daemontus

One more fun fact: this is also the reason why Turing machines are a popular complexity model. The tape on a Turing machine does not allow random access, so it simulates the act of "going somewhere to get your data". And as you might expect, hash table operations are not O(1) on a Turing machine.

This is less of an issue with systems where there is little monetary value attached (I don't know anyone whose mortgage is paid for by their Stack Overflow reputation). Now imagine that the future prospects of a national lab with multi-million yearly budget are tied to a system that can be (relatively easily) gamed with a Chinese or Russian bot farm for a few thousand dollars.

There are already players that are trying hard to game the current system, and it sometimes sort of works, but not quite, exactly because of how hard it is to get into the "high reputation" club (on the other hand, once you're in, you can often publish a lot of lower quality stuff just because of your reputation, so I'm not saying this is a perfect system either).

In other words, I don't think anyone reasonable is seriously against making peer review more transparent, but for better or worse, the current system (with all of its other downsides) is relatively robust to outside interference.

So, unless we (a) make "being a scientist" much more financially accessible, or (b), untangle funding from this new "open" measure of "scientific achievement", the open system would probably not be very impactful. Of course, (a) is unlikely, at least in most high-impact fields; CS was an outlier for a long time, not so much today. And (b) would mean that funding agencies would still need something else to judge your research, which would most likely still be some closed, reputation-based system.

Edit TL;DR: Describe how the open science peer-review system should be used to distribute funding among researchers while begin reasonably robust to coordinated attacks. Then we can talk :)

(a) [Name 2005] is much easier to mentally track if it appears repeatedly in longer text than [5] (at least for me). [5] is just [5]. [Name 2005] is "that paper by Name from twenty years ago".

(b) By using [Name 2005], I might not know which exact paper this is, but I get how recent it is w.r.t. what I am reading. In many cases, this is useful context. Saying "[5] proves X" could mean that this is a new result, or a well known fact. Saying "[Name 1967] proves X" clearly indicates that this is something that has been known for some time.

Yes, retracting these is still shameful, but it's not a "we found extraterrestrial life" claim. It's a "we received weird signals from a nebula that we don't understand so far" claim.

And yes, a lot of supporting but inconclusive evidence is still supporting evidence. My point is not that (most) scientists would risk lying about replicating a superconductor, but rather that uncertain or inconclusive results with a solid chunk of plausible deniability in a rapidly evolving environment go a long way towards being "in the room where it happened".

- "this could ruin their career": Depends. If they posted completely fake numbers or intentionally fake videos. Sure, that would be bad. But none of this is peer reviewed, and all of this can be retracted. A contaminated sample? Oops, retract. Bad measurement methodology? Oops, retract. Sure, somebody will remember that you made the controversial paper in the first place, but as long as you are not provably fabricating, a lot can be attributed to "an honest error". There are tons of peer reviewed papers out there with errors that completely change the outcome. Does not mean the authors are "finished".

- "they have nothing to gain": Oh, they absolutely do. While "science should be fully objective", funding agencies very much aren't. Obviously, just like VC funding, science funding is not a complete coin toss. But having "the right" team and background is often as important as the idea itself. One way to get the right background is to "touch shoulders with the giants" and one way to get the right team is to be highly visible and attract talent.

So overall, if LK99 is eventually shown to be a superconductor by someone else, you have a lot to gain, even if your own initial study is not perfect.

Let's say your team synthesised something. It looks like LK99 and it has some properties that are not really superconducting but at least a bit unusual. This clearly isn't what you hoped for. Now, do you run a bunch of other controls to see if it is some form of contamination, process error, combination of both... or do you publish a vague click-bait paper on ArXiv and hope that other results will somewhat align with yours?

Finally, I'm not claiming this paper or any other paper intentionally published untrue or misleading results. Just that scientists are also people. They have FOMO, they follow trends, they see what they want to see. As always, big claims require big evidence, and so far we don't really have that. But that does not mean there isn't some truth to the big claims :)

Bit focused on eastern Europe, but has a hiking mode with very good coverage of the official routes (not only in eastern Europe ;)). And everything is free, including offline maps. Terrific value for casual trips.

https://play.google.com/store/apps/details?id=com.bergfex.to...

This one is not free (there is a free tier though) but seems to have more details in some areas, so the pro tier may be worth it if you hike a lot.

Google will probably work ok for the most popular trails, and I guess you can use it as a supercharged compass. But at least in Europe, if you actually plan a route in any mountains based on Google, you're in for an adventure :)

- A phone that is used a lot in the car as GPS is often charged/discharged continuously, often for hours.

- Furthermore, this often happens in very hot or cold conditions which are bad for battery charging.

- A lot of people seem to live with the perpetual 5% of battery, or generally don't care about properly charging the device. This is also terrible for longevity.

- There are other reasons why you may want to constantly charge/discharge your phone (e.g. you are making Android apps, or it's the phone where people call your place of business, etc.).

So, just to make myself clear: I completely agree that on average, batteries should last for a long time. But in practice, people often have irregular activities which appear negligible on average ("it's just a few charge cycles"), but end up damaging the battery more than regular prolonged use. But again: I'd very much like more hard data on this :)

Out of the 10+ phones in our family over the last 5-10 years, one was water damage and one was failure of the internal flash memory. Every other phone was replaced because the battery died. Every single one.

Official replacement was no longer available and DIY was either impossible (lack of parts) or eventually ended up damaging the device beyond economical repairability.

Regular people that don't have thousands of dollars in disposable income (and nothing useful to spend it on) haven't cared about phone specs for years. Hell, I love tech and could buy a new phone every year and even I haven't cared about phone specs since the original Google Pixel.

If you brick your phone every year because that's just who you are, no judging.

If you want a new phone every year and can afford one, its your money. Just remember that you are fortunate enough to be able to do so. And someone will surely buy your used phone and likely (try to) replace the battery in it.

Overall, it's like claiming that nobody drives cars that are 10+ years old because they needed a new clutch. Or that a 50 year old house needs to be torn down because fixing the roof economically is clearly beyond our engineering prowess. Are there people that swap cars every 5 years? Absolutely. But that does not mean those cars go to a scrapyard.

I will not comment on the technical aspects of this proposal, since the actual outcome might very well need to be settled in the court still. But dismissing the general point of legislature which demands better longevity for devices that basically everybody needs to partake in modern society is rather shortsighted.

A "software replacement for MMU" would thus need to solve fragmentation of the address space. This is something you would solve using a "heavier" runtime (e.g. every process/object needs to be able to relocate). But this may very well end up being slower than a normal MMU, just without the safety of the MMU.

Threadripper Pro exists and as far as I can tell, certain industries are practically begging AMD to keep updating it. A system with 32-core TR Pro and a few hundred gigs of RAM is easily $10k. With a 64-core CPU, you are probably closer to $15k. If a Mac Pro can give you 40-60 cores, 128-512GB of RAM plus a powerful GPU for $10-20k, its certainly niche, but not dead on arrival.

I think the main issue is that while AMD can "justify" TR Pro by having disaggregated compute and IO chiplets, Apple does not. AMD can just "print" as many CPU cores as it likes (within the power budget), and then slap on a different IO tile depending on what product it's making.

Currently, Apple isn't doing that. Furthermore, they put themselves into an even bigger corner by gluing their CPU and GPU onto one die. Most professional tasks are fine with a monster CPU and no/little GPU, or a monster GPU and an ok CPU. Adding PCIe with support for GPUs would help with that. For memory heavy tasks, you could add CXL memory expansions. But that then adds a new problem: what dies would Apple fab for this product?

With M1, there were essentially 2-3 dies: The power efficient M1, the M1 Max/Ultra with the interposer, and M1 Pro (there were rumours some Pros are just failed Max-es with a part of the chip cut off, but afaik nobody was able to verify this, so 3 dies it is). For M2, we have only seen the power efficient die so far. If M2 Extreme would be 4x M2 Max, then the previous strategy could work. But if Apple wants PCIe or CXL memory modules on M2 Extreme, they have to put it on all of their Max (and maybe Pro) dies as well. Even though these will be in laptops/all-in-ones that won't use any of that. In other words, a ton of analog circuitry that's a complete waste of silicon. The only other option is to fab special dies for M2 Extreme, which might have been the plan, and what probably made it a very bad ROI.

It's kind of like Sapphire Rapids: SR is certainly fast for what it's doing, but it's super expensive compared to EPYC and less scalable exactly because you need different dies to implement different SKUs (SR is monolithic up to afaik ~20 cores and the "chiplets" only appear above that, plus the IO you get depends on the chiplets). And SR doesn't even include a GPU...

Finally, Apple's GPUs don't appear to be really scaling as great as they were hoping. I have yet to see a real-world M1 Ultra review that wouldn't end on a "it's +20-50% more performance for +100% price" note. The CPU cluster seems to be doing much better. But by tying four of them together for M2 Extreme, people who need CPU would have to pay for the whole thing, and people who need GPU would be probably left disappointed.

My personal "best bet" would be to just keep releasing a power efficient "consumer" die, but disaggregate everything on the "pro level": A single CPU-heavy "Pro" die with a bit of GPU and a bit of IO, then a GPU-heavy die that slaps onto that to make the Max, and then an IO-only die for the Mac Pro mixed and matched with a combination of CPU and GPU dies. I wouldn't be shocked if this was the plan for M3/M4, the question is if the packaging technology will be there in time (and economical; wink wink Intel).

Sure, Threadripper makes economical sense for AMD only when "subsidised" by EPYC/Ryzen sales and the shared chiplet architecture. But Apple has deep enough pockets for halo products. They are allegedly repurposing some of the binned/sub-par silicon into internal server hardware anyway.

So the argument that Windows is somehow responsible for the death of perfect 2x scaling is a bit exaggerated. People just want more space and anti-aliasing is mostly good enough so that no one cares.