Might the logic behind this be this?: RAM is expensive. Storage is expensive. Nobody's going to buy a computer anyway, so you might as well make the other components more expensive too.

It even goes with Trump's more general agenda to make everything more expensive.

There is a reason I qualified that with "open source projects for AI."

Toasters will fly (again) before Nvidia's graphics tech gets open sourced.

Nvidia has been a pretty big supporter of open source projects for AI over the last half-decade or so. Many of the company's technologies are open source, most notably their open-weights model, Nemotron, and Dynamo, their inference serving and distribution framework. So it would be surprising to see them do anything to close off the Hugging Face collection. If nothing else, keeping it open is in Nvidia's own self-interest. The frontier AI companies themselves are all designing their own AI chips (e.g. OpenAI Jalapeno, Meta MTIA), which reduces the amount of Nvidia hardware they need to buy. Whereas smaller operations using open source models will inevitably pair those with commodity COTS hardware, which is where Nvidia reigns supreme.

Gates proposed taxing AI or robots the way you would pay a human employee's payroll tax

Unless we also roll out ubiquitous surveillance through a Vingean "Secure Hardware Environment"-like scenario where people aren't fully in charge of their own computers, I don't see how anyone could possibly detect whether or not I'm running any LLMs. Much like private DMCA violations (e.g. playing a CSS-protected DVD that you purchased, without getting authorization from the copyright owner first), it wouldn't have to interact with the world outside my house in any way, so it would be completely undetectable.

How would you tax that? I don't see this as reasonably possible without some pretty extreme measures.

The male/female ratio in China isn't that skewed, it's something like 106:100. A lot of it is probably the same thing you see in every other country, where both men and women lose social skills and have unrealistic standards of what kind of partner they are entitled to.

Right-wingers have been loudly cheering the inevitable economic downfall of California for years as its economy continues to grow. It must be so infuriating to them that Commiefornia just keeps getting richer.

"After 9 years as a US citizen, he could run for the US Senate. He would be 76 (or 74) years old.In short, it looks highly unlikely that he could (or even would) run for the US Senate."

Yeah, he would be way too young for our Senate.

I feel bad for entry-level folks -- though continually surprised how many of them outsource so much of their thinking to AI themselves. It seems like most college students cheat with AI, making them less useful as entry-level employees.

That's why he said "That makes it usually cheaper to use a non-HEPA filter but a higher air throughput rate."

It's a tradeoff, like almost everything in life. Whether his "usually" is correct depends mostly on who wants to buy the system, and only they can tell.

You miss the point completely. The technology is there and unstoppable. Cutting down one company doesn't destroy the technology. Killing Napster didn't kill the technology, it just spread it around, decentralized it, then there were thousands of sites to control, and they never did manage to do that, did they? Killing Flock will do exactly the same.

Killing Flock won't kill the concept or the capability and more than demolishing Napster stopped music copying. I bet within 5 years, this scanning will be common in most dashcams and phone apps will be available.

Lashing out in anger without having a plan or knowing your target is juvenile.

I agree, especially with that last part. They have no idea what they are missing. I'm a gamer, and I have nothing but respect for game devs. You guys make life *fun*. :) As I mentioned, I am a sysadmin, not a coder. But -- with the help of an LLM I vibe coded two successful mods for a couple of my favorite games and figured out (again, with the help of an LLM) to get one of them published to Steam's workshop. At my college commencement thirty-odd years ago, my CS advisor noted that in his 25 years on faculty, I was the only graduate who genuinely couldn't code his way out of a wet paper bag. Fair assessment. But an LLM bridges the gap between architectural intent and actual syntax, which lets me build things in my head. I keep getting the feeling that the anti-AI backlash is coming from the same kind of people that blame their tools when they screw up. I'm a baby with a flamethrower when it comes to using an LLM to write code for me, but I figured out (eventually) how to put guardrails around *everything* so that the LLM converges on my intent, and not the semantics I used to convey that intent. That's the real hard part, I think. Sounds like you figured that out as well.

It's only local to China in the sense that they choose what {packages/CCP poison} go in there.

For all values of u, Linux is local to u in the sense that u chooses what packages go in there.

And you think the fact that carbon dioxide has steadily increased over the past 150 years or as we pump a lot of carbon dioxide into the atmosphere is a coincidence? You honestly believe that there is zero connection between pumping gigatons of carbon dioxide into the atmosphere, and there being gigatons more carbon dioxide in the air than pre-industrial times? Completely unrelated events?

Torvalds is right. This is a bit of a me too post, although my use case is a little less kernel-adjacent. :)

Up front -- I'm not a dev. I'm a retired sysadmin with a BS in CS and several decades in cubicle land managing systems and networks for a very, very large defense contractor. And I hate coding with a purple passion...if I couldn't solve it with a shell script, I would hand it off to a real coder. With that said, I've spent the last several days using an LLM as a development partner to build a fairly ridiculous personal music system. What surprised me wasn't that it could generate Python. That's useful, but not especially interesting.

What became interesting was using it as a persistent collaborator. My sysadmin lizard brain imposed enough engineering discipline that neither of us was allowed to hand-wave about system state. The result was actually amazingly useful to me: a user-specific taste model from actual listening evidence rather than genres. It (currently) has nine weighted dimensions: melodic continuity, spatial/textural architecture, emotional landscape, developmental architecture, background-to-foreground permeability, conceptual/lyrical reach, contextual integrity, arrangement integration, and register/timbral fit, and two engines, one cloud and one local, that actually can generate context aware playlists, one from the music mines available from my Spotify subscription, or one from my local mp3 media library managed by my wine-supported Winamp install. And fine, go ahead and insert Ok, boomer jokes here. :)

Both engines reduce requests like "I'm surfing slashdot for a couple of hours and don't want the music getting in my way" or "I'm about to try this damn slaughterspine fight for the umpteenth time and I need something to propel me into a flow state" into an activity envelope, apply the taste model, and then produce something that both Spotify's API and winamp can grok. The end result is a private playlist in my spotify account, or a .m3u8 playlist for winamp. The taste matrix guarantees the list will be generated from music that I genuinely like to listen to, and still match the context I want to listen to it in.

As a pleasant surprise when I was building the local model, I ended up creating a seriously functional ID3 metadata scrubber. Did you know that there is an entire cottage industry out there for figuring out what exact physical carrier your MP3s were derived from? I didn't, but the LLM did. It fingerprinted all my mp3s, matched them to online digital signatures, record label catalogs, and even pulled down and digitally fingerprinted free samples from Apple/Amazon music when it couldn't find a good fit elsewhere, including deep dives in USENET alt.music.mp3 archives. These forensic tactics were brand new to me, and they helped to completely fix my Winamp ID3 tag jungle. I ended up with a very decent forensic model with a control surface that let me find provenance and preserve it in a SQLite catalog for almost my entire winamp library; I'm down to just 17 holdouts out of the 914 mp3s I've ripped from CDs over the course of the last four decades or so -- many of which I no longer possess and can't consult for provenance.

But the part that made the LLM genuinely useful was the boundary between its world and me. The development loop was roughly:

wild ass idea -> generate helper -> run locally -> deterministic evidence -> inspect/adjudicate -> next operation

rather than:

AI says it probably will work -> continue

The LLM has been exceptionally useful for finding contradictions in my schemas, designing forensic queries, generating one-off analysis tools, keeping long dependency chains straight, spotting places where I was promoting an inference into a fact, and remembering why some ugly-looking safeguard exists after I had long forgotten the incident that created it.

TBH, It has also confidently proposed things that were just plain wrong, misunderstood what layer owned a fact, tried to solve problems more broadly than the evidence justified, and occasionally decided that some particularly unpleasant corner was probably not worth pursuing. Which is where Torvalds' comment made me laugh. The useful mode isn't "tell the AI to build a system." It's much closer to "keep track of this shit for me, please, and try to keep us from shooting ourselves in the foot."

It's like having a very fast, very sharp indefatigable summer intern with an absurdly large working notebook, broad technical knowledge, apparently no need for sleep, and a tendency to press shiny red buttons just to see what happens. If you give an LLM observable state, narrow authority, regression checks, and provenance, and are willing to accept that you might have to herd some hallucinating cats, it can become one hell of a collaborator.