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What Happens When the Cost of Intelligence Drops 100x

catalystneuro.com

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Re: What Happens When the Cost of Intelligence Drops 100x

#32
post #22

> Reading everything becomes the default. At a cent per document, a model can read every paper I love how in our day "reading everything" means "the computer reads it for me". I expect soon the computer will be able to go on bicycle rides, and spend time with my wife.

Hasn't the computer already been spending time with your wife?

Re: What Happens When the Cost of Intelligence Drops 100x

#34
post #21

Jevons Paradox [1] > when technological improvements that increase the efficiency of a resource's use lead to a rise, rather than a fall, in total consumption of that resource. [1] - https://en.wikipedia.org/wiki/Jevons_paradox Las Vegas replaced the expensive incandescent lighting on the strip with cheaper to run LED equivalents. But the costs didn't come down because they were able to add more lights and larger dis…

Turns out Grey Goo was just thermal paste

Re: What Happens When the Cost of Intelligence Drops 100x

#35
post #22

> Reading everything becomes the default. At a cent per document, a model can read every paper I love how in our day "reading everything" means "the computer reads it for me". I expect soon the computer will be able to go on bicycle rides, and spend time with my wife.

Hasn't the computer already been spending time with your wife?

You're absolutely right!

Re: What Happens When the Cost of Intelligence Drops 100x

#36
I think speed is actually going to be a bigger factor than cost. Even projects where “money is no object” often hit a wall with LLM response times.

Sure you can speed things up with parallel work under subagents, but as with parallelizing traditional computational tasks, there are diminishing gains.

I keep hearing people saying just change the way you work to trust long-running agents and multi-task more, because they’re too slow to work with interactively for many use cases. I think that’s painful in a world where we expect humans to still heavily guide and interact with agents for their day-to-day work.

Re: What Happens When the Cost of Intelligence Drops 100x

#37
post #22

> Reading everything becomes the default. At a cent per document, a model can read every paper I love how in our day "reading everything" means "the computer reads it for me". I expect soon the computer will be able to go on bicycle rides, and spend time with my wife.

Hasn't the computer already been spending time with your wife?

Asymmetric multiprocessing with your mom

Re: What Happens When the Cost of Intelligence Drops 100x

#38

Personally I still see LLMs as very advanced search engines which lack intelligence. To me it seems that the cost of getting data is reduced by LLMs, not the cost of intelligence. I mean: we tell the model what we want to achieve, and the model responds with the right data in de form of code in seconds. That's why 'stackoverflow programmers' will have a hard time competing with LLMs but engineers are still needed for…

I think this viewpoint fails to understand what "intelligence" is. The idea must be that intelligence is some special thing that only humans have. So when machines couldn't do jack s... we said "it's the Turing test". When machines blew through the Turing test we said "that was just prediction..not really intelligence, that's different".

It's not different. The delusion humans have is that intelligence is special and magical. It's not. It's just nature's prediction machine. A very fancy version to be sure. But not qualitatively different .

All statements that "oh but it'll never be able to do that" will prove false.

Re: What Happens When the Cost of Intelligence Drops 100x

#39
post #36

I think speed is actually going to be a bigger factor than cost. Even projects where “money is no object” often hit a wall with LLM response times. Sure you can speed things up with parallel work under subagents, but as with parallelizing traditional computational tasks, there are diminishing gains. I keep hearing people saying just change the way you work to trust long-running agents and multi-task more, because the…

Given the 750 tok/sec GPT 5.6 Sol Ultrafast (via Cerebras), the many-1000 tok/sec Chinese models, and the 15000 tok/sec Taalas HC1, I think we're well on the way towards seeing that solved too. Combine the two, and yeah, wild ride incoming.

What's especially bewildering to me is that translated back to raw bandwidth, even 15000 tok/sec is just like what, 75 KB/s? Extremely meager amounts of data, moving mountains.

It's already kinda funny seeing LLMs throw out effort estimates in wall time terms. It's always some "hours, days, weeks" tier thing, when in reality, it's gone and done in minutes.

Re: What Happens When the Cost of Intelligence Drops 100x

#40
post #26
post #23

I've been working with the chinese open models for 4 months. They are more than capable for a tiny fraction of the cost of the frontier ones. And yet they also continue to get significantly better and (Deepseek's recent price increase aside) cheaper. Its hard to fathom how the truly frontier stuff will be able to compete long-term.

And why won’t the frontier models continue to become better? The open models are getting better but so are the frontier models. The frontier models might remain in a constant race to remain ahead

They are running out of novel, clean training data and compute. There is probably a limit to how much improvement can be squeezed out of LLMs. Recent improvements have been more about orchestration and "reasoning" loops (i.e. iteratively feeding context back through the model).
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