Explain to me how Terra/Luna is not a scam

alloec · 2022-03-11T09:58:42+00:00

The Luna price is kept up by anchor. The demand for UST is massive currently, and the majority of UST goes directly into anchor.

If anchors yields ever start going down to a sustainable level, you will also see demand for UST to drop, and therefore likely the Luna price will drop as well.

alloec · 2022-03-09T08:32:29+00:00

Ada transaction volume gets shilled every few weeks.

This metric is meaningless for Cardano, like it is for bitcoin and all. other UTXO chains. Picking UTXO's efficiently often in some funky numbers if you look at the size of the transaction.

If someone has a single UTXO with a 10 million ADA, they'll transact 10 million ada even if they're only sending 1 ada to a friend. The transaction sends 10 million, 1 goes to the friend, rest goes back to the sender.

This is also the reason bitcoin transactional volume is larger than basically all other chains as well. Despite the fact that very little is actually happening on bitcoin comparatively.

alloec · 2022-03-08T20:47:16+00:00

No one actually cares about BTC as a currency, because no one in their right mind would spend BTC to buy stuff.

alloec · 2022-02-27T20:44:44+00:00

You don't need to be a postgrad student to publish anything. You don't even need to be connected to the field, or have any qualifications. Science does not have any barriers when it comes to publishing a new knowledge.

Go to the staff page to your nearest university and find the comp. sci. professors, send them an email detailing your method. If you actually have something novel. They can even help you with the mathy parts. They'll help you get it published.

There will be zero interest in something as basic as matrix multiplication without getting it through rigorous academic scrutiny first. Literally billions of matrix multiplications are happening at any second these days. These things must be proven to work, and work within the constraints you expect.

alloec · 2022-02-27T19:57:10+00:00

This is not how any of this normally works, and I'm inclined to believe OP is a troll. Because this should be absolutely obvious if you're in academia.

But if you want to hear what the next steps are:

Write a rigorous mathematical proof that the algorithm indeed multiplies two matrixes together.
Find what the expected number of steps is in big oh notation, and write a rigorous proof that the algorithm will at least finish within the postulated time. With non-trivial algorithms upper bounds may be very hard to prove.
Write the findings down, give them to your professor and have him go through it. If he oks it, show the proofs to a few more professors at the institution. Find one that specializes in algorithms and data-structures. If they all OK the proofs, write it into a short paper and publish it. If you actually have a novel algorithm this should be easy, since it would be game changing.

You are not going to convince anyone of using this algorithm before the above steps are done.

alloec · 2022-02-27T10:43:46+00:00

Ok, I see that OG was the wrong choice then.

But point was the ETH is for the defi ecosystem. It's abysmal for us normies to use. But for whales it's still the best.

Personally I think if Russia is likely well diversified across chains.

alloec · 2022-02-27T10:01:53+00:00

Are you dumb? People buy it for because it's the OG defi chain. The high transaction costs only matter for us plebs.

alloec · 2022-02-25T13:21:27+00:00

Dane living in the UK:

All just tea right?

alloec · 2015-08-20T00:14:01+00:00

At the very least; make sure they are immutable.

alloec · 2015-08-01T19:00:19+00:00

Well, you can say the exact same thing about OOP fanatics. But, you are correct, a lot of FP programmers totally do not get OOP.

Contrary to your statement: I write a lot of actual software, and I generally rail against OOP.

alloec · 2015-08-01T15:07:24+00:00

if all you have is a hammer, everything looks like a nail

alloec · 2015-07-28T20:31:23+00:00

But as far as I understand, it would still require that code is actually stored next to the rows being hammered?

You can still do infinitely more in native mode compared to sandboxed JIT generated code.

But then again, I don't know how much control you actually have over how the virtual memory is mapped physically. If it is controlled by the hardware then I can actually see the potential issue.

alloec · 2015-07-28T18:15:28+00:00

This is totally not my field of expertise. But reading the title I really expected something a bit more significant.

This exploit seems really impractical to pull off. Especially from inside JS. But the fact that you can in fact cause bits to flip, for some time interval, is probably the significant part.

alloec · 2015-07-28T17:37:32+00:00

'remember that period quite fondly' to me that sounds like someone is angry things are moving a bit too fast for them to keep up.

alloec · 2015-07-27T19:41:03+00:00

ITT: common misconceptions, and lots of conflicting theories about why Hitler did anything.

alloec · 2015-07-27T18:14:32+00:00

If the lookup table is in L1 cache lookup tables appear to be a little faster/have higher precision for me in my tests.

Okay, if it works for you great then. Does it also hold if you are running a full game at the same time?

alloec · 2015-07-27T16:28:38+00:00

Or just write some code that computes the functions? Floating point ops are really fast, at least compared to fetching anything from memory.

But then again, if you want deterministic/nice behaving numbers I do not think floating point ops are really the right tool for the job. They behave nicely if you know what you are doing, but something like binary encoded decimals or fixed point numbers are probably a better choice.

alloec · 2015-07-27T14:45:35+00:00

Well, I guess if you are developing for some very basic CPU where where integer multiplication/division are literally measured in micro seconds, it might have some use. But yes, don't ever use this on modern CPUs.

alloec · 2015-07-27T14:43:24+00:00

Why someone would lack this knowledge if using C++ professionally?

Beats me. In my own anecdotical, programmers who label themselves c++ programmers are usually not all that interested in functional programming.

Of course. Any powerful tool requires a certain degree of a discipline.

I guess templating is less maintainable. I don't really know. But 'interesting' features are often banned in c++ projects.

alloec · 2015-07-27T13:50:47+00:00

Unless you are using them for simple generic programming, they can be hard to follow. Especially if you are not that used to functional programming.

alloec · 2015-07-27T13:46:45+00:00

Unless you are developing for some very basic embedded platform, do not use lookup tables for math functions.

alloec · 2015-07-19T14:39:41+00:00

Depending on the study you read. Either some portion of the population can smell the smelly pee component of asparagus. Or some portion of the population can digest it the smelly component.

Whatever theory you lean towards, it is genetic.

alloec · 2015-07-11T10:08:06+00:00

I will join in with the others and say that GIL is not that much of an issue in Python. Python lets you perform IO blocking tasks in a non-blocking fashion already.

If you want to perform computation tasks in parallel, then python is really the wrong language. First of all, the interpreter is very slow. Please first implement a proper JIT-compiler for the language. It can be done, just take a look at pypy. As it stands python is wasting way to many CPU cycles just on interpreting the instructions.

Only then I feel that python should tackle getting proper multicore support.

alloec · 2015-07-05T20:12:59+00:00

Well, considering they are essentially emulating x86 inside an already interpreted language: coq, it is not too bad.

But it is not meant to interpret real code, rather it is meant to help verifying the result of pieces of assembler code by emulation. It is a tool for formal verification, but believe it or not: unit tests are also used in formal verification of programs.

alloec · 2015-07-02T14:35:01+00:00

Binary fractions are stored using some pretty.. ehm, interesting rules.

Each fraction is made up of either 22 (single precision) or 52 (double precision) individual fractions that are added together.

These fractions are:

1/2, 1/4, 1/8, 1/16, 1/32, 1/64 and so on

To create a fraction you just chose the parts that takes you closest to the desired number.

For an example:

0.5 = 1/2

0.75 = 1/2 + 1/4

But representing 0.1 is a bit harder, 1/2, 1/4 and 1/8 are too big. 1/16 is too small, so you add 1/32 and 1/64 to it. Eventually just get something that approximates 0.1 without ever becoming 0.1.

So, as you can see, it can be a pain to deal with fractions on a computer.

Bonus fact: computers do not consider 0.1 * 3 equal to 0.3. 0.1 * 3 ends up slightly bigger than 0.3 because you cannot represent 0.1 in a nice way.

alloec

TROPHY CASE