Bootstrap is immortal

Sure, but it’ll be orders of magnitude cheaper in a few years. The consumer industry is already moving in this direction, with Apple leading the pack

The moat is money. And now they’ll have access to plenty of it.

The endgame is to game the index funds by bribing or otherwise.. convincing the big stock exchanges to forgo their index inclusion rules so SpaceX will get included in Nasdaq 100 within 10 days or something stupid like that. SpaceX will initially float a tiny fraction of shares at a wildly inflated value and use a combination of artificial scarcity and Elon Stans (retail) to keep the stock from crashing until it gets included in the indexes. Then, your 401k will auto-buy SpaceX, letting insiders exit at their ludicrous valuation.

Eventually, stock prices will correct hard, and retail/passive investors will be left with the bag.

The idea that merging these companies has some business purpose is hilarious. It’s purely financial engineering. Unfortunately, our existing system has little consumer protection against this kind of fraud, so Elon will probably get away with it, at least in the short term

> endgame is to game the index funds

Buying Cursor does nothing for this.

It gives them some amount of paying customer base using AI. That is some magic voodoo you need to sprinkle onto the public sale to get the highest possible price point.

X doesnt yet have a paying customer base using AI?

lol what? That’s ridiculous.

Name one conflict we’ve been in since WW2 that protected the “American way of life”

Maybe if you put your data in Atlassian the you failed to adequately protect your trade secret? IIRC you need to make a reasonable effort to protect the secret.

Establishing MNDAs is considered reasonable effort and this is a policy update that basically says "we are ignoring all MNDAs".

I doubt that’s the case. My guess is we’ll hit asymptomatic returns from transformers, but price-to-train will fall at moore’s law.

So over time older models will be less valuable, but new models will only be slightly better. Frontier players, therefore, are in a losing business. They need to charge high margins to recoup their high training costs. But latecomers can simply train for a fraction of the cost.

Since performance is asymptomatic, eventually the first-mover advantage is entirely negligible and LLMs become simple commodity.

The only moat I can see is data, but distillation proves that this is easy to subvert.

There will probably be a window though where insiders get very wealthy by offloading onto retail investors, who will be left with the bag.

>I doubt that’s the case. My guess is we’ll hit asymptomatic returns from transformers, but price-to-train will fall at moore’s law.

There hasn't been a real Moore's law for a good while even before LLMs.

And memory isn't getting less expensive either...

It’s considered national security concern by this administration. Will the next be a clown show like this one? Unclear

The administration doesn't decide spending. Congress does. There's no chance we get an anti-AI majority until a major AI catastrophe turns the public against it.

I just don’t see how they’ll be able to make a profit. Open models have the same performance on coding tasks now. The incentives are all wrong. Why pay more for a model that’s no better and also isn’t open? It’s nonsense

I wouldn't say the same but it's pretty close. At this point I'm convinced that they'll continue running the marketing machine and people due to FOMO will keep hopping onto whatever model anthropic releases.

Which open model has the same performance as Opus 4.7?

They dont have to be parity today.

If the frontier models reach a point of barely any noticeable improvements the trade off changes.

You do not need a perfect substitute if you are getting it for free...

People will factor in future expectations about the development of open source vs frontier models. Why do you think OAI and anthropic are pushing hard on marketing? its for this reason. They want to get contractual commitments that firms have to honour whilst open source closes the gap.

The person they were responding to said "Open models have the same performance on coding tasks now." AFAIK this is bullshit, but I'd love to be corrected if I'm wrong.

Open models, in actual practice, don't match up to even one or two generation prior models from Anthropic/OpenAI/Google. They've clearly been trained on the benchmarks. Entirely possible it was by mistake, but it's definitely happening.

GLM 5.1 is absolutely on par with Sonnet 4.5, sometimes better in practice (it holds abstractions over longer context windows better)

It’s about the only one that is at that level though to be fair. They’re all still useful, still!

That hasn’t been my experience. For coding at least I find little difference between closed and open models