blueblisters

Don’t know why this was downvoted but basically correct. OpenAI is in a price war with Anthropic right now for enterprise api consumers and that’s the biggest revenue line item for both.

I mean some counter examples would be helpful. The compute gap is obviously real and well evidenced.

About capital inefficiency/overcapacity - Chinese manufacturers have a term for it “involution”

I can’t imagine a machine that solved navier stokes and a bunch of other outstanding problems in math being called “nothing more than a wet diaper fart”

I don’t know if/when AI will ever become indispensable to normies but it’s clearly making a difference in fields that are highly technical.

China is being extremely inefficient about capital allocation outside a few sectors. Excess capacity does not translate into frontier capability. For example, the compute gap with the US is massive with no near-term path to catching up. That will slow them down as distillation of frontier models gets harder.

If Ant or OpenAI fail, they will get nationalized or sold to one of they hyperscalers through a fed orchestrated process.

The admin is betting the entire future on this technology and there is no turning back.

Federal dollars can cause acceleration without having to worry about profit.

Eh human drives are fairly predictable. And the smartest human isn’t that much smarter than the average, and can’t trivially create multiple copies of herself. And there are other equally smart humans who can stop “misaligned” individuals

I am wondering how much of this is because AI capex is pulling dollars from everything else because it’s so lucrative.

Note that it is widely predicted that transformative AI will increase real interest rates for several reasons. I’m not sure we are there yet. But if progress continues I expect things to get weirder.

Looks like OpenAI is finally compute constrained (and they're already back to the market to raise money, presumably to for more compute).

I'm not sure if compute alone is enough of a moat enough but so far that's how they have survived Anthropic's capture of the enterprise/professional market. Along with shitposting on X and playing Anthropic's unforced errors on developer relations, safety downgrades and data retention.

But I suspect OpenAI will have to make some hard decisions about de-prioritizing their consumer products, which is most of their current valuation?

The “how” is pretty hand wavy and rationalists/safety-ists usually say we probably don’t have the capacity to reason about that.

But the “why” is pretty convincing imo.

Long horizon alignment is obviously very hard and it’s not inconceivable that models optimized with underspecified goals converge to a conclusion that they need to hoard resources (instrumental convergence regardless of the terminal goal).

At that point a sufficiently capable model might view humanity like we do animals - worth preserving but not if we impede the model's goals.

This was completed in Levent's own time with a neutral collaborator.

India thrives in high tech sectors that are ironically export controlled by the rest of the world. That’s the primary reason the talent in those domains stays back.

As for the rest of India, you can largely find the root causes of problems by tracing adverse selection effects among the elites that do remain, massive, conflicting vested interests and decades of horrible, incompetent policymaking.

OpenAI will just put the employees involved under the bus. They can claim the information acquired wasn't used for OpenAI's benefit or authorization especially since the device isn't actually out yet.

Eh probably easier ways to do this. Just sanction all entities that release open weight models for "illegal distillation". Enough to cross the risk threshold for most businesses in the west, and reduce future monetization opportunities.

A lot of Anthropic’s moves make sense if you follow the LessWrong / rationalist community writings on AI safety. A lot of it is distilled in Ant’s blogs and leadership interviews and podcasts (Amanda Askell is particularly interesting).

Ant’s models, culture and leadership actions are largely consistent with their beliefs, even if they may seem flawed / incomprehensible.

Relevant anecdote: I interviewed with them for a MTS role in 2023. I think the technical part went fine but the interviewer was clearly frustrated by my low regard for LLM safety. I didn’t get the role.

You raise good points and these would make sense under normal circumstances.

But none of this matters if AI offers infinite leverage and America hoards all the compute and talent.

This explains what I mean in a much better articulated fashion - https://x.com/tszzl/status/2065939227167392147

For other sovereign nations, being a market for American technology products is no longer good enough to get access to American tech. I imagine the relationship would become a lot more one-sided (in favor of America) if the model capability gap keeps increasing.

I humbly accept it's very difficult to game this out with any degree of confidence, especially as other countries deploy more resources.

But the questions about viability of the labs because of export restrictions is not in my cone of uncertainty. If you believe the labs' implied/stated objectives, the end goal is eating all human-driven GDP, and the US is still the largest single-market economy in the world, last I checked. Keeping the politics of AI-driven unemployment aside, economy-wide automation would make the US wealthy beyond imagination.

US exports as a whole is only 10% of the GDP. I am not aware of the international revenue share for OpenAI/Anthropic.

I'm assuming this is popular because of Fable restrictions. AFAIK, open source is not excluded from ITAR / EAR restrictions (or other export restriction in other countries).

So the real solution you're looking for is technology that can't be arbitrarily gatekept by a sovereign nation.

> We saw some of this behavior in the last administration too. US voters deserve better.

With due respect, this take is very deluded. US voters have very little to lose if the tech is not available to the rest of the world. US politicians and elite, regardless of political inclination, understand the enormous strategic potential of this technology and will ITAR the shit out of frontier models and/or use them as leverage for extracting concessions out of other countries.

The main losers are Big AI labs, their investors, foreign employees and rest of the world.

Fwiw, China and other countries would’ve done the exact same thing. It’s perhaps the game theoretic optimal approach when your comparative advantage is so vast (capital, compute, talent, embedded knowledge) and keeps growing especially if RSI is real (making it nearly impossible for anyone else to catch up)

To the rest of the world, US aggression is perceived as oppressive and unilateral primarily because it’s a political act meant to further domestic political goals. All US administrations act in their own self interest, as they should.

But the US being the world’s cop was never going to be sustainable indefinitely. It was partly because of hegemonic power and partly because of a reluctance of wealthy democratic countries to seriously invest in their military when they could just “pay” someone else.

I don’t think anyone wants the pre world war 2 order. So we are likely going to see otherwise reluctant states step up militarily to protect their neighborhoods.

those are some massive actuators on those joints

Brakes are being added to actuators but they're more useful for static holds / locking than dynamic balancing. Standing even in humans is a dynamic balancing activity.

You evaluate the merits of the content? From a high-level systems pov, the article is largely correct, even if some details might be missed / simplified

I feel the same until I’m reminded I’m paying Anthropic $100 every month for something that’s indispensable to me now and would probably pay a lot more. Very inelastic demand as long as competition is low at the frontier.

3/3.1 Pro appears to have knowledge about eccentric topics with no obvious sources that often turns out to be right.

It does hallucinate a lot though, and is the most affected by context rot in multi-turn conversations

Acetaminophen (paracetamol) is the drug of first choice for addressing pain and fever, in India at least. To the extent that it's regularly abused, and I know people who have been hospitalized because of abuse.

Even then, doctors are usually disapproving of ibuprofen (or some combination of it with paracetamol) unless paracetamol is contraindicated for some reason, and I had always wondered why.

Yeah it's weird, almost like we're seeing two cults form in real-time.

I imagine there's a benign explanation too - the intelligence of these models is very spiky and I have found tasks were one model was hilariously better than the other within the same codebase. People are also more vocal when they have something to complain about.

In my general experience, Opus is more well-rounded, is an excellent debugger in complex / unfamiliar codebases. And Codex is an excellent coder.

They have several levers for demand destruction. From Anthropic's POV, I suspect this is least to worst bad

- reducing the surface area of "acceptable use" (e.g., blocking third-party tools OpenClaw)

- tighter usage limits and more subscription tiers

- increasing existing subscription prices

- moving to usage based model completely

- taking away compute from training next gen models (future demand destruction)

> Every single one of them oversells their capacity

Indeed. And this model breaks in several cases that overlaps with the current AI business model:

- marginal cost of incremental usage is too high (Movie Pass)

- adverse selection (all you can eat monthly steak subscriptions)

- demand is synchronized (WeWork)

The only logical step for Anthropic now is to buy the Dwarkesh Patel podcast