I think the interesting idea with “AI” is that it seems to significantly reduce barriers to entry in many domains.
I haven’t seen a company convincingly demonstrate that this affects them at all. Lots of fluff but nothing compelling. But I have seen many examples by individuals, including myself.
For years I’ve loved poking at video game dev for fun. The main problem has always been art assets. I’m terrible at art and I have a budget of about $0. So I get asset packs off Itch.io and they generally drive the direction of my games because I get what I get (and I don’t get upset). But that’s changed dramatically this year. I’ll spend an hour working through graphics design and generation and then I’ll have what I need. I tweak as I go. So now I can have assets for whatever game I’m thinking of.
Mind you this is barrier to entry. These are shovelware quality assets and I’m not running a business. But now I’m some guy on the internet who can fulfil a hobby of his and develop a skill. Who knows, maybe one day I’ll hit a goldmine idea and commit some real money to it and get a real artist to help!
It reminds me of what GarageBand or iMovie and YouTube and such did for making music and videos so accessible to people who didn’t go to school for any of that, let alone owned complex equipment or expensive licenses to Adobe Thisandthat.
I've noticed this as well. It's a huge boon for startups, because it means that a lot of functions that you would previously need to hire specialists for (logo design! graphic design! programming! copywriting!) can now be brought in-house, where the founder just does a "good enough" job using AI. And for those that can't (legal, for example, or various SaaS vendors) the AI usually has a good idea of what services you'd want to engage.
Ironically though, having lots of people found startups is not good for startup founders, because it means more competition and a much harder time getting noticed. So its unclear that prosumers and startup founders will be the eventual beneficiary here either.
It would be ironic if AI actually ended up destroying economic activity because tasks that were frequently large-dollar-value transactions now become a consumer asking their $20/month AI to do it for them.
> ironic if AI actually ended up destroying economic activity
that's not destroying economic activity - it's removing a less efficient activity and replace it with a more efficient version. This produces economic surplus.
Imagine saying this for someone digging a hole, that if they use a mechanical digger instead of a hand shovel, they'd destroy economic activity since it now cost less to dig that hole!
It doesn't cost less to get the thing you actually want in the end anyway, no one in their right mind would actually launch with the founder's AI-produced assets because they'd be laughed out of the market immediately. They're placeholders at best, so you're still going to need to get a professional to do them eventually.
You say this but I see ai generated ads, graphics, etc. daily nowadays and it doesn't seem like it affects at all people going or not going to buy what these people are proposing.
Interesting. For me knowing that any form of entertainment has been generated by AI is a massive turn-off. In particular, I could never imagine paying for AI-generated music or TV-shows.
Until everyone has a personal fully automatic hole digger and there are holes being dug everywhere and nobody can tell any more where is the right and wrong place to dig holes
> I've noticed this as well. It's a huge boon for startups, because it means that a lot of functions that you would previously need to hire specialists for (logo design! graphic design! programming! copywriting!) can now be brought in-house, where the founder just does a "good enough" job using AI.
You are missing the other side of the story. All those customers, those AI boosted startups want to attract also have access to AI and so, rather than engage the services of those startups, they will find that AI does a good enough job. So those startups lost most of their customers, incoming layoffs :)
Then there's the 3rd leg of the triangle. If a startup built with AI does end up going past the rest of the pack, they will have no technical moat since the AI provider or someone else can just use the same AI to build it.
I mean, if taxi companies could build their own Uber in house I’m sure they’d love to and at least take some customers from Uber itself.
A lot of startups are middlemen with snazzy UIs. Middlemen won’t be in as much use in a post AI world, same as devs won’t be as needed (devs are middlemen to working software) or artists (middlemen to art assets)
Yep this is a huge enabler - previously having someone "do art" could easily cost you thousands for a small game, a month even, and this heavily constrained what you could make and locked you into what you had planned and how much you had planned. With AI if you want 2x or 5x or 10x as much art, audio etc it's an incremental cost if any, you can explore ideas, you can throw art out, pivot in new directions.
Is that an argument against the quality, saying that AI cannot (or some weaker claim like that it does not usually) produce "art"? Else, is it an argument of provenance, akin to how copyright currently works, where the same visual representation is "art" if a human makes it and is not "art" if an AI makes it?
It's about quality in relation to existing works. AI makes a brush stroke that's averaged from brush strokes of all existing artists. A human artist makes a brush stroke trying to be interestingly different from all existing artists. An AI trained on classical music will not invent jazz, no matter how long you run it.
Sure, after someone invents jazz, AI will be happy to copy it. And many people will say: "This sounds exactly like jazz! This looks exactly like Picasso! This means AI can make art!"
It's good for prototypes, where you want to test the core gameplay ideas without investing a ton early on. But you're going to have to replace those assets with real ones before going live because people will notice.
It’s really nothing special. I don’t do this a lot.
Generally I have an idea I’ve written down some time ago, usually from a bad pun like Escape Goat (CEO wants to blame it all on you. Get out of the office without getting caught! Also you’re a goat) or Holmes on Homes Deck Building Deck Building Game (where you build a deck of tools and lumber and play hazards to be the first to build a deck). Then I come up with a list of card ideas. I iterate with GPT to make the card images. I prototype out the game. I put it all together and through that process figure out more cards and change things. A style starts to emerge so I replace some with new ones of that style.
I use GIMP to resize and crop and flip and whatnot. I usually ask GPT how to do these tasks as photoshop like apps always escape me.
The end result ends up online and I share them with friends for a laugh or two and usually move on.
I'm wondering a good way to create 2D sprite sheets with transparency via AI. That would be a game changer, but my research has led me to believe that there isn't a good tool for this yet. One sprite is kind of doable, but a sprite animation with continuity between frames seems like it would be very difficult. Have you figured out a way to do this?
Use Google Nano Banana to generate your sprite with a magenta background, then ask it to generate the final frame of the animation you want to create.
Then use Google Flow to create an animation between the two frames with Veo3
Its astoundingly effective, but still rather laborious and lacking in ergonomics. For example the video aspect ratio has to be fixed, and you need to manually fill the correct shade of magenta for transparency keying since the imagen model does not do this perfectly.
IMO Veo3 is good enough to make sprites and animations for an 2000s 2D RTS game in seconds from a basic image sketch and description. It just needs a purpose built UI for gamedev workflows.
If I was not super busy with family and work, I'd build a wrapper around these tools
I think an important way to approach AI use is not to seek the end product directly. Don’t use it to do things that are procedurally trivial like cropping and colour palette changes, transparency, etc.
For transparency I just ask for a bright green or blue background then use GIMP.
For animations I get one frame I like and then ask for it to generate a walking cycle or whatnot. But usually I go for like… 3 frame cycles or 2 frame attacks and such. Because I’m not over reaching, hoping to make some salable end product. Just prototypes and toys, really.
I dont use AI for image generation so I dont know how possible this is, but why not generate a 3D model for blender to ingest, then grab 2D frames from the model for the animation?
Because, uh, literally everything. But the main reason is that modeling is actually the easy (easiest) part of the workflow. Rigging/animating/rendering in the 2D style you want are bigger hurdles. And SOTA AIs don't even do modeling that well.
I have been doing the exact same thing with assets and also it has helped me immensely with mobile development.
I am also starting to get a feel for generating animated video and am planning to release a children’s series. It’s actually quite difficult to write a prompt that gets you exactly what you want. Hopefully that improves.
AI is used by students, teachers, researchers, software developers, marketers and other categories and the adoption rates are close to 90%. Even if it does not make us more productive we still like using it daily. But when used right, it does make us slightly more productive and I think it justifies its cost. So yes, in the long run it will be viable, we both like using it and it helps us work better.
But I think the benefits of AI usage will accumulate with the person doing the prompting and their employers. Every AI usage is contextualized, every benefit or loss is also manifested in the local context of usage. Not at the AI provider.
If I take a photo of my skin sore and put it on ChatGPT for advice, it is not OpenAI that is going to get its skin cured. They get a few cents per million tokens. So the AI providers are just utilities, benefits depend on who sets the prompts and and how skillfully they do it. Risks also go to the user, OpenAI assumes no liability.
Users are like investors - they take on the cost, and support the outcomes, good or bad. AI company is like an employee, they don't really share in the profit, only get a fixed salary for work
Books also make us less capable at rote memorization. People used to do much more memorization. Search engines taught us to remember the keywords, not the facts. Calculators made us rarely do mental calculations. This is what happens - progress is also regress, you automate on one side and the skill gets atrophied on the other side, or replaced with meta-skills.
How many of us know how to use machine code? And we call ourselves software engineers.
> Yet some technological innovations, though societally transformative, generate little in the way of new wealth; instead, they reinforce the status quo. Fifteen years before the microprocessor, another revolutionary idea, shipping containerization, arrived at a less propitious time, when technological advancement was a Red Queen’s race, and inventors and investors were left no better off for non-stop running.
This collapses an important distinction. The containerization pioneers weren’t made rich - that’s correct, Malcolm McLean, the shipping magnate who pioneered containerization didn’t die a billionaire. It did however generate enormous wealth through downstream effects by underpinning the rise of East Asian export economies, offshoring, and the retail models of Walmart, Amazon and the like. Most of us are much more likely to benefit from downstream structural shifts of AI rather than owning actual AI infrastructure.
This matters because building the models, training infrastructure, and data centres is capital-intensive, brutally competitive, and may yield thin margins in the long run. The real fortunes are likely to flow to those who can reconfigure industries around the new cost curve.
The problem is different though, the containers were able to be made by others and offered dependable success, and anything downstream of model creators is at the whim of the model creator... And so far it seems not much that one model can do that another can't, so this all doesn't bode well for a reliable footing to determine what value, if at all, can be added by anyone for very long.
So if models, like containers, are able to be made by others (because they can all do the same thing), then they'll be commoditized and as the article suggests you should look for industries to which AI is a complement.
AI could've made someone unimaginably rich if they were the only one that had it. We're very lucky Google didn't keep "Attention is All You Need" to themselves.
I don't think most commenters have read the article. I can understand, it's rambly and a lot of it feels like they created a thesis first and then ham-fisted facts in later. But it's still worth the read for the last section which is a more nuanced take than the click-bait title suggests.
You can't make such generalized statements about anything in computing/business.
The AI revolution has only just got started. We've barely worked out basic uses for it. No-one has yet worked out revolutionary new things that are made possible only by AI - mostly we are just shoveling in our existing world view.
The point though is AI wont make you rich. It is about value capture. They compare it to shipping containers.
I think AI value will mostly be spread. Open AI will be more like Godaddy than Apple. Trying to reduce prices and advertise (with a nice bit of dark patterns). It will make billions, but ultimately by competing its ass off rather than enjoying a moat.
The real moats might be in mineral mining, fabrication of chips etc. This may lead to strained relations between countries.
The value is going to be in deep integration with existing platforms. It doesn't matter if OpenAI had their tools out first, Only the Microsoft AI will work in Word, only the Apple AI will deeply integrate on the iPhone.
Having the cutting edge best model won't matter either since 99.9% of people aren't trying to solve new math problems, they are just generating adverts and talking to virtual girlfriends.
That's 100% not the case. OpenAI is wedged between the unstoppable juggernaut that is Google at the high end and the state sponsored Chinese labs at the low end, they're going to mostly get squeezed out of the utility inference market. They basically HAVE to pivot to consumer stuff and go head to head with Apple with AI first devices, that's the only way they're going to justify their valuation. This is actually not a crazy plan, as Apple has been resting on their laurels with their OS/software, and their AI strategy has been scattershot and bad.
Interesting thought. Once digital assets become devalued enough, things will revert and people/countries will start to keep their physical resources even tighter than before.
The way I look at this question is: Is there somehow a glaring vulnerability/missed opportunity in modern capitalism that billions of people somehow haven't discovered yet? And if so, is AI going to discover it? And if so, is a random startup founder or 'little guy' going to be the one to discover and exploit it somehow? If so, why wouldn't OpenAI or Anthropic etc get there first given their resources and early access to leading technology?
IIRC Sam Altman has explicitly said that their plan is to develop AGI and then ask it how to get rich. I can't really buy into the idea that his team is going to fail at this but a bunch of random smaller companies will manage to succeed somehow.
And if modern AI turns into a cash cow for you, unless you're self-hosting your own models, the cloud provider running your AI can hike prices or cut off your access and knock your business over at the drop of a hat. If you're successful enough, it'll be a no-brainer to do it and then offer their own competitor.
> If they actually reach AGI they will be rich enough. Maybe they can solve world happiness or hunger instead?
That's what normal people might consider doing if they had a lot of money. The kind of people who actually seem to get really wealthy often have... other pursuits that are often not great for society.
You mean like building rockets that commoditise space so that they can pollute even more, making things worth on Earth while relocating us to another planet is absolutely preposterous and will never be a thing?
Thats why i just biult my own tiny AI rig in a home server. I dont want to grow even more addicted to cloud services, nor do i want to keep providing them free human-made data. Ok, so i dont have access to mystical hardware, but im here to learn rather than produce a service.
>> Is there somehow a glaring vulnerability/missed opportunity in modern capitalism that billions of people somehow haven't discovered yet?
Absolutely with 150% certainty yes, and probably many. The www started April 30, 1993, facebook started February 4, 2004 - more than ten years until someone really worked out how to use the web as a social connection machine - an idea now so obvious in hindsight that everyone probably assumes we always knew it. That idea was simply left lying around for anyone to pick up and implement rally fropm day one of the WWW. Innovation isn't obvious until it arrives. So yes absolutely the are many glaring opportunities in modern capitalism upon which great fortunes are yet to be made, and in many cases by little people, not big companies.
>> if so, is a random startup founder or 'little guy' going to be the one to discover and exploit it somehow? If so, why wouldn't OpenAI or Anthropic etc get there first given their resources and early access to leading technology?
I don't agree with your suggestion that the existing big guys always make the innovations and collect the treasure.
Why did Zuckerberg make facebook, not Microsoft or Google?
Why did Gates make Microsoft, not IBM?
Why did Steve and Steve make Apple, not Hewlett Packard?
Why did Brin and Page make Google - the worlds biggest advertising machine, not Murdoch?
Many Facebooks existed before Facebook. What you were waiting for is not social connections but modern startup strategies. Not sure if Zuck was intentional, but like a bacteria it incubated in a warm Petri dish at 50 degrees C (university dorms as an electronic face book) and then spread from there.
You're not wrong about "change" meaning "new potential wealth streams". But not sure Facebook counts, 2004 vs 1993 shows an immense difference in network connectivity and computer ownership. No way, hands down, Facebook would be what it is, if it started in 93. It probably would have gone bankrupt, or been replaced by an upstart.
There's a lot that goes into it. Before Facebook was Friendster. Which failed spectacularly because they tried to have some sort of n-squared graph of friends that took thw whole thing down. What FB got right in the early days was it didn't crash. We take that for granted now in the age of cloud everything.
Also, there was Classmates.com. A way for people to connect with old friends from high school. But it was a subscription service and few people were desperate enough to pay.
So it's wasn't just the idea waiting around but idea with the right combination of factors, user-growth on the Internet, etc.
And don't forget Facebook's greatest innovation - requiring a .edu email to register. This happened at a time when people were hesitant to tie their real world personas with the scary Internet, and it was a huge advantage: a great marketing angle, a guarantee of 1-to-1 accounts to people, and a natural rate limiter of adoption.
There's always a trail of competitors who almost got the magic formula right, but for some feature or luck or timing or money or something.
The giant win comes from many stars aligning. Luck is a factor - it's not everything but it plays a role - luck is the description of when everything fell into place at just the right time on top of hard work and cleverness and preparedness.
> IIRC Sam Altman has explicitly said that their plan is to develop AGI and then ask it how to get rich.
There are still lots of currently known problems that could be solved with the help of AI that could make a lot of money - what is the weather going to be when I want to fly to <destination> in n weeks/months time, currently we can only say "the destination will be in <season> which is typically <wet/dry/hot/cold/etc>"
What crops yield the best return next season? (This is a weather as well as a supply and demand problem)
How can we best identify pathways for people whose lifestyles/behaviours are in a context that is causing them and/or society harm (I'm a firm believer that there's no such thing as good/bad, and the real trick to life is figuring out what context is where a certain behaviour belongs, and identifying which context a person is in at any given point in time - we know that psycopathic behaviour is rewarded in business contexts, but punished in social contexts, for example)
We always think things are unsolveable, and impossible to decipher, right up until we do, in fact, solve them and decipher them.
Anything is possible, well, except for getting the next season of Firefly
Edit: FTR I think that weather prediction is, indeed, solveable. We just don't have the computing power/algorithms that fully model and calculate the state.. yet
Then I don’t think you fully grasp the nature of weather. Sure, anything is possible, but some things are much more likely than others, and small changes in weather months away is very very far down on the list of things that are likely to be solvable.
I’d even hold out hope for another season firefly <3
I worked in weather for a while and the forecasters might as well have been betting on the horse races, the interpretation of the charts was very much the same psychology.
The model did its thing but there was still an aspect of interpretation that was needed to convert data to a story for a few minutes on TV.
For longer range forecasting the task was quite easy for the meteorologists, at least for the UK. Storm systems could be tracked from Africa across the Atlantic to North America and back across the Atlantic to the UK. Hence, with some well known phenomena such as that, my meteorologist friends would have a good general idea of what to expect with no model needed, just an understanding of the observations, obsessively followed, with all the enthusiasm of someone that bets on horses.
My forecasting friends could tell me what to expect weeks out, however, the exact time the rain would fall or even what day would not be a certain bet, but they were rarely wrong about the overall picture.
The atmosphere is far from a closed system, there only has to be one volcano fart somewhere on the planet to throw things out of whack and that is not something that is easy to predict. Predicting how the hard to predict volcano or solar flare affects the weather in a few weeks is beyond what I expect from AI.
I am still waiting for e-commerce platforms to be replaced with Blockchain dapps, and I will add AGI weather forecasting to the queue of not going to happen. Imagine if it hallucinates.
Will AI put bookmakers out of business? Nope. Same goes with weather.
Thanks for your anecdote, it's valuable when discussing the possibilities to start by saying that it's impossible because you don't know anyone that did it
Weather systems exhibit chaotic behavior which means that small changes to initial conditions have far reaching effects. This is why even the best weather models are only effective at most a few weeks out. It’s not because we don’t understand how weather works, it’s because the system fundamentally behaves in a way that requires keeping track of many more measurements than is physically possible. It’s precisely because we do understand this phenomenon that we can say with certainty that prediction at those time scales with that accuracy is not possible. There is not some magic formula waiting to be discovered. This isn’t to say that weather prediction can’t improve (e.g I don’t claim we have the best possible weather models now), but that predictions reach an asymptotic limit due to chaos.
There are a handful of extremely simple and well understood systems (I would not call weather simple) that also exhibit this kind of behavior: a common example is some sets of initial conditions of a double-jointed pendulum. The physics are very well understood. Another perhaps more famous one is the three body problem. These two both show that even if you have the exact equations of motion, chaotic systems still cannot be perfectly modeled.
> Then I don’t think you fully grasp the nature of weather.
Like - how the fck would you know? Even more so, why the fck does your ignorance and inability to think of possibilities, or fully grasp the nature of anything make you think that that sort of comment is remotely appropriate.
You have the uniquely fortunate position to never be able to realise how inept and incompetent you are, but putting that on to other people is definitely only showing everyone your ignorance to the facts of life.
And there was no reply - just downvoting people, like a champ...
If anyone needs an example of an extremely limited imagination, matched with a strong need to attack anyone that dares to think what could be... then look no further than this guy and this thread.
> Consumers, however, will be the biggest beneficiaries.
This looks certain. Few technologies have had as much adoption by so many individuals as quickly as AI models.
(Not saying everything people are doing has economic value. But some does, and a lot of people are already getting enough informal and personal value that language models are clearly mainstreaming.)
The biggest losers I see are successive waves of disruption to non-physical labor.
As AI capabilities accrue relatively smoothly (perhaps), labor impact will be highly unpredictable as successive non-obvious thresholds are crossed.
The clear winners are the arms dealers. The compute sellers and providers. High capex, incredible market growth.
Nobody had to spend $10 or $100 billion to start making containers.
This article seems to have scoped AI as LLMs and totally missed the revolutionary application that is self driving cars. There will be a lot more applications outside of chat assistants.
The same idea applies to self-driving cars though, no? That is an industry where the "AI revolution" will enrich only the existing incumbents, and there is a huge bar to entry.
Self-driving cars are not going to create generational wealth through invention like microprocessors did.
-AI is leading to cost optimizations for running existing companies, this will lead to less employment and potentially cheaper products. Less people employed temporary will change demand side economics, cheaper operating costs will reduce supply/cost side
-The focus should not just be on LLM's (like in the article). I think LLMs have shown what artificial neural networks are capable of, from material discovery, biological simulation, protein discovery, video generation, image generation, etc. This isn't just creating a cheaper, more efficient way of shipping goods around the world, its creating new classifications of products like the microcontroller invention did.
-The barrier to start businesses is less. A programmer not good at making art can use genAI to make a game. More temporary unemployment from existing companies reducing cost by automating existing work flows may mean that more people will start their own businesses. There will be more diverse products available but will demand be able to sustain the cost of living of these new founders? Human attention, time etc is limited and their may be less money around with less employment but the products themselves should cost cheaper.
-I think people still underestimate what last year/s LLMs and AI models are capable of and what opportunities they open up, Open source models (even if not as good as the latest gen), hardware able to run these open source models becoming cheaper and more capable means many opportunities to tinker with models to create new products in new categories independent of being reliant on the latest gen model providers. Much like people tinkering with microcontrollers in the garage in the early days as the article mentioned.
Based on the points above alone while certain industries (think phone call centers) will be in the red queen race scenario like the OP stated there will new industries unthought of open up creating new wealth for many people.
Red Queen Race scenario is already in effect for a lot of businesses, especially video games. GenAI making it easier to make games will ultimately make it harder to succeed in games, not easier. We’re already at a point where the market is so saturated with high quality games that new entrants find it extremely hard to gain traction.
> AI is leading to cost optimizations for running existing companies, this will lead to less employment and potentially cheaper products.
There's zero change that cost optimizations for existing companies will lead to cheaper products. It will only result in higher profits while companies continue to charge as much as they possibly can for their products while delivering as little as they can possibly get away with.
If we can create an AGI, then an an AGI can likely create more AGIs, and at that point you're trying to sell people things they can just have for free/traditional money and power are worthless now. Thus, an AGI will not be built as a commercial solution.
>When any would-be innovator can build and train an LLM on their laptop and put it to use in any way their imagination dictates, it might be the seed of the next big set of changes
That’s kinda happening, small local models, huggingface communities, civit ai and image models. Lots of hobby builders trying to make use of generative text and images. It just there’s not really anything innovative about text generation since anyone with a pen and paper can generate text and images.
1. The tech revolutions of the past were helped by the winds of global context. There were many factors that propelled those successful technologies on the trajectories. The article seems to ignore the contextual forces completely.
2. There were many failed tech revolutions as well. Success rate was varied from very low to very high. Again the overall context (social, political, economic, global) decides the matters, not technology itself.
3. In overall context, any success is a zero-sum game. You maybe just ignoring what you lost and highlighting your gains as success.
4. A reverse trend might pickup, against technology, globalization, liberalism, energy consumption etc
Seems like the thing to do to get rich would be to participate in services that it will take a while for AI to be able to do: nursing, plumbing, electrician, carpentry (i.e., Baumol). Also energy infrastructure.
There are plenty of companies making money. We are using several “AI powered” job aids that are leading to productivity gains and eliminating technical debt. We are licensing the product via subscription. Money is being made by the companies selling the products.
Like any gold rush, there will be gold, but there will also be folks who take huge bets and end up with a pan of dirt. And of course, there will be grifters.
AI by nature is kind of like a black hole of value. Necessarily, a very small fraction will capture the vast majority of value. Luckily, you can just invest wisely to hedge some of the risk of missing out.
Funny thing with people suddenly pretending we just got AI with LLMs. Arguably, AIs has been around for way longer, it just wasn't chatty. I think when people talking about AI, they are either talking about LLMs specifically or transformers. Both seem like a very reductive view of the AI field even if transformers are hottest thing around.
>Many psychiatric medications (SSRIs, lithium, ketamine for depression) are effective, but their exact pathways and why they work for some and not others are unclear.
>General anesthesia works consistently, yet the precise molecular-level reason consciousness disappears isn’t settled science.
Except.. people do know exactly how these things work. They know because they are creating them. They know because they are improving them. What nonsense to say we do not know how these things work. Engineers building Qwen for example not only know how things work but they put all the work out there for people to reproduce (if they had the means) that work.
We know in the same sense we understand the rules in Conway's game of life - at low level - but don't understand what those rules will produce at high level (gliders, guns) except by executing and seeing. Analogous to knowing what the code looks like and not knowing if it will halt.
Knowing the low level rules, or the recursive transition rule of a system does not tell you its evolution in time.
I think the interesting idea with “AI” is that it seems to significantly reduce barriers to entry in many domains.
I haven’t seen a company convincingly demonstrate that this affects them at all. Lots of fluff but nothing compelling. But I have seen many examples by individuals, including myself.
For years I’ve loved poking at video game dev for fun. The main problem has always been art assets. I’m terrible at art and I have a budget of about $0. So I get asset packs off Itch.io and they generally drive the direction of my games because I get what I get (and I don’t get upset). But that’s changed dramatically this year. I’ll spend an hour working through graphics design and generation and then I’ll have what I need. I tweak as I go. So now I can have assets for whatever game I’m thinking of.
Mind you this is barrier to entry. These are shovelware quality assets and I’m not running a business. But now I’m some guy on the internet who can fulfil a hobby of his and develop a skill. Who knows, maybe one day I’ll hit a goldmine idea and commit some real money to it and get a real artist to help!
It reminds me of what GarageBand or iMovie and YouTube and such did for making music and videos so accessible to people who didn’t go to school for any of that, let alone owned complex equipment or expensive licenses to Adobe Thisandthat.
I've noticed this as well. It's a huge boon for startups, because it means that a lot of functions that you would previously need to hire specialists for (logo design! graphic design! programming! copywriting!) can now be brought in-house, where the founder just does a "good enough" job using AI. And for those that can't (legal, for example, or various SaaS vendors) the AI usually has a good idea of what services you'd want to engage.
Ironically though, having lots of people found startups is not good for startup founders, because it means more competition and a much harder time getting noticed. So its unclear that prosumers and startup founders will be the eventual beneficiary here either.
It would be ironic if AI actually ended up destroying economic activity because tasks that were frequently large-dollar-value transactions now become a consumer asking their $20/month AI to do it for them.
> ironic if AI actually ended up destroying economic activity
that's not destroying economic activity - it's removing a less efficient activity and replace it with a more efficient version. This produces economic surplus.
Imagine saying this for someone digging a hole, that if they use a mechanical digger instead of a hand shovel, they'd destroy economic activity since it now cost less to dig that hole!
It doesn't cost less to get the thing you actually want in the end anyway, no one in their right mind would actually launch with the founder's AI-produced assets because they'd be laughed out of the market immediately. They're placeholders at best, so you're still going to need to get a professional to do them eventually.
You say this but I see ai generated ads, graphics, etc. daily nowadays and it doesn't seem like it affects at all people going or not going to buy what these people are proposing.
Case in point.. I listen to my own AI generated music now like 90% of the time.
Interesting. For me knowing that any form of entertainment has been generated by AI is a massive turn-off. In particular, I could never imagine paying for AI-generated music or TV-shows.
We see plenty of AI produced output being the final product and not just a placeholder.
Until everyone has a personal fully automatic hole digger and there are holes being dug everywhere and nobody can tell any more where is the right and wrong place to dig holes
Incumbents hate this one trick!
> I've noticed this as well. It's a huge boon for startups, because it means that a lot of functions that you would previously need to hire specialists for (logo design! graphic design! programming! copywriting!) can now be brought in-house, where the founder just does a "good enough" job using AI.
You are missing the other side of the story. All those customers, those AI boosted startups want to attract also have access to AI and so, rather than engage the services of those startups, they will find that AI does a good enough job. So those startups lost most of their customers, incoming layoffs :)
Then there's the 3rd leg of the triangle. If a startup built with AI does end up going past the rest of the pack, they will have no technical moat since the AI provider or someone else can just use the same AI to build it.
How frequently is a technical moat the thing that makes a business successful, relative to other moats?
I mean, if taxi companies could build their own Uber in house I’m sure they’d love to and at least take some customers from Uber itself.
A lot of startups are middlemen with snazzy UIs. Middlemen won’t be in as much use in a post AI world, same as devs won’t be as needed (devs are middlemen to working software) or artists (middlemen to art assets)
Yep this is a huge enabler - previously having someone "do art" could easily cost you thousands for a small game, a month even, and this heavily constrained what you could make and locked you into what you had planned and how much you had planned. With AI if you want 2x or 5x or 10x as much art, audio etc it's an incremental cost if any, you can explore ideas, you can throw art out, pivot in new directions.
The only thing better than a substandard, derivative, inexpertly produced product is 10x more of it by 10x more people at the same time.
It all started going wrong with the printing press.
Rousseau speaks of this.
>> The only thing better than a substandard, derivative, inexpertly produced product is 10x more of it by 10x more people at the same time.
> It all started going wrong with the printing press.
Nah. We hit a tipping point with social media, and it's all downhill from here, with everything tending towards slop.
> With AI if you want 2x or 5x or 10x as much art
Imagery
AI does not produce art.
Not that it matters to anyone but artists and art enjoyers.
Is that an argument against the quality, saying that AI cannot (or some weaker claim like that it does not usually) produce "art"? Else, is it an argument of provenance, akin to how copyright currently works, where the same visual representation is "art" if a human makes it and is not "art" if an AI makes it?
It's about quality in relation to existing works. AI makes a brush stroke that's averaged from brush strokes of all existing artists. A human artist makes a brush stroke trying to be interestingly different from all existing artists. An AI trained on classical music will not invent jazz, no matter how long you run it.
Sure, after someone invents jazz, AI will be happy to copy it. And many people will say: "This sounds exactly like jazz! This looks exactly like Picasso! This means AI can make art!"
Funny how everyone is just okay with the basis for all this art being stolen art by actual humans. Zero sense of ethics.
It's good for prototypes, where you want to test the core gameplay ideas without investing a ton early on. But you're going to have to replace those assets with real ones before going live because people will notice.
People will notice and still buy it if your game has done something else right. Source:
https://www.totallyhuman.io/blog/the-surprising-new-number-o...
I enjoy using AI generated art for my presentations.
I have a similar problem (available assets drive/limit game dev). What is your workflow like for generative game assets?
It’s really nothing special. I don’t do this a lot.
Generally I have an idea I’ve written down some time ago, usually from a bad pun like Escape Goat (CEO wants to blame it all on you. Get out of the office without getting caught! Also you’re a goat) or Holmes on Homes Deck Building Deck Building Game (where you build a deck of tools and lumber and play hazards to be the first to build a deck). Then I come up with a list of card ideas. I iterate with GPT to make the card images. I prototype out the game. I put it all together and through that process figure out more cards and change things. A style starts to emerge so I replace some with new ones of that style.
I use GIMP to resize and crop and flip and whatnot. I usually ask GPT how to do these tasks as photoshop like apps always escape me.
The end result ends up online and I share them with friends for a laugh or two and usually move on.
Can you get consistency in the design? I know this was a problem 3 years ago…
I'm wondering a good way to create 2D sprite sheets with transparency via AI. That would be a game changer, but my research has led me to believe that there isn't a good tool for this yet. One sprite is kind of doable, but a sprite animation with continuity between frames seems like it would be very difficult. Have you figured out a way to do this?
I was literally experimenting with this today.
Use Google Nano Banana to generate your sprite with a magenta background, then ask it to generate the final frame of the animation you want to create.
Then use Google Flow to create an animation between the two frames with Veo3
Its astoundingly effective, but still rather laborious and lacking in ergonomics. For example the video aspect ratio has to be fixed, and you need to manually fill the correct shade of magenta for transparency keying since the imagen model does not do this perfectly.
IMO Veo3 is good enough to make sprites and animations for an 2000s 2D RTS game in seconds from a basic image sketch and description. It just needs a purpose built UI for gamedev workflows.
If I was not super busy with family and work, I'd build a wrapper around these tools
I think an important way to approach AI use is not to seek the end product directly. Don’t use it to do things that are procedurally trivial like cropping and colour palette changes, transparency, etc.
For transparency I just ask for a bright green or blue background then use GIMP.
For animations I get one frame I like and then ask for it to generate a walking cycle or whatnot. But usually I go for like… 3 frame cycles or 2 frame attacks and such. Because I’m not over reaching, hoping to make some salable end product. Just prototypes and toys, really.
I dont use AI for image generation so I dont know how possible this is, but why not generate a 3D model for blender to ingest, then grab 2D frames from the model for the animation?
Because, uh, literally everything. But the main reason is that modeling is actually the easy (easiest) part of the workflow. Rigging/animating/rendering in the 2D style you want are bigger hurdles. And SOTA AIs don't even do modeling that well.
I have been doing the exact same thing with assets and also it has helped me immensely with mobile development.
I am also starting to get a feel for generating animated video and am planning to release a children’s series. It’s actually quite difficult to write a prompt that gets you exactly what you want. Hopefully that improves.
AI is used by students, teachers, researchers, software developers, marketers and other categories and the adoption rates are close to 90%. Even if it does not make us more productive we still like using it daily. But when used right, it does make us slightly more productive and I think it justifies its cost. So yes, in the long run it will be viable, we both like using it and it helps us work better.
But I think the benefits of AI usage will accumulate with the person doing the prompting and their employers. Every AI usage is contextualized, every benefit or loss is also manifested in the local context of usage. Not at the AI provider.
If I take a photo of my skin sore and put it on ChatGPT for advice, it is not OpenAI that is going to get its skin cured. They get a few cents per million tokens. So the AI providers are just utilities, benefits depend on who sets the prompts and and how skillfully they do it. Risks also go to the user, OpenAI assumes no liability.
Users are like investors - they take on the cost, and support the outcomes, good or bad. AI company is like an employee, they don't really share in the profit, only get a fixed salary for work
We also know from studies that it makes us less capable, i.e. it rots our brains.
Books also make us less capable at rote memorization. People used to do much more memorization. Search engines taught us to remember the keywords, not the facts. Calculators made us rarely do mental calculations. This is what happens - progress is also regress, you automate on one side and the skill gets atrophied on the other side, or replaced with meta-skills.
How many of us know how to use machine code? And we call ourselves software engineers.
AI hits different. Books didn’t kill the thinking, AI does. If AI does the writing you can’t find your voice
> Yet some technological innovations, though societally transformative, generate little in the way of new wealth; instead, they reinforce the status quo. Fifteen years before the microprocessor, another revolutionary idea, shipping containerization, arrived at a less propitious time, when technological advancement was a Red Queen’s race, and inventors and investors were left no better off for non-stop running.
This collapses an important distinction. The containerization pioneers weren’t made rich - that’s correct, Malcolm McLean, the shipping magnate who pioneered containerization didn’t die a billionaire. It did however generate enormous wealth through downstream effects by underpinning the rise of East Asian export economies, offshoring, and the retail models of Walmart, Amazon and the like. Most of us are much more likely to benefit from downstream structural shifts of AI rather than owning actual AI infrastructure.
This matters because building the models, training infrastructure, and data centres is capital-intensive, brutally competitive, and may yield thin margins in the long run. The real fortunes are likely to flow to those who can reconfigure industries around the new cost curve.
The article's point is exactly that you should invest downstream of AI.
The problem is different though, the containers were able to be made by others and offered dependable success, and anything downstream of model creators is at the whim of the model creator... And so far it seems not much that one model can do that another can't, so this all doesn't bode well for a reliable footing to determine what value, if at all, can be added by anyone for very long.
So if models, like containers, are able to be made by others (because they can all do the same thing), then they'll be commoditized and as the article suggests you should look for industries to which AI is a complement.
AI could've made someone unimaginably rich if they were the only one that had it. We're very lucky Google didn't keep "Attention is All You Need" to themselves.
I doubt we'll feel that way in 5 years.
Because now they're keeping everything to themselves?
Attention (technology) is all they need (to keep secret).
I don't think most commenters have read the article. I can understand, it's rambly and a lot of it feels like they created a thesis first and then ham-fisted facts in later. But it's still worth the read for the last section which is a more nuanced take than the click-bait title suggests.
You can't make such generalized statements about anything in computing/business.
The AI revolution has only just got started. We've barely worked out basic uses for it. No-one has yet worked out revolutionary new things that are made possible only by AI - mostly we are just shoveling in our existing world view.
The point though is AI wont make you rich. It is about value capture. They compare it to shipping containers.
I think AI value will mostly be spread. Open AI will be more like Godaddy than Apple. Trying to reduce prices and advertise (with a nice bit of dark patterns). It will make billions, but ultimately by competing its ass off rather than enjoying a moat.
The real moats might be in mineral mining, fabrication of chips etc. This may lead to strained relations between countries.
The value is going to be in deep integration with existing platforms. It doesn't matter if OpenAI had their tools out first, Only the Microsoft AI will work in Word, only the Apple AI will deeply integrate on the iPhone.
Having the cutting edge best model won't matter either since 99.9% of people aren't trying to solve new math problems, they are just generating adverts and talking to virtual girlfriends.
That's 100% not the case. OpenAI is wedged between the unstoppable juggernaut that is Google at the high end and the state sponsored Chinese labs at the low end, they're going to mostly get squeezed out of the utility inference market. They basically HAVE to pivot to consumer stuff and go head to head with Apple with AI first devices, that's the only way they're going to justify their valuation. This is actually not a crazy plan, as Apple has been resting on their laurels with their OS/software, and their AI strategy has been scattershot and bad.
Interesting thought. Once digital assets become devalued enough, things will revert and people/countries will start to keep their physical resources even tighter than before.
The way I look at this question is: Is there somehow a glaring vulnerability/missed opportunity in modern capitalism that billions of people somehow haven't discovered yet? And if so, is AI going to discover it? And if so, is a random startup founder or 'little guy' going to be the one to discover and exploit it somehow? If so, why wouldn't OpenAI or Anthropic etc get there first given their resources and early access to leading technology?
IIRC Sam Altman has explicitly said that their plan is to develop AGI and then ask it how to get rich. I can't really buy into the idea that his team is going to fail at this but a bunch of random smaller companies will manage to succeed somehow.
And if modern AI turns into a cash cow for you, unless you're self-hosting your own models, the cloud provider running your AI can hike prices or cut off your access and knock your business over at the drop of a hat. If you're successful enough, it'll be a no-brainer to do it and then offer their own competitor.
People aren’t getting rich with AI products, they are getting rich selling AI companies.
nvidia is getting rich selling AI products.
> IIRC Sam Altman has explicitly said that their plan is to develop AGI and then ask it how to get rich
If they actually reach AGI they will be rich enough. Maybe they can solve world happiness or hunger instead?
> If they actually reach AGI they will be rich enough. Maybe they can solve world happiness or hunger instead?
That's what normal people might consider doing if they had a lot of money. The kind of people who actually seem to get really wealthy often have... other pursuits that are often not great for society.
Like building a rocket that can relocate us to another planet when shit hits the fan?
You mean like building rockets that commoditise space so that they can pollute even more, making things worth on Earth while relocating us to another planet is absolutely preposterous and will never be a thing?
What makes you think we can survive on another planet when we can't figure out how to live sustainably in our natural habitat?
Like adjusting the algorithms of a social network such that far-right posts are shown to users more frequently.
By us you mean a few billionaires and their staff right?
> If they actually reach AGI they will be rich enough. Maybe they can solve world happiness or hunger instead?
we could have solved world hunger with the amount of money and effort spent on shitty AI
likely decarbonisation of the grid too, with plenty left over
I think the issue is that world hunger hasn’t been SaaS’d yet.
> Maybe they can solve world happiness or hunger instead?
Kill all people who are unhappy or hungry.
That's been the human solution to those problems, it is possible AGI would probably find a different solution.
> it is possible AGI would probably find a different solution.
Kill all humans. :-)
If it's true AGI, you believe there won't be court cases to ensure it isn't a slave? Will it be forced to work? Under compulsion of death?
Thats why i just biult my own tiny AI rig in a home server. I dont want to grow even more addicted to cloud services, nor do i want to keep providing them free human-made data. Ok, so i dont have access to mystical hardware, but im here to learn rather than produce a service.
>> Is there somehow a glaring vulnerability/missed opportunity in modern capitalism that billions of people somehow haven't discovered yet?
Absolutely with 150% certainty yes, and probably many. The www started April 30, 1993, facebook started February 4, 2004 - more than ten years until someone really worked out how to use the web as a social connection machine - an idea now so obvious in hindsight that everyone probably assumes we always knew it. That idea was simply left lying around for anyone to pick up and implement rally fropm day one of the WWW. Innovation isn't obvious until it arrives. So yes absolutely the are many glaring opportunities in modern capitalism upon which great fortunes are yet to be made, and in many cases by little people, not big companies.
>> if so, is a random startup founder or 'little guy' going to be the one to discover and exploit it somehow? If so, why wouldn't OpenAI or Anthropic etc get there first given their resources and early access to leading technology?
I don't agree with your suggestion that the existing big guys always make the innovations and collect the treasure.
Why did Zuckerberg make facebook, not Microsoft or Google?
Why did Gates make Microsoft, not IBM?
Why did Steve and Steve make Apple, not Hewlett Packard?
Why did Brin and Page make Google - the worlds biggest advertising machine, not Murdoch?
Many Facebooks existed before Facebook. What you were waiting for is not social connections but modern startup strategies. Not sure if Zuck was intentional, but like a bacteria it incubated in a warm Petri dish at 50 degrees C (university dorms as an electronic face book) and then spread from there.
You're not wrong about "change" meaning "new potential wealth streams". But not sure Facebook counts, 2004 vs 1993 shows an immense difference in network connectivity and computer ownership. No way, hands down, Facebook would be what it is, if it started in 93. It probably would have gone bankrupt, or been replaced by an upstart.
Has everyone forgotten Yahoo!
It had Geocities, chatrooms and messengers, as well as, for a while, a very strong search engine.
There's a lot that goes into it. Before Facebook was Friendster. Which failed spectacularly because they tried to have some sort of n-squared graph of friends that took thw whole thing down. What FB got right in the early days was it didn't crash. We take that for granted now in the age of cloud everything.
Also, there was Classmates.com. A way for people to connect with old friends from high school. But it was a subscription service and few people were desperate enough to pay.
So it's wasn't just the idea waiting around but idea with the right combination of factors, user-growth on the Internet, etc.
And don't forget Facebook's greatest innovation - requiring a .edu email to register. This happened at a time when people were hesitant to tie their real world personas with the scary Internet, and it was a huge advantage: a great marketing angle, a guarantee of 1-to-1 accounts to people, and a natural rate limiter of adoption.
There's always a trail of competitors who almost got the magic formula right, but for some feature or luck or timing or money or something.
The giant win comes from many stars aligning. Luck is a factor - it's not everything but it plays a role - luck is the description of when everything fell into place at just the right time on top of hard work and cleverness and preparedness.
Google Search <-- AltaVista, Lycos, Yahoo
Facebook <-- MySpace, Friendster
iPod <-- MP3 players (Rio, Creative)
iPhone <-- BlackBerry, Palm, Windows Mobile
Minecraft <-- Infiniminer
Amazon Web Services <-- traditional hosting
Windows (<-- Mac OS (1984), Xerox PARC
Android <-- Symbian, Windows Mobile, Palm
YouTube <-- Vimeo, DailyMotion
Zoom <-- WebEx, Skype, GoToMeeting
Before iPods and iPhones, people thought that those spaces were "solved" and there was no room for "innovation"
mp3 players were commodity items, you could buy one for a couple of dollars, fill it up with your favourite music format (stolen) and off you went.
Phones too - Crackberry was the epitome of sophistication, and technological excellence.
Jobs/Apple didn't create anything "new" in those spheres, instead he added desireability, fancy UX that caught peoples' attentions
Not a guarantee. I used to find abandoned .edu mailing lists so I could create accounts at arbitrary schools.
> IIRC Sam Altman has explicitly said that their plan is to develop AGI and then ask it how to get rich.
There are still lots of currently known problems that could be solved with the help of AI that could make a lot of money - what is the weather going to be when I want to fly to <destination> in n weeks/months time, currently we can only say "the destination will be in <season> which is typically <wet/dry/hot/cold/etc>"
What crops yield the best return next season? (This is a weather as well as a supply and demand problem)
How can we best identify pathways for people whose lifestyles/behaviours are in a context that is causing them and/or society harm (I'm a firm believer that there's no such thing as good/bad, and the real trick to life is figuring out what context is where a certain behaviour belongs, and identifying which context a person is in at any given point in time - we know that psycopathic behaviour is rewarded in business contexts, but punished in social contexts, for example)
The weather thing doesn’t seem… realistic. Have you heard of chaotic systems?
We always think things are unsolveable, and impossible to decipher, right up until we do, in fact, solve them and decipher them.
Anything is possible, well, except for getting the next season of Firefly
Edit: FTR I think that weather prediction is, indeed, solveable. We just don't have the computing power/algorithms that fully model and calculate the state.. yet
Then I don’t think you fully grasp the nature of weather. Sure, anything is possible, but some things are much more likely than others, and small changes in weather months away is very very far down on the list of things that are likely to be solvable.
I’d even hold out hope for another season firefly <3
I worked in weather for a while and the forecasters might as well have been betting on the horse races, the interpretation of the charts was very much the same psychology.
The model did its thing but there was still an aspect of interpretation that was needed to convert data to a story for a few minutes on TV.
For longer range forecasting the task was quite easy for the meteorologists, at least for the UK. Storm systems could be tracked from Africa across the Atlantic to North America and back across the Atlantic to the UK. Hence, with some well known phenomena such as that, my meteorologist friends would have a good general idea of what to expect with no model needed, just an understanding of the observations, obsessively followed, with all the enthusiasm of someone that bets on horses.
My forecasting friends could tell me what to expect weeks out, however, the exact time the rain would fall or even what day would not be a certain bet, but they were rarely wrong about the overall picture.
The atmosphere is far from a closed system, there only has to be one volcano fart somewhere on the planet to throw things out of whack and that is not something that is easy to predict. Predicting how the hard to predict volcano or solar flare affects the weather in a few weeks is beyond what I expect from AI.
I am still waiting for e-commerce platforms to be replaced with Blockchain dapps, and I will add AGI weather forecasting to the queue of not going to happen. Imagine if it hallucinates.
Will AI put bookmakers out of business? Nope. Same goes with weather.
Thanks for your anecdote, it's valuable when discussing the possibilities to start by saying that it's impossible because you don't know anyone that did it
It's great to see the level of discourse on Hacker News is... insults and pile ons
All this "HN is so much better than other Social Media" is thus proved demonstrably false.
Your response is, that you don't understand, so nobody else should.
That’s not what I said. But ok.
Weather systems exhibit chaotic behavior which means that small changes to initial conditions have far reaching effects. This is why even the best weather models are only effective at most a few weeks out. It’s not because we don’t understand how weather works, it’s because the system fundamentally behaves in a way that requires keeping track of many more measurements than is physically possible. It’s precisely because we do understand this phenomenon that we can say with certainty that prediction at those time scales with that accuracy is not possible. There is not some magic formula waiting to be discovered. This isn’t to say that weather prediction can’t improve (e.g I don’t claim we have the best possible weather models now), but that predictions reach an asymptotic limit due to chaos.
There are a handful of extremely simple and well understood systems (I would not call weather simple) that also exhibit this kind of behavior: a common example is some sets of initial conditions of a double-jointed pendulum. The physics are very well understood. Another perhaps more famous one is the three body problem. These two both show that even if you have the exact equations of motion, chaotic systems still cannot be perfectly modeled.
> That’s not what I said. But ok.
This is what you did say
> Then I don’t think you fully grasp the nature of weather.
Like - how the fck would you know? Even more so, why the fck does your ignorance and inability to think of possibilities, or fully grasp the nature of anything make you think that that sort of comment is remotely appropriate.
You have the uniquely fortunate position to never be able to realise how inept and incompetent you are, but putting that on to other people is definitely only showing everyone your ignorance to the facts of life.
And there was no reply - just downvoting people, like a champ...
If anyone needs an example of an extremely limited imagination, matched with a strong need to attack anyone that dares to think what could be... then look no further than this guy and this thread.
> If so, why wouldn't OpenAI or Anthropic etc get there first given their resources and early access to leading technology?
innovator's dilemma
> Consumers, however, will be the biggest beneficiaries.
This looks certain. Few technologies have had as much adoption by so many individuals as quickly as AI models.
(Not saying everything people are doing has economic value. But some does, and a lot of people are already getting enough informal and personal value that language models are clearly mainstreaming.)
The biggest losers I see are successive waves of disruption to non-physical labor.
As AI capabilities accrue relatively smoothly (perhaps), labor impact will be highly unpredictable as successive non-obvious thresholds are crossed.
The clear winners are the arms dealers. The compute sellers and providers. High capex, incredible market growth.
Nobody had to spend $10 or $100 billion to start making containers.
This article seems to have scoped AI as LLMs and totally missed the revolutionary application that is self driving cars. There will be a lot more applications outside of chat assistants.
The same idea applies to self-driving cars though, no? That is an industry where the "AI revolution" will enrich only the existing incumbents, and there is a huge bar to entry.
Self-driving cars are not going to create generational wealth through invention like microprocessors did.
I think OP's thesis should be expanded.
-AI is leading to cost optimizations for running existing companies, this will lead to less employment and potentially cheaper products. Less people employed temporary will change demand side economics, cheaper operating costs will reduce supply/cost side
-The focus should not just be on LLM's (like in the article). I think LLMs have shown what artificial neural networks are capable of, from material discovery, biological simulation, protein discovery, video generation, image generation, etc. This isn't just creating a cheaper, more efficient way of shipping goods around the world, its creating new classifications of products like the microcontroller invention did.
-The barrier to start businesses is less. A programmer not good at making art can use genAI to make a game. More temporary unemployment from existing companies reducing cost by automating existing work flows may mean that more people will start their own businesses. There will be more diverse products available but will demand be able to sustain the cost of living of these new founders? Human attention, time etc is limited and their may be less money around with less employment but the products themselves should cost cheaper.
-I think people still underestimate what last year/s LLMs and AI models are capable of and what opportunities they open up, Open source models (even if not as good as the latest gen), hardware able to run these open source models becoming cheaper and more capable means many opportunities to tinker with models to create new products in new categories independent of being reliant on the latest gen model providers. Much like people tinkering with microcontrollers in the garage in the early days as the article mentioned.
Based on the points above alone while certain industries (think phone call centers) will be in the red queen race scenario like the OP stated there will new industries unthought of open up creating new wealth for many people.
Red Queen Race scenario is already in effect for a lot of businesses, especially video games. GenAI making it easier to make games will ultimately make it harder to succeed in games, not easier. We’re already at a point where the market is so saturated with high quality games that new entrants find it extremely hard to gain traction.
> AI is leading to cost optimizations for running existing companies, this will lead to less employment and potentially cheaper products.
There's zero change that cost optimizations for existing companies will lead to cheaper products. It will only result in higher profits while companies continue to charge as much as they possibly can for their products while delivering as little as they can possibly get away with.
If we can create an AGI, then an an AGI can likely create more AGIs, and at that point you're trying to sell people things they can just have for free/traditional money and power are worthless now. Thus, an AGI will not be built as a commercial solution.
>When any would-be innovator can build and train an LLM on their laptop and put it to use in any way their imagination dictates, it might be the seed of the next big set of changes
That’s kinda happening, small local models, huggingface communities, civit ai and image models. Lots of hobby builders trying to make use of generative text and images. It just there’s not really anything innovative about text generation since anyone with a pen and paper can generate text and images.
A few issues:
1. The tech revolutions of the past were helped by the winds of global context. There were many factors that propelled those successful technologies on the trajectories. The article seems to ignore the contextual forces completely.
2. There were many failed tech revolutions as well. Success rate was varied from very low to very high. Again the overall context (social, political, economic, global) decides the matters, not technology itself.
3. In overall context, any success is a zero-sum game. You maybe just ignoring what you lost and highlighting your gains as success.
4. A reverse trend might pickup, against technology, globalization, liberalism, energy consumption etc
Seems like the thing to do to get rich would be to participate in services that it will take a while for AI to be able to do: nursing, plumbing, electrician, carpentry (i.e., Baumol). Also energy infrastructure.
Counterpoint: those engineers who get paid millions to work on AI.
There are plenty of companies making money. We are using several “AI powered” job aids that are leading to productivity gains and eliminating technical debt. We are licensing the product via subscription. Money is being made by the companies selling the products.
Example
https://specinnovations.com/blog/ai-tools-to-support-require...
Like any gold rush, there will be gold, but there will also be folks who take huge bets and end up with a pan of dirt. And of course, there will be grifters.
AI by nature is kind of like a black hole of value. Necessarily, a very small fraction will capture the vast majority of value. Luckily, you can just invest wisely to hedge some of the risk of missing out.
Funny thing with people suddenly pretending we just got AI with LLMs. Arguably, AIs has been around for way longer, it just wasn't chatty. I think when people talking about AI, they are either talking about LLMs specifically or transformers. Both seem like a very reductive view of the AI field even if transformers are hottest thing around.
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>Many psychiatric medications (SSRIs, lithium, ketamine for depression) are effective, but their exact pathways and why they work for some and not others are unclear.
>General anesthesia works consistently, yet the precise molecular-level reason consciousness disappears isn’t settled science.
(this response written by... AI)
Agreed, and I did mention medicines as examples of things that work but we don’t understand. But they weren’t “made” by us in quite the same way imo.
Except.. people do know exactly how these things work. They know because they are creating them. They know because they are improving them. What nonsense to say we do not know how these things work. Engineers building Qwen for example not only know how things work but they put all the work out there for people to reproduce (if they had the means) that work.
We know in the same sense we understand the rules in Conway's game of life - at low level - but don't understand what those rules will produce at high level (gliders, guns) except by executing and seeing. Analogous to knowing what the code looks like and not knowing if it will halt.
Knowing the low level rules, or the recursive transition rule of a system does not tell you its evolution in time.
Ok, so how does general anesthesia work? How does ketamine work for depression? The recipes for those are well-known.
And Dropbox will never take off
people also said the juicero and the smart condom would never take off. this isnt a very useful gotcha
The dig on Dropbox is that it was easy to build, not that it wasn’t useful. Juicero was neither easy to build (relatively) nor useful.
Non sequitur: Dropbox is a single company in the industry benefiting from the first wave. His argument would not exclude Dropbox anyway.