The rocket can still explode while in space and parts of the rocket can reach the ground without burning up.
Thats not a big risk with rockets built mainly out of aluminium etc, but Starship with its stainless steel that can handle higher temperatures and its heat shield is more likely to reach the ground.
The 11 Starships that have gone through re-entry have so far had no issues with reaching their designated landing zone/spot in one piece (except from some minor parts melting off in their earlier V1/V2 flights).
So far SpaceX has shown that they are willing to play it very safe, but there is always a risk and their future re-entries will also do go over land like Flight 15 did.
TFA mentions low end is higher risk; it would seem foolish to assume the cheapest wines have been faked, and if they somehow had been, even more foolish to assume the buyers even cared.
It is definitely in the spirit of the story of Mel, since Tom was exploiting an intimate knowledge of the machine to achieve the impossible by using instructions in unintended ways, but always remember that Tom is not a real programmer:
Real Programmers wrote in machine code.
Not FORTRAN. Not RATFOR. Not, even, assembly language.
Machine Code.
Raw, unadorned, inscrutable hexadecimal numbers.
Directly.
That said, I prefer Tom's story. It's more about the joy of understanding the machine than it is about the framing of a legend.
Most of the "laws" of economy in this form say often as a footnote "all else being equal", which remains to be seen. Otherwise you can justify any attempts at price decrease in any industry the same way.
> it’s quite rational that demand increases as price decreases
This is not necessarily wrong, but neither is it right; it is underspecified. Even if we were ignoring other factors and taking into account only the assumptions of a classical economic model, the shape of the demand curve still depends on the size of the market and the price elasticity of demand.
I absolutely disagree number of users is saturated. Fortune 500 companies, for all of their 'AI accelerating' shareholder speeches, are doing very little to actually integrate or spend on AI for the average employee. I've talked to a lot of people who work white collar jobs that could absolutely be accelerated by AI, and they just... aren't using it at all. Some of the companies make Copilot available. Some people just copy paste their tasks into the free version of chatGPT and spend a lot of time correcting the dumb model. A lot of orgs are concerned about data leakage and just have a blanket AI ban.
I recently joined a software dev team in which nobody is using any AI at all. They weren't conceptually against it, they just didn't feel the need to change their process.
That doesn't make them more money. Those people who aren't maximizing their AI subscriptions already have an AI subscription. If anything this would hurt AI companies if people were actually using the compute they have access to with their subscription, instead of how it is right now where most of these underused subscribers are floating the people who are really using it.
> I don’t think this is naive at all; it’s quite rational that demand increases as price decreases, which does seem inevitable.
But that's not what OC is saying, isn't it? Frontier models becoming better and cheaper at the same time are not a given.
Near-frontier models that have 99% of the capabilities of frontier models, at a tenth of the cost of frontier models, might ironically be what pops the bubble.
CPUs (and a million other things) got better and cheaper with time, I see no reason that AI would be any different.
The distinction between frontier/non-frontier models doesn’t matter much here, for the overall market. With CPUs, for example, Pentiums got better and cheaper while Cyrix/AMD did the same.
The real question is not if the technology is going to get better and cheaper, but rather if it's going to meet the market expectations to justify trillions of USD in valuation.
1. What you want changes as the market does, in the way people use agentic coding now rather than just cheaper versions of Cursor autocomplete
2. Frontier labs are cheaper than open-source models too
Is there seriously a non-frontier model out there that can do what Opus 5.5 does? I can say: go look at a ticket in Jira and figure out how to fix it, write end to end tests for it, make sure it aligns with previous architectural decisions we've recorded in documents, and then test it, summarize all the testing you did, and open up a PR for review?
Anthropic, for one, doesn't seem to be replacing their human engineers and data scientists with Opus 5.5 yet even when they would be better positioned to do so than any other company. https://www.anthropic.com/careers/jobs
A 10x will always be beat by 10x+ai. But ai+10x is better than just ai. The world has an over supply of ai (or soon will) but a finite number of 10x coders.
To me it’s more about the scale of these numbers. After billions, people (like me) kind of lose intuition about how gigantic these numbers actually are. Yes GDP has time in its unit, but it still gives a general idea of the size.
I’ve set a hard rule for my agents to “never add all files, never commit all files, always reference the specific files you are adding or committing”
They violate it so regularly that my “git” command is now a wrapper, when the agent fucks up and tries to add/commit-all anyway, it now gets a nastygram error chiding it for not following instructions.
I think solyin is trying to imply that the anti-AI sentiment is as formulaic as any hopped-up markov chain. So perhaps a better way of rephrasing their question is "What's it like to be meat?"
https://en.wikipedia.org/wiki/Spacecraft_cemetery
were these other craft not headed for Point Nemo? if not then wtf
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