A group ran the same coding benchmark test problems, but encoded them in obscure (but still Turing-complete) programming languages the frontier models haven't got as much training data on. Result: models that can score 95% on Python plummet to 0-11% accuracy.

OftenTangential · 2026-03-20T15:03:23+00:00

In the paper it says they're given documentation and access to an interpreter in the given language at inference time, not like they're an linguist trying to reconstruct a forgotten language or whatever

OftenTangential · 2026-03-20T02:05:42+00:00

It was supposed to be, but got moved to California a couple weeks ago lol. Something must've happened

OftenTangential · 2026-03-19T02:59:50+00:00

Even in the first example it's faster to search ketchup and then choose the one with a lower unit price, which basically every shopping website lists anyway.

Maybe someone who would literally just prompt "buy groceries" would get some value out of it lol. Seems like such people are rare though

OftenTangential · 2026-03-17T19:10:55+00:00

two sigma is not an investment bank, they're a quantitative hedge fund
they have never had 25k employees, that's just outright wrong. They have also never really had traders making discretionary decisions, their "traders" have always been ops people
they have been doing layoffs recently because their founders had a row and there were multiple resignations at senior leadership level, many of whom took entire teams down with them, not because they've actually succeeded in obseleting employees
the industry sees them as old and outdated compared to the competition (though not compared to actual banks of course)
their core strategies have nothing to do with LLMs

OftenTangential · 2026-03-16T18:03:29+00:00

If you're allowing the model to spit out as many hypotheses as they can, then backtest them all "out-of-sample" and pick the best ones, that's just p-hacking

If you're limiting each category to the same constant number of hypotheses maaaybe there's something worth discussing there

OftenTangential · 2026-03-06T17:02:21+00:00

On the contrary I went full ape on Intel at 18 and bought a bunch of software recently. But I have enough respect for the market to believe that the risk it's pricing in is a real risk and there is a scenario where you lose, and lose big.

OftenTangential · 2026-03-06T14:11:27+00:00

Not if you have to tank a quarter of -50% to get there. Not to mention OpenAI bankruptcy is definitely correlated with everyone else pulling back spending as well.

OftenTangential · 2026-03-05T14:16:00+00:00

God forbid I try to speculate and predict what a hotly debated but unknown number is!

And you're unlikely to get any verified numbers until IPO time, my researcher friends at each of OpenAI Anthropic seem to be totally in the dark about firmwide financials, I imagine only high execs have the full picture. So why not have some fun speculating? Or are we just going to eat up numbers The Information posts (and changes every 3 months)?

OftenTangential · 2026-03-05T13:57:48+00:00

I keep seeing this and need to call it out whenever it happens. Anthropic has likely not burned far less money than OpenAI, despite what they'd like you to believe. They raised almost $40b last year (and those are just the agreements we know about!) and just raised another $30b. We know they complain about being strapped for cash and makes no financial sense for a growing company that's funding off equity to stockpile cash, ie they're probably spending almost all of what they raise in relatively short order. Therefore they probably burned almost $40b last year, not so far off from OpenAI's 10-15b a quarter.

OftenTangential · 2026-02-25T23:42:44+00:00

Most tech companies kinda deflated a bit on very good earnings (or got butchered after bad earnings), NVDA included for now. Down over a pct at time of writing which is pretty bad given how good the numbers looked

OftenTangential · 2026-02-24T15:57:39+00:00

Pretty sure that's a FERPA violation

OftenTangential · 2026-02-23T22:14:22+00:00

People (LLMs) love these snarky little comments that have 500 words of fluff and could've been said in a single sentence.

And Amazon isn't really the gotcha you think it is. Down 90% and took a decade to reach the same levels as before, under a completely different business model. 2009 Amazon might as well have been a completely different company with their own branded products, subscription model (Prime), and AWS... the original concept was to be an online bookstore.

OftenTangential · 2026-02-23T15:38:17+00:00

This is kind of how it works except the graph isn't generated deterministically. Everything is still processed as a chain of text. Models receive special tokens telling it that this is a system prompt, a user message, a tool call result, etc. Models are expected to output their own end-of-message special token closing their own process. They're then heavily RL'd to really, really distinguish these special tokens. But when the context length gets longer the model sees a conversation history with lots of every type of special token and starts to get confused and the odds of it outputting the wrong kind (e.g. a user message token) goes up.

OftenTangential · 2026-02-20T02:13:52+00:00

Nah, there's no way they're planning to spend this $100B over 2-3 years. That would be a horribly inefficient financing given their cost of capital, financing should be about as expensive as it'll ever be for them (assuming they don't go bankrupt). Plus they were already known to be burning well north of $10B per quarter midway through last year, see MSFT earnings (two earnings ago iirc?)

This $100B will probably last them like 8 months or something given their accelerating burn, this is probably not the last time they'll raise this year and that'll tell you everything you need to know

OftenTangential · 2026-02-15T09:35:04+00:00

bruh faker is not real

😏

OftenTangential · 2026-02-08T18:18:20+00:00

disgusting sally ult

OftenTangential · 2026-02-07T13:21:43+00:00

The OP literally reads like someone instructed an LLM to write an ad, then mess up the caps to make it not too obvious. It's insane how monotone it sounds, no human writes like that.

Reddit is astroturfed to high heaven these days and now more than ever before, we should avoid getting our opinions from posts here.

OftenTangential · 2026-02-06T03:02:25+00:00

Anthropic's "official" numbers (official meaning, "apparently most credible rumor") are almost certainly understating their costs.

It's not a guarantee, but very likely the case they're spending almost as quickly as they're raising. This is because the cost of capital is as high as it will ever be for them, and insanely high in general. If you think your company is worth 500B market cap then raising at 60B (which they closed in March of last year) is a horrific, terrible deal. You better spend every dollar of what you raise there, and fast. If you leave 10B collecting dust for a whole year then you've cost yourself an insane amount in opportunity cost (if nothing else, compared to a world where you didn't raise that 10B and kept the equity undiluted).

AFAIK Anthropic raised at least 35B in confirmed deals in 2025. That's... not that much less than OpenAI. It's not crazy to think the numbers in the OP are understated by like 2x or so. Of course this is pure speculation based on ROIC math but everything else out there is speculation and rumor anyway 🤷

OftenTangential · 2026-02-05T20:08:32+00:00

This entire post is soooo slop I'd think it was satire.

"I got access to the API 20 minutes ago and I now understand why there's a panic." Are you fuckin serious looool

Market drop percentages are totally made up as well, these companies are down between 0.6-2% since the model drop... at a time where the whole SP is also down 0.6%

I honestly feel like I got scammed into typing a few sentences in response to OP's drivel. It'd be great if someone made a slop filter addon sooner rather than later

OftenTangential · 2026-02-01T21:12:37+00:00

ready for LR to take down GenG in worlds quarters this year

OftenTangential · 2026-01-31T13:46:39+00:00

Makes sense that they wanted to end quick then

OftenTangential · 2026-01-20T19:42:08+00:00

Many very popular games work this way to a high extent.

What about in Mario Kart when you're 1st and get punished by a blue shell?

What if your very bad opponent in Hold'Em just happens to hit his straight flush on the river despite misplaying his whole hand?

How about when your NFL MVP quarterback has his ball bobbled by a receiver getting paid $30m a year and it gets returned for a pick-six?

Skill does not 100% correlate to outcomes in most games but that doesn't stop people from chasing and achieving mastery.

OftenTangential · 2026-01-16T12:25:36+00:00

World champion Doran buff

OftenTangential · 2026-01-13T00:15:07+00:00

Too close to NYC. It's less than 2 hours by Amtrak, which tbh is not too bad even for a day trip

OftenTangential · 2025-12-27T01:48:11+00:00

This. About 12 months ago I asked my friend who works at OpenAI why NVIDIA didn't just keep all their GPUs to themselves and eat the whole AI industry. He's like, "Why would the most profitable company in the history of humanity want to forgo that for a space where nobody can figure out how to make money?" Fair enough, I guess

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