Wouldn’t it be more impressive if I could point you to a solution to a puzzle you’ve been stuck on than if I present my own puzzle and give you the solution to that?
It would, but you didn’t ask for such a thing. Are you asking for such a thing now? If so, here is one in AI, which is on everyone’s minds: How do we interpret the inner-workings of neural networks.
I expect though, that you will say that your theory isn’t applicable here for whatever reason. Therefore it would be helpful if you gave me an example of what sort of puzzle your theory is applicable to.
“How do we interpret the inner-workings of neural networks.” is not a puzzle unless you get more concrete an application of it. For instance an input/output pair which you find surprising and want an interpretation for, or at least some general reason you want to interpret it.
The LDSL series provides quite a few everyday examples, but for some reason you aren’t satisfied with those. Difficult examples require that you’re good at something, so I might not be able to find an example for you.
Here you ask a lot of questions, approximately each of the form “why do ‘people’ think <thing-that-some-people-think-but-certainly-not-all”. To list a few,
Why are people so insistent about outliers?
Seems to have a good answer. Sometimes they’re informative!
Why isn’t factor analysis considered the main research tool?
Seems also to have a good answer, it is easy to fool yourself if you do it improperly.
How can probability theory model bag-like dynamics?
I would sure love a new closed-form way of modeling bag-like dynamics, as you describe them, if you have them! I don’t think you give one though, but surely if you mention it, you must have the answer somewhere!
Perception is logaritmic; doesn’t this by default solve a lot of problems?
Seems less a question than a claim? And I don’t think we need special math to solve this one.
None of these seem like concrete applications of your theory, but that’s fine. It was an intro post, you will surely explain all these later on, as worked examples at some point, right?
I proposed that life cannot be understood through statistics, but rather requires more careful study of individual cases.
Wait, I don’t think your previous post was about that? I certainly use statistics when doing performance optimization! In particular, I profile my code and look at which function calls are taking the bulk of the time, then optimize or decrease the number of calls to those.
Hey look a concrete example!
Let’s take a epidemic as an example. There’s an endless number of germs of different species spreading around. Most of them don’t make much difference for us. But occasionally, one of them gains the capacity to spread more rapidly from person to person, which leads to an epidemic. Here, the core factor driving the spread of the disease is the multiplicative interaction between infected and uninfected people, and the key change that changes it from negligible to important is the change in the power of this interaction.
One it has infected someone, it can have further downstream effects, in that it makes them sick and maybe even kills them. (And whether it kills them or not, this sickness is going to have further downstream effects in e.g. interrupting their work.) But these downstream effects are critically different from the epidemic itself, in that they cannot fuel the infection further. Rather, they are directly dependent on the magnitude of people infected.
… well more like a motivating example. I’m sure at some point you build models and compare your model to those the epidemiologists have built… right?
Your solution here to the problem you outline seems like a cop-out to me, and of course (other than the tank/dust example, which is by no means an example in the sense we’re talking about here), there are no examples.
Here you give the example of elo, but you don’t really provide any alternatives, and you mostly mention that picking bases when taking logarithms may be hard, so also doesn’t seem like an example.
Therefore, if it seemed like I didn’t read your sequence before (which I did! Just a while ago), I have certainly at least skimmed it now, and can say with relative confidence that no, you don’t in fact give concrete examples of circumstances where your theory performs better than the competition even once. At most you give some statistical arguments for why in some circumstances you may want to use various statistical tools. But this is by no means some theory of everything or even really much a steel-man for anti-reductionism.
You don’t even come back to the problems you originally listed! Where’s the promised theory of autism? Where’s the closed form model of bag-like dynamics? Where’s the steel-man of psychoanalysis, or the take-down of local validity and coherence, or the explanation of why commonsense reasoning avoids the principle of explosion?
This is the behavior of a lazy crack-pot, who doesn’t want to admit the fact that nobody is listening to them anymore because they’re just wrong. It is not the case that I’m just not good at anything enough to understand your oh-so-complex examples. You just don’t want to provide examples and would rather lie and say you’ve provided examples in the past, relying on your (false) assumption that I haven’t read what you’ve written, than actually list anything concrete.
I do remember liking this post! It was good. However, the conclusions here do not seem dependent on your overall conclusions.
This post has the table example. That’s probably the most important of all the examples.
Wait, I don’t think your previous post was about that? I certainly use statistics when doing performance optimization! In particular, I profile my code and look at which function calls are taking the bulk of the time, then optimize or decrease the number of calls to those.
That’s accounting, not statistics.
… well more like a motivating example. I’m sure at some point you build models and compare your model to those the epidemiologists have built… right?
AFAIK epidemiologists usually measure particular diseases and focus their models on those, whereas LDSL would more be across all species of germs.
Therefore, if it seemed like I didn’t read your sequence before (which I did! Just a while ago), I have certainly at least skimmed it now, and can say with relative confidence that no, you don’t in fact give concrete examples of circumstances where your theory performs better than the competition even once. At most you give some statistical arguments for why in some circumstances you may want to use various statistical tools. But this is by no means some theory of everything or even really much a steel-man for anti-reductionism.
There is basically no competition. You just keep on treating it like the narrow domain-specific models count as competition when they really don’t because they focus on something different than mine.
AFAIK epidemiologists usually measure particular diseases and focus their models on those, whereas LDSL would more be across all species of germs.
I would honestly be interested in any concrete model you build based on this. You don’t necessarily have to compare it against some other field’s existing model, though it does help for credibility’s sake. But I would like to at least be able to compare the model you make against data.
I’m also not sure this is true about epidemiologists, and if it is I’d guess its true to the extent that they have like 4 different parameterizations of different types of diseases (likely having to do with various different sorts of vectors of spread), then they fit one of those 4 different parameterizations to the measured (or inferred) characteristics of a particular disease.
The most central aspect of my model is to explain why it’s generally not relevant to fit quantitative models to data.
I’m also not sure this is true about epidemiologists, and if it is I’d guess its true to the extent that they have like 4 different parameterizations of different types of diseases (likely having to do with various different sorts of vectors of spread), then they fit one of those 4 different parameterizations to the measured (or inferred) characteristics of a particular disease.
Each disease (and even different strands of the same disease and different environmental conditions for the same strand) has its own parameters, but they don’t fit a model that contains all the parameters of all diseases at once, they just focus on one disease at a time.
“How do we interpret the inner-workings of neural networks.” is not a puzzle unless you get more concrete an application of it. For instance an input/output pair which you find surprising and want an interpretation for, or at least some general reason you want to interpret it.
Which seems to imply you (at least 3 hours ago) believed your theory could handle relatively well-formulated and narrow “input/output pair” problems. Yet now you say
You just keep on treating it like the narrow domain-specific models count as competition when they really don’t because they focus on something different than mine.
If I treat your theory this way, it is only because you did, 3 hours ago, when you believed I hadn’t read your post or would even give you the time of the day. You claimed “How do we interpret the inner-workings of neural networks.” was “not a puzzle unless you get [a?] more concrete application of it”, yet the examples you list in your first post are no more vague, and often quite a bit more vague than “how do you interpret neural networks?” or “why are adversarial examples so easy to find?” For example, the question “Why are people so insistent about outliers?” or “Why isn’t factor analysis considered the main research tool?”
There is basically no competition.
For… what exactly? For theories of everything? Oh I assure you, there is quite a bit of competition there. For statistical modeling toolkits? Ditto. What exactly do you think the unique niche you are trying to fill is? You must be arguing against someone, and indeed you often do argue against many.
Which seems to imply you (at least 3 hours ago) believed your theory could handle relatively well-formulated and narrow “input/output pair” problems. Yet now you say
The relevance of zooming in on particular input/output problems is part of my model.
If I treat your theory this way, it is only because you did, 3 hours ago, when you believed I hadn’t read your post or would even give you the time of the day. You claimed “How do we interpret the inner-workings of neural networks.” was “not a puzzle unless you get [a?] more concrete application of it”, yet the examples you list in your first post are no more vague, and often quite a bit more vague than “how do you interpret neural networks?” or “why are adversarial examples so easy to find?” For example, the question “Why are people so insistent about outliers?” or “Why isn’t factor analysis considered the main research tool?”
“Why are adversarial eamples so easy to find?” is a problem that is easily solvable without my model. You can’t solve it because you suck at AI, so instead you find some AI experts who are nearly as incompetent as you and follow along their discourse because they are working at easier problems that you have a chance of solving.
“Why are people so insistent about outliers?” is not vague at all! It’s a pretty specific phenomenon that one person mentions a general theory and then another person says it can’t be true because of their uncle or whatever. The phrasing in the heading might be vague because headings are brief, but I go into more detail about it in the post, even linking to a person who frequently struggles with that exact dynamic.
As an aside, you seem to be trying to probe me for inconsistencies and contradictions, presumably because you’ve written me off as a crank. But I don’t respect you and I’m not trying to come off as credible to you (really I’m slightly trying to come off as non-credible to you because your level of competence is too low for this theory to be relevant/good for you). And to some extent you know that your heuristics for identifying cranks is not going to solely pop out at people who are forever lost to crankdom because you haven’t just abandoned the conversation.
For… what exactly? For theories of everything? Oh I assure you, there is quite a bit of competition there. For statistical modeling toolkits? Ditto. What exactly do you think the unique niche you are trying to fill is? You must be arguing against someone, and indeed you often do argue against many.
Theories of everything that explain why intelligence can’t model everything and you need other abilities.
And to some extent you know that your heuristics for identifying cranks is not going to solely pop out at people who are forever lost to crankdom because you haven’t just abandoned the conversation.
I liked your old posts and your old research and your old ideas. I still have some hope you can reflect on the points you’ve made here, and your arguments against my probes, and feel a twinge of doubt, or motivation, pull on that a little, and end up with a worldview that makes predictions, lets you have & make genuine arguments, and gives you novel ideas.
If you were always lazy, I wouldn’t be having this conversation, but once you were not.
No it doesn’t. I obviously understood my old posts (and still do—the posts make sense if I imagine ignoring LDSL). So I’m capable of understanding whether I’ve found something that reveals problems in them. It’s possible I’m communicating LDSL poorly, or that you are too ignorant to understand it, or that I’m overestimating how broadly it applies, but those are far more realistic than that I’ve become a pure crank. If you still prefer my old posts to my new posts, then I must know something relevant you don’t know.
“Why are adversarial eamples so easy to find?” is a problem that is easily solvable without my model. You can’t solve it because you suck at AI, so instead you find some AI experts who are nearly as incompetent as you and follow along their discourse because they are working at easier problems that you have a chance of solving.
Wouldn’t it be more impressive if I could point you to a solution to a puzzle you’ve been stuck on than if I present my own puzzle and give you the solution to that?
It would, but you didn’t ask for such a thing. Are you asking for such a thing now? If so, here is one in AI, which is on everyone’s minds: How do we interpret the inner-workings of neural networks.
I expect though, that you will say that your theory isn’t applicable here for whatever reason. Therefore it would be helpful if you gave me an example of what sort of puzzle your theory is applicable to.
“How do we interpret the inner-workings of neural networks.” is not a puzzle unless you get more concrete an application of it. For instance an input/output pair which you find surprising and want an interpretation for, or at least some general reason you want to interpret it.
Ok, then why do AI systems have so many adversarial examples? I have no formal model of this, though it plausibly makes some intuitive sense.
… can you pick some topic that you are good at instead of focusing on AI? That would probably make the examples more informative.
It sounds like, as I predicted, your theory doesn’t apply to the problems I presented, so how about you provide an example
The LDSL series provides quite a few everyday examples, but for some reason you aren’t satisfied with those. Difficult examples require that you’re good at something, so I might not be able to find an example for you.
Lets go through your sequence shall we? And enumerate the so-called “concrete examples” you list
[LDSL#0] Some epistemological conundrums
Here you ask a lot of questions, approximately each of the form “why do ‘people’ think <thing-that-some-people-think-but-certainly-not-all”. To list a few,
Seems to have a good answer. Sometimes they’re informative!
Seems also to have a good answer, it is easy to fool yourself if you do it improperly.
I would sure love a new closed-form way of modeling bag-like dynamics, as you describe them, if you have them! I don’t think you give one though, but surely if you mention it, you must have the answer somewhere!
Seems less a question than a claim? And I don’t think we need special math to solve this one.
None of these seem like concrete applications of your theory, but that’s fine. It was an intro post, you will surely explain all these later on, as worked examples at some point, right?
[LDSL#1] Performance optimization as a metaphor for life
I do remember liking this post! It was good. However, the conclusions here do not seem dependent on your overall conclusions.
[LDSL#2] Latent variable models, network models, and linear diffusion of sparse lognormals
Wait, I don’t think your previous post was about that? I certainly use statistics when doing performance optimization! In particular, I profile my code and look at which function calls are taking the bulk of the time, then optimize or decrease the number of calls to those.
Hey look a concrete example!
… well more like a motivating example. I’m sure at some point you build models and compare your model to those the epidemiologists have built… right?
[LDSL#3] Information-orientation is in tension with magnitude-orientation
This seems like a reasonable statistical argument, but of course, for our purposes, there are no real examples here, so let us move on.
[LDSL#4] Root cause analysis versus effect size estimation
Seems also a reasonable orientation, but by no means a theory of everything, and again no real examples here, so lets move on once again
[LDSL#5] Comparison and magnitude/diminishment
Your solution here to the problem you outline seems like a cop-out to me, and of course (other than the tank/dust example, which is by no means an example in the sense we’re talking about here), there are no examples.
[LDSL#6] When is quantification needed, and when is it hard?
Here you give the example of elo, but you don’t really provide any alternatives, and you mostly mention that picking bases when taking logarithms may be hard, so also doesn’t seem like an example.
Therefore, if it seemed like I didn’t read your sequence before (which I did! Just a while ago), I have certainly at least skimmed it now, and can say with relative confidence that no, you don’t in fact give concrete examples of circumstances where your theory performs better than the competition even once. At most you give some statistical arguments for why in some circumstances you may want to use various statistical tools. But this is by no means some theory of everything or even really much a steel-man for anti-reductionism.
You don’t even come back to the problems you originally listed! Where’s the promised theory of autism? Where’s the closed form model of bag-like dynamics? Where’s the steel-man of psychoanalysis, or the take-down of local validity and coherence, or the explanation of why commonsense reasoning avoids the principle of explosion?
This is the behavior of a lazy crack-pot, who doesn’t want to admit the fact that nobody is listening to them anymore because they’re just wrong. It is not the case that I’m just not good at anything enough to understand your oh-so-complex examples. You just don’t want to provide examples and would rather lie and say you’ve provided examples in the past, relying on your (false) assumption that I haven’t read what you’ve written, than actually list anything concrete.
This post has the table example. That’s probably the most important of all the examples.
That’s accounting, not statistics.
AFAIK epidemiologists usually measure particular diseases and focus their models on those, whereas LDSL would more be across all species of germs.
There is basically no competition. You just keep on treating it like the narrow domain-specific models count as competition when they really don’t because they focus on something different than mine.
I would honestly be interested in any concrete model you build based on this. You don’t necessarily have to compare it against some other field’s existing model, though it does help for credibility’s sake. But I would like to at least be able to compare the model you make against data.
I’m also not sure this is true about epidemiologists, and if it is I’d guess its true to the extent that they have like 4 different parameterizations of different types of diseases (likely having to do with various different sorts of vectors of spread), then they fit one of those 4 different parameterizations to the measured (or inferred) characteristics of a particular disease.
The most central aspect of my model is to explain why it’s generally not relevant to fit quantitative models to data.
Each disease (and even different strands of the same disease and different environmental conditions for the same strand) has its own parameters, but they don’t fit a model that contains all the parameters of all diseases at once, they just focus on one disease at a time.
Before you said
Which seems to imply you (at least 3 hours ago) believed your theory could handle relatively well-formulated and narrow “input/output pair” problems. Yet now you say
If I treat your theory this way, it is only because you did, 3 hours ago, when you believed I hadn’t read your post or would even give you the time of the day. You claimed “How do we interpret the inner-workings of neural networks.” was “not a puzzle unless you get [a?] more concrete application of it”, yet the examples you list in your first post are no more vague, and often quite a bit more vague than “how do you interpret neural networks?” or “why are adversarial examples so easy to find?” For example, the question “Why are people so insistent about outliers?” or “Why isn’t factor analysis considered the main research tool?”
For… what exactly? For theories of everything? Oh I assure you, there is quite a bit of competition there. For statistical modeling toolkits? Ditto. What exactly do you think the unique niche you are trying to fill is? You must be arguing against someone, and indeed you often do argue against many.
The relevance of zooming in on particular input/output problems is part of my model.
“Why are adversarial eamples so easy to find?” is a problem that is easily solvable without my model. You can’t solve it because you suck at AI, so instead you find some AI experts who are nearly as incompetent as you and follow along their discourse because they are working at easier problems that you have a chance of solving.
“Why are people so insistent about outliers?” is not vague at all! It’s a pretty specific phenomenon that one person mentions a general theory and then another person says it can’t be true because of their uncle or whatever. The phrasing in the heading might be vague because headings are brief, but I go into more detail about it in the post, even linking to a person who frequently struggles with that exact dynamic.
As an aside, you seem to be trying to probe me for inconsistencies and contradictions, presumably because you’ve written me off as a crank. But I don’t respect you and I’m not trying to come off as credible to you (really I’m slightly trying to come off as non-credible to you because your level of competence is too low for this theory to be relevant/good for you). And to some extent you know that your heuristics for identifying cranks is not going to solely pop out at people who are forever lost to crankdom because you haven’t just abandoned the conversation.
Theories of everything that explain why intelligence can’t model everything and you need other abilities.
I liked your old posts and your old research and your old ideas. I still have some hope you can reflect on the points you’ve made here, and your arguments against my probes, and feel a twinge of doubt, or motivation, pull on that a little, and end up with a worldview that makes predictions, lets you have & make genuine arguments, and gives you novel ideas.
If you were always lazy, I wouldn’t be having this conversation, but once you were not.
A lot of my new writing is as a result of the conclusions of or in response to my old research ideas.
Of course it is, I did not think otherwise, but my point stands.
No it doesn’t. I obviously understood my old posts (and still do—the posts make sense if I imagine ignoring LDSL). So I’m capable of understanding whether I’ve found something that reveals problems in them. It’s possible I’m communicating LDSL poorly, or that you are too ignorant to understand it, or that I’m overestimating how broadly it applies, but those are far more realistic than that I’ve become a pure crank. If you still prefer my old posts to my new posts, then I must know something relevant you don’t know.
What is the solution then?
I do think I’m “good at” AI, I think many who are “good at” AI are also pretty confused here.
I don’t really care what you think.