You’ve described a corporation. Think of YC companies - equity owned by early employees. Controlled by “someone senior”. And if things are going good more friends are invited to join in, multiple companies start owning equity within each other and you back new incomers by directing demand towards their products. The difference between that and a coop is that in a corporation there is some legal standing to enforce the rules and control abuse. In eastern europe where coops had more of a presence the people in power would just abuse the coops - theft, misdirection of resources towards “friends”, pyramid schemes benefiting “older members”… but you couldn’t go and sue as a shareholder because via political connections the entrenched leader and his buddies could use their power to pay off someone and hurt you. The real prof in concepts like this are enforceable contracts.
Eh, I think this is where it's important to distinguish between different types of corporation. The very point of going through YC is to trade ownership and control for external capital: the capital ends up in control of the business. Other types of corp other than "limited liability with shares" are possible.
However the article describes something even looser. It's more like the opposite of a boycott, a loose buyer's group focusing on directing spending towards something positive rather than away from something negative.
> the people in power would just abuse the coops - theft, misdirection of resources towards “friends”
The US has recently seen a sharp uptick of this kind of thing, under the cover of law.
Visited a recycling facility recently. It’s a private company that covers an entire county in California. They filter the garbage wit people and a big machine and seem to get paid by companies abroad to ship them all recyclable materials - plastics, cardboard, metals, glass. That pays enough to keep them in business for decades. Someone really needs to look at where the materials from our garbage go.
I toured a sorting facility in Seattle recently. They said the only really profitable output is aluminum, everything else costs more than virgin material.
I worked at a plastic furniture manufacturer in Indiana for a few projects.
They got paid to accept bales of recycled "HDPE" that they could mix at between 10 and 30% into their virgin materials. They get paid to accept it! Negative profit for the waste management company, pure profit for the "user".
This worked best on black, coffee, slate grey, mahogany - you get the idea - the whites and tans and bright colors were basically pure virgin material (and their own internally-recycled offcuts of dyed virgin materials of matching colors) even though their FAQ states:
> What percentage of recycled materials are used?
> The percentage of recycled materials in our lumber can vary depending on the availability of post-consumer and post-industrial plastics. We continuously strive to maximize the use of recycled content in every piece of lumber.
Personally, I don't think that the fact that you started with pure virgin material, extruded some plastic, cut it up and used most of it, but put some of what was virgin material a few hours ago back into the grinder and extruder makes the resulting plastic "recycled".
It's 100% recycling, if the alternative was just "throw away the excess". For all practical purposes, recycling just means "repurposing material that you would have otherwise sent to a landfill".
My understanding is that glass gets downcycled into a lot of products like concrete or asphalt or aggregates. It's not profitable, but it's really easy to provide at a low loss.
If apple provides native support with enough bandwidth to run an external NVIDIA GPU for Inference and training, I will upgrade to the latest MBP instantly. Raise your hand if you would too.
The economist in me immediately asks: Where is the financial incentive to do this? Just the same way the programmer would ask what the stack is. Some possibilities:
1) Money laundering - large content farm someone can argue makes xyz in revenue to hide an alternate source of revenue.
2) Ad fraud - leading up podcast charts or SEO results to attract clicks to sell ads. Bot farms could also be making clicks to pretend sell ads as well.
3) Attempt to dominate the niche for sale of knitting products. Or to pretend to dominate it so they can sell their the business later at a larger multiple.
4) Test the waters of a much bigger engine for doing 1-3 above in an innocuous hidden subject, before they do it with elections or some other more profitable field. Regulatory waters as well - seeing what they can get away with.
Feel free to brainstorm more incentives for making something like this.
I don't understand your question, are you asking what's the financial incentive to AI-generate thousands of podcasts a week? Isn't it obviously the income from streams and/or ads?
Are they? Or do they think they are listening to something real?
I've enjoy reading alt-history at times. However I can only enjoy this when it is clear that this isn't real history. Often one of the more enjoyable parts is authors notes of how real history differs.
I have heard some human written songs that really sounded real and tugged at the heart strings - until I found out it was fiction, and then I was offended. The key here is that it showed someone good (to modern ideals - they all considered themselves good Christians) existed in a timeline where they where we know almost nobody was good.
the bitch of it, though, is that it doesn't only work if people listen to it. it also works if a bunch of AI bots can convincingly fake people listening to it. and, of course, those types of bots exist and have financial incentive to continue faking it, too.
at some point, these two competing interests are going to find out that they're paying each other to stare at each other's dwindling profits, but my bet is that it's going to be a while yet before that wake up call. and it will be an even longer churn into something else because no one is going to admit that they were funneling money into nonsense for years. they're going to "adjust strategies" to "modernize against changing markets" for "new potential growth". all shit that takes a long time to do because it's a half measure aimed at saving face to investors. so it'll work for a long time just based on the momentum of bullshit. =/
they said, podcasts had 12 million downloads. 750k weekly at the moment.
They get people listening. And when you download you don't know it will be crap AI slop.
I now get a bunch of this in youtube - just endless drivel about some theme I am interested in. They create so much crap it's hard to see which one is real. I started banning the accounts that are making AI crap, but there are so many now.
Podcast network is an established and proven business model. You spend money to make episodes, you make money from ads. You make a bunch of different podcasts with a bunch of different target demos to reach a wider range of listeners and this grows your revenue and makes it more consistent. It's not complicated.
The specific incentives for starting a slop network are the promises of increased margins via reduced production costs (don't have to pay any pesky creative types) and more rapid growth via reduced production time (you can theoretically produce an episode in about the time it takes to listen to one, perhaps less).
I explored starting an AI slop network a few years ago. The tech wasn't quite ready at the time. My motivation was far more base: watching numbers go up.
Nevada makes it much harder to sue corporate officers when they do malfeasance. Wyoming has tons of privacy perks for the officers (similar to cayman island accounts). “Perks” though also convert into signaling for the intent of the founders.
Tried DeepSeek V4 Pro and Flash on Open Router and they worked fine - flash might have actually produced a better result, but also the same prompt across different inference providers produced the same result. Then tried DS4 Pro again via tinfoil.sh and got the same design but littered with random Chinese characters in the code. Tinfoil pegs prompt data as private / not trained on. Do know know DS4 providers that are verifiably private and not training on your prompts and outputs?
There is no insinuation. I am looking for both private and quality inference. I am not sure why Tinfoil had the characters. I will keep trying them, but it’s an issue if not resolved.
My push for trying local was the wildly unpredictable but systematic performance of large models like Opus and ChatGPT. It feels like at different times of day or week they are getting degraded beyond belief. I don’t know if it is deliberate, a function of demand, or a function of the models themselves. We are all learning the shape of this space by trying. I need to be able to rely on consistent performance - and maybe that means putting some harness of benchmarks between models and maybe it means between different inference providers, and maybe local.
Children learn by playing because not much is expected of the outcome in play. Improvement happens when you can play. When AI has a play environment to learn with reinforcement. When entrepreneurs are allowed to try and fail and do better. Doctors learn by practicing under supervision, or on corpses, until they can do it for real. No straight line goes up without a jiggle in the beginning.
Go to Open Router, ask your own in investigative prompt that meets your needs to all the top open models. See how they do. Then notice if you can run any of those locally. Repeat at least once a month.
> From a very early age, perhaps the age of five or six, I knew that when I grew up I should be a writer.
I think "what one wants to be" is a fashion and depends on the era. Today's children want to be youtuber or content creator. I grew up in consuming youtube and social media so I consider those mediums to be more captivating and allows for vivid storytelling captivating dominant senses.
