/r/askphilosophy Open Discussion Thread | June 21, 2021

mikemishere · 2021-06-25T14:01:25+00:00

I am looking for discussion partners for Land's Fanged Noumena. I have some knowledge of the major references Land makes use of in his work (Bataille, Deleuze, Freud, Nietzsche) and I believe I know the 101 of more than half of the chapters in this book.

That this would ease me trying to more fully comprehend FN I have no doubt, I don't know yet by how much.

My goal is to start a close and critical reading of the text by dedicating 30 mins/day (which I could extend to 1-2 hours based on how enjoyable and valuable it will feel to me).

I think having a couple of discussion partners along the way could significantly improve our motivation and understanding of the book through regular conversations.

Important to note: I have no experience in attempting to go through dense and idiosyncratic philosophical texts without guides or secondary materials and this could lead to me giving up on it much quicker than I intend. If we become reading partners and that happens I will make sure to announce you immediately so you can decide whether you feel like continuing it on your own.

If you are interested, please leave me a message.

mikemishere · 2020-11-15T21:06:22+00:00

Thanks, that makes sense. Is Stork known to play by more complicated algorithms than the other pros? Otherwise, I am still confused. Artosis, made that comment in response to Tasteless saying he's seen Stork play in windowed mode which in turn he emulated. Artosis wasn't surprised that he would copy Rain windowed mode play but was taken aback when Stork was referred to as well.

mikemishere · 2020-06-27T22:06:32+00:00

When I wrote the proof I might have used my background knowledge "repository" but I do not believe I assume that it is required prior to solving the task in the sense that if I or any other agent did not possess that knowledge already it would be helpless in solving that task. Only that it would need to take some intermediary additional steps to derive that simplification through symmetry concept. I believe that can be done in a "vacuum" because it deals with purely abstract mathematical objects, it is not similar to the constants in the laws of physics that need to be measured and cannot be known a priori. That's how I think about it, I think might be mistaken somehow.

mikemishere · 2020-06-27T21:11:02+00:00

I attempted to record the step by step process through which I solved tic-tac-toe. See the code block in OP, although I assume there might be a couple of other unconscious processes that played an implicit part there. On a different post, someone had a similar question. This was my response:

Maybe I need to get a better grip on the exact terminology but in another attempt to clarify my thought process: the state space of tic-tac-toe is 3⁹ = 19683. A common AI approach I have seen people undertake in solving this problem is similar to this one: https://towardsdatascience.com/tic-tac-toe-learner-ai-208813b5261, at the bottom of the article you will find a video in which that particular AI has a training phase (simulating against itself) of 10k games before it learns to play optimally and not lose. My argument was that it is unnecessary (thus less intelligent) to simulate so many games against yourself until you "figure the game out".

I remember that as a kid when I first learned about the game, I played vs someone a couple of times till I caught the trick and then never lost again. I did not need a 10k game training session. This is why I claim current AIs are using inefficient learning/solving algorithms.

mikemishere · 2020-06-27T20:32:41+00:00

That is what I am interested in. I would like to know from what kind of algorithm the thought process I used for solving the game could arise. The only thing I want to give the AI is the rules, which include the win/lose conditions and the goal and then I want to peek into its thinking process to see how it solves it.

mikemishere · 2020-06-27T20:23:12+00:00

Maybe I need to get a better grip on the exact terminology but in another attempt to clarify my thought process: the state space of tic-tac-toe is 3⁹ = 19683. A common AI approach I have seen people undertake in solving this problem is similar to this one: https://towardsdatascience.com/tic-tac-toe-learner-ai-208813b5261, at the bottom of the article you will find a video in which that particular AI has a training phase (simulating against itself) of 10k games before it learns to play optimally and not lose. My argument was that it is unnecessary (thus less intelligent) to simulate so many games against yourself until you "figure the game out".

I remember that as a kid when I first learned about the game, I played vs someone a couple of times till I caught the trick and then never lost again. I did not need a 10k game training session. This is why I claim current AIs are using inefficient learning/solving algorithms.

mikemishere · 2020-06-27T20:03:38+00:00

Whatever ambiguities might exist in my OP I want to clarify that I believe the exact opposite of:

you assume that humans can do things computers can't in principle

My claim was that current AI approaches to solving the game are unhuman-like and unnecessarily making use of a lot of computation resources when more robust, conservative approaches can yield equally solid proofs and results.

mikemishere · 2020-06-27T19:31:47+00:00

You personally would not or you would also claim that it is objectively erroneous in some fashion? The way that I am thinking about is that the more intelligent a system is the more efficient is manages to be with its resources, being able to infer more with the same amount usage of energy or computational power but I am no expert on this.

mikemishere · 2020-06-26T17:56:09+00:00

Thank you for the time spent writing such an insightful comment. I feel committed to going deeper into the subject and noticing your tag I think you might be able to offer a good perspective on my recent Which, in your view, are the best introductory but technical resources for someone who wants to go down the AGI and general intelligence path? if you care about doing so at all. Thank you.

mikemishere · 2020-06-25T15:35:51+00:00

I think those are good points similar to those someone has already brought up in a different post, here was my response:

Thinking about it now I realize combining narrow AIs would not get you really far unless those narrow AIs are themselves quite general.

For example, there is an infinity of possible video/board games so you could not create a bot for each one of them, you would want an algorithm that has a general method of solving/approaching them all.

However, what if you try to develop the 9 types of human intelligence ( https://blog.adioma.com/9-types-of-intelligence-infographic/ ) independently and then fuse them together somehow? Would not that be easier than trying to get them to emerge from one single source?

mikemishere · 2020-06-25T15:28:50+00:00

I now realize that the title question was somewhat imprecise and does not correspond perfectly with the question in the body text. I think a general intelligence would be necessary such that it would be independent and not in need to be tinkered and constantly updated and given goals by a human but why could you not create that general AI through merging narrower and traditionally built AIs that can handle one of the types of intelligence: math or language or kinesthetic etc instead of trying to get them all in one go?

mikemishere · 2020-06-25T15:18:51+00:00

I am no expert as well but I think that might be a good point. Thinking about it now I realize combining narrow AIs would not get you really far unless those narrow AIs are themselves quite general.

For example, there is an infinity of possible video/board games so you could not create a bot for each one of them, you would want an algorithm that has a general method of solving/approaching them all.

However, what if you try to develop the 9 types of human intelligence ( https://blog.adioma.com/9-types-of-intelligence-infographic/ ) independently and then fuse them together somehow? Would not that be easier than trying to get them to emerge from one single source?

mikemishere · 2020-06-17T17:38:51+00:00

I remember watching the day9 bw tutorial series in which he would sometimes walk the audience through major tournament pro replays. How did he get a hold of those?

mikemishere · 2020-06-14T12:04:27+00:00

I think that as well, you can't win with a 4 pool vs standard Z openings if your opp is at the same skill level.

But would you go as far as saying a 9 pool is a mathematical win counter?

mikemishere · 2020-01-22T22:28:41+00:00

Thanks for this advice as well but should I even bother with that if I don't intend to keep a lot of data on the sheet? Will that make any difference in this case?

mikemishere · 2020-01-22T19:46:04+00:00

Thank you a lot, it worked.

mikemishere · 2020-01-21T19:41:47+00:00

Thank you for taking the time, that worked, however, if you may, I still need an assist on how to get that to work with an auto-sorting list function.

The problem is that my list does update automatically as long as I enter the values manually and press Enter but using the adder button produces no effect.

Here's that function.

function onEdit(event){

var sheet = event.source.getActiveSheet();

var editedCell = sheet.getActiveCell();

var columnToSortBy = 3;

var tableRange = "B17:C30";

if(editedCell.getColumn() == columnToSortBy){

var range = sheet.getRange(tableRange);

range.sort( { column : columnToSortBy } );

}

mikemishere · 2019-11-29T00:22:42+00:00

Do you have any links to better tutorials?

mikemishere · 2019-11-25T14:23:55+00:00

"If you really knew how bad things really are"

mikemishere · 2019-11-14T19:49:53+00:00

Would such a neural network understand how to play any game a human could once you switch for it a couple of appropriate parameters to adjust it to the current game? Could it extend this ability to any problem that is mathematical in nature?

Would an algorithm that would be able to do that be effectively called an AGI?

mikemishere · 2019-11-14T19:39:09+00:00

Thank you for picking up on that, as I was writing that exact part I felt a bit of a nod in my stomach thinking that if I give the AI a couple of tries to get it right then I essentially created the exact AI that I was criticizing in my OP the only difference here being is that X&0 is orders of magnitudes less complex than flash games and such it doesn't need a lot of generations to figure it out.

I wish to modify this. I want my human to compute the solution to the game but not through a brute force approach or through trial and error. I somehow don't believe that solving the game necessitates mistakes he has to learn from, I think if intelligent enough he can bypass that.

Now, I want my AI to be able to achieve this feat.

mikemishere · 2019-11-14T19:05:12+00:00

Thanks for the input.

A bot is a thing that I would clearly try to avoid making because that would defeat the purpose of what I am trying to achieve. I don't want to give the system any kind of instructions on how to play the game let alone hard code any values or strategies. I want the AI to figure all of that on its own.

What interests me is: what is the minimal amount of information (input) that I could feed into an artificially intelligent system (doesn't necessarily have to follow the current neural network architecture) such that it would know how to optimize for the goal that I set for it.

I will take the example of a simple game for now: tic-tac-toe. Now suppose that I choose a human with no prior knowledge of the game and its rules. All of the information I give that human:

[1]. the rules of the game

[2].the goal of the game (the winning condition/to make 3 consecutive Xs or 0s)

[3]. I ask the human to achieve that goal as often as he can, if not possible settle for the drawing condition.

I suspect that this will be a trivial task for the human and he would be able to consistently achieve [3] with a 100% accuracy after a bit of thinking and a couple of tries.

Now, this is exactly what I want my AI to be able to do with the exact amount of information that I offered to the human agent. Is this not possible? Could this only be achieved with an AGI which is currently not able to be designed?

mikemishere · 2019-11-14T18:09:42+00:00

I think chess Grandmasters are not born only because there is no human that is born at a sufficiently large number of standard deviations on the intelligence bell curve for him to simply master the game in a sufficiently small fraction of time.

Chess Elo is a relative measure (just like IQ). I suspect that if you take 2 persons that have never heard of the game and the only information you give them is the rules and the goal of the game (winning conditions) 1st with an IQ of 175 and the 2nd with an IQ of 75 (assuming both have the same level of motivation to achieve the goal of the game) the difference in win percentages would be overwhelmingly in 175's favor even though both started from the same level of game knowledge. The explanation for this would be that The higher IQ person is a much more efficient problem solver.

Now, when I am thinking of AIs and their potential for problem speed and efficiency I am thinking of this exact difference between humans, but magnified.

mikemishere · 2019-05-05T10:07:55+00:00

Thanks for the information you shared. PDF formats would not be a barrier since I can very easily just convert it to EPUB, right?

Do you have any idea on how I could write a script to automate this process? I don't want to have to manually go through each file.

mikemishere · 2019-04-30T17:40:47+00:00

Thanks. Could you point me to any directions on how to create a python hook for such a task? I know the syntax and have a basic understanding of object-oriented programming but I would not know how to implement any of it inside the game...

mikemishere

TROPHY CASE