The cost of development for the Falcon 9 and Falcon Heavy were incredibly low and they are currently the cheapest way to get cargo into orbit. So, for these two programs, SpaceX has been cheaper than any government run program.
Flacon 9 : $2600/kg Falcon Heavy : $1500/kg Long March 5 : $2800/kg Everyone else : $4000+/kg
The Dragon space craft and the Falcon 9 together received about $400 million in tax payer money to design. The total cost of development for the Falcon 9 was around $400 million. SpaceX spent an additional 100 to 200 million dollars to develop the Falcon Heavy. For comparison, the Starliner space craft cost the US tax payers about $5 billion. The US tax payer paid around $25 billion to develop the SLS. The space shuttle cost about $30 billion to develop in today's dollars. The Saturn V cost about $50 billion to develop in today's dollars. The SLS and Saturn V could take over 100 tons to orbit. The Falcon 9 and Falcon Heavy can take about 22 tons and 63 tons to orbit. If successful, the Starship will deliver 100 to 150 tons while recovering both stages or 200 tons to LEO without recovery.
The cost of development for the starship first and second stage is about $5 billion so far. Elon is hoping the total cost will be $10 billion. If SpaceX can get the lower stage of Starship to land softly 95% of the time and the second stage is able to deploy satellites without blowing up, then the cost to LEO for Starship will be on the order of $1100/kg. If SpaceX can get both stages to land softly, then the cost to LEO will be less than $100/kg, a factor of 11 reduction! (Elon has stated that SpaceX may be able to reduce the cost to LEO to $20/kg if Starship is able to recover both stages.)
In summary, so far, SpaceX had been much better than anyone else at developing the best rockets on earth (best both due to reliability and cost per kg to orbit) more cheaply than any other rocket development program.
I guess the silly metric that we look at the most is GDP/capita. I looked at the Wikipedia IMF nominal GDP per capita https://en.wikipedia.org/wiki/... and that shows that between 1980 and 2020, the US, Germany, UK, Italy, and France grew by 410%, 326%, 276%, 275%, and 211% respectively (the Berlin wall fell in 1989, so I am suspicious of the cited GDP per capita in Germany in 1980.) If we adjust for inflation using the CPI, we get a real growth of 56%, 29% 14% 14% and -5% respectively. So, by that metric, the US has done relatively well compared to Europe. I think the PPP figures (purchase power parity) is similar. I did not look at other date ranges.
Another perhaps less silly metric would be the growth in median income after taxes after paying for health care and adjusting for PPP. The closest I could get for that was median disposable income which does not include health care as far as I can tell. I asked GPT to do the computation and it got 133%, 80%, 68%, 49%, and 76% respectively for the same countries. Again the US did the best by that imperfect metric. I suspect that if we included health care costs, the US would not do as well. (See https://www.oecd.org/en/public...)
So, it seems to me that the quality of life in Europe may be better because of better health care and less worry about retirement. On the other hand, over the last 40 years, the US seems to be a bit more innovative and there is more opportunity to become very rich in the US. Demographic changes will hit Europe harder over the next 40 years if the fertility rates do not change a lot. On the other hand, who knows how AI will change things.
So, our data is constantly leaked. One reason is that there usually isn’t much of a penalty. If consumers were paid $10 every time their data was leaked, then leaking the data of 10 million people would cost $100 million. Consequently, entities that hold the data would be more careful or might decide that storing customer data isn’t worth the risk.
How could they be more careful? For one thing, customer data should always be encrypted. It appears that combining homomorphic encryption with zero-knowledge proofs could keep all the data distributed and make access more difficult. While this approach would significantly slow down data access, if a company had to pay $10 to each customer in the event of a data leak, the delay might be justified in many use cases.
https://github.com/ldsec/drynx https://arxiv.org/abs/2410.155...
Also, computer AI's are proving theorems. They are not good theorems, but they are theorems that other mathematicians did not want to bother proving. So, in this case it is "new" knowledge, but not new novel knowledge.
When I look at AI generated images I often feel like I am seeing something that is new and novel.
Given the surprising fact that the SpaceX Starship is doing well with its test flights, the SLS is no longer a good investment. The cost per launch of the SLS is estimated to be 2.5 billion. The cost per launch of the Starship will be less than $50 million and it could easily be as little as $20 million per launch.
2.5 billion / 50 million = 50.
(Also, the Starship has a payload capacity that is at least double that of the SLS.)
"The voters have spoken, the bastards..." -- unknown