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Comment by blonder | Hacker News Reader

I appreciate your rabid optimism, but considering that Moores Law has ceased to be true for multiple years now I am not sure a handwave about being able to scale to infinity is a reasonable way to look at things. Plenty of things have slowed down in progress in our current age, for example airplanes.

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Someone always crawls out of the woodwork to repeat this supposed "fact" which hasn't been true for the entire half-century it's been repeated. Jim Keller (designer of most of the great CPUs of the last couple decades) gave a convincing presentation several years ago about just how not-true it is: https://www.youtube.com/watch?v=oIG9ztQw2Gc Everything he says in it still applies today.

Intel struggled for a decade, and folks think that means Moore's law died. But TSMC and Samsung just kept iterating. And hopefully Intel's 18a process will see them back in the game.

During the 1990s (and for some years before and after) we got 'Dennard scaling'. The frequency of processors tended to increase exponentially, too, and featured prominently in advertising and branding.

I suspect many people conflated Dennard scaling with Moore's law and the demise of Dennard scaling is what contributes to the popular imagination that Moore's law is dead: frequencies of processors have essentially stagnated.

See https://en.wikipedia.org/wiki/Dennard_scaling

Yup. Since then we've seen scaling primarily in transistor count, though clock speed has increased slowly as well. Increased transistor count has led to increasingly complex and capable instruction decode, branch prediction, out of order execution, larger caches, and wider execution pipelines in attempt to increase single-threaded performance. We've also seen the rise of embarrassingly parallel architectures like GPUs which more effectively make use of additional transistors despite lower clock speeds. But Moore's been with us the whole time.

Chiplets and advanced packaging are the latest techniques improving scaling and yield keeping Moore alive. As well as continued innovation in transistor design, light sources, computational inverse lithography, and wafer scale designs like Cerebras.

Yes. Increase in transistor count is what the original Moore's law was about. But during the golden age of Dennard scaling it was easy to get confused.

Agreed. And specifically Moore's law is about transistors per constant dollar. Because even in his time, spending enough could get you scaling beyond what was readily commercially available. Even if transistor count had stagnated, there is still a massive improvement from the $4,000 386sx Dad somehow convinced Mom to greenlight in the late 80s compared to a $45 Raspberry Pi today. And that factors into the equation as well.

Of course, feature size (and thus chip size) and cost are intimately related (wafers are a relatively fixed cost). And related as well to production quantity and yield (equipment and labor costs divide across all chips produced). That the whole thing continues scaling is non-obvious, a real insight, and tantamount to a modern miracle. Thanks to the hard work and effort of many talented people.

The way I remember it, it was about the transistor count in the commercially available chip with the lowest per transistor cost. Not transistor count per constant dollar.

Wikipedia quotes it as:

> The complexity for minimum component costs has increased at a rate of roughly a factor of two per year. Certainly over the short term this rate can be expected to continue, if not to increase. Over the longer term, the rate of increase is a bit more uncertain, although there is no reason to believe it will not remain nearly constant for at least 10 years.

But I'm fairly sure, if you graph how many transistors you can buy per inflation adjusted dollar, you get a very similar graph.

Yes. I think you're probably right about phrasing. And transistor count per inflation adjusted dollar is the unit most commonly used to graph it. Similar ways to say the same thing.

The Law of Accelerating Returns is a better formulation, not tied to any particular substrate, it's just not as widely known.

https://imgur.com/a/UOUGYzZ - had chatgpt whip up an updated chart.

LoAR shows remarkably steady improvement. It's not about space or power efficiency, just ops per $1000, so transistor counts served as a very good proxy for a long time.

There's been sufficiently predictable progress that 80-100 TFLOPS in your pocket by 3035 is probably a solid bet, especially if a fully generative AI OS and platform catches on as a product. The LoAR frontier for compute in 2035 is going to be more advanced than the limits of prosumer/flagship handheld products like phones, so theres a bit of lag and variability.

You could put 64TBs of storage into your pocket with current technology. There are 4TB microSD cards available.

Not sure about the stated GFlops.. but I suspect we find that AI doesn't need that much compute to begin with.

You can run models locally on high end smartphones today with apps like PocketPal or Local LLM.

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