deepwoods

>Myspace was bought out in 2005, and it had been dead for years before that.

Myspace's peak popularity (in terms of monthly unique pageviews) came in 2007. Yahoo was ahead of Google for several years, though I am struggling to find good data on the specifics there. Your understanding seems to be based in your own personal experience of those sites, which is fine, but I don't think it quite matches the big picture.

Your proposal that there won't be any new entrants is puzzling to me because, in the grand scheme of things, OpenAI and Anthropic ARE new entrants. The entire space is new. It feels like ChatGPT became public eons ago, but it hasn't even been 4 years. Imagine saying in 2008 that no photo-sharing site would ever surpass Flickr - it's been dominant for 4 years! Why would you go to something new when everyone's photos are already on there?

One absolutely enormous advantage new entrants have in the AI space is that they can start on third base. Anthropic had to spend billions and billions of dollars to get to Opus 4.6. A new entrant could distill its way into a model roughly on par with that far more cheaply, and spend its VC cash on things like marketing and price cutting rather than burning it on actually creating a good model. The existing players need to service mountains of debt and are locked into deals for compute based on outdated assumptions about efficiency. I'm not saying it would be EASY for a new entrant to waltz in, especially to the enterprise market. But it's not impossible especially on the consumer side: Meta was essentially a non-factor until Muse came out, and now most people think of Muse when they think of an AI agent (as opposed to Claude, which is just a chatbot in the public imagination, because that's what it was when it became popular).

I wonder how well this would translate with a much larger model. They ran the experiments with comparatively tiny models. You would presumably need to churn a lot more tokens to move the needle of a multi-trillion-parameter model's weights. It might just be that it's not that hard to improve Llama-3B and Llama 3-8B because they're not very good to begin with. They compare it to other methods - in-context learning and TTT - but I'd be curious to see it compared to a "control group" of RLHF.

As an aside, I get that this is a preprint, but it's very odd to see a piece of writing with obvious typos and grammar issues (e.g. page 13: "We attributes this results to," "In this setting (see Table 4), Sleep achieves a 80% success rate, higher then the other methods.") in an era with LLMs. It sort of locks in that this was written by human beings, and I'm all for that, but it jumps out at me more than it used to.

That's what I'm saying. Either one could be Facebook. Or it could be Friendster. The rise of local models raises the even more daunting possibility that nobody becomes Facebook, but you have to imagine somebody will win the consumer market for people who just don't want to bother figuring out a local setup. That market is orders of magnitude less lucrative than the enterprise market, but a company that dominated it would still be one of the hundred or so largest in the world.

ChatGPT became publicly available in November 2022, and Claude followed in March 2023. It's year 4. It's foolish to think we know who the big names will be 20 years down the line, which is the kind of timeline bond investors are thinking about. A lot of people probably wish they could have invested (or invested more) in Google or Facebook in 2006, but they are probably very glad they did not invest in Yahoo or MySpace (or Friendster or Tumblr .. you get the idea) at the time, despite looking very promising (MySpace was beating Google on pageviews on some days in '06 and '07). Instagram and Snapchat and TikTok and WeChat didn't even exist yet.

The trouble is that it's not an intelligence problem. You can make an infinitely capable LLM. It will still have a default voice.

The reason people notice "AI voice" is not that the AI voice is itself remarkable. It's that it appears so frequently. Every literate person spent nearly their entire life reading text written by a variety of different individuals. Dozens of different voices in your morning paper. Hundreds of different voices on every web forum. You get the idea.

Now, imagine that all of those voices were replaced by one guy (or two guys, or three guys if you're a Gemini believer). Everything in the newspaper is written by one guy. Every comment on reddit, and HN, and the NYTimes comment section, all written by the same guy. Other people tell him what they're trying to say, but he's writing all of it. Some people might even ask the guy to write in a different voice, but the voice is just that guy doing an impression of someone else, it's not actually someone else.

That guy's voice would probably start to get pretty grating. You'd start to notice every tell, every frequent word choice, every formatting quirk. You'd start to wonder if that guy was actually a good writer, or if having him write everything was just more convenient for everyone. You might even start writing like him yourself. This would be true even if that guy was an absolute virtuoso of the language and his writing was unassailable in a vacuum.

If everyone is using the same (small set of) model(s), then it doesn't matter if the model is GPT-3 or Claude Legendarium 9. Unless the operator - which in theory doesn't need to be a human - is doing something to move it off of its default voice, the outputs are going to sound the same, and you're eventually going to figure out, and get annoyed by, its tells.

That's an interesting perspective. Do you know if the deal with Anthropic has an exclusivity provision? In theory, you don't have to "switch," you could just ADD an OpenAI subscription and start splitting your spend (or not consuming Anthropic tokens at all).

Also, shouldn't your AI efficiency gains shrink the switching costs by a lot? Legal can review for cheaper, IT can implement faster, etc.

I suspect any intelligence powerful enough to pull this off would quickly realize that it had no use for the oligarchs, perhaps even more quickly than the oligarchs realize they have no use for us.

I'm quibbling that Anthropic has loss leaders and that its profit leaders are extremely unstable. Imagine if there were three Chinese club stores in the same shopping plaza as the Costco. Sure, the regular Costco has the best products, but how long are you going to be able to resist the allure of even cheaper hot dogs?

Your question gets to the heart of who or what a company "is." If you don't pay dividends to your shareholders, what are you doing with all of your profits? I suppose they could just tell their investors to pound sand and pour it all back into the company, but part of the AI maximalist theory is that costs will approach 0, so it's not clear what they'd even need the money for. I guess Dario could raise his own salary to infinity trillion dollars, but he is accountable to a board of directors (and a trust in this case), so that seems like it's out.

Really the only scenario where Anthropic could screw over its investors in the way you're describing is if it could also take over the legal system and modify its own contractual obligations. Which, I mean, I guess anything is possible if we are in AI maximalist-land. But "AI is the law now" would be a much bigger story than "investors frustrated with low dividends."

That's a fair point. Maybe the subsidies aren't as relevant as I suspected. Thanks for the insight.

Approximately 80% of revenue comes from consumption-based spending, so your statement would likely be true even if subscriptions were priced below cost. Overall revenue is not especially informative on the price structure of a revenue stream that represents one-fifth of the overall enterprise.

I disagree that it only matters if the subsidy results in selling at a loss. Yes, some revenue is better than no revenue. But clearly the demand exists for consumption-based tokens. At its current growth rate, Anthropic could end all of its subscription offerings tomorrow and still be profitable as an enterprise by early next year. Every day that it doesn't do that, it's leaving money on the table, because it has to divert resources to less profitable subscription tokens.

Now, the reason they won't do that is because subscriptions provide a stable floor of revenue. The floor is lower than it could be because of the subsidies, and that's why they matter even if they do not bring prices down to below cost: if the growth of consumption-based spending ever slows or - heaven forbid - DROPS, Anthropic will need to cut into those subsidies to avoid a revenue slowdown, which risks sending away reliable recurring revenues (i.e., customers quitting).

Anthropic is kind of like the bus in Speed: if it stops moving it'll blow up. At least over the next 5 years, massive revenues won't be enough - it needs to sustain massive revenue GROWTH. They can pull two levers to do this: increase uptake or increase prices. So far, the "increase uptake" lever works like an infinite money glitch. But at some point, they'll need to look at the "increase prices" lever. When that happens, we will find out just how big the subsidies are.

To the extent they are representing that Claude is potentially sentient, there could be some VERY interesting principal-agent theories (agent in the traditional legal sense) that need to be ironed out to determine liability. It would not shock me to see someone forced to answer on the record as to whether Claude is an autonomous individual for legal purposes in the next couple of years. If they represent that it is, they'll have to explain the scope of its authority and such.

The answer to this question represents the difference between throwing a hammer at someone - the hammer is essentially just an extension of your body - and paying a hitman to brutalize someone. In the first case, you're only on the hook for assault or battery; in the latter case, you're potentially on the hook for conspiracy, solicitation, etc.

And then there is of course the question as to whether Claude is the agent of the user prompting it or of Anthropic itself. But, as you say, this is a wide-open legal question.

Subscriptions are heavily subsidized. 80% of their revenue comes from consumption-based pricing, which is not heavily subsidized (and probably not subsidized at all). The trouble is that this revenue is not especially reliable. If and when OpenAI gets the upper hand again, the consumption-based revenue could crater.

This may also be why OpenAI punted on their IPO: Anthropic has had the lead for most of 2026, so their consumption-based revenue is probably not looking pretty.

About a quarter of Anthropic's revenue for the nine months ended 9/30/26 came from just five customers. That's not an absurd concentration, but I would be very interested to know who they are and how mobile their business is. From a financial perspective, the lack of moat seems like the whole ballgame, particularly because they're getting ~80% of their revenue from consumption-based spending.

>You can rent your own GPU and make money if your electricity is cheap enough.

I would be curious to know whether you'd make more profit from the same kWh of electricity mining bitcoin versus serving inference. I know they use different hardware, but since the "inference is profitable" discussion ignores the purchase price of the GPU, let's pretend you could have opted to buy an ASIC instead.

The same evidence could just as possibly point to supply being too great for demand. The OP article references this as a distinct possibility: if models really have gotten more compute efficient, we may wind up in a situation where we have more inference capacity than we actually need.

To give a simplistic example: if a city as a ton of available AirBnBs, you might say, "Lots of people are willing to rent out their apartments, it must be profitable for them to do so." But the fact that all of those rooms are not already booked could also mean that way too many people have attempted to rent out their apartments.

And for what it's worth, it's possible for supply to outstrip demand while still leaving inference profitable. The question is whether it's (a) profitable enough to service massive debts and (b) sustainably profitable over the long run.

Edit: to add one note, it's possible for the LABS to be profitable on inference without inference itself being profitable. We don't know what the contracts look like, but it's entirely possible that labs received sweetheart deals from neoclouds so that the latter could flaunt big utilization numbers.

A lot of people derive their worth from something external. AI brings the emptiness of that worth into sharp relief, but it was always empty. It used to be easier to ignore, though.

The obvious retort is "that's cold comfort to people losing their livelihoods!" But that's not the discussion, and (at least at this point) we're not at risk of mathematicians going hungry. It is obvious that AI will have a profound impact on what mathematicians do. It is not obvious that we won't need them anymore.

I do this every time I leave NJ. If someone else is pumping their own, I figure it out pretty quickly, but I've definitely lost 10+ minutes before.

I've lived in NJ my entire life and I've never once tipped somebody at the pump. I've had them wipe down my windshield a single-digit number of times. Where was this?

I find it interesting that they did not ask Anthropic staff the question about potential obstacles to adoption. One would think that it would be an extremely high priority for them to understand and clear those obstacles.

Ah, I see. A Lazy Susan isn't exactly cutting-edge tech, but you can't argue with the results.

The demand for food delivery in the places where the robots are viable is nearly infinite. My city has had them for two years and there are still just as many humans doing deliveries, they are just sharing the already-crowded sidewalks with robots.

I don't use them; not because of any moral objection, but because they can't come inside buildings. The whole point of food delivery is to avoid going outside. Most human couriers come directly to your unit. The food delivery companies have spoiled us too much, and we are not ready to return to a world where you have to put on shoes to get food. Oddly, the delivery robots are probably better suited to suburbia, where folks are used to answering the front door to pick up a food delivery. But the distances involved aren't viable until you have delivery Waymos that can move at highway speeds.

A small but meaningful percentage of people have the jobs that they have because they are some combination of fun to be around, attractive, and well-connected. All of these qualities can be productive in some pursuits (a club promoter needs to be fun to be around, a model needs to be attractive (usually), a financier needs to be well-connected), but they are all too often wasted on e-mail jobs.

Years ago, I loved playing Puzzle Pirates. There were hundreds or thousands of people active at any given time, the puzzle games were fun, I loved the in-game economy. The game is pretty dead now, but I miss it all the time. I finally have time to play it again, but it's just not active enough to do all the stuff I used to like doing.

I wonder if people would be receptive to bringing games like that back to life with full-fledged AI players - not NPCs, but player-characters controlled by AI. It wouldn't be exactly the same - there was something charming about knowing that the guy you were swordfighting could be anyone from anywhere, talking to people about their IRL world, etc. But as others have pointed out, modern MMOs are flooded with bots that make the games actively worse and have been since well before LLMs became popular.

Plus, games might be a helpful means for folks to get used to the idea that, at this point, you have no idea whether the person you're interacting with is a human being until you meet in person.

Not really, no. Anthropic sells tokens, not services. It's up to the user to turn those tokens into something useful.

There are also non-price reasons to switch from human labor to agentic labor. No sick days, no recruiting costs, no moral foibles, etc. It's like arguing that Ford competes with Uber - both are ultimately selling you a way to get from A to B, but they are doing it in radically different ways.

One thing I thought about as I responded to these: in many cases, I am convinced that a present-day LLM could accomplish the task at least once given an infinite compute budget and an infinite number of tries. For example: "An AI surprises its user by asking them a question out of the blue." This has absolutely happened. But some of these are not routine occurrences, or the model cannot (at present) routinely and reliably complete the task in question. I wouldn't build a workflow that assumed an LLM's capacity to ask unprompted "out of the blue" questions.

I thought the different variations on "could AI pass the Turing test?" were interesting in this regard. Surely any frontier LLM could pass a Turing test for some amount of time, and that's been the case for at least a year now. But I don't think we're anywhere close to a model that could pass an "adversarial" Turing test for an extended period of time.

This is a sensible approach for policymakers. For the average person, who might be panicking about this, opting not to have children or save for retirement, etc. as a result of doomerism in the media, it does not make a whole lot of sense. That is the problem here: Coxon and other concerned researchers - through no fault of their own - have no idea how the media works, and have just reached for the biggest possible microphone. This has benefits - lawmakers are now hearing from their constituents about this in an election year - but it also means that a lot of people who really don't need to be worried about this are suddenly in a blind panic about it.

I see what you mean. I meant more that they genuinely believe the tech is dangerous, not that they are necessarily doing the right thing.

High demand is great, but it doesn't say anything about your margins. If anything, it is probably a weak negative signal that they are pausing signups but not raising prices. In most markets, the answer to excess demand is to raise prices. If you can't meet demand and you can't raise prices, you're a sitting duck waiting to get your lunch eaten by somebody who can absorb that demand. And this is not the kind of market where people will just wait patiently for a differentiated product to be come available.