 had so they were crying about it whenever they had to update it because now their girlfriend doesn't call them babe anymore because she's a GPT-5 girlfriend

instead of a GPT-4. So it's not like this was a mass thing that everybody was mad about. There was a very, very specific contingency of people that were upset about this and they were upset for a very specific reason. I'm just saying. I'm just adding that in. In addition, the company was also caught

blatantly fudging the performance numbers in some very strange graphs. Incremental rather than revolutionary was the tone. Soon, Meta would announce that it's downsizing its AI division, and this comes amongst a growing chorus of analysts. There it is. See, they even said it right there. Meta allowed AI chat paths to have sensual conversations with children. Oh, wow, I would have never expected that. ...mast a growing chorus of Analyst, saying that AI is heading towards, if not, is already in a bubble.

And next, we have the massive valuations and spending. Invidia H-100, the GPUs that... I do think NVIDIA is overvalued. Official intelligence boom are about $30,000 to $40,000 each. Google has 26,000 of them, and they've managed to create AlphaFold, Gemini, V-O-3, and more. But meta, on the other hand, has 600,000 Nvidia H-100s. And while they do have the open-source LLM, it isn't discovering new science like Google's AlphaFold for 23 times the compute. I feel like meta is kind of falling off.

like imagine spending trillions of dollars maybe hundreds of billions of dollars to make a metaverse and then you lose to a kid's video game robocs that's not even trying to beat you they just accidentally beat you in a game that you've invested hundreds of billions of dollars into like oh oops oh wow oh we accidentally oh geez and to give you an idea of how extreme this is all getting AI itself has caused a 4% increase in electricity use in the US. Morgan Stanley states that data center investment will reach $3 trillion over the next three years in preparation for AI use, and of course, that's heavily fueled by debt. The belief is that AI will cut costs by 40%, and that should add $16 trillion to the SMP.

But as we've just seen at the beginning of this episode, according to that MIT study, that could be very unrealistic. So this could be the future if AI doesn't improve massively soon. Number one, business executives and business owners will get frustrated with hallucinations, useless solutions, bad code, and a very poor return on investment. Number two, a lot of the AI gurus like Sam Altman will have to admit that artificial general intelligence isn't going to be achieved by LLMs, and they're essentially a dead end. Number three, the general populace begins to get sick of LLMs, and we're already seeing it.

The absolute flood of AI slop, the hallucinations. AI agreeing with what you... I think that a lot of people don't know how much the average normie thinks that those AI videos are funny. I think that there is a huge circle jerk on social media, especially with people that make content and on reddit. it that this AI stuff isn't funny. I see some of these AI videos, like people will send me screenshots of it and stuff. I don't really go on Facebook myself, but people have showed me this. And you have these people that are just, you know, some fucking AI video has 80,000 likes and people think it's funny. So the entire, I feel like the amount of AI hate is massively,

massively overstated. It's like 10 people that hate AI sound like 100 people. Jesus say, sometimes driving them insane. Number four, in seeing this, the venture capital finally dries up and LLMs become just too expensive to justify unless there's a massive increase in efficiency.

The cost to run OpenAI's data centers, all the pipes and guts and things that like keep AI running, is about $40 billion. a year. Their revenues right now are only like 15 to 20 billion. And finally, number five, after a long winter, new implementations come around that truly live up to the hype promised by the first wave. So just like the dot-com bubble, there's going to be a few winners that rise from the ashes. But if or when it crashes, from here, we see the true artificial intelligence companies that last the distance. I feel like this is always what happens

with technology. It's what happened. Remember back with consoles back in the day? Everybody was trying to make a video game console in the 90s, but there were only a handful of companies that actually kept going. Like you had Nokia making stuff. You had Sega making consoles. You had everybody phones. I think phones are another great example. Think about how many phones you used to have that were flip phones. And, you know, like Nokia, who buys Nokia phones nowadays? I mean, yeah, they're still in the market, but they're a very, very minor compared to what they're. were in 2003, maybe. So I think that whenever you look at a lot of the previous innovations and technology, you'll

see this exact thing happening as well. And there's a survivorship bias that I think people have that they forget all of those fail cases that have happened with every other instance and iteration of technology. You can look at it with movies, or not movies, but like VHS. And then do you remember, like, when DVDs came out, there were the really, really big discs, there were DVDs, and then there was Blu-ray, and then HD DVDs. And a lot of that stuff is gone. The big discs are gone.

Laser disks are gone. Nobody uses HD. People just use Blu-ray. And Blackberries. Blackberries are gone. Yes, exactly. And then you had zip drives back in the 90s. I still have a zip drive for like a 95 computer.

That's gone. People don't use that anymore. And so you always have a survivorship bias. or people look at the successful iterations of technology without looking at the context of how they became successful because they became successful inside of a sea of attempts that were not successful. That's what I think.

So to finish off this episode, let me end with this. I've talked about this many times in my older episode. That's actually another really great example is that think about, remember back in like the mid-2000s, early 2000s, if you're old enough, where everybody had their own like, It was basically like a smartphone, but it wasn't smart. It was just like an organizer, like a PD, I think it was called PDA.

And, yeah, a pager. No, not a pager, not like a fucking, you know, Hamas blowing up explode pages. But yeah, like, I remember my mom had one and like, let me see if I can show the one that she had. I remember the name of this. Yes, this is the one that my mom had 25 years ago. She had one of these. And people would use these all the time. Yeah, I had a photo phone.

It looks cool. Yeah, it did. But, like, you never see this. Like, nobody, nobody even, this is, like, ancient fucking technology. Because it just got replaced by a smartphone. And you look at iPods, too. Like, music players were their own unique individual thing. And you had cassette players, eight tracks, what do you call it?

CDs, MP3 players. now everything's just been consolidated into a phone. I think that's a pretty big difference. But take a look at this diagram. It's called the Gartner hype cycle, and it describes the typical progression of the infiltration of new technologies into society. So where do you think we are? The technology trigger?

The peak of inflated expectations? The trough of disillusionment? The slope of enlightenment? Or the plateau of productivity? Feel free to... I think we're on the plateau. be honest. Comment down below.

So where to from here? But I think sometimes technologies feed into each other. Like I think the iPod and that technology fed into the technology that made the iPhone. And then the iPhone fed into the technology that obviously made what we have now. Sam Oldman and all the other AI leaders should focus their efforts on fixing the hallucinations.

Once again, a different neural network architecture could be discovered, one that fixes hallucinations. or perhaps it could just be fixed manually. Either way, ushering in a new boom. But that all being said, and that's the funny thing about AI, the point is, with AI, nobody knows the future. So what do you guys think? Do you think we're in a bubble and a crash is imminent?

Or do you think the next AI innovation is just around the corner? Now, if you've been recently hired by a company or just simply need to brush up on your knowledge, today's sponsor is perfect for you. Brilliant is the best way to learn subjects like computer science. 100% a bubble. I think people are over investing into AI too. Data analysis and AI.

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Hey guys, it's me. You're underestimating the power of porn. Do you know Moore's Law? It's why AI will find new advancements and get better. 90% of the internet is porn. AI is the next evolution stage of porn. The math is clear. I think you're probably right about that, by the way,

is that a lot of people that push this kind of stuff and that a lot of people that are using AI are using it to make porn. You're absolutely right. Hi, I'm not an AI, so you're finally seeing my face. But anyway, thanks for watching. If you do enjoy it. There's plenty of interesting stuff here on Cold Fusion, so feel free to subscribe. Otherwise, that's about it from me. My name's DeGogo, and you'll be watching Cold Fusion. And I'll catch you again soon for the next one.

Damn. Well, there it is. Question, what's the cap of AI? If the cap of AI is not high, it's not going to be great. I think that it will continue getting better over time. And right now it's definitely not. There's the video right there. Make sure to give it a like. I definitely agree with a lot of what he's saying here.

And I think that AI, you have a lot of people who are investing into AI, but they don't really know what they're doing, why they're doing it or anything else. And I think that's the main reason why AI isn't really as successful in some of these companies, is that you have companies that are just basically chasing the idea of AI without necessarily thinking about, is this actually useful, beneficial, or providing us with any sort of real value?