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.
 

Some may not recognize the Brazil reference.

No need to be antagonistic. Respond with inflation adjusted BLS salary average and percentile for the job and region.

https://www.bls.gov/oes/curren...

Itâ(TM)s unclear what happens when one aspect of their system changes unless other parts also change. The bags flying free was designed to make boarding more efficient, which reduces gate time. If bag check is not free, then itâ(TM)ll mean more people bringing their bags on plane. This means boarding will be more complex and time consuming. Itâ(TM)s not clear their âoefirst come first chooseâ seat process will work as well, as people trying to backtrack, or holding up the entire boarding process.

I get that AI is costly, hard to run on the average desktop, and hence APIs. However, it seems we've shifted as a community to fully supporting proprietary web APIs where we not only don't have source code but even lack the binaries. Couldn't slashdot moderators help by promoting truly open source tools, especially AI, that can be run locally, even if it requires a 10k hardware? It seems very reasonable if a company sells API as cost-sharing model. Even so, at least we could support entities that fully open their models and have active "hacker" communities that are not bound to a proprietary service.

Presuming they used DNA to find the suspect, located with some statistical certainty (say one in a million). I'm wondering then if that person's DNA match was the presented as proof, eg "one in a million this isn't the killer"? If so, isn't this a form of double dipping? If you "used up" the one in a million chance to find the suspect, can you use the statistics dice again to claim that this suspect is also the killer?

The existing practice of human car drivers in this situation is to slowly inch though the crowd. Amend the regulations to reflect practice, then update wamo to behave according to the regulations.

> Have been screen sharing with Zoom and MS Teams for at least two years...

You mean other tabs within Chrome only? Or actual windows/screens from other applications?

I worked at Huawei sales until the end of the last decade. We used a hodgepodge of different systems running on Oracle SAP and Salesforce masked as "eQuote" etc. It was a fucking nightmare...

Nowadays I'm working as sales in a large US IT company and we use Salesforce along with dozens of excel sheets and some legacy systems.

We get fired for political reasons, rarely for lack of (team) performance...

Generally, countries don't consider even offensive cyber operations to be acts of war. Every country has said they reserve the right to change their mind, but countries like Russia with their own cyberops capability don't really want to push that button -- they've definitely been relying on cyberops not being seen as acts of war, and it's in their interests to keep that status quo.

At some point, some offensive op will go too far and some major power will see it as an act of war. That's going to be a huge event when it happens. I doubt it will happen in this conflict.

fringe sites like 4chan, far-right social networks like Gettr and Rumble and mainstream social media sites

They called out all of two right-wing sites, and they're both well-known places where extremists gather and communicate -- at the moment, there isn't any good example of a large-scale far-left forum (at the moment, it's much more fragmented than the far-right); 4-chan isn't right-wing (it does have a lot of right-wing activity, but it's definitely got lots of left-wing/far-left communities and content), and neither are the mainstream social media sites.

Seems to me like the plan is to monitor social media including fringe sites to look for early indicators of activity to disrupt an election; it's certainly not "only conservatives".