Hacker News Reader

Yes, agree that token consumption will increase exponentially for the next while.

Disagree that the frontier model is where the economic gains will be realized.

The smaller the relative gap between frontier and non-frontier/open weights, the less pricing power.

This gap has shown only to shrink over time, not expand.

Businesses will pay more for frontier, but not meaningfully more to justify the economics. It's always going to be a low margin business, perhaps outside of cyber security, warfare/intelligence and perhaps drug discovery.

Though the expensive and time consuming part of drugs is doing the trials and getting approval, not coming up with ideas

how much would you pay for a prompt that could cure cancer? if you're a pharma company you would pay millions to get there days faster than your competitor. as intelligence rises the marginal value it can deliver rises with it.

Something like curing cancer (more realistically, curing a specific kind of cancer) has to interact with much slower real-world processes. The most expensive part of drug development is Phase 3 clinical trials in humans. Even the smartest model in the world can't accelerate that meaningfully. Even much earlier when drugs are just testing in cell cultures, it's a lot slower to run lab tests than to run software tests or mathematical proof checkers.

Or to put it another way, there's enough natural variation in real-world bottlenecks that no pharma company can assume they'll beat competitors to market by using a smarter model.

A really smart model could significantly improve the pharma business if it could identify promising approaches to cancer treatment that are less likely to fail in clinical trials, but I don't think that the frontier labs have data to make that work yet. Much of the biomedical literature is poorly reproducible ("replication crisis") and much of the drug-development-specific data is proprietary, never published in the first place.

I do have hopes that general laboratory automation will go faster with LLM assistance, even if all the LLM does is write Python glue scripts to enable custom workflows and instrument integrations.

Sounds kind of like another K shaped economy. Low end models will be highly competitive and low profit. Problems that can be solved by low end models will be highly competitive and low profit too.

Where the interesting work will be is at the median point where cheap models do almost all of it but need to hand off some parts to the SOTA/more expensive models. Seems like there's money to be made by maximizing low end use while maintaining quality.

Certainly there's still a business there, I'm not saying they won't exist. But it's not going to be a monopoly-esque business with so many players in the ring, OpenAI, Anthropic, Google, Meta, Deepseek, Alibaba, GLM, Kimi etc. It will be cutthroat and a race to the bottom on price. And the difference from today -> 6 months ago intelligence will not be very meaningful.

Investors are largely treating these as future monopolies though.

We can already do so much with existing models. Harness improvements are probably more meaningful at this point.

e.g. say most image recognition can get saturated by a model of size xB parameters, so your tool for that can handoff to a smaller model. Document text extraction can use a model of size yB parameters. A model of size zB for summarizing text.

We are starting to get to a point where you can reasonably scope out an upper bound of required size/effort for many common tasks, and if you string these together, the frontier will largely act as an intelligent invoker of more efficient models.

Up until now there have been meaningful gains to each of those types of workstreams by using newer models, but that is starting to no longer be the case.

Yes, I do believe token consumption will rise exponentially from here in the near term. But cost of switching is low, and substantial profitability will be difficult.

yea you see no body are vibecoding games before opus 5 and astra, after they are released games basically got commoditized

If the output is commoditized, how much can you afford to pay for the input?

Is this sarcasm? I assume most studios are integrating AI into their workflows, but I still haven't seen a single vibecoded game that looks interesting.

I was yelled at repeatedly here that AI is not used in gaming.

> daily cancer scans instead of one every few years

Silly nitpick: the reason we don’t do daily cancer scans isn’t the cost, it’s the false positive rate. Invasive procedures like biopsies come with complications like infections that happen at a higher rate and do more damage than the cancer that doesn’t even exist. This dilemma is pervasive in medicine, because our tests aren’t perfect but the thing they’re testing for is rare.

The whole paradigm changes, though, when you can do daily cancer scans. You don't get a biopsy when the scan shows a lump. You get a biopsy after a couple weeks of daily scans showing the lump growing. Plus, having all the data from the daily scans improves your testing accuracy so false positives and negatives are more rare.

The errors are correlated, not random. Lumps are usually benign cysts. If you start cutting people open for every cyst on a scan, you’d kill a lot more people than you’d save.

This isn’t something you can solve with more scans because the tests test for data that is indistinguishable. They look the same on a scan, there’s an overlap in the assay with some random protein with the same binding sites that is only present in 1% of the population, the coding gene in one person gets repeated in a noncoding region in another, and so on. The “more data” that works is a doctor applying professional judgement (which they’re also famously bad at because biology is a fickle mistress).

More data (daily scans) can mean we get better at medicine, though, and more accurate. You're assuming "daily cancer scans" look just like they do today, rather than eg unobtrusive devices in our daily lives that measure changes over time.

The frequent "muh false positives" comment we hear from doctors appears to be a lack of imagination?

It comes from experience.

If you're doing non-redundant tests and your uncertainty bars aren't shrinking, it's usually a skill issue.

If it looks like a duck, it might be a duck - or a painting of one. If it looks like a duck, swims like a duck, and quacks like a duck? The joint duck estimation is much more confident now. There might be a few more observational tests one should administer before committing to a duckhood decision, but each tests pins down variables and rejects confounders. Uncertainties are cut down, and we get closer to crossing the threshold between "duck-informative" and "duck-actionable".

Thus, it's often worth it to improve observability. If you managed to make a certain test more reliable, or cheaper to administer, or reduced the chance of adverse effects? Or, in other words, improved SNR, reduced costs, and reduced costs? You can get more information for your buck. Paired with good knowledge: you can make better decisions more easily.

The fact that the thought of "having more information might be bad actually" even occurs in the field of medicine shows just how far it is from being optimal. Having more information isn't always beneficial - some information is genuinely redundant. Some information is not worth the effort of gathering and integrating it. But if you get more information and it results in worse outcomes? You're doing something wrong.

Wouldn't daily cancer scans give you cancer from all the radiation? I thought that's why the doc hides behind a wall when giving an X-ray.