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The article vastly underestimates how often no was said before ZIRP. Getting to yes was very, very, very hard. Zirp moved the default to build it snd they will come.

It is so comforting to deal with known unknowns particularly when the unknown unknowns are the ones that get you.

How would one call such a strategy? Embrace and extend comes to mind.

This has really little to do with embrace and extend. They are not taking over an open standard or anything like that.

If anything, it's forced dogfooding, i.e., forcing their own workforce to beta-test their product.


We always knew the limits to Moore‘s Law are first and foremost economic. Given an industry used over decades to predictable lowering of price per compute function and thus swallowed any advance for new user functions and overhead when the limits are reached there is going to be a squeeze. AI scaled up at the time the production capacity became more inelastic.

Maybe it is time not just shrink transistors but also software bundles. I can see decades of possible progress hiding in plain sight behind a browser screen.


AI data centers are eating like 80% of memory.

Making user space applications more memory efficient is not even going to be a rounding error on memory demand.

I am with you that it needs to happen, but it's not going to solve a memory shortage.


It would make memory-poor phones more viable. Like why can't we have a 512MB, or even 256MB RAM phone. Although I doubt that the software effort would be cheaper than just buying the extra RAM. It's definitely much more uncertain.

Those exist, they're just feature phones. Smartphones have to run general purpose apps and that takes RAM.

That was my point, make it so that apps can run on that RAM budget. At least some apps.

The OpenMoko Freerunner only had 128MB RAM, it was able to run a Linux desktop of the time, Englightenment/E16. There were lots of apps for it too. IIRC the cut down QtMoko distro ran best though.

https://wiki.openmoko.org/wiki/Neo_Freerunner https://wiki.openmoko.org/wiki/Applications https://wiki.openmoko.org/wiki/QtMoko

Before that Linux ran on the Zaurus too:

https://en.wikipedia.org/wiki/Sharp_Zaurus https://en.wikipedia.org/wiki/OpenZaurus


That's newly fabbed memory vs. an existing stock. The stock is quite massive, so optimizing existing use and enabling it to be repurposed can be meaningful.

Not really...

If the new memory is needed for AI data centers, it doesn't matter if your existing MacBook doesn't need as much memory anymore.


If the existing MacBook needs less memory, it can use its current memory spec for higher-level uses that formerly required a MacBook Pro. That meaningfully affects the market.

You don't seem to understand supply and demand.

That does not help the demand side for AI data centers - which is the vast majority of the market...


If your point is purely about supply and demand for datacenter HBM and LPDDR, you're probably right. Local model inference (using the existing memory stock) can make a dent in current use, but not in projected future uses that will plausibly involve much larger models.

One value of learning on my Macbook is that mps is not as well supported as cuda which forces me to go down roads I would not have traveled.

That's more of a disadvantage. CUDA is an industry standard, MPS/MLX/Metal compute shaders are a novelty.

> every keystroke, with millisecond timestamps

Finally someone has figured out how to hire accurately.


Funniest comment in this thread :-D

There is a reason moderation decisions are not perfectly transparent: They are gamed otherwise. So there needs to be legal recourse with discovery and meaningful liability attached to submitting to the role of acting as the agent of a foreign government.


While I agree with adding code contributing to complexity is problematic there is lots of code in existing code basis which is overly complex due to past outdated requirements or less than perfect human coders. The current flood of AI driven security fixes demonstrates that AI can be pretty good in detecting security edge cases. It is not inconceivable to use it to also reduce code complexity.


And they are enticing human agents to further their agendas using techniques learned from the white mice.


Yesterday in Lidl I was a bit shocked seeing the coupons offered by their app. They did a really good job with their mixture of stuff I had bought or might buy.


Note for people who don't know:

They profile you and offer discounts based on your past purchases


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