I'm not sure what this comment is trying to say. Theranos was a company build from the ground up on fraud. Apple, for all its faults, is provably at the forefront of technology used in personal computing devices.
And theranos did that too? Theranos, a medical company, was an affordable luxury (??) brand that makes sleek hardware? In fact the hardware was not sleek at all, since it didn't function.
That's obviously true. On the other hand its also true this is more likely to work because it is rust compared to python or js for example. And that's not only because of memory safety. It's because static typing gives an automatic proof of a certain level of correctness of the code. That correctness is correlated with correct business logic bugs. So it is valid argument to make.
Of course that doesn't mean that there are no businesses logic bugs.
This is perhaps the least believable comment I have seen on HN, ever. It would be more believable for someone using C to say "In about 22 years of writing C code. I have never ran into a memory bug".
Avoiding "memory bugs" in C is trivial, but tedious, so too many C programmers fail to use an appropriate programming style. Nonetheless, there are some who have never encountered a "memory bug" in programs written by them.
I agree that a programming language should enforce such features, instead of counting on competent programmers.
In these cases of the TI parts, some of their most important specifications, like maximum supply voltage, noise and slew rate, have been changed, and not by a few percent, but by even a factor close to 2.
For so great changes, it is really not acceptable to use the same part number, especially when the part numbers have been in widespread use for many decades, so most users who are familiar to them will not bother to check again their latest specifications, where they could notice that they are no longer what they knew.
Once you now something is correct, with a proof. It is MUCH easier to understand why it is correct. Than to start from a slate that you don't even know whether something is correct or not. In that sense AI that can just solve high level math problems is immensely useful. It allows a mathematician to explore ideas at a much more rapid pace.
Consider that since an LLM is really just an large encoding of data, the "proof" is in there already. All further work on it is effectively only rearranging words. Then all math an LLM is capable of is "done" and we have the "proof" in the LLM which by your definition is now "MUCH easier to understand" and this work is somehow sufficient.
You're confusing "contains information" with "has produced a result."
A proof being latent in an LLM is no more significant than a proof being latent in a book, a theorem prover, or the axioms themselves. Einstein's papers were latent in the genetic code of his parents and the environment of his time. That doesn't mean general relativity was "already done" before Einstein was born.
By your logic, no computation has ever accomplished anything because the output was always implicit in the inputs.
The entire purpose of computation is extracting information from representations where it's difficult to see into representations where it's easy to see.
So no, this isn't a problem with the original reasoning. It's a problem with yours.
Too bad linux x86 on arm story is still terrible. Fex is great in a sense but getting it run is a herculean feat, with pagesize mismatched requiring a VM.
Why do you feel the need to attack the person character by stating he is probably young and/or has not dealt with disability in his social circle? This is needlessly aggravating and actually pissed me of when reading it.
Just because there arepeople who type slow doesnt invalidate the point that typing has a much higher speed ceiling. It's like saying well cars can go slower than some people who walk. So we may as well walk everywhere.
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