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Comment Re:Solution looking for the wrong problem (Score 2) 19

ED: Looks like it's 24(!) hives per beehome, and they charge $2k delivery ($83/hive) plus $400/mo ($400/hive/yr) for maintenance.

Clearly not something of use to amateurs, and I'm not sure whether you can make that economics work out for professionals, either. I guess it depends on how truly independent it is, vs. your local labour costs.

Comment Re:Solution looking for the wrong problem (Score 3, Interesting) 19

There is little correlation between "presence or absence of pollution" (what a general term to begin with...) and CCD. There is a strong correlation with the presence / absence of varroa. And this system treats varroa.

I've been thinking about getting into beekeeping (I first need to increase the accessibility of my ravine where they'd be), and had been thinking about a sort of high tech solution, with electric blankets, heat-exchanging baffles, a flow hive, and maybe some mass and/or noise sensors for monitoring colony health. But this is WAY more high-tech than I envisioned, and honestly I'm scared to even look up the price ;)

Comment Re:No success? (Score 1) 137

Leaders aren't there out there e.g. building the rockets or doing the vast majority of the engineering. Musk doesn't get credit for that. But they do set the culture and direction for their companies. And in this regard, the "build quickly, launch quickly, fail quickly, learn quickly, and iterate quickly" culture developed for SpaceX happens to be very effective. Musk gets credit for instilling that. Another thing he should get credit for is the broad design strokes such as "focus on designs that are cheap enough that they can be mass produced, gaining you economies of scale and the ability to iterate quickly during testing, but are still capable of being reused" (this differs from the two previous predominant paradigms, either super-expensive low-volume reusables, or cheap high-volume disposables).

I don't like the guy, but absolutely, credit where it's due.

Comment Re:Erm... (Score 5, Interesting) 137

I think a lot of people miss the fact that SpaceX engineers know very well that what they're doing might fail spectacularly, and that this is the cost of speed.

A random example: autogenous pressurization.

It's beneficial to have a rocket's engines pressurize the tanks themselves rather than to haul up pressurant tanks and a separate pressurant. But it's surprisingly tricky. For a methalox rocket, you ideally want hot methane injected into the methane tank, and hot oxygen into the oxygen tank. But hot oxygen is very difficult to work with in an engine, as it tends to eat your engine.

If you're still working on reliably producing hot oxygen, there is a hack available to you, but it's not pretty: just inject exhaust into the oxygen tank; after all, it's not combustible. BUT, it is water and carbon dioxide. Both can settle out as frosts or plated ices, and in the liquid, the water ice will float at the top, while the CO2 will form a snow at the bottom. Frosts / ice plating can block e.g. your RCS jets. The CO2 snow will kill your engines. You can put in filters around their intakes, but it'll clog your filters. You might try expanding the filters, and maybe that'll work for a while, but then you rotate the rocket, the snow rushes ti one side, and a bunch of engines die from clogging. You may put some big mesh plates across the whole tank to keep the snow off the bottom, but they can cause their own problems with fluid flow and still sometimes clog or let snow through during maneuvers. Etc.

So then comes the question: put Starship on hold while working on getting the engines to reliably produce hot oxygen, potentially for years, or forge ahead with a hack solution that you know has a reasonable chance of killing your rocket?

To SpaceX, the question is obvious. You cannot afford to give up years of critical flight data just to avoid some booms. The decision is immensely lopsided in favour of "put in the hack solutions and launch, while you work on the proper solutions". Because you learn SO much from every launch that can be used to evolve your design. And you also learn so much from every rocket that you build, whether you launch it or not, so you might as well launch it.

To be clear, you don't want to lose rockets due to doing stupid things. Like, for example, if it turns out that some SpaceX engineer installed the wrong COPV and caused the recent pad explosion**, basically the only thing they would learn from that is "have tighter controls on your COPV processes", which isn't at all worth the cost of the explosion. But in general, if you launch and it clears the pad, you're getting good, important data from it, it's worth it even if it blows up seconds later, and it's on to the next evolved version of the rocket in your production sequence with both production- and flight lessons learned.

** It's clear that the recent explosion was from a COPV failure, but it's unclear why. Some claimed leaks state that a COPV may have been coded to a higher pressure than it actually was during production, so when they scanned it it checked out as being the right tank, but actually was not designed to handle the needed pressures. But I'll wait for official confirmation on this. SpaceX only makes some of their COPVs, usually not the smaller ones - ones that have washed up ashore were made by Luxfer. So this could be a supplier problem, like the strut failure on a 2015 Falcon flight. But again, too early to say.

Comment Re:Erm... (Score 2, Informative) 137

"What am I missing?"

That the author of this article is an idiot.

Yes, humans went to the moon in the 1960s. It also consumed a huge chunk of the federal budget. Adjusting for inflation by NASA's NNSI inflation index, the entire Lunar program cost $288,1B. If the US were to prioritize a project to the same degree today as then, accounting for GDP growth in inflation-adjusted terms, it would be $702,3B. NASA's annual budget is around $25B.

The cost of access to space today is a tiny fraction of what it used to be, when accounting for inflation. And keeps pushing lower. No, it's not "easy", but it absolutely is being done.

Comment Were they that good or trained on similar problems (Score 1) 69

Made it to the BBC too. tldr, sounds great but:
1. They apparently used puzzle cases that would be hard for humans. Is AI more on a par with humans for non-puzzle cases?
2. How sure are we that the quoted models have not already been trained on those puzzle cases, or other cases perhaps in medical school exams that were created based on knowledge of them? It sounds pretty suspicious for such a disparity.
3. If doctor sees two potential solutions with similar probability (maybe 60% vs 70%) they might pick either one, but a computer likely would pick the more probable one. What was the reason humans were bad at it. Was it just tons of data they could not crunch and so they got fooled by the most obvious points which (being a puzzle problem) tricked them as planned?
4. So how do doctors usually handle difficult cases IRL? IANAD but my guess is something like: Local doctors don't know and (possibly after lots of consultations and time lost with wrong treatments) send the patient to a top tier medical research facility where the world's top experts are. More tests are implemented to narrow down possible diagnoses. Then I am guessing treatments are executed and as they fail other treatments are given. Maybe a researcher picks them up for a new study, etc. An LLM doesn't actually care about healing the sick, it is just a math problem. Humans I am guessing are going to try to heal them by trying different things and I am guessing this is actually how it works. It isn't clear the AI will actually deliver the best results in the end, with the exception that it saves a lot of wasted time and costs (unless it ends up costing a lot to use an AI, because medical industry and liability).

Comment Re:Makes sense. (Score 1) 38

Yeah, I once looked into them and got sticker shock :P That said, the prices are coming down. The research seems to continue to show that they're safe for humans (although from the data I've seen I doubt they're safe for houseplants; their cuticle is much thinner than our skin). But for us... it can't penetrate dead skin, and while the outer layers of our eyes are alive, the cells there are constantly being shed and replaced.

Comment Makes sense. (Score 3, Interesting) 38

It makes sense. Clavascidium laciniatum forms a biological soil crust in harsh areas like Joshua Tree. And it's incredibly slow growing. So the rate at which it accumulates UV damage versus the rate at which it can repair itself is super-high. Hence it's been under intense selective pressure to develop good resistance to the ionizing radiation damage caused by UV.

Comment Re:AI is great for project localization (Score 1) 239

Long time resident, have recently asked Claude to check my translations and flag any bad problems. It is really good at catching typos I missed even when reviewing when I'm tired and has recommended grammar or stylistic changes that make it sound better. But this is just writing technical docs, not prose! It is good at telling me what is more common usage (which is great since obviously it knows common usage really well) and can tell me why. Actually it is really good as a living dictionary and never gets tired ;) But.. never trust Claude to translate a spreadsheet without skipping rows. I made a pretty tool with it but only after realizing how cavalier it could be, saying it had checked things it didn't, etc.

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