Why AI Is Tech's Latest Hoax

Tech is a sector unlike any other - it’s an industry where individuals can turn into billionaires overnight, ideas supersede fundamentals, and leaders are rewarded for showmanship. In today’s Silicon Valley, innovation is crowned and not earned. Venture capitalists and founders are symbiotic. Unprofitable companies are kept alive with injections of capital, gamed valuations, and manufactured hype with the goal of surviving long enough to IPO.

Starting in the early 2010s, Silicon Valley had championed big data as a revolutionary technology that could unearth deep insights, hidden patterns, and innovation from massive amounts of data. Yet the market started to question in the early 2020s if any of these promises had even been real as nearly all consumer and SaaS startups were still bleeding nearly a decade later.

Out of nowhere, ChatGPT was released and AI became Silicon Valley’s next big thing. Every tech company is now an “AI company”, every Fortune 500 needs an “AI strategy”, VCs are only investing in AI startups, and every product is an “AI” product. This is a deep dive into how artificial intelligence is just the latest tale spun by Silicon Valley to sweep prior failed trends under the rug, keep valuations high, and outlook positive.

Before AI, there was crypto, web3, blockchain, virtual reality, big data, IoT, and wearables - all supposedly revolutionary technologies that have never lived up to the hype. In this episode, we’ll dive into the market dynamics that push companies and individuals to jump headfirst into tech trends, how this all started with big data, and why AI is ultimately just another pump-and-dump.

0:00 Modern Silicon Valley
6:42 Sponsor Break (Kajabi)
8:29 Post Dot-Com Beginnings
17:22 Data-Driven FOMO
28:19 Shovel Economics

[ZontarDow]

As with any gold rush, the only one making money is the one selling shovels and beer, which in this case is Nvidia.

[Cookiemaster]

This video made me realize something for the first time. Every company is trying to use big data and/or AI to "understand the consumer", with the goal of trying to sell their crappy, overpriced product. So instead of focusing efforts trying to make a good product, for a reasonable price, they are trying to sell me their crappy product for as much as possible, and hope that AI tells them how to do that. I think customers are easy to understand - just don't rip me off man. No wonder most of them are failing.

[RaidPanda]

My boss : Can AI help us with anything ?

Me : After reviewing all our technological needs, I've seen one use case for machine learning for this QC task, but it costs so much that the ROI will be virtually never.

My take as a software engineer is that we should always do low tech if it can be done with low tech. Over engineering everything and using AI and sophisticated sensors when a simple limit switch could do the job is what people do when they can't find how to make their skills really useful. There is no need in selling BS when you do good work. But hey, that's what makes me a worker instead of a billionaire con artist. Maybe some people take more pride in being rich than being useful, what do I know.

[oskari]

Those corporate talk videos made me feel physically uncomfortable.

[kewgardensstation]

Starbucks is confused about its precipitous loss of revenue in 2024? I'm not.

I'll tell you EXACTLY why. Everything that was unique about the Starbucks experience - ordering a cup of coffee, perhaps a bakery item or a lunch (love their PB&J meal) sitting down on one of their comfy couches, propping my feet up and doing work on my laptop, or just browsing the Internet, or even just meeting a friend for coffee, all disappeared during the pandemic.

They took out all the comfortable seating, removed the electrical plugs for your laptop, and replaced everything with low, long wooden tables, hard wooden stools with no backs to sit on, reduced the seating to almost nothing, and basically turned Starbucks into just another place to get an overpriced cup of coffee.

The business model is now "Order your coffee by mobile app, come pick up your coffee, and get the f*ck out. Next in line, please!"

Hell, I can just brew my coffee at home cheaper and have a more pleasant experience.

[creativestudiesagency]

Dell stock dropped 33% after just saying AI, AI, AI for three straight months and then investors realizing they couldn’t show any revenue for their products. Money talks, BS walks.

[tedbendixson]

I was not expecting this video to strike such a chord with me. I've worked as a software engineer for over a decade, and I had this overwhelming feeling my job was complete bullshit for most of that time. We use bad technologies simply because they're popular, and most of the engineers don't really understand how computers actually work. The section about people being extremely tribal and only learning things because it pads a resume is 100% the truth. It's just a disgusting industry to be a part of if you have any integrity, just lies lies and more lies.

I hadn't heard a great explanation of *why* it sucks to work in tech until I came across this video. Thank you, from the bottom of my heart, for making this.

[lephtovermeet]

I 3d printed an direct to consumer self driving all electric ai block chain app, I'm worth 80 trillion dollars now.

[Immortal..]

I just need to log into Amazon to see that even one of the worlds biggest companies with sheer endless data fails to increase my spending. No matter how many targeted ads I see I wont buy stuff I dont need. And I dont need a lot.

[schlichter]

I was told by a CTO that my proposal to cut IT department expenditure by over 50% at our company by moving away from those Tribal providers, was DOA b/c when this company failed everyone had to get another job and having those ‘industry standard’ solutions on their resume was the only way to do it. Company went bankrupt about 18 months later. But to his credit we all did get other jobs.

[BRichard]

I am a Data Scientist. I would like to chime in on this fascinating topic. I was a Software Engineer before I transitioned to Data Science. To me, the big scam is not AI it's BIG DATA. Does anyone know that through statistics, the difference between a sample and a population determines whether you think big data must be used or not? The reality is big data is NOT required, and let me say this again, big data is NOT required to generate predictive analytics. What is needed is TARGETED data and that is a big difference. Now you do in fact need some data but I can turn out a very compelling machine learning model using 100, 000 records of data if I can get a sample size that represents the population. That is the key to reducing the overfitting of a ML model which is one of the most challenging aspects of developing a successful prediction model. You need to know the difference between a statistically significant SAMPLE which is the key to machine learning. So, if you don't know any better, you believe that you must spend thousands of dollars on some nonsensical cloud solution to host 100 million records of data for analysis. That is utter BS. Give me a distribution with a standard error of .01 to .10 and I will give you a VERY accurate ML model with less than 100, 000 records.

[LloydWaldo]

I worked in tech venture capital for 10 years. What I saw was a whole crop of “world changing” concepts that one by one, failed to change anything. But at the end of that ten years we were talking about a whole new idea of what was going to change the world next.

I realized all that talk never got us anywhere.

[FictionHubZA]

The funniest part of all of these hype cycles is watching people jump from one hyped up product to another. Crypto, Ai, drop shipping, ChatGPT, and the rest. I like how they always insult others for just being rational about the technology being useless or, at the very least, not good enough as it is.

They just forget the broken promises of the last piece of tech and jump to the next one.

[aphantasiagreyman]

After 20+ years in IT the only consistently performing tech innovation I have seen is Bullshido.

[Foxhood]

Moments like these i am so happy to have gone for Electrical Engineering and NOT Software engineering/Computer science.
Instead of being stuck in that crazy world, I work for a modest company that has been creating Bio-medical laboratory equipment based on a novel way to indent at a nanoscopic scale.
Basically It uhm... Pokes cells and measures how springy they are.

It doesn't sound exciting, but its Tech how it should be: Not some big-data harvesting boom&bust cycle, but novel inventions furthering society and science

[NobodyInTraining]

Rory Sutherland makes an interesting point about this: despite all the data being collected about you from every website, personalised advertising has largely failed.

Online ads are 99% irrelevant to me.

They can predict my demographics and some topics of interest. But heck, even TV and magazine ads could do that.

There is none of the hyper-personalisation that's been prophesied for 30 years, that the machines would understand my preferences better than I do.

Same with content recommendations from Facebook, Spotify etc.

They also cannot predict any new things I might be interested in based on my personality.

They just just shovel more of what I've once interacted with.

That reminds me of another relevant Rory quote: "All big data comes from the past."

[samsaek]

Once I started seeing generic airport ads from big dinosaur companies mentioning AI I knew it was dead

[kristiankho]

“When in a gold rush, sell shovels” and so because of that, in 2024 we’re in a gold rush where 9 out of 10 participants are shovel sellers with the other guy actually mining gold but prt time because their real job is also selling shovels

[alphaperez]

Hey wall street tech analyst here, love the channel. One of your earlier videos actually cited/displayed a chart I had created many years ago and I thought that was kinda cool. My team tested numerous consumer AI services, and none of them could produce text I would consider publishing in one of my reports. The question is 1) who is making money on AI currently? The answer is Nvidia, but this is hardware used to enable AI services. The software services themselves are a much harder value prop and people/companies are balking at pricing. OpenAI has decent revenue from the early-adopter crowd. Alphabet, Meta, Amazon, Microsoft....biggest names in tech and nobody is seeing surging revenue, nobody is seeing rapid margin improvement from AI. The other question is 2) why is Nvidia making SO MUCH MONEY selling its chipsets? The answer is because Alphabet, Meta and others are spending literal effing BOATLOADS of cash on AI infrastructure. Again, the smartest names in tech are spending like drunken sailors to upgrade their servers to accommodate Nvidia's AI chipsets, under the premise that these AI server farms will power the surging AI compute needs of the future. Look at the Capex spending of the large tech giants, and they are all doing the same thing, they are pouring cash into AI investments chiefly by purchasing Nvidia chipsets like the H100. It's also not a coincidence that having a huge number of H100s is great for attracting and retaining talent. I do believe in the ultimate promise of AI but we are not there yet.

[realmetapro]

Corporations are so eager to be first to market with things like AI that they don’t spend enough time upfront to understand how it can actually fit in and drive value for their brand. Just release the AI deck and we’ll figure it out along the way. It’s bad.