Whether someone is a victim of assault or rightfully practiced self-defense is often a difficult question dependent on the states of mind of the people involved in a volatile situation, remembered through the veil of faulty human memories. Details like who used force first are pretty much impossible to determine without a video recording. Of course, police officers are as fallible as anyone else. Defamation requires a willful disregard for truth, and I have a hard time believing that “they committed assault” would be defamation when “they got in a fight” is accurate.
For what it’s worth, I consider myself a liberal, and I went to a liberal arts college cut from the same cloth as Oberlin and wrote anonymous posts debating what I perceived as the excesses of liberal campus activists.
I’ve thought along these lines myself, and I do wonder if we’re going to approach general AI by finding ways to “compress” a simulation of a human brain, or just by coming up with new neural net architectures. The second approach is the one everybody’s working on, and to me it seems more practical.
How many particles make up a human, and how many transistors does it take to simulate the behavior and interactions of all those particles? How much energy does it take to power that many transistors? How does that compare to the Sun’s output? There are a few of the questions we need to answer before confidently predicting that we will ever be able to make a physics-based human simulator.
I heard a similar scenario as a plan to kill mosquitoes. I’m not sure how it’s supposed to work but a lot of smart people seem to believe it’s possible.
We can float things in the earth atmosphere at sea level. My completely ignorant prior is that we should be able to do it there too, if the temp and pressure are the same.
Maybe your colleagues perceive that they are being asked to study a bunch of off-topic material. Is reading RFC 2119 really the most productive use of their time?
Agreed, I should have specified that all-seasons are the safe option in some parts of California. My frame of reference is the warm climates of Silicon Valley and SoCal. Summer tires could even lose traction in one of the colder nights in a San Jose winter.
Does Google get false positives (incorrectly detecting a mistake and “fixing” it?) or false negatives (failing to detect a mistake you make) more often? Is it possible that cognitive biases prevent you from giving Google credit when it fixes your mistakes? Is it possible Google has done extensive studies to find the preferred trade-off? Is it possible that your preferences are different than the average person because you’re an engineer?
This is a forum for hackers, who are likely to obsess over systems like this. I don’t think it’s indicative of a society-wide focus on Uber passenger ratings.
In California, summer tires get the best traction and all-seasons are generally worse (many people mistakenly believe that all-seasons perform better than summer in the rain, I suppose because winter is the rainy season here).
“Spend other people’s money” is a really weird way to put it IMO - people chose to invest in the company because they thought it was a good investment. Investors would rather have the stock than the cash they paid for it. When the company does a buyback, the shareholder investment in the company becomes more concentrated. Each share represents more stock and less cash, making it possible to construct a higher-equity lower-cash portfolio. This more purely fulfills the investor’s revealed preference of owning the stock. If they change their mind, they can always sell.
Our tax policy encourages this. You can write off the interest you pay to bondholders, but you can’t write off the dividends you pay to shareholders. Everyone involved (except for the government) is better off if you sell bonds and buy back stock.
Perhaps it’s all good when the implementers work for the architects, but when the architects are designing an interface that is going to be sold, it has to be something people want to use.
I’ve worked on projects designed by architects. They had big, beautiful interfaces defined by types. When I implemented the interfaces, working systems magically appeared. But it was my job to implement the interfaces. They didn’t get organic adoption from other engineers. Nobody was voluntarily choosing to implement their system via the big beautiful interface. These projects ultimately failed.
Projects I’ve worked on that succeeded had small, comprehensible interfaces. Engineers can quickly understand how to use them and see what the benefits are. The pitch is “our service does this one thing you need,” not “build your entire project by implementing the interface of our type-safe general data processing system.”
Don’t make excuses to yourself when you know there is a problem with your code. Don’t say “well, it will only fail in these edge cases and I know not to use it that way.” You’ll forget, or someone else will use it the wrong way and it will break. The easiest time to fix it is when you are already working on the code and first notice the problem, not later.
I think a more reasonable attitude is that it’s usually possible to improve your material wealth with effort, and people can decide to make the trade-off if they think it’s worth it. This is not a value judgement.
If juries are allowed to go around awarding billions of dollars to individuals, the big bad wolf won’t be around for long. I hope whatever we replace capitalism with is good!
It may seem obvious with the benefit of hindsight, but I would have guessed that the better answers might be different in terms of word choice or style.
I’m not downvoting you but I’m skeptical that the problems with homelessness can be fixed by putting more money toward mental health care. Are there a lot of skilled mental health practitioners who aren’t working due to a lack of demand?