The robot hardly jumps over anything, and when it jumps onto something it doesn't even keep moving. This robot has as much to do with parkour as a baby takings its first steps has to do with olympic sprinting. Actually that would be more related because at least the baby uses basically the same limbs. So let's say an alien baby. The video left me feeling sad and disappointed, at a lower hedonic level than previously. I cannot conceive why 1300 separate people chose to upvote the video. Unless perhaps they only watched the clip of the robot sprinting into the air. Which was cool the first time. But not the following ten times.
the Berkeley Earth Surface Temperature (BEST) project
https://en.wikipedia.org/wiki/Berkeley_Earth_Surface_Temperature
was done by and funded by people who wanted to show global warming wrong or already thought it was, no way would they tweak their model to fit the consensus of other climate researchers yet they came to the same conclusion.
They didn't make a model, they measured temperatures. I agree that you can measure temperatures accurately. From skimming the article it seems they discredited the 'urban heat bias' hypothesis which is interesting to know.
Also you can test climate models ability to match reality, make them using a limited data set (eg 20k-1k years ago) and then test them on another(eg last 1k years) to see weather they match. Again this is not a hard method to understand, if the new set does not match perditions your wrong, if it does then you are more likely correct. This method is standard across biology as well as several other fields not ideal but good enough.
That doesn't show your model matches reality, it shows that you managed to make a complicated mathematical formula that managed to use some data points to generate some other data points.
Yes, it is possible to estimate how well a climate model models reality.
It's possible to make a climate model, then wait for reality to happen, then see how well they matched, yes. But you can't run experiments to see if your model is sound. And climate models do diverge from reality as reality happens, see this graph for example.
The parameters that vary in climate models are not unconstrained, but constrained by physics (experimental evidence). If your climate model accurately hindcasts the climate developments of the 20th century (say), but the parameters are at the extreme range of what's plausible from experimental physics, then it probably isn't a very good model.
That hasn't stopped astronomers from positing ridiculous things such as dark matter and dark energy.
In the case of climate simulations, different models (both physics-wise and code-wise) are run with different computers on the same input data, and yield basically the same results.
Yes, but how many of those basically same results were achieved by tweaking the model until the output was basically the same?
The problem with climate science is that it's not experimental. You cannot run controlled experiments on the climate. Thus, the quality of climate science research is determined not by how accurately it models reality (since it's impossible to test), but by how accepted your research is by other climate scientists. This can easily lead to the point where the science becomes totally disconnected from the reality. Much like astronomy with its dark matter & energy & ridiculous constants to attempt to fit together the observed structure of the universe into a failing model.
Diablo 2 had much more replay value. On multiple occasions over the years I've gotten together with a friend or two to replay D2 just for the heck of it. I have absolutely zero motivation to do anything of the sort whatsoever for Diablo 3. Why is that?
And the US health care system provides for that medical support by taking taxes from those who work in the US. It does not come out of nowhere. If the US health care system did not exist, citizens would be spending that same money on a private health care system. This might, arguably, be better. (Consider, for example, how Lasik eye-surgery keeps getting cheaper and better over the years, much like computer parts do, in opposition to the rest of the health care system which seems to get more expensive and prohibitive as the years go by. What's the difference between the two?)
I could always see it that way. I thought it looked that way to everyone? I always wondered why when I took a photo I wouldn't see the waves in the photo.
That's how we lost ol' Timmy. Asked him to give us a few digits of that good ol' pi and he just durn went and hung himself right in the ol' barn. We stopped teachin' the young'uns maths after that lil' incident.
No you see, by pi he meant the mathematical number - 3.1415... - not pie as in "food". Even so, the value of pie wouldn't be "more" and "with ice cream" - that's not the value of something, those are desires and descriptors of something. Value would be more like how many dollars it's worth or how many good deeds/grades one has to get to receive the pie.
Ultimately the source of all our information comes from sensory input. That's how we know ice is cold, that things fall, some things hurt, others are pleasurable, etc. On top of that sensory data we construct an intelligent (symbolic) representation of the world, in tandem with a language (or several languages) which we share with others and can thus use to exchange ideas.
What AI researchers seem to be doing is skipping the sensory input part, because it's hard, and just trying to codify the intelligent representations directly. In light of the above, it's clear why common sense eludes AIs built on this principle.
Perhaps the approach that will ultimately succeed - and I don't see a convincing reason why we won't ultimately be able to build a sentient self-reflective machine which ends up being more intelligent than a human - is to mimic the human developmental approach from the start. Hook up a shitload of sensors to a massively parallel brain-structure-type thing and have it "learn" from there. We won't so much program it as direct its growth and evolution. This probably requires a ton more computing power than we have now, but seeing as how it on average doubles every 2 years, it will eventually catch up. The first artificial humans will likely be pretty unintelligent, but then they'll quickly surpass humans because we'll have bested evolution - we'll have figured out exactly what makes intelligence and sentience, and then we'll be able to turn that knob up to 11 and beyond in a relatively short period of time.
At that point we can only hope one of them doesn't go rogue and kill us all.
Oh that's a good point about the higher-order functions. I hadn't thought about that. I use Python mostly, where map + filter are usually replaced by list comprehensions.
Good example w/ the async code. Two more uparg closure examples I thought of:
1) One thing in Python where closures are useful is with wrapping functions. e.g. I made a function which memoizes another function's results based on the hash of its arguments. The cache is stored in the closure that the memoize function generates. It's a very neat thing in that it allows a sort of microcosm to be built, and then essentially be ignored (given you know what you're doing) without complicating the rest of the code, much.
2) In JavaScript, closures are often exploited to implement hidden variables.
Ha I see you got sniped by a "I disagree - mod Troll". Funny given what your sig is.
What it comes down to is that GC is a tool. If you don't understand how it works and assume it's magic, then you'll get bitten in the ass at some point down the line - although for most things it actually won't matter so you can get away with it for a bit. But of course you'll get more out of it if you understand it - for example I recently had to use weakrefs in a Python project to break circular references.
True, but that's where they are the most useful - like for event handlers. To be honest I've never used closures in a language without automatic memory management so I'm not sure how that would end up working out.
Oh interesting, seems I was wrong. You were right that when an object loses a reference, and it's reference count hits 0, it is deallocated - there's no stop-the-world there. Apparently garbage collection only happens in order to clear circular references - and that's based on the number of objects, not the amount of memory being used. Learn something new each day! Thanks.
You're talking about "stop-the-world" garbage collection, which Python is also an example of. It doesn't have to do tracing, but it still grinds everything to a halt when it cleans up memory. I think real-time garbage collection is hard to come by these days.
"Copyright is supposed to increase the availability of a work." No, all copyright does is restrict a work from being presented, transmitted, reproduced, displayed, etc., in certain circumstances. How would that ever increase the availability of a work?
Hopefully this will help put to rest the notion that copyright & patents & other intellectual property help to *promote* works, and bring about the understanding that all they really accomplish is to *limit* works (as all they do is make it illegal to produce & use works under certain circumstances).
What did you mean when you said "I'd really like to know who thought the word 'influencers' meant anything."? Clearly it means something. You mean who thought it had any poetic meaning?
It's certainly not pass by reference. However, it is "call by sharing" for objects. You've demonstrated your ignorance by not reading the Wikipedia article, which even says: "However, the term "call by sharing" is not in common use; the terminology is inconsistent across different sources. For example, in the Java community, they say that Java is pass-by-value [...] Call-by-sharing implies that values in the language are based on objects rather than primitive types."
The distinction is this: although you could certainly implement Java's passing scheme by passing pointers (memory addresses) by value, the language itself doesn't deal with pointers at all. The semantics are such that both the caller and the callee have variables that point to/refer to the same object - i.e. they share the same object. Thus you could describe it "as call-by-value, where the value is implied to be a reference to the object.", or you could describe it as "call by sharing", which is simpler. Note that with "call-by-value" you have to specify that the value isn't the object itself but rather a reference to the object.
Either way we're describing the same behavior. It's just a matter of the words we're using.
Slashdot Mirror
What about regular Nevada and Louisiana?
Sometimes I make myself laugh. Just burst out laughing re-reading my comment. I think it's time to go to sleep.
The robot hardly jumps over anything, and when it jumps onto something it doesn't even keep moving. This robot has as much to do with parkour as a baby takings its first steps has to do with olympic sprinting. Actually that would be more related because at least the baby uses basically the same limbs. So let's say an alien baby. The video left me feeling sad and disappointed, at a lower hedonic level than previously. I cannot conceive why 1300 separate people chose to upvote the video. Unless perhaps they only watched the clip of the robot sprinting into the air. Which was cool the first time. But not the following ten times.
You mean misleading title, and I think that deserves a "woosh"...
the Berkeley Earth Surface Temperature (BEST) project https://en.wikipedia.org/wiki/Berkeley_Earth_Surface_Temperature was done by and funded by people who wanted to show global warming wrong or already thought it was, no way would they tweak their model to fit the consensus of other climate researchers yet they came to the same conclusion.
They didn't make a model, they measured temperatures. I agree that you can measure temperatures accurately. From skimming the article it seems they discredited the 'urban heat bias' hypothesis which is interesting to know.
Also you can test climate models ability to match reality, make them using a limited data set (eg 20k-1k years ago) and then test them on another(eg last 1k years) to see weather they match. Again this is not a hard method to understand, if the new set does not match perditions your wrong, if it does then you are more likely correct. This method is standard across biology as well as several other fields not ideal but good enough.
That doesn't show your model matches reality, it shows that you managed to make a complicated mathematical formula that managed to use some data points to generate some other data points.
Yes, it is possible to estimate how well a climate model models reality.
It's possible to make a climate model, then wait for reality to happen, then see how well they matched, yes. But you can't run experiments to see if your model is sound. And climate models do diverge from reality as reality happens, see this graph for example.
The parameters that vary in climate models are not unconstrained, but constrained by physics (experimental evidence). If your climate model accurately hindcasts the climate developments of the 20th century (say), but the parameters are at the extreme range of what's plausible from experimental physics, then it probably isn't a very good model.
That hasn't stopped astronomers from positing ridiculous things such as dark matter and dark energy.
In the case of climate simulations, different models (both physics-wise and code-wise) are run with different computers on the same input data, and yield basically the same results.
Yes, but how many of those basically same results were achieved by tweaking the model until the output was basically the same?
The problem with climate science is that it's not experimental. You cannot run controlled experiments on the climate. Thus, the quality of climate science research is determined not by how accurately it models reality (since it's impossible to test), but by how accepted your research is by other climate scientists. This can easily lead to the point where the science becomes totally disconnected from the reality. Much like astronomy with its dark matter & energy & ridiculous constants to attempt to fit together the observed structure of the universe into a failing model.
Diablo 2 had much more replay value. On multiple occasions over the years I've gotten together with a friend or two to replay D2 just for the heck of it. I have absolutely zero motivation to do anything of the sort whatsoever for Diablo 3. Why is that?
Funny yet also insightful and informative.
And the US health care system provides for that medical support by taking taxes from those who work in the US. It does not come out of nowhere. If the US health care system did not exist, citizens would be spending that same money on a private health care system. This might, arguably, be better. (Consider, for example, how Lasik eye-surgery keeps getting cheaper and better over the years, much like computer parts do, in opposition to the rest of the health care system which seems to get more expensive and prohibitive as the years go by. What's the difference between the two?)
I could always see it that way. I thought it looked that way to everyone? I always wondered why when I took a photo I wouldn't see the waves in the photo.
That's how we lost ol' Timmy. Asked him to give us a few digits of that good ol' pi and he just durn went and hung himself right in the ol' barn. We stopped teachin' the young'uns maths after that lil' incident.
No you see, by pi he meant the mathematical number - 3.1415... - not pie as in "food". Even so, the value of pie wouldn't be "more" and "with ice cream" - that's not the value of something, those are desires and descriptors of something. Value would be more like how many dollars it's worth or how many good deeds/grades one has to get to receive the pie.
Ultimately the source of all our information comes from sensory input. That's how we know ice is cold, that things fall, some things hurt, others are pleasurable, etc. On top of that sensory data we construct an intelligent (symbolic) representation of the world, in tandem with a language (or several languages) which we share with others and can thus use to exchange ideas.
What AI researchers seem to be doing is skipping the sensory input part, because it's hard, and just trying to codify the intelligent representations directly. In light of the above, it's clear why common sense eludes AIs built on this principle.
Perhaps the approach that will ultimately succeed - and I don't see a convincing reason why we won't ultimately be able to build a sentient self-reflective machine which ends up being more intelligent than a human - is to mimic the human developmental approach from the start. Hook up a shitload of sensors to a massively parallel brain-structure-type thing and have it "learn" from there. We won't so much program it as direct its growth and evolution. This probably requires a ton more computing power than we have now, but seeing as how it on average doubles every 2 years, it will eventually catch up. The first artificial humans will likely be pretty unintelligent, but then they'll quickly surpass humans because we'll have bested evolution - we'll have figured out exactly what makes intelligence and sentience, and then we'll be able to turn that knob up to 11 and beyond in a relatively short period of time.
At that point we can only hope one of them doesn't go rogue and kill us all.
Oh that's a good point about the higher-order functions. I hadn't thought about that. I use Python mostly, where map + filter are usually replaced by list comprehensions.
Good example w/ the async code. Two more uparg closure examples I thought of:
1) One thing in Python where closures are useful is with wrapping functions. e.g. I made a function which memoizes another function's results based on the hash of its arguments. The cache is stored in the closure that the memoize function generates. It's a very neat thing in that it allows a sort of microcosm to be built, and then essentially be ignored (given you know what you're doing) without complicating the rest of the code, much.
2) In JavaScript, closures are often exploited to implement hidden variables.
Ha I see you got sniped by a "I disagree - mod Troll". Funny given what your sig is.
What it comes down to is that GC is a tool. If you don't understand how it works and assume it's magic, then you'll get bitten in the ass at some point down the line - although for most things it actually won't matter so you can get away with it for a bit. But of course you'll get more out of it if you understand it - for example I recently had to use weakrefs in a Python project to break circular references.
True, but that's where they are the most useful - like for event handlers. To be honest I've never used closures in a language without automatic memory management so I'm not sure how that would end up working out.
Oh interesting, seems I was wrong. You were right that when an object loses a reference, and it's reference count hits 0, it is deallocated - there's no stop-the-world there. Apparently garbage collection only happens in order to clear circular references - and that's based on the number of objects, not the amount of memory being used. Learn something new each day! Thanks.
You're talking about "stop-the-world" garbage collection, which Python is also an example of. It doesn't have to do tracing, but it still grinds everything to a halt when it cleans up memory. I think real-time garbage collection is hard to come by these days.
Man you try using closures with manual memory management. Quite a nuisance. GC is really quite nice.
"Copyright is supposed to increase the availability of a work." No, all copyright does is restrict a work from being presented, transmitted, reproduced, displayed, etc., in certain circumstances. How would that ever increase the availability of a work?
Hopefully this will help put to rest the notion that copyright & patents & other intellectual property help to *promote* works, and bring about the understanding that all they really accomplish is to *limit* works (as all they do is make it illegal to produce & use works under certain circumstances).
What did you mean when you said "I'd really like to know who thought the word 'influencers' meant anything."? Clearly it means something. You mean who thought it had any poetic meaning?
It's certainly not pass by reference. However, it is "call by sharing" for objects. You've demonstrated your ignorance by not reading the Wikipedia article, which even says: "However, the term "call by sharing" is not in common use; the terminology is inconsistent across different sources. For example, in the Java community, they say that Java is pass-by-value [...] Call-by-sharing implies that values in the language are based on objects rather than primitive types."
The distinction is this: although you could certainly implement Java's passing scheme by passing pointers (memory addresses) by value, the language itself doesn't deal with pointers at all. The semantics are such that both the caller and the callee have variables that point to/refer to the same object - i.e. they share the same object. Thus you could describe it "as call-by-value, where the value is implied to be a reference to the object.", or you could describe it as "call by sharing", which is simpler. Note that with "call-by-value" you have to specify that the value isn't the object itself but rather a reference to the object.
Either way we're describing the same behavior. It's just a matter of the words we're using.
influencers: those who influence.