> The volume of space from the ground to 50,000 feet is about 200x smaller than the volume from the Karman line to the top of LEO alone (~2,000 km).
Volume is the natural way to assume space scales, but it's incorrect. Two planes can fly parallel, side by side. Two satellites cannot orbit side by side.
In the limit, if Earth had a solid ring of infinitesimal width, it would take zero volume but all orbits.
The paper says we are 2.8 days away from a collision. It doesn't say we're '2 days away from kessler'. In fact, the paper explicitly warns against your interpretation.
> We emphasize that the CRASH Clock does not measure the onset of KCPS, nor should it be interpreted as indicating a runaway condition.
The stock market learns from experience, because it's made of people who learn from experience.
Imagine an investor's experience with TSLA. From the beginning, they're flooded with news reports about 'fundamentals' this, 'fundamentals' that, about how Tesla would imminently collapse, how it's a scam, yada yada. Said investors _constantly_ see themselves being right and those skeptics wrong. Tesla is in fact disrupting an industry. They really are just continuing to scale. Marginal profitability keeps going up. Their cars keep getting better. FSD keeps getting better. The competition that people kept pointing at kept failing to materialize. None of this seems to change the skeptics' byline.
Tesla is actually in a materially worse position than it was a few years ago, by many metrics, but the stock price isn't set by 'fundamentals', it's set by the people setting demand for the stock. With TSLA, this is disproportionately going to be people who have learned to and gotten rich from ignoring the people loudly telling them why investing in Tesla is a bad idea.
A market will correct eventually, but corrections either require people to change their minds or run out of capital. Neither has happened yet, so the market can't correct.
Indeed, Bayesian approaches need effort to correct bad priors, and indeed the original hypothesis was bad.
That said. First, in defense of the prior, it is infinitely more likely that the probability is exactly 0.5 than it is some individual uniformly chosen number to each side. There are causal mechanisms that can explain exactly even splits. I agree that it's much safer to use simpler priors that can at least approximate any precise simple prior, and will learn any 'close enough' match, but some privileged probability on 0.5 is not crazy, and can even be nice as a reference to help you check the power of your data.
One really should separate out the update part of Bayes from the prior part of Bayes. The data fits differently under a lot of hypotheses. Like, it's good to check expected log odds against actual log odds, but Bayes updates are almost never going to tell you that a hypothesis is "true", because whether your log loss is good is relative to the baselines you're comparing it against. Someone might come up with a prior on the basis that particular ratios are evolutionarily selected for. Someone might come up with a model that predicts births sequentially using a genomics-over-time model and get a loss far better than any of the independent random variable hypotheses. The important part is the log-odds of hypotheses under observations, not the posterior.
...do you not see the parallel in the words you just wrote? That AI's value will continue increasing even as the buzzwords fall out of the public consciousness, just as crypto continued to gain value even as the buzzwords fell out of the public consciousness?
I think when most people talk about the "AI bubble bursting", they mean a dramatic end to this notion that AI is the "next big thing". Much like how we had Web3 and NFTs and all those other things that were going to change how we interacted with the internet.
Sure, my BTC is up, but I can go weeks or months without interacting with a blockchain in any way, directly or indirectly.
Valuations of individual AI companies might (and will) drop, but we are currently experiencing the least amount of AI in our everyday lives that we (or our children) ever will.
It's hard for me to respect the intrinsic superiority of a format whose main value-add is exclusivity, rather than fair market competition based on merits.
If theatres pivoted to competing first on format rather than exclusive access to recent releases, and managed to do well in that regime, I'm sure Netflix and other new media would be more than happy to indulge. Seems unlikely, though, doesn't it? The demand exists but I would be surprised if it was a quarter the size.
It‘s also hard to respect a format whose main value-add is quantity over quality, but that‘s Netflix‘s strategy. And will continue to be Netflix‘s strategy if they get WB.
If the award is already being given based on perceived quality, that would be handled by the existing rules. Low quality movies don't tend to win Oscars in the first place so that's hardly an argument for changing the rules to preclude Netflix releases.
Falcon Heavy is a huge outlier, and has never actually demonstrated the capability to lift close to its nameplate capacity to LEO. Falcon 9 is already volume constrained to LEO outside of Starlink or Dragon launches, and Starlink is packed incredibly densely to get to that point. When I ran the numbers some time back, New Glenn was similar to Falcon 9.
Increasing thrust by 15% doesn't just increase payload by 15%. I don't know a simpler way to estimate this than to run a simulation, and I don't have one with numbers I can toggle.
The really big change will be launch thrust to weight ratio. Going from ~1.2 to ~1.35 gives you 75% more thrust at launch which means you spend less time fighting gravity, less time in the thick parts of the atmosphere, and less time to get past the trans-sonic region.
There are other constraints on how quick the vehicle should be, even when engine performance allows: you probably won't want to hit maximum dynamic pressure in too-thick air.
Tesla got rid of radar because of sensor fusion, and particularly for reasons that wouldn't apply to high resolution radar. Sensor fusion with a high resolution source like LiDAR isn't particularly tricky.
Au contraire, the space program stalled because pouring national wealth into gigantic space projects was _too_ sustainable. The idea that NASA has had a lack of funding is a myth. The problem has long been them spending it ineffectively.
Volume is the natural way to assume space scales, but it's incorrect. Two planes can fly parallel, side by side. Two satellites cannot orbit side by side.
In the limit, if Earth had a solid ring of infinitesimal width, it would take zero volume but all orbits.