724 karma · joined February 9, 2021
Or just vague gesturing about how immigrants aren’t entitled to anything? (but you presumably are!)
What about the sweeping halt of all legal immigrant visa processing?
You get a jmp to some arm64 instructions of your choosing, with a bunch of CPU features locked out.
They don’t provide any source code or documentation (which they easily could) so if want to do literally anything with your “open” device you must first reverse engineer the entire MacOS driver stack like the Asahi project did. Great fun, but it’s a criminal waste of incredibly talented engineer hours.
On top of that, the reason Asahi doesn’t work on M4 and later is that Apple has intentionally modified the ARM core to prevent stock MacOS from running once the hardware is “unlocked,” which makes it way more difficult to reverse engineer.
Bastards.
It’s true we usually don’t care about all the details, which is why abstractions exist. An abstraction hides details by fixing them, and lets you specify the rest precisely.
An LLM isn’t an abstraction in this sense any more than asking a coworker to do something is. The details are not fixed, but decided for you. If you can’t understand or modify what was decided yourself, the only interface left is going back and forth in natural language.
So no, the abstractions won’t become unnecessary. The details don’t just go away. Plenty of people really don’t care about them, and for them the LLM is fine, but only because it’s gluing together the millions of LoC of existing libraries and frameworks where the details have already been fixed, overwhelmingly by humans.
There will always be a need for human professionals who aftually understand all that obscure stuff, and per TFA, it’s looking like it won’t be the ones who went all in on AI.
And if you really want to record all your work and project context somewhere, just let people ... look at that directly? Or summarize and query it with their own LLM if they want to?
It’s composed of 4-bit multiplier cells that compute all 16 possible results in parallel. The top metal wiring layer physically selects the one that corresponds to a multiplication with that cell’s constant weight, and routes it to the next layer.
Of course some overworked analyst is going to start neglecting the details and erring on the side of bomb it if the AI summary is dangerous sounding.
It’s gross negligence to be offloading this type of analysis to claude. Do you decide what’s factual based on the google AI summary? They’re deciding to end thousands of lives with about the same amount of rigor, including those schoolchildren. Have some humanity.
The benchmark of 2m black-scholes evals/sec is meaningless without additional context. Also seems a couple orders of magnitude slower than what I’d expect even for a single core. What exact transformations are being done, and what’s the throughput in GB/sec? Is it multi threaded? Benchmark against the equivalent query in kdb+ and ClickHouse?
https://github.com/ChristofferGreen/PrimeStruct/blob/d4f1a8e...
Rendering untrusted model output, ooh scary! Of course we want full audit surface!
Case in point: look at all the people who’ve now built their entire political identities atop this unfalsifiable distrust. They’d even distrust “stand further apart” if the wrong person said it.
> I do not know how this trust can be rebuilt but definitely not by publishing more reviews.
This is the crux. Outrage spreads way faster than the boring truth.
Funny how much easier it is to tolerate something when it only affects other people.
What you’re saying is functionally equivalent to “just deal with it,” since ultimately people will choose to have their privacy violated over the lifelong Sisyphean task of trying to avoid all of that. That doesn’t mean people don’t care about privacy, it’s just the current equilibrium in our broken system.
> I think we have been stuck in this way of life so long we can't imagine an alternative.
I agree.