The compute cost for DeepSeek V3 was $5.6M. Training costs for traditional US frontier labs model is about $70 to $200M+, with estimates of up to $1B+ to train the next generation models. It's expensive, but it's not even in the ballpark of "There is no viable economic model to do so." Google revenue in Q2 was $1.32 billion *per day*. $1B is trivially less than a day; $5.6M is just 6 minutes of revenue.

The cost problem is in the compute buildout and the subsidized compute to capture users.

> It remains to be seen if even using their models can be profitable,

I presume we can stipulate there exists some tasks that are cheaper to do using an LLM than doing it "by hand". As a such, using an LLM model can be profitable. To me, it is also obvious that the business of serving an LLM model can be profitable. There's large benefits to being able to get tokens quickly, and you can expect people to pay for that, even if we presume they could run the model locally with no maintenance overhead. There's even cases where using the cloud is cheaper than you can serve locally at all - I saw one guy that measured his added cost of electricity when his computer ran a specific LLM, and it was more expensive to run it locally than to buy tokens from the cheapest inference provider for the same model, presumably because they had better hardware and cheaper electricity.

I love a term a friend of mine used to use when talking about AI: "Narrowly superhuman" (before "superintelligence" got to be a thing).

AI is narrowly superhuman. It is able to do specific things that used to be defined as a "hallmark of intelligence" much better than a human. The easiest one? Summing numbers. It's both faster and more precise than a human.

AI gets more and more such areas it can do better than a human.

If we define "Superintelligent" to be "A computer system able to do absolutely everything we can somehow call intelligence better than any human", we will *never* have superintelligence. The things we define as intelligence will be in conflict; we'll land at the system being better at one at the cost of another.

I'm in favor with being careful about this development. But "prohibiting the development of superintelligence" isn't an option. It's already here.

Dividing the yearly US spend on Internet advertising by the number of people in the US that has Internet access gives $900-$970 spend per person per year, or $75-$81 per month.

Please choose the option you want:

1. I want to pay about $75 per month per member in my family into the ad auctions to not see any ads. Ie, keep the infrastructure, but let you opt to pay your share through money rather than attention.
2. I want to prohibit ads, and accept that everybody will have to pay for the sites they want access to, that there will be much fewer services, that there will be much higher transaction costs, and that the poor will have much less ability to access services. (Microtransactions won't solve this, due to the need for trust evaluation of same.)
3. I want some combination of 1 and 2, where some sides of ads are prohibited so it is possible to buy my way out of them at a lower price,. I accept that this will result in the loss of some services and lower access to others for the poor.
4. I want legislation that makes Internet ad blockers work more consistently. I accept that this just shifts the attention cost to other people, and have me getting the benefit without paying the cost.
5. I want to remove Internet ads and subsidize the sites through taxes.
6. I want to increase the requirements of Trust and Safety checks and format restrictions for ads, potentially accepting higher overhead (in what goes to content vs infrastructure) for less annoying/bad ads. I accept that doing this creates significant advantages of scale for ad networks.
7. Other, please describe, including where costs gets shifted with your proposal.

The above are my best attempt at listing possible options and their correct caveats. In most situations, I find ads annoying (who doesn't). Unfortunately, they are the main money highway of Internet content.

DISCLOSURE: I used to work for Google, where I rang infrastructure for stopping bad ads/advertisers and for removing fake clicks. I've also been interested at the use of sub-cent microtransactions to pay for content since the 1990s, though I've become disillusioned as I've learned more about the attention economics involved. Approving individual microtransactions has a higher attention cost than dealing with the ads, and bulking them per-site (through micro-subscriptions) will limit the number of sites that can have content.

OK, which particular aspect of the LLM learning do you think doesn't exist in the human brain? Backprop exists (and the other training methods the brain uses has similar effects), embeddings more or less exists and seems to be very similar to the LLM embeddings (shown by brain activation in various areas linearly matching with embeddings) - see e.g. High-level visual representations in the human brain are aligned with large language models (Adrien Doerig et al, 2025), and speech/text generation by humans has similar error patterns as for LLMs.

They obviously don't learn in the EXACT same way, but there's also clearly a lot of bits that are the same, and I'm fairly sure nobody knows how much is similar yet, particularly not weighted by importance.
 

Thus sure to cause dramatic and noticeable breakage for any parsers not having tabs correctly. What is "dramatic" about it? Is adding that "dramatic" an AI writing style or is it a subtle thing which I as a non-native English speaking person don't grasp?

> Every year since ï1966 when the country transitioned from pounds and shillings to decimal currency, the total value and number of notes in circulation increased.

> That all came crashing to a halt in the 2022-23 financial year, with a sharp decrease in $50 notes especially.

So every year for 57 years it went up, and this year it went down, and that is then immediately extrapolated to "they're going cashless, mark my words!".

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Time to pull out all your electrons from the exchanges!

We had one of these worldwide DECnet WAN infrastructures around 1996 or so. Bloody system came down every week with lots of meetings, RCAs, with everybody and their dog etc.

Then one week it didn't. And the next week neither. And nothing in the third week.

Then we were called into a meeting to explain why the DECnet trafic didn't go through their DECnet nodes anymore but all went through our Cisco routers, despite that they explicitly had told us not to do it.

> "I am not going on Twitter, I am going to stay on Truth. I hope Elon buys Twitter because he'll make improvements to it and he is a good man, but I am going to be staying on Truth."

He's going back, isn't he?

Cats always land on their feet, buttered bread always lands on the side with butter.

Is that true in a vacuum as well?

Is that true at lower gravities?

And does a cat/bread pendulum exist on these conditions?

"Do you want to know what Microsoft is doing to keep XXXX". No, get lost, it's a lock screen, not free real-estate to dump ads.

Software development is like the September that never ended: You keep getting new people every year who don't have the defensive part of programming in their mindset.

It will favour zealots in both directions, which should mostly even out assuming zealotry is roughly as common in both directions. Also, I don't know of any less zealot-based approach except forced participation - which seems worse.

Citizen conventions typically consists of randomly selected citizens. This one consists of 150 randomly selected citizens using a statistical procedure (sortition, a variant of stratified sampling) to make it represent the whole.