6,644 karma · joined August 14, 2007
Feel free to email me (spam armored): hn.rpdillon@xoxy.net
There was a massive famine I didn't know about in the mid-to-late 1990s in NK, and millions died. During this period, an underground capitalism took over, where people were producing food in various ways, often grown in their own gardens, and then buying and selling from each other, with barter rates / prices determined by availability.
While I agree with you that countries can make rules that fix prices (or do whatever they want), there is an underlying set of mechanisms to supply and demand that are not derived from law, but logic. If I have 5 cupcakes, and there are 100 people that want them, unless someone points a gun at me and says "Sell them each for 5 cents" (while the 100 people all fight over who gets to pay), the natural incentive structure would essentially be an auction to figure out who is willing to pay the most, and then sell it to them. That's not some legal theory or set of laws, but rather the human condition.
Of course, it doesn't play out this way in reality. In reality, it all comes down to power, and those with power take whatever they want, but my point here is that supply and demand exist outside of a legal structure, and if there's only one electrician, and there's enough work for 10 electricians, that one electrician can server the richest 1/10 of those in need (and charge accordingly to select that 1/10), and it is rational to do so independent of any laws made. So much so, in fact, that laws are advisory, but the fundamental incentives are inherent.
This is why I like incentives more than rules: they're less brittle.
I've been doing local inference for a couple of years on the side, and I'm astonished at the number of variables you need to have control over to get a reliable result. Inference engine, model parameters (top_k, temp, MTP-enabled/not), quant level, and harness all have a big impact on the results.
DS4-0731 at 2bit on llama.cpp (ROCm) and 250k context with omp.sh has been consistently reliable for me, just a bit slow (10 t/s) compared to what I'd prefer. Trying out DwarfStar today (benching it right now) to see if I can get better speed, but otherwise I've found it to be great on my side projects that are smaller (up to 10ksloc).
There could also be a domain issue - I tend to do lots of web programming and sysadmin work in these projects; if your work is more esoteric, it might not be nearly as good. I haven't tested much outside of my narrow domain.
By discussing the code.
> maintainers can simply sabotage them and accuse them of using an LLM to explain the code
Bad faith enforcement is possible no matter the rules. If you think it's bad faith, a different policy won't save you.
Following them for years, they seem extremely well put-together, and have excellent judgment. They are using the same policy as Linux and Debian (in my words, the speed of light is human understanding and judgment). Whether it is reasonable is a different question from enforcement, which typically comes down to "this seems fishy, explain your reasoning".
As for code review, the rule of thumb I've used for decades is: it takes about as long to review and understand as it does to write. Your 100x metric is completely outside of anything I've seen in any hobby or professional project, ever.
I'd like to see specific files you scanned and specific vulnerabilities cited.
> Two changes are urgently needed. First: AI companies need to rely more on the safety expertise that already exists in other fields. And second, before we create systems significantly more capable than the ones we have today, we need new science to ensure that more capable models (and their successors) will make safe choices when we aren’t looking.
He mentions farther down about learning from aerospace engineers and nuclear engineers about safety. Those industries are heavily regulated, so perhaps regulation above a certain capability level is needed. Defining what that level is might be tough, though.
The second point is harder: in the field of AI, practice has extended far beyond theory, so his call for new science is going to be fundamentally tough, because we can't effectively coordinate a global slowdown in AI development so we can let theory catch up. This means, like so many other industries, the safety lessons will be written in blood.
There's also the ability to distill other models, which is also not illegal (though I'm sure they like to come after whomever for TOS violations, but thats a civil matter).
And, of course, the obligatory copying-isn't-theft observation. A recent supreme court judgment put it well.
> Since the statutorily defined property rights of a copyright holder have a character distinct from the possessory interest of the owner of simple “goods, wares, [or] merchandise,” interference with copyright does not easily equate with theft, conversion, or fraud. The infringer of a copyright does not assume physical control over the copyright, nor wholly deprive its owner of its use. Infringement implicates a more complex set of property interests than does run-of-the-mill theft, conversion, or fraud.
Folks are pretty smart here, I think we can handle these nuances, even if we don't agree about whether they are good.
Edit: reading through the full text of their post, it looks like they are using common crawl, which is likely just as much of a copyright infringement as Anna's Archive -- it's not like published works have a unique claim to copyright. I think this strengthens your point, though: I was expecting to see scans as training data, but it doesn't appear to be the case.
I don't mean to be cynical, but the trend is very real, in my experience.
> Select Transfer to see if your order is eligible for transfer.
Anyone have any idea how often events are allowed to transfer? I assume the artist/venue drive this decision.
https://www.amazon.com/wholefoodsapp/prime-code
The web was smart. URLs were smart. We've lost a lot moving to crappy user interfaces people have to dig through. I'm have hopes this will get better soon.
Edit: Isn't there trivial fix with scanning a QR in the store that either opens the site or deep-links into the app? This is like 15 minutes of store manager time + one Claude prompt away for the mobile app, I'd think.
Took about 45 minutes and produced a working mock that we could then play with and see if the UX felt right. It was surprisingly high fidelity, and while the code was entirely throw away, it helped a room full of people make decisions about how we wanted the tool to feel within the first couple of hours of thinking about the project. Designers bring a wealth of UX thinking to that discussion, but the process of creating the mock was done entirely by engineering.