Help me understand where Meta and Alphabet's issues are. They seem to be doing quite well on paper -- nothing anomalous in terms of profitability or scaling recently. Layoffs are to be expected when AI can increase productivity.
The problem with judging Alphabet and Meta on aggregate performance is that their advertising businesses print so much money that they can invest everything in a boondoggle and coast when it blows up. Zuckerberg burned $100,000,000,000 on the metaverse and it didn’t make a dent.
That said, Alphabet and Meta are borrowing against their future advertising profits to fund their AI boondoggles. If the advertising businesses keep growing then they’re somewhat insulated from their own missteps but the reliability of the advertising business depends on companies having money to spend on advertising.
The metaverse was mostly self-contained and the failure had zero consequence for the broader economy. AI on the other hand, every major fund is investing everything into AI companies. Every advertiser is using subsidized AI tools to generate hyper specific adverts. If this all goes south, who knows how advertising spend will be impacted.
Google specifically are backstopping billions in data centre build out costs. They’ve committed to spending, like, all of their cash to data centres. If the market gets nervous and funding disappears, Google are deep in the hole.
Anthropic “invested” $50bn in data centers to be built by Fluidstack who raised a billion dollars from Situational Awareness who used their Anthropic ownership to raise money to fund these investments. Google are backstopping much of the Fluidstack build out, i.e: if Fluidstack goes out of business then Google is on the hook for $10bn+ in costs. And Google’s Anthropic investment makes up like $100bn on the balance sheet. So, Anthropic fails to live up to expectations and fails to pay Fluidstack who can’t pay their suppliers which puts Google on the hook to hand over tens of billions in cash while at the same time their biggest investment is going down the pan.
The top line numbers don’t really do justice to the scale of the risk. You need to look at the long term commitments they’re making.
Agreed. The area I think will become more prevalent in the future for organizations are cost per intelligence -- effectively efficiency. An unoptimized model that costs 90x more than another that is only 10-15% less intelligent is something I would say is not a good deal.
"Price. Fable 5.1 will cost an estimated 25% less than Fable 5 for typical workloads, wherever usage is billed by token. This is because we’re reducing our pricing on cache reads (where the model reads inputs that have already been processed and stored). For highly agentic work, the savings will often be much larger—up to approximately 45%."
They show this off, but artificial analysis contradicts the statement. Fable 5 cost $3.14 per task, while 5.1 cost $3.69 -- around a 15% jump in pricing.
These, IMO, are marginal improvements for a more expensive model. I stopped using Claude ~3 months back; its outputs are too jargoned, it makes architectural decisions that are not right, and it's incredibly pricey for what it is. Each decision it makes, it acts as if a problem as major as world hunger has been solved. And the overly verbose code comments, strange commit descriptions, duplicate code, and slop it generates -- which I know is not specific to Fable -- is just too much for me.
I found the best is to use something like Deepseek V4 Flash -- with a fast TPS provider -- and work on the code myself. For agentic work with computer use, GLM 5.3 flash with Hermes Desktop works well.
I run a small hardware startup, InfiShark Tech -- we sell affordable battery-powered cybersecurity hardware worldwide. Europe has been by far the hardest market for us.
The costs in this article are understated for products like ours. This is not just for packaging -- they have separate compliance schemes for electronics (WEEE). If selling products with batteries, you must comply with separate battery regulations. If you pass a certain threshold or contain specific chemicals within your product, you must also comply with the REACH regulation. They work almost exactly the same the article describes, but often with higher costs.
Additionally, you must have CE certification for your hardware product. There is no threshold. This means going to a lab and testing RF capabilities, and for wireless / Bluetooth devices it can cost $1,500-$8,000. You can self-certify but it is risky.
We pay 800-2,000 EUR per country annually for the authorized representative (AR) and producer responsibility organization (PRO) fees. The AR's task is to hold some documents and provide them to the government when requested -- but that's it. We can do this for free. There's no reason the costs should be this high -- and I see minimal reason why they should exist in the first place. But we must comply.
It is important to understand which regulations and which fees to pay for the product. Therefore it is important to use something like PRONEXA -- a "One-Stop-Shop for simple compliance management".
With them, we paid ~800-1,000 EUR per country as a one-off registration fee. Then we pay 975 EUR annually per country to keep compliance. Note that these costs are ONLY to PRONEXA, not to each AR or PRO. They are effectively the middleman between us and the ARs / PROs.
The fee stability is quite poor, too. We paid the 2025 annual fees roughly a month before year-end and were charged another full annual fee in February 2026. In November 2025, we paid ~500 SEK for Sweden, and in Feb 2026, we were invoiced ~15,000 SEK for that same line.
With all of this burden we only pay the countries ~0.5-50 EUR annually for the actual environmental fees. This only makes sense for the government if that number jumps up to the thousands.
I think this contributes to lack of innovation in Europe. Small startups can't ship there, and you are limited to large companies overseas. The fix is dead simple -- just introduce a threshold, or charge a recycling fee upfront with each parcel coming in, depending on the HS code. What they did with IOSS is great. You register with one country, and all parcels under 150 EUR can be sent to all of Europe while being VAT compliant. They could implement the same thing for WEEE, battery regulations, packaging, and REACH. Register with one country and cover the rest.
We are barely break-even on some countries, and others we are totally underwater. We decided to do it as a future scaling opportunity, but this first year is quite tough. We are debating if we should continue selling to Europe at this stage.
That’s what I thought, the European market is already very difficult for startups, market entry is overly restrictive and therefore expensive and time consuming. From this perspective, the new waste regulations are just the straw that breaks the camel's back.
If humanity is over-reliant on frontier labs' models to perform work, the result is a dependence on the actual intelligence of these models -- not on human intelligence. This could be a small reason, on top of many others, why investors are throwing hundreds of billions of dollars a bit "carelessly" to these labs. It's fascinating seeing the models do the "hard work" (the deep, challenging thinking) for you.
The conundrum which tricks me though - is this a net negative or a positive? If humans are less intelligent, but their output is 2-3 times more intelligent (with AI), what's the result? At what point do we, as humans, stop comprehending anything and give all intelligent work to the neural nets?
And if that does happen, could we live in a society where no work, or at least a significantly less amount of work, is needed? To me, it seems like a dystopian net positive.
It might seem far-fetched to ask these, but I think these questions are getting more prevalent by the day.
If there was a way to guarantee that every human would have equal access to external intelligence then it would be hard to argue against it but everyone knows that the US oligopoly will do everything they can to ensure that no one else has the keys to the kingdom.
Just listen to what the SV ownership class says out loud. They openly discuss how China cannot "win the AI arms race" and how China's development is existential. Existential to who? It's impossible to fully subjugate people with agency.
I am going to try to cheer you up. Hear me out. One day, not long from now, I am going to buy a humanoid bot for 40k. This human android will 1) get my groceries, 2) make my elderly parents meals, 3) go to the backyard and plant 1 acre of corn, 4) paint my neighbors house. 5) get the kids from school 6) change my oil.
What will happen? Massive. Deflation. What will you pay for an oil change? Corn? Meals? Everything is about to be free. But tokens will be expensive!! Sure but, you wont do white collar work anymore so it wont matter what tokens cost.
> am going to try to cheer you up. Hear me out. One day, not long from now, I am going to buy a humanoid bot for 40k. This human android will 1) get my groceries, 2) make my elderly parents meals, 3) go to the backyard and plant 1 acre of corn, 4) paint my neighbors house. 5) get the kids from school 6) change my oil.
Hahahahahahahha. You're delusional if you think this is true.
It's not just a dependence on the intelligence of the models, but also their intentions, as programmed by their owners.
A friend of mine asked me if I was optimistic about AI. I told him, it depends on who owns it. If the people own it, I'm optimistic. If the oligarchs own it, I'm pessimistic.
Seems like we're starting to get reliant on the intelligence of these models to keep our outputs less "sloppy". Effectively an IaaS (Intelligence-as-a-Service). With the U.S. putting the suspension on Fable 5, we might be stuck with slop.
With open-weight AI, there might not be an incentive to put large sums of capital towards training / research. There might be a donation fund of some sorts, but it certainly won't reach the level of fundraising that the frontier labs are receiving.
Because of this, I think it might not be possible to have AI *only* open-weight; major players like OpenAI, Anthropic, Google will likely stay for good, with better models than open-source versions.
I think it might look something like Photoshop & GIMP, with Photoshop being a frontier lab, and GIMP being the open-weight model. GIMP is decent for many different image editing workflows, but Photoshop is just better.
I would definitely prefer to have an open-weight model better than frontier labs'. Though I don't think it's possible.
I think the same, but I also think that local AI is actually inevitable, even if not open source models. I wouldn't be surprised to see OpenAI and others release an on-prem product. Whether that's effectively an appliance rack, or some other form, people (large companies) are going to want to run inference locally for data sovereignty & cost controls. Especially if we get to a point where companies want AI integrated into manufacturing and other air-gapped networks.
I do believe that if OpenAI and others release an open-weight model that is better or on par with their frontier variants, it might ruin their primary business model.
That is, of course, unless they develop their own hardware specifically to run this open model. But, that does ruin the point of open models.
When/if gains slow down, I can definitely see branching out into hardware to sell for on-prem inference once the models can be etched into the silicon with hard wired weight chips. I'd guess maybe at least 5+ years away from that though.
I think this is inevitable. Sooner or later, model-specific ASIC's will make economical sense. We're already seeing it happening with Taalas/Cerebras so I think it's sooner than 5 years. And inference is order of magnitude faster which is amazing.
Yeah I think that's a decent analog (Photoshop & GIMP). We're in a sort of "rapid expansion" phase right now, but unless the tech behind "AI" really evolves, better and better models will be harder to come by, with diminishing returns.
Even if the GIMP of LLMs is only 80% as good as the VC-funded stuff, that will still be plenty useful for lots of people.
And I think just having the option to use open source models is a win, even if it turns out to be true they'll never be quite as good as the proprietary ones.
Zoom out. It's a matter of time the trillion valuations will be deemed senseless, only once it will prove inpossible to extract trillions from consumers.
In the meanwhile, and regardless, software optimisations coupled with hardware continuing to scale, we will end up, soon enough, with some open weight that run on a mobile device with greater capabilities than Fable.
This is utopian thinking. The products are way too useful to not subscribe. The argument presupposes the worst-case negative-utility in the long-term scenario (AI companies will create a totalitarian nightmare) and pits it against the radical usefulness that the products are creating right now.
I've used over a trillion tokens in the last few years with zero subscription. In fact I have one with deepseek, spend 13 cents to test some automation. The rest is consumed free of charge to bleed the bleeders.
If/when they ALL enforce paid subscriptions, I will only run inference locally. By then consumer hardware will equal frontier models in term of speed and performance.
> Because of this, I think it might not be possible to have AI only open-weight; major players like OpenAI, Anthropic, Google will likely stay for good, with better models than open-source versions.
There's a more fundamental reason for this: some AI models are large enough that they can plausibly only be reasonably run in a state-of-the-art hyperscale datacenter. Open sourcing such models would be largely pointless. Note that this would be a significantly larger scale than even the largest open models available today, one that precludes even doing inference slowly on a small-scale, cheap makeshift cluster. But it's plausible that Fable is there already.
Which is the nearterm future that we must demand: a stop to the amounts of capital flowing to ASI research. Join me, Anthropic, Google, and OpenAI’s-founding-charter in saying the obvious, y’all; Pause AI, now.
It should be clear by now that there’s a whole universe of work to do with the models we have today, from studying to securing to ‘harness’ing. There are tons of economic benefits to be reaped already, if applied carefully. Doesn’t that sound nicer than rolling the dice with the lives of trillions?
That is fantastic news then, if commercial product products will always be better than open source, and open source products will continue to get better
Agreed. The only "issue" is that commercial products will always be ahead, with less friction for most users. This ultimately results in most people using these over open-weight variants. Users might not even be aware that the open-model variants exist. Similar to Windows / MacOS and Linux.
In a way that's ok, though? I run Linux on my laptop, and in some ways it's better than Windows or macOS, and in other ways it's lacking. But that's fine; the existence of Windows and macOS doesn't mean I can't run Linux, and doesn't mean I have a worse experience.
(Yet; I do worry about future required hardware attestation for basic things, but that's another issue.)
Well. Right now buying hardware to run your own models tops off at about 32gb VRAM at any price point that's not insane. Sure you can get a Mac mini, or a PC equivalent. But the problem is RAM.
More RAM means bigger models, which means smarter models.
Which is why Qwen and Gemma have been so interesting to a lot of us who run our own... Now 32gb VRAM isn't so bad, as these models can be run on that with decent results.
Where this gets interesting is in a couple years, when all the A100, etc, all the Enterprise hardware hits eBay.
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