Kajabi is currently offering a free 30-day trial to start your business if you go Tech is a sector like no other – it’s an industry where people can become overnight billionaires, ideas shift the basics, and leaders are rewarded for demonstrativeness. In today’s Silicon Valley, innovation is crowned, not won. Venture capitalists and founders are symbiotic. Unprofitable companies are kept alive with capital injections, fraudulent valuations and fabricated advertising in order to survive long enough to go IPO. Beginning in early 2010, Silicon Valley has championed big data as a revolutionary technology that can uncover deep insights, hidden patterns, and innovation from massive amounts of data. Yet the market began to question in the early 2020s whether any of these promises were even real, as nearly all consumer and SaaS startups were still bleeding nearly a decade later. Out of nowhere ChatGPT and AI was launched…

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34 thoughts on “Why AI Is Tech’s Latest Hoax”
  1. great video at cutting thru the hype!

    personally, i think big data (and many of the fads, not necessarily ai) still have enormous potential for the long term future. it's just that it won't be truly unlocked until we cooperative build systems that aggregate data we voluntarily commit, in order that we can improve societal efficiency for all.

    it will be more like doing cooperatively doing science at a universal scale instead individual companies trying to win over competition tru whatever imperfect slice they manage to hoard.

    the perspective all these companies operate from are simply not broad, or voluntary, enough to achieve these kinds of cooperative results.

  2. You are wrong. Just because the hype is overblown doesn't mean some of these techs aren't important "advances". These topics are not binary, more than one thing about them can be true.

  3. Our new robot vacuum has 'AI Mapping.' Mate that's not some high tech AI. It's an infrared diode, a phototransistor and a few lines of code for recording and saving timespans between phototransistor activations. This super high tech AI sensor is like $0.25 in material costs.

  4. Hey, @ModernMBA can you please do a video with Jimmy Johns at the forefront? I work for Jimmy John's and I have a gut feeling the business is failing and making very poor decisions. Thank you for consideration.

  5. Usually ModernMBA is academic, but this clip seems very populist. I work in IT, and my company is really adopting AI as much as possible since last year. Developers use it everyday whether it's merely as a search engine or otherwise using AI tools to improve the code. Literally everyone agrees that it has increased productivity (and allow more break time too). There is a saying that AI will not replace you unless you do not use it. A lot of AI is still rudimentary, but wow, this is just the start.

  6. Here's the thing though.
    Both SaaS and Big Data aren't hoaxes.
    Everything is SaaS today. Everyone is doing big data.
    They're just not the hip new thing anymore. The hype is over, maybe, but Microsoft and Amazon are making obscene amounts of money on SaaS and IaaS.

  7. I share the sentiment around big tech hype (it's terrible), however one shouldn't necessarily dismiss big data / analytics any more one should dismiss weather forecasting. Data and analytics provide a lens and perspective into domains you wouldn't otherwise have. It's also important to consider that having a analytics window doesn't guarantee success anymore one could mitigate damage from a forecasted hurricane. Businesses do not operate in vacuums and success usually comes from an organizations ability to move with market trends and remain relevant. Usually successful businesses do one thing really well (and you're right, there can only be a few winners)

    As for AI, it's largely built on machine learning techniques derived from the big data era. While there is a lot of hype around AI technologies, it's impact is not to be underestimated either. Big data did not disappear, rather it's become a fundamental aspect of modern business (always has been). Artificial Intelligence (or ML) is an exceptionally powerful tool for data introspection and it's likely to become as fundamental as a component of big data analysis.

    As for generative AI, It's terrible, but will likely continue to improve. It's mostly going to be useful for data summary, image and video manipulation and various other niche tooling. It's not going to be a huge game changer for a while, but AI tech firms do need investment and I assume the only path is over hyping the capabilities of the technology.

    Anyway, the odds of anyone reading this are 1 in 1000. I think ill finish here.

  8. As someone who has been working in tech for years. I have been saying this forever. Thank you for the video on the topic it's a great way to point other people to the trends I have been noticing and it even unearthed new things I didn't know about.

  9. AI is just like the information superhigh way hoax I grew up with as a kid, where they said everybody would own a computer connected to a public network of other computers.

    Those dumbasses never knew what they were talking about.

  10. So data isn’t valuable, and chatgpt is on a par with NFTs? Interesting take. Seems to me that it’s already having a big effect, it has a much higher ceiling, and is improving by the week. The argument here isn’t negating anything that AI does, it’s more like a “what about” argument. “Steam cars and unicycles didn’t take off so cars have no chance”. I wouldn’t write it off so easily

  11. Algorithms have been around since 300 BCE, mobile apps since 2008 and AI has been used since the 1950's, there are many applications for it, e.g. face-, speech- and medical image recognition, computer games, autonomous vacuum cleaners and what not. They are not hoaxes but here to stay😂.

  12. The difference between "big data" and AI is that in the case of AI, there is actually substantive technology behind it.

    What's really happening is that computer systems have started to acquire the capacity to manipulate qualitative information rather than just quantitative. The real game here, the one that's going to matter long term, is finding the use cases which are enabled by these new capabilities and which are also valuable enough that they justify the cost of development and continued operation.

    These could be thing like natural language interfaces, virtual assistants, self driving cars or robots that can understand spoken instructions. Systems where AI is a necessary component, but not necessarily the central focus.

    That being said, I'd say you're right to write of "big data" as (mostly) nonsense. I've been saying as much for almost a decade. The idea that hoarding data and throwing data scientists at it indiscriminately somehow magically translates to better business outcomes was always silly. But there are counterexamples, cases where data driven systems have been instrumental to the success of a company or product. Recommendation algorithms are critical to social media for example. If your recommendations aren't any good, then you can't keep people on the platform, which has a direct effect on revenue. Targeted advertising is another example. The devil, as always, is in the details.

    TL;DR: Big data was a bit silly, but you'd be throwing the baby out with the bathwater to write AI off along with it.

  13. Your whole narrative is driven by confirmation bias. It’s absolutely silly how you just went on with example after example but left out the ones that didn’t fit your pattern. For example, given that you barely brushed upon Doordash, let’s talk about them. Yes, they scaled negative operating income, but their revenue and number of subscribers has increased consistently. Over the last decade, most startups scaled negative margins because of VC money, yes, but that was fuelled by ZIRP pouring in free money into the market. Which good founder in their right mind would not leverage such an opportunity to scale their startup as long as they have achieved product market fit?! Now that the free money has dried up startups like Doordash are tightening their belts and moving towards turning a profit which is why you see a steady decline in their losses. Airbnb is another example. These are examples of startups built on data science and algorithms. Look at the moat Zomato has built in India. Just because you don’t get it, doesn’t make it non-existent. If operating income is your only measure of success, I have a bootstrapped startup with $20 in profit to sell you.
    How do you get traffic projections if not for all the data Google and Apple have aggregated? Companies were chasing big data until the last few years because transformer models were still in their nascency. Ilya Sutskever, after all, published his first PhD thesis in 2013. There wasn’t an obvious better way to extract meaningful insights from data without amassing huge piles of it until then. Every technology progresses one step at a time. Doesn’t mean until something has runaway success everything is a failure. If you think these technologies would inevitably fail, you are welcome to sit aside and watch the show. I’ll send a self-driving car to collect your fossil.
    I don’t know how much development experience you have, but at least in this video, you don’t sound like someone who has any. “There’s no consensus over which tool is best.” Endless debate about React vs Angular? Tensorflow vs PyTorch? It’s called having options, just as in any free market. And developers do prefer one over another per their end goal. If you don’t know what I’m talking about, go and check out this year’s Stack Overflow Developer Survey, not some Indeed.com data from 2020. Resume-driven software development? Again, it’s demand and supply. The preference of a technology drives its adoption, and vice versa. If you don’t have in depth knowledge about a space, talk to someone who belongs to it instead of throwing together a biased narrative.

  14. Dam, I was about to subscribe to you but this video is so lazy. So many logical leaps you took, you totally lost touch my guy. I think you make some valid points but come on, do better.

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