Sure, but “alpine villages” or something alike, were called “astronomical waste” in the MIRI’s language from the old days. When the “fun space”, as they called it, was nearly infinite. Now they say, its volume is almost certainly zero.
I know, that “Right now no one knows how to maximize either paper clips …”. I know. But paper clips have been the official currency of these debates for almost 20 years now. Suddenly they aren’t, just because “right now no one knows how to”?
And then, you are telling me what is to be done first and how?
As I see, nobody is afraid of “alpine village life maximization”, as some are afraid of “paper-clip maximization”. Why is that? I wouldn’t mind very much, a rouge superintelligence which tiles the Universe with alpine villages. In the past discussions, that would be “astronomical waste”, now it’s not even in the cards anymore? We are doomed to die, and not to be “bored for billion of years in a nonoptimal scenario”. Interesting.
Okay, I didn’t know that. I find all his accounts quite interesting to read, and quite consistent with each other, too. Despite the fact, that they are from different times.
On topic, he was quite wrong in this particular Ukraina-Russia case. But who wasn’t?
FYI, Samo Burja’s username here is [removed by Ben Pace].
After nearly 300 years of not solving the so-called Fermat’s last problem, many were skeptical that’s even (humanely) possible. Some, publicly so. Especially some of those, who were themselves unable to find a solution, after years of trying.
Now, something even much more important is at stake. Namely, how to prevent AI to kill us all. The more important, but maybe also even (much?) easier problem, after all.
It’s not over yet.
A Neural Network, observing itself, instead of some other input, could be intriguing, if not perhaps even conscious? The input layer is smaller than all those hidden layers and synapses between them. But the input layer may hover across its own interior, just as it normally hovers over many cat pictures. Has anyone already tried it?
It was a slippery slope, with those Neural Networks. They were able to do more and more things, previously unimagined to be possible for them. It was a big surprise for everyone, how good they were at chess, 3600 or so Elo points. Leela Chess Zero invented some theoretical breakthroughs, soon to be exploited by more algorithmic, non-NN chess engines like Stockfish, for its position evaluation function. Even back then, I was baffled by people expecting that this propagation will soon stop, due to some unexpected effect, which never came. Not in chess, nor anywhere else.
It was indeed a matter of “when”, not of “maybe not” anymore. Yes, those first mighty AI’s were quite fake, they have no real clue. Except that this mattered less and less and it was less and less true. In an increasing number of fields.
It was only a matter of time when the first translators from the gibberish weight tables learned by NN’s, to exact algorithms will emerge. Something which people have previously done, stealing ideas from Leela, implementing them with rigor into algorithmic schemes of Stockfish—AI learned as well. Only better, of course.
By then, the slope was very slippery, indeed. I still can’t comprehend, how this wasn’t clear to everyone, even back then, less than 10 years ago.
It’s nothing wrong with the Googling method. Besides, one could search for <<pizzeria at the end of the world papa mamma>>. Should work now, too.
Maybe, next year’s solution to this problem will be “at least 13”.
You are right. It’s 12 or more different kinds of pizza. If it was 1 kind of pizza served, he could be certain, that one kind of pizza was at the majority (in that case at all minus one) orders. Since somebody could order a salad. But only one without pizza, to avoid equal orders by pizza kind.
Even if there were 11 different pizza kinds on the menu, Marco could be sure, there is the majority kind of pizza there. Since this Fraenkel conjecture has been proved up to 11 by now.
But for 12 or more, no one really knows yet. Probably it’s true, but who knows. Congratulation, you were rather quick. Despite the fact, the problem formulation looks vague to you.
After some time, a new math puzzle.
I don’t see how “2.5 batteries” could mean “independence from fossil fuels”.
Perhaps, it’s not you who is missing something.
I recently discovered there’s no closed-form formula for the circumference of an ellipse
Yes. I’ve asked the computer, to give me some simple approximation formula then. This came out:
It’s quite good when b >> a.
Well, Oracle, which under 1000 words question, would be answered by the most influential answer for our future? What answer to which question would be the most earthshattering?
CROSSPOST from my blog:
The R0 factor for this illness, which denotes the average number of people infected by a carrier, isn’t a constant, it’s a function of time. R0 = R0 (time). In fact, it’s a function of more parameters and not just time. For example, if quarantined, R0 should be close to 0. There are many unknown factors here, of course, some even known. Some push this now well known R0 term bellow 1, others above 1. It’s all about reducing R0 below 1, and the illness will die out. Otherwise, the number of sick people will go through the roof, by the exponential growth function manner.
All of the above is very well known and understood and repeated over and over again now.
Then you get infected, you caught the virus somehow, what now? Your cells will spread the virus among each other by the factor R0IC !
R0IC is the average number of cells, one infected cell will further infect on average. “IC” in standing for “Inter-Cellular”. This is again not a constant but is a function of time and many other known and unknown factors. For example time, temperature, the immune system activity and so on. R0IC = R0IC (t, T, ISactivity, …, ). At least as complex as the transmission factor R0 between humans, is the transmission factor R0IC between cells. When R0 falls bellow 1 for a considerable time period, the epidemics burn out. When R0IC falls bellow 1 for a considerable time period, the particular human’s illness burns out.
The last paragraph above is a less well-known fact, but it’s a fact none the less. Spreading of this virus among cells, in a way closely imitates the spreading among humans. Medical doctors and medical nurses work hard to minimize R0IC in already infected people. They might call it differently, but it is what it is. Stoping the intercellular infection, “flattening the curve” inside the patient’s body, “delaying the disease” inside the patient’s lungs—you name it! Medical professionals thus “delay the disease” inside you, hoping that the immune system will kick in and do the same until done.
Now, when you are infected and breath, you inhale more or less clean air and exhale quite a lot of viruses. Soon, you are inhaling some previously exhaled viruses back and some of those might infect an additional lung cell. By breathing through SCUBA, there are no previously exhaled viruses and therefore this R0IC should go down slightly, shouldn’t it? By breathing some higher oxygen concentrations than normal, this R0IC should go down even more. Since oxygen is a bit toxic for COVID-19.
By breathing some WARMER air than normal, this R0IC should go down even more, since the COVID-19 virus doesn’t like hot air, does it? Especially if the air is salty or smells of some detergent, pure alcohol and so on, it’s killing the viruses. Some even inside your nose and downward, perhaps.
Then, you may, sometimes after infection, during the asymptomatic phase, run up the hill in sunny weather. Puffing like an old locomotive, you will exhale a lot of viruses. Fortunately, nobody is with you and those exhaled viruses will die under the Sun. Again, you even so slightly decreased the R0IC factor and “flattened the curve” of the internal infection between your cells. You may as well try to inhale some eucalyptus hot vapors under the towel, as they suggest already. Perhaps you should insulate yourself in a sauna. Not too hot, not too humid, but just enough for you to survive and not the virus. Under medical control, of course!
And then perhaps, medical doctors should think about their doctrinal procedures for COVID-19 in this light and to refine these suggestions above considerably. I am no medical doctor! But then again, Marylin Vos Savant was no mathematician either but gave a valuable lesson to Paul Erdos himself. There are times when IQ matters the most.
Anyway. When and if you are infected with COVID-19, in the presymptomatic phase, keep the R0IC down as much as you possibly can. The second symptomatic phase may never come. Doing so, you will (ever so slightly) lower the R0 too!
Either I have no clue, either …
I’ve done some benchmarking in 2018. I benchmarked an “AI software” we devised, by some benchmarks mostly I invented, too. Which doesn’t look very good, I know, but bear with me!
For one, I have given an unsolved Sudoku puzzle to this software with two working names, “Spector” and/or “Profounder”. It concluded, that for every X and every Y: X==Y implies that column(X) != column(Y) and row(X)!=row(Y). (Zero Sudoku topic knowledge by Spector is, of course, a necessary condition.)With several unsolved Sudoku puzzles, Spector concluded that subsquare(X) != subsquare(Y). Just for one puzzle, the concept of “3 by 3 subsquare” isn’t economical. It’s economical for several of them, though.The second benchmark I invented, was giving the string “ABCDEFGHIJKLMNOPQRSTUWXYZ” to Spector. The string generating algorithm would be simpler if the letter “V” wasn’t missing. This is the way Spector notices something might be wrong with the given string. (Zero alphabet topic knowledge by Spector is, of course, a necessary condition.)
Yet another benchmark was numbers from 3 to 122. Each labeled by 0 or 1, depends if it’s nonprime or prime. The simplest generating algorithm is a sort of Eratosthenes sieve. Not for numbers, but for their labels. Spector finds and generates it, with zero knowledge about primes.
Another benchmark was inspired by a mistake someone made. There is a nursing school here somewhere, which sends their students to practice in a nearby hospital for a day or two every week. Except for freshmen in the first year. They teach them everything else in this school, of course, including the gym (boys and girls separated there) and they feed them all once a day, too. It’s standard in this part of the world. But the school does not feed them when they are at the hospital.
So they forget to feed girls from 2B department on Thursdays when they are in school. They forget to include that into their schedule. Boys from 2B have eaten while girls were exercising, but poor girls were forgotten and nobody noticed.
I asked Spector, giving him the school schedule in CSV format if anything is wrong with it. Spector did conclude, that every student has a lunch break once a day when not practicing, except for those girls on Thursday. Which was (probability-wise) odd enough to be significant.
Spector/Profounder is all about one mayor and three to five lesser tricks. To find a generating algorithm for every part of any data it gets. This is the mayor. Then to see if some small data alteration would mean a significantly simpler generation. Then to evaluate the probabilities and needed complexities. And then Spector also asks itself, what data changes are possible but which conserve already observed rules. Which is particularly handy in the unsolved Sudoku case for example.
We will do some more benchmarking this year.
For Eve and her apple pieces. She may eat one piece per second and stay in Paradise forever because at any given moment only a finite number of pieces has been eaten by her.
If her eating pace doubles every minute, she is still okay forever.
Only if she, for example, doubles her eating pace after every say 100 pieces eaten, then she is in trouble. If she supertasks.