adam_arthur

aka waited for cost of storage, bandwidth, compute to come down below revenue from advertising.

As it would have done naturally anyway

You can now start to add automations on top of typical dev flows.

There are a ton of use cases that open up with cheaper models.

E.g. extensive security scanning on every PR, quality scans, adversarial reviews etc

Surprised by these takes.

Are people not getting that this (Jev) can do classification, programmatic branching, real time decision making (e.g. applicable to robotics) an order of magnitude faster and cheaper?

When wages decline, cost of producing the service/good does down too. And when the costs go down, relative demand goes up.

When relative demand goes up, the total labor needed expands.

How many Uber rides would you take at $5 vs $20?

How many times would you eat out at $10 vs $50?

Would you pay for a house cleaner at $25/visit over $150/visit?

A live in nurse at 50k/year vs 200k?

The costs of all these things will decline materially when the labor pool expands meaningfully due to displacement.

Technology has always been deflationary in the long run throughout history.

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.

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

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

There are an enormous number of tasks that can get by on good enough.

If you need image recognition, and a 30B model saturates the use case with 100% accuracy, you absolutely wouldn't continue to use the next frontier model as they come out.

And I'd argue most economically meaningful tasks will be saturated by cheaper models than those requiring frontier.

Think about what today's models can do with pretty close to 100% accuracy, and then consider that they will be orders of magnitudes cheaper over the years.

5.6 Sol can already obviate tons of labor, and why would you pay 2x or more for no meaningful gain?

The relative gap between frontier and non frontier also continues to shrink, so it's not like you take a meaningful performance loss by rewinding to models from 3-6 months ago. And soon that gap will expand to 12-24 months.

I get the impression the majority of people on here only think about coding, which net net will be a tiny volume of overall AI use in the end.

Nominal wage doesn't really matter, just real wages+purchasing power.

Goods and services prices will fall far more than wages for most people.

Why?

Because there will be far more efficiency and competition than pre-AI. It's plainly evident from the nature of the technology.

If one business can do something cheaper, other businesses will do it cheaper too, and have to cut prices to compete.

But the shock will be sudden so it won't feel good for our gen. Future generations will benefit without the drama.

Don't get me wrong, there will be big losers in some fields, and the short term will be painful due to retraining and loss of purpose/emotional toll.

Many of us built careers doing things that may not be relevant anymore. Or relevant in a different, perhaps diminished way.

But the same has happened to many professions throughout history and it's always led to general improvement of the broader public's welfare.

It seems obvious that labor displacement due to AI will create labor surpluses in existing fields.

Which will feel quite bad for many of us in the present, but net-net be good for society in the long run.

Wages will go down, but cost of goods and services will decline even more.

Markets will be more competitive than ever, which limits the moat/margin capability of many businesses.

It's only really particularly bad for those earning very high wages where there likely won't be any way to materially fill the gap.

I've long speculated this when I see these types of comments, because it's actually really difficult to hit usage caps with an efficient dev flow, even when running multiple threads for hours every day.

I think some combination of:

1) Using 1 thread for everything

2) Reviving old threads which are no longer in cache

3) Really broad prompts on badly vibecoded codebases, so model spends huge amount of time tracking down whatever you're trying to do.

4) Non-coding workflow which is more output than input heavy

5) (Less likely IMO) Intelligent use of many passive CI/cron-like scans. E.g. regular security, quality etc scans. Automated issue resolution/PR

Just a guess. I think 3 is likely the primary reason.

You can literally go all day every day with multiple threads with Sol on the Codex 100/month plan IME