• 0 Posts
  • 7 Comments
Joined 2 years ago
cake
Cake day: June 12th, 2023

help-circle



  • Well it all depends on what you want to do. I interpreted your question as we need to go there asap, what can we do? And then the answer is we can do an crewed orbit in about a year time.

    If we just want to do it with a good chance of survival, building all the shit we need, but still get there soon, the answer would be different. If we just want to go fast, we would probably use all our heavy lift vehicles to build a moon vehicle in LEO. Then put a big ass engine on that and a bunch of fuel and launch the whole thing to the moon. That’s something we could do within 5-7 years if we would put our minds and money to it. I feel the suits we currently have in development could be ready within that time as well. The lander would be a problem however, we don’t have any of those in development right now. Blue Origin has their Blue Lander, but that’s been on the drawing board for so long now. They did get extra funding to get it ready for 2030, but haven’t shown their progress publicly, so who knows how far they are. On the other hand, if we want to take some risks for this special mission I’m sure we can get something together in 5-7 years if humanity unites and puts their weight/money/faith behind it.

    However if we keep going like we’ve been going since Apollo was cancelled, we are never going to get there at all. The politics are complicated and the private sector has been hit or miss. Plus with the Musk factor, we don’t know what’s going to happen. I have zero faith in anything we have going right now.


  • At the moment, we just cannot.

    We don’t even have space suits that can operate on the moon. The stuff they use on the ISS is made to be used in a total vacuum only, not walking around in the dust and on sharp rocks. There are new suits in development, but nothing final as far as I know. I’m not sure if any are close to being finished, let alone tested and certified.

    There’s also no vehicle that can land on the moon with crew right now. Nasa is relying on SpaceX to get their Starship program to the point they can do it. People are divided on this, but anyone with technical knowledge I heard about this say the SpaceX program is very challenging and probably not feasible. Especially with the super optimistic timelines they’ve been throwing around.

    In theory you could put a Crew Dragon with a big trunk of supplies on a Falcon Heavy, which has the delta-V to go to the moon. But obviously that’s pretty risky, once you go you’re committed. When working in LEO you almost always have some kind of disaster recover scenario available where you abort and get back to earth asap. If you are underway to the moon, there is no turning back. The Crew Dragon has very limited mobility. But I think a trans-lunar injection and orbit around the moon would be possible, with a free return trajectory. So if going around the moon is good enough, that would be possible.

    Still it would probably take 9-12 months to put such a mission together and it would be very risky indeed. And like I said, landing on the moon is a total no-go right now.

    We should ask Scott Manley to do a video about this, I would love to hear his thoughts on this.



  • One thing I’ve also noticed is people doing code reviews using ai to pad their stats or think they are helping out. At best it’s stating the obvious, wasting resources to point out what doesn’t need pointing out. At worst it’s a giant waste of time based on total bullshit the ai made up.

    I kinda understand why people would think LLMs are able to generate and evaluate code. Because they throw simple example problems at them and they solve them without much issue. Sometimes they make obvious mistakes, but these are easily corrected. This makes people think LLMs are basically able to code, if it can solve even some harder example problems, surely they are at least as good as beginner programmers right? No, wrong actually. The reason the LLM can solve the example problem, is because that example (or a variation) was contained within its training data. It knows the answer not by deduction or by reason, it knows the answer by memorization. Once you start actually programming in the real world, it’s nothing like the examples. You need to account for an existing code base, with existing rules, standards and limitations. You need to evaluate which solution out of your toolbox to apply. Need to consider the big picture as well as small details. You need to think of the next guy working with the code, because more often than not, that next guy is you. LLMs crumble in a situation like this, they don’t know about all the unspoken things, they haven’t trained on the code base you are working with.

    There’s a book I’m fond of called Patterns of Enterprise Application Architecture by Martin Fowler. I always used to joke it contained the answer to any problem a software engineer ever comes across. The only trick is to choose the correct answer. LLMs are like this, they have all these patterns memorized and choose which answer best fits the question. But it doesn’t understand why, what the upsides and downsides are for your specific situation. What the implications of the selected answer are going forward. Or why this pattern over another. When the LLM answers you can often prompt it to produce an answer with a completely different pattern applied. In my opinion it’s barely more useful than the book and in many ways much worse.