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kangs

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- Software is copy-able for nearly free. - Hardware is not. Even if you have the plans, you've to build the infrastructure for it, and its a fairly finite, physical item.

Both are however hard and expensive to produce. It's much better for profits to develop and sell the hardware, and copy the software someone else spent resources on.

it is getting there, and not so slowly though. The remaining problem is that it's still just a tool. Telling a random dev "make zig faster in a one shot PR" isn't going to give good results either.

In the past, OSS projects were self-selective because you needed to be able to make working code, and if you did, you probably also reasonably did the right things as you spent years learning this, and have some sort of reasoning behind your feature, need, etc.

Today, even if the LLM was perfect and could reason well, it still does the bidding of the prompter - and you no longer have self-selection. Heck, it'll be difficult for zig devs to decide what's actually made by an LLM or a human anyway, I'm sure there's already LLM generated code in there - but at least these [human submiters] still need to be reasonably good at code.

I wonder if we'll end up with "only human with trusted badge of honor" can commit, and/or "LLMs now reason well enough to tell you: 'no, f off, this feature, plan, idea is garbage I'm not generating it" hehe.

When i was a kid, my dad had a Mac with the A/V PAL-SECAM cards. Hooked up a make-shift copper wire antenna and wrote a decoder with the free codewarrior cd folks gave me at Paris' Mac convention (we were 12 and crazy I guess). Good opportunity to learn powerplant and c/c++.

I ended up brute forcing most of it as I did not really understand what I was doing, but it turns out, with enough time, you get things going.

Wish the pages were still up, I lost that software long ago, and I'm sure my code was garbage (not that its much better today, but at least I can blame Claude..) and fun to read.

The 90's were fun.

it's actually just trust but verify type stuff:

- verifying isn't asking "is it correct?" - verifying is "run requests.get, does it return blah or no?'

just like with humans but usually for different reasons and with slightly different types of failures.

The interesting part perhaps, is that verifying pretty much always involves code, and code is great pre-compacted context for humans and machines alike. Ever tried to get LLM to do a visual thing? why is the couch at the wrong spot with a weird color?

if you make the LLM write a program that generate the image (eg game engine picture, or 3d render), you can enforce the rules by code it can also make for you - now the couch color uses an hex code and its placed at the right coordinates, every time.

google even has specially signed fw that let you root the device and unlock anything that doesn't rely on the passcode. secureboot passing and all. i can't imagine that the nsa doesnt have them. after that you just gotta crack the usually very simple passcode. wouldny be surprised if thats what cellrite has lol.

you seem to believe that llm are a neutral engine with bias applied. its not the case. the majority of the bias is in the model training data itself.

just like humans, actually. fe: grow up in a world where chopping one of peoples finger off every decade is normal and happens to everyone.. and most will think its fine and that its how you keep gods calm and some crazy stuff like that.

right now, news, reddit, Wikipedia, etc. have a strong authoritarian and progressive bias, so do the models, and a lot of humans who consume daily news, tiktoks, instagrams.

its not an llm thing -- its just -- folks don't know how to use them (pun intended).

Same for ; "" vs '', ex, eg, fe, etc. and so many more.

I like em all, but I'm crazy.

to be fair, most of MTE's benefit is realized by having enough users running your apps with MRE enabled, rather than having it everywhere.

This is because MTE facilitate finding memory bugs and fixing them - but also consumes (physical!) space and power. If enough folks run it with, say Chrome, you get to find and fix most of its memory bugs and it benefits everyone else (minus the drawbacks, since everyone else has MTE off or not present).

trade offs, basically. At least on pixel you can decide on your own

Dan Kaminski popularized this in 2007-8 or so. Not that it didn't exist here and there, but he made the perhaps first public version of a dns tunnel (ozyman). he inspired iodine and others and was a fairly well known guy.

Dan passed away in 2021, rip.

if you search for it its hard to find. his blog is down (hea dead...), and many companies and people talked about it on his behalf to drive traffic (hi duo sec..), so you can see the internet forget, rediscover, and rewrite some history even in a few years.

they do but not extraordinary either.

ive a x elite and a bunch of other laptops

i like the mba 13 (but barely) and the zbook 395+

the x elite is just a bit slow,.incompatible and newer x86 battery life isnt far off

a lot of the western world learns only speaks about ww2 (let alone ww1, americans civil war, etc.).

there has been countless western and non western wars with slightly different patterns and a taste of "winner writes history".

one i find interesting is the french revolution. its also fairly recent, but not as tampered with as ww2 history. for example, there still are records of how terrible and cruel the revolutionaries were, how everyone was a royalist that needed to die and how the populace started to be ready to revolt - again - right after the change of power. thankfully, things eventually calmed down - as they were cruel, but not dumb.

either way I'd basically recommend expending the reading curriculum a bit.

Principles are just nice words, and that's it.

It's, IMO, the action/reward loop that matters most (i.e. incentives).

Most, if not all big tech companies do not align incentives with principles - quite the opposite. Most folks in a position of leadership utilize principles and other "nice sounding arguments" for their own personal benefit, i.e. block internal competitors with principles (works great against employees with integrity and quality ethics) while claiming to follow these.. without actually following any.

I'm sure everyone here has had some taste of it, or even discussions on how this sucks but "they gotta play the game". Not playing the game is extremely hard when it comes to promos, salary, or getting a large project to go with your name on it (I'd know..).

So, until this rant become common sense, principles will just be that - nice words.

it mainly means control these days. ive made SSL then later TLS requirements for web browsers and we had fights on this sort of stuff.

yeah encryption is needed. but then you need authentication. and then, if authentication is controlled by corporations you're f'd.

instead youd want identities to be distributed and owned by everyone. many trust models have been developed and other than raw UI problems (hi gpg/pgp) its really not a terrible UX.

yes and no. i have macbook pro m4 and a zbook g1a (ai max 395+ ie strix halo)

In day to day usage the strix halo is significantly faster, and especially when large context LLM and games are used - but also typical stuff like Lightroom (gpu heavy) etc.

on the flip side the m4 battery life is significantly longer (but also the mpb is approx 1/4 heavier)

for what its worth i also have a t14 with a snapdragon X elite and while its battery is closer to a mbp, its just kinda slow and clunky.

so my best machine right now is the x86 actually!

IMO there a flaw in this typical argument: Humans are not less fallible than current LLMs in average, unless they're experts - and even that will likely change.

what that means is that you cannot trust a human in the loop to somehow make it safe. it was also not safe with only humans.

The key difference is that LLMs are fast, relentless - humans are slow and get tired - humans have friction, and friction means slower to generate errors too.

once you embrace these differences its a lot easier yo understand where and how LLM should be used.

Most people, even here, only read headlines anyway. Every time a really weird science claim is made in the news, finding the paper takes a while, if it's at all available. Then reading it correctly. Then usually, you can write a a blog post about how fake and bad the paper is (that 10 people in the world will read, vs the news reaching millions), and wonder how the one and a half peer reviewers approved it.

It's actually a fun exercise, IMO. I did it a couple of time for surface temperature claims, which were completely bogus. It took me a couple of days to actually "peer review" the paper though, so it's expensive in time.

Beside "science" is not a thing to trust, it's a process. It's never fully correct by definition.