Obviously the black box can only record what the computer tells it is the state of the switches. There's no camera looking at the switches to confirm they actually were moved. No doubt the switches are wired such that a short or an open circuit will not fool the computer into thinking the switch was moved and shut the engines down. But if something caused the computer to think (pardon the expression) the switches had changed state, it would shut the engines down and the flight recorder would dutifully record this change of state.

Suppose for a moment a computer glitch did shut the engines down. The pilot, upon noticing this asks the copilot about it and he says, no I didn't shut them down. Knowing he has to do something, reaches over, flips them to off and back to on again to try to get them going again, after which the engines did restart but sadly not in time to prevent disaster.

Mods, this should not have been rated -1 flamebait! Totally inappropriate mod.

I deeply respect Captain Steeeve and his videos are great. Any nervous flyer should watch his videos (except the Air India ones!). And indeed Captain Steeeve's summary of the report is accurate. And his videos about the cutoff switches are accurate too. The chance of those switches being flipped inadvertently or on their own from mechanical wear and vibration is zero. And indeed the computer shows that inputs from those switches went from on to off and back to on again with timing suggestive of human intervention.

That said, one of Captain Steeeve's youtube collaborators, Garybpilot with whom he has done videos about Air India (Hanger Talk) has done his own videos on Air India. In one (https://www.youtube.com/watch?v=M0n3iIjvQk8) he mentioned that at Air India, there is not one pilot who believes the official report blaming the pilots. These are pilots who knew well both of the pilots in the cockpit on that tragic flight and find the suggestion difficult to believe. The Indian investigation board has been mired in political intrigue and controversy the whole time (before even). They were definitely under pressure to exonerate Air India and blame the pilots. Also to exonerate Boeing. Not that long ago a 787 had both engines shut down during landing. And there is a minor history of electrical anomalies on 787s, including RATs deploying mid flight for no discernible reason.

If the pilots did not shut the engines down, I don't think we will ever know what actually happened unless there is another accident. And given the problems Boeing has had in recent years (and other planes with engine shutdowns during flight), another accident is a possibility.

Those words were said, definitely. and the other guy responded, "I did not."

I don't know anything about what conspiracy theories are going around on the Internet, but I do know there among some professional pilots there is skepticism. There are no pilots at Air India who knew well these two pilots who believe they were simply suicidal. Plus there was at least one other incident this year with a 787 where both engines shut down during landing. The investigation has certainly been fraught with political tension. Obviously it's in Air India and Boeing's best interests to blame the pilots.

I find the various LLMs are helpful as a form of search engine, enabling me to drill down to potentially useful information more quickly. However at the same time they are far worse than a search engine because they aren't able to actually give you the sources to check. When ChatGPT generates a chunk of code, if you ask it where it got it from, it will say it didn't get it from a specific site, it just knows this stuff. Which of course ends up wrong half the time. So you end up with wrong stuff confidently passed off as accurate, which is ultimately stolen from real human sources. When I was in uni it was drilled into me to list my sources. Why should LLMs be held to any different standard? Google's AI summary does show sources, at least few, which is good. I always check them.

Even Claude AI which is supposed to be geared towards coding suffers from these same problems. I am trying to do some esoteric Qt 6 programming involving OpenGL, and all the AIs really struggle here because there's a limited amount of source material to steal from. It's certainly not capable of digesting the API documents and synthesizing code to do something without first seeing someone else's code. Claude AI seems to work best if you use a popular library or framework with lots of online discussion and github code for it. The popular languages and frameworks of the day.

Make more what? Dragon capsules? Currently SpaceX has no plans to make any more dragons beyond the five they currently have. I believe the fifth capsule had its inaugural flight this year with the private Axiom-4 excursion. These dragon capsules are currently rated for just five flights each, but SpaceX and NASA are working to extend their certifications to 15 flights each. Currently the contract with SpaceX does not include additional missions that would have been flown by Boeing. While it's possible NASA could try to buy some more flights, I don't think they will. SpaceX has the falcon 9 pretty well booked, and their other resources are fixed on Starship. I'm not saying NASA "needs" the Starliner, though. Just that it's not a simple thing to substitute Dragon for Starliner.

I think this view gives the crypto bros too much credit. They might now be thinking about taking advantage of the opportunity to wrestle the system away from the Wall Street bros, but there was no such plan.

To intercept them you still have to identify them, which you can't do until after they perform the sabotage. Given that, what's the benefit in sinking them rather than seizing them? Sinking them gains you nothing, seizing them gains you the sabotage vessel. It probably won't be worth much, but more than nothing. I guess sinking them saves the cost of imprisoning the crew, but I'd rather imprison them for a few years than murder them.

Well it's a problem or the US too. The last bastion of American industry is heavy equipment including construction and agricultural machines. Interestingly this is also a prime industry for Europe too. A lot of stuff is still made locally. But China is now making their own versions and just beginning to exporting them. And it's a double whammy. They can make them cheaper, but choose to just barely undercut western equivalent products (say by 20%), making a huge profit.

The Trump administration seems to think so. Increased government regulation through tariffs will fix it, along with bigger government. Ironic how the GOP has done a complete 180 over the years isn't it.

Except that in the case of Canada, there was a great deal of trade in both directions, in terms of commodities and also finished goods. It was a mutually beneficial trade arrangement too. It promoted the US' interests without ham-fisted authoritarian threats. This sort of trade made the US the powerhouse it was. In other words this was a sharp shift in US government attitude from one of friendship to one of an adversary (which is really how all relationships and business deals have ever been done in Trump's life). Sadly there's no going back. The damage is done and the US will never ever recover the good will and trade benefits it once had with its closest allies and trading partners, no matter what a future Democrat does to try to undo the damage, now that Trump's attitude has become the attitude of the GOP.

With China, though, there was no abrupt shift. China's goals have always been clear. The only thing they want from the west in terms of trade is raw commodities and foreign currencies. Whereas the west demands cheap goods, full stop. So China's domination of European industry and economies has been ongoing for years, and it's benefited by European policy and attitudes. China is happy to build high quality items and sell them for a premium, but there's no very little demand from the west. If there was demand, we wouldn't have seen local manufacturing capability disappear in the first place. Tariffs are not going to change these fact.

Very much unlike an intern (the doing-over part).

You ignored his core point, which is that "rocks don't think" is useless for extrapolating unless you can define some procedure or model for evaluating whether X can think, a procedure that you can apply both to a rock and to a human and get the expected answers, and then apply also to ChatGPT.

Heh. It says a lot about the pace of AI research and discussion that a paper from last year is "old".

This is a common thread I notice in AI criticism, at least the criticism of the "AI isn't really thinking" or "AI can't really do much" sorts... it all references the state of the art from a year or two ago. In most fields that's entirely reasonable. I can read and reference physics or math or biology or computer science papers from last year and be pretty confident that I'm reading the current thinking. If I'm going to depend on it I should probably double-check, but that's just due diligence, I don't actually expect it to have been superseded. But in the AI field, right now, a year old is old. Three years old is ancient history, of historical interest only.

Even the criticism I see that doesn't make the mistake of looking at last year's state of the (public) art tends to make another mistake, which is to assume that you can predict what AI will be able to do a few years from now by looking at what it does now. Actually, most such criticism pretty much ignores the possibility that what AI will do in a few years will even be different from what it can do now. People seem to implicitly assume that the incredibly-rapid rate of change we've seen over the last five years will suddenly stop, right now.

For example, I recently attended the industry advisory board meeting for my local university's computer science department. The professors there, trying desperately to figure out what to teach CS students today, put together a very well thought-out plan for how to use AI as a teaching tool for freshmen, gradually ramping up to using it as a coding assistant/partner for seniors. The plan was detailed and showed great insight and a tremendous amount of thought.

I pointed out that however great a piece of work it was, it was based on the tools that exist today. If it had been presented as recently as 12 months ago, much of it wouldn't have made sense because agentic coding assistants didn't really exist in the same form and with the same capabilities as they do now. What are the odds that the tools won't change as much in the next 12 months as they have in the last 12 months? Much less the next four years, during the course of study of a newly-entering freshman.

The professors who did this work are smart, thoughtful people, of course, and they immediately agreed with my point and said that they had considered it while doing their work... but had done what they had anyway because prediction is futile and they couldn't do any better than making a plan for today, based on the tools of today, fully expecting to revise their plan or even throw it out.

What they didn't say, and I think were shying away from even thinking about, is that their whole course of study could soon become irrelevant. Or it might not. No one knows.

Very interesting point. For all the talk of how efficient EVs are, the fact is at higher speeds you need much more energy to accelerate. In other words going from 0-20 in an instant requires not much kw compared to trying to accelerate from 60 to 80 mph.. This is why EVs have such ludicrous motor power ratings for their direct drive systems. And in reality all EVs have a gear train even if it's a fixed ratio with few parts. It's a real head scratcher why more don't use a two speed gearbox to better handle the difference in energy requirements for high speed acceleration vs low speed. Could use much smaller and cheaper electric motors too with good efficiency.