kotlin2

7 ms·

1.
by kotlin2 4y ago
Digital ocean doesn't charge traffic costs. I'm not sure if that was used in the article, but DO can provide significant savings for high-bandwidth services.
2.
by kotlin2 4y ago
People, even those at other big tech companies, unironically refer to working at Google as "retiring." Not sure 'big tech' is a great example to use when talking about productivity.
3.
by kotlin2 4y ago
Is there hard data on how deadly they are vs. other auto manufacturers? There is definitely a narrative that the cars are dangerous, but I'd like to see that quantified.
4.
by kotlin2 4y ago
You can also use green hydrogen in place of blue hydrogen, e.g. when making ammonia.
5.
by kotlin2 4y ago
I think LoC has been determined to be a bad productivity metric because it’s gameable and incentivizes bad behavior. However, that doesn’t apply here as the engineers didn’t know they were going to be evaluated by LoC a priori. I struggle t
6.
by kotlin2 4y ago
A world where your cash is held in British pounds? Why do you accept forex fluctuations but not security fluctuations?
7.
by kotlin2 4y ago
I’ve worked in big companies and I’ve worked in small companies. The one constant has been that writing code is required to make product changes. No code likely means no changes. Maybe LOC != productivity makes sense when algorithms are of
8.
by kotlin2 4y ago
Judging the sizes of the stacked pages from the last 60 days of code would probably be a pretty good indication of productivity. Perfect? No. Good enough? Maybe.
9.
by kotlin2 4y ago
Equity in Meta is liquid net worth, unless you're a materially important share holder. The stocks you hold right now can be converted into cash easy at any point in time. In what world is that nearly equivalent to cash?
10.
by kotlin2 4y ago
Large public companies aren't innovators. Innovations requires risk. Meta is a huge part of retirement portfolios and pensions, which are extremely risk averse. There is an expectation that the company is going to do an efficient job a
11.
by kotlin2 4y ago
Companies are valued based on future cash flows. A stable company typically has a P/E ratio of 20. Meta’s is around 10, which is an indication the market believes profits will cut in half and then stabilize.
12.
by kotlin2 4y ago
That seems really inconvenient to be honest.
13.
by kotlin2 4y ago
I don’t think it’s valid to use “only” with “e.g”. “e.g” means it’s an example, which implies the existence of other cases that satisfy the criteria. “Only” implies some uniqueness of the subject.
14.
by kotlin2 4y ago
Why not try to service it yourself? It could be fun to take it apart and reassemble it.
15.
by kotlin2 4y ago
I think the backups end up stored in a GCS bucket in your account and can be removed manually or with an object lifecycle.
16.
by kotlin2 4y ago
What languages allow such a construct? It seems like it would be super confusing if these two code samples produced different values: # One a = d["a"]["b"]["c"] # Two a = d["a"]
17.
by kotlin2 4y ago
Ok, but what about the other 95% of emissions. We could just ignore what Russia does and still make a big impact.
18.
by kotlin2 4y ago
If d["a"]["b"] is 42, then how could d["a"]["b"]["c"] also be 42? What you want doesn't make sense semantically. Normally, we'd expect these two statements to be equivalent d[&quot
19.
by kotlin2 4y ago
c = defaultdict(lambda: 42) b = defaultdict(lambda: c) a = defaultdict(lambda: b) a["a"]["b"]["c"] # --> 42
20.
by kotlin2 4y ago
Now do an associative array containing another associative array.
21.
by kotlin2 4y ago
I mean what was the difference between your outstanding mortgage principal and the value of the homes at the time of default?
22.
by kotlin2 4y ago
How much did you owe after the properties were sold?
23.
by kotlin2 4y ago
In most states, lenders have recourse. So if you stop paying your mortgage, the bank will foreclose on your home and then come after your other assets to make up the difference in what you owe vs. what the home is currently worth.
24.
by kotlin2 4y ago
You could delist yourself from the phone book.
25.
by kotlin2 4y ago
Exactly. So your claim that: > So you can remove the ones that do not halt by inspecting them one by one and developing a specific algorithm for each one that determines if it halts or not. Is impossible. You can’t, in general, inspect T
26.
by kotlin2 4y ago
That's true. The part that "feels" weird is that there is no algorithm that could perform the separation into halting / non-halting subsets. Choosing elements from a set based on uncomputable properties almost feels like
27.
by kotlin2 4y ago
If you could inspect any Turing machine and devise a specific algorithm that determines if it halts, then you yourself would be an algorithm that solves the generic halting problem.
28.
by kotlin2 4y ago
In the proof you just provided, you have a step "remove ones which do not halt". By which process do you do that? By the halting-problem, you can't actually make that selection. This ties back into the fact that BB(n) is not
29.
by kotlin2 4y ago
I didn’t realize the initial state of the tape was part of the definition of a Turing machine. I was picturing having the same operations applied to different tapes, but that’s not the definition so I’m wrong.
30.
by kotlin2 4y ago
I'm unfamiliar with BB(n), so this raises an interesting question for me. How do we know that BB(n) exists for all n? This is relevant to this post because the author's definition of omega relies on BB(n) being defined for all n.

More ›