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.
> 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 :)
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.
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?
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 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.
> 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.
-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.
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.
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.
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.
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?
>> 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.
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.
> 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.
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.
> 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.
>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.
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.
The style of thinking in this piece is interesting but relies, understandably, on all the historical precedents and the rationalizations around them. But it’s different this time :). One way I think it actually is different is this: we don’t really understand how this thing, created by humans, really works. What other advancement has that property? I can’t think of one. Perhaps certain important medicines? Other new technologies: nuclear power, solar cells, etc., say, were fully engineered by a scientific understanding that was basically complete. Things like locomotives, or flight, or even the internet were fully understood in scientific and engineering terms. They were extrapolations. Forseeing how people would use it was, of course, difficult, and that is shared with AI.
But it does seem a singular property of AI (this generation anyway) that even though “we” made it, we don’t understand it. That it works so well (e.g. next token prediction at scale) is unexpected even by the people who did it (at least that’s my relatively uninformed take … there’s a great book of scientific history to be written on that topic imo). In that sense AI is almost like an alien intelligence that landed here. It’s more of a discovery than an invention. Maybe superconductivity or quantum phenomena are analogues.
In any case, what is the consequence of this for predicting how it will play out?
>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.
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.
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.
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.
> 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 :)
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.
> 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.
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.
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.
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 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 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.
> 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.
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.
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.
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.
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.
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.
> 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 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?
> 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. :-)
>> 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.
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.
> 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.
> If so, why wouldn't OpenAI or Anthropic etc get there first given their resources and early access to leading technology?
innovator's dilemma
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.
> 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.
>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.
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?
The style of thinking in this piece is interesting but relies, understandably, on all the historical precedents and the rationalizations around them. But it’s different this time :). One way I think it actually is different is this: we don’t really understand how this thing, created by humans, really works. What other advancement has that property? I can’t think of one. Perhaps certain important medicines? Other new technologies: nuclear power, solar cells, etc., say, were fully engineered by a scientific understanding that was basically complete. Things like locomotives, or flight, or even the internet were fully understood in scientific and engineering terms. They were extrapolations. Forseeing how people would use it was, of course, difficult, and that is shared with AI.
But it does seem a singular property of AI (this generation anyway) that even though “we” made it, we don’t understand it. That it works so well (e.g. next token prediction at scale) is unexpected even by the people who did it (at least that’s my relatively uninformed take … there’s a great book of scientific history to be written on that topic imo). In that sense AI is almost like an alien intelligence that landed here. It’s more of a discovery than an invention. Maybe superconductivity or quantum phenomena are analogues.
In any case, what is the consequence of this for predicting how it will play out?
>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.
Ok, so how does general anesthesia work? How does ketamine work for depression? The recipes for those are well-known.
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.
Example
https://specinnovations.com/blog/ai-tools-to-support-require...
Counterpoint: those engineers who get paid millions to work on AI.
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.
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
Non sequitur: Dropbox is a single company in the industry benefiting from the first wave. His argument would not exclude Dropbox anyway.