Right. The authors have overlooked the fact, as shown by their own map, that, in 1347, the plague moved into Europe along a broad front: the Mediterranean coastline. I imagine that it spread along that front by ship, a good deal faster than the inland spread that the authors base their thesis on.
Furthermore, the authors summarily dismiss the effect of the disease on its spread. It was very debilitating, and a traveller on land who fell sick would be unlikely to continue his journey. The authors exaggerate the distance a sick traveller would be likey to spread the disease.
Add to this the failure of the authors to recognize that almost all land travel would be by foot (with what animals were being used for transport mostly being used to carry the baggage of foot travellers) and you have three strikes against their argument. I don't doubt that the world was less connected than than it is now, but the authors overstate their case. By overestimating the rate at which land travel would, in practice, spread the diseease, they have underestimated the amount of travel.
Isn't the energy released from a fusion reaction ALWAYS larger than the energy absorbed?
In the case of lightweight elements, the energy released by two fusing nuclei is less than the kinetic energy smashing them together, but only a small fraction of the nuclei in a pellet fuse, and most of the energy absorbed by the pellet goes into heating and ionizing the atoms that don't undergo fusion.
"Lalueza-Fox was able to isolate a small amount of Y chromosome from the inner part of the head, which is transmitted from male to male each generation."
Microsoft usually can see the train coming long before it arrives.
In my reading of its history, Microsoft has spent a good deal of its existence catching up with one train or another. Two notable examples: GUIs and the internet.
That is what it looks like in retrospect...
I recall it looking that way at the time, too. Of course, in each case, there was a lag between when the train left the station and when Microsoft realized it needed to be on it, and in that interval, it was preoccupied with the things you describe.
The tablet/touch part must hurt because, for once, they were pioneers of the software technology (albeit on a mainframe-sized surface), but then they repeated Xerox' canonical mistake (that's definitely a retrospective view - I didn't see it coming at the time. I am a curmudgeon in these matters, and for most purposes, I still find a mouse to be superior to any of its supposed replacements, including touch - Englebart was a genius.)
Microsoft usually can see the train coming long before it arrives.
In my reading of its history, Microsoft has spent a good deal of its existence catching up with one train or another. Two notable examples: GUIs and the internet.
Oh, for fuck's sake, this argument is just awful. "Well, people SHOULD pay protection money, because otherwise anyone with enough strength might break their legs."
You must be a philosopher, because your analysis, and the course of action that you derive from it, is only valid in a possible world that we don't live in. In the real world, society incurs expenses all the time to protect itself from malicious parties. Last time I bought a car, they were still putting locks on them. If you want to get worked up over this, you should start with the defense budget of the nation you live in.
Except, as it says in TFA, the guy now "welcomes cold calls". I can see the point of slugging cold-callers with what is effectively a "fine", but once you go to the extreme of extending unsolicited calls just for the revenue, then that is just profiteering.
Personally, I just say "Please hold the line..." and put the phone under a cushion. I don't care if the underpaid caller loses on his quota: that is not my problem.
Your response targets someone who is arguably being exploited by the scheme, rather than those who instigated and profit from it.
I agree with Dishevel, and I do also use the 'please hold' response - maybe it will get me flagged as 'waste of time'. If there was an easy way to be more than a trivial inconvenience to them, I would do it.
I think that the punchline is " if the texter knows, or has special reason to know, the recipient will view the text while driving."
Agreed, and I wonder if the judges are thinking of situations such as where a company texts one of their drivers while she is on the road, especially if the company has created an environment where the driver is under pressure to respond immediately.
On the other hand, this is mainly just another revenue stream for lawyers, because you know it is going to be pursued in every case, regardless of whether it is plausible the sender knew, and the sender will have to defend against it.
The premium rate 09 lines you are talking about are separately regulated and abuse is prosecuted.
The only abuse here is the cold-calling (I am, of course, writing from an ethics point of view, which should not be confused with the legal or telco views.)
If you go back to the start of this discussion, you can see that it didn't start as a disagreement over the definition of 'intelligence'. What has happened here is that you have painted yourself into a corner where you have to use a definition of 'intelligence' that is so weak that my thermostat qualifies.
It sounds like you want to define intelligence entirely in terms of how you do something, not in terms of what you do. But that raises a difficult question: what techniques count as "intelligence"? And how do you decide that?
It doesn't raise a difficult question - the question is difficult no matter how you look at it. Unless you are proposing that an intelligent action is defined as anything that a human does, which has a host of problems that I touched on in my previous post, then, in your approach, we face the same question when deciding which actions are intelligent.
Consider playing chess. You say that computer chess programs are not intelligent because we understand how they work, and those are different from what a human does.
Not exactly - It is not my position that AI has to work like human intelligence. The reason no extant chess program counts as intelligent is because there is clearly more to intelligent chess-playing than brute-force search, a vast memory of pre-computed partial results, and custom heuristics that are inscrutable to the agent. We can see that this is true because a) humans cannot perform the searches or memorize end-games to a degree even remotely close to what the machine is capable of, yet the best human players perform comparably to the best computers; b) if you take those capabilities from the machine, its performance crashes; and c) humans not only understand the heuristics they use, they developed them themselves.
Developing those heuristics is part of intelligent play. I believe some of Deep Blue's heuristics came from machine learning applied to a vast set of games against other programs, which is where things begin to get interesting, but it is not as if Deep Blue figured out what training it needed to do to improve itself.
You don't have to take my word for it - The developers of Deep Blue carefully and deliberately avoided describing it as intelligent.
But human chess playing is actually pretty easy to understand...
That's what an earlier generation of AI developers thought, but after a promising start, they ran into a wall of diminishing returns. It was an early example of the AI community prematurely anticipating success.
Furthermore, you glossed over the difficult bits, such as how the heuristics are developed in the first place.
And all of these techniques are ones that computer chess programs can also be programmed to use.
And yet the humans kept on winning. Deep Blue finally scraped a Pyrrhic win by brute force. The difficulty of that achievement belies your claim that chess is just a matter of a few easily-understood algorithms coupled with memorization.
You want to say that human chess players use some mysterious power called "intelligence" that is different from what computers do. But that just isn't true.
To accurately state what I think, 'mysterious' should be read as 'currently poorly understood' and 'different from what computers do' should be read as 'different from what computing has done so far.' And that I believe to be empirically true, for all the reasons I have given here and in my first post.
On the other hand, you are now arguing against the role of intelligence in chess-playing, which is the opposite of your position in your first post.
Likewise, you say that humans translate a text by "understanding" it, which you define with the Potter Stewart approach of, "We can't explain it, but we know it when we see it."
That is the nature of things that are not well understood, and you can't change that by rephrasing the problem.
But do we really know it when we see it?
You assumed you could when you chose to define an intelligent action as something that an intelligent agent does - specifically, when you decide whether an agent is intellige
Where does this end? Maybe never, since there may always exist a future test that it will fail. However, if a system goes, say, ten years without failing, a lot of people will probably be satisfied with that.
I think that, in the situation you predict, we will find it more useful to recognize degrees of intelligence, rather than talk in pass/fail terms.
When a human does these things [play chess, translate documents, plan a route], we call it intelligence. Our judgement that they are "displaying intelligence" is not based on understanding how they did it. We therefore must accept a computer that does them as being intelligent too.
The fact that we cannot explain intelligence does add some difficulty to talking about it, and while reasonable people can disagree over this, I think the approach you use here tends to confuse two things, which you then have to separate by introducing the qualifiers 'weak' and 'strong'.
In your argument, you consider intelligence to be an attribute of an activity, such as playing chess, and then you transfer this attribute to any agent performing the activity. But how do you decide which activities are intelligent? My guess is that you do it by the human test: if humans use intelligence to perform the act, then it is an intelligent act.
There is a sort of semantic flow here, and it has formed a self-referential circle: intelligent actions bestow the quality of intelligence on the agents performing them, but the actions were bestowed the quality of intelligence in the first place by the agents performing them.
The other problem with this approach is that you still have to make a completely independent judgement of what constitutes intelligent action: if moving from A to B or eating were to be included, all animals are intelligent, and the term loses its usefulness. If you can make the distinction for a human's action, you can do it for any agent's actions without invoking semantic flow. By this analysis, we can see that intelligence is a property of the means by which things are done, not the actions themselves.
So the semantic flow approach has not helped in the definition of intelligence, but it also adds another difficulty. Out of the specific examples you give, a computer finding the best route too the airport is not considered to be AI, weak or otherwise. In the case of Deep Blue, even its developers were at pains to say it was not AI, because we know that the techniques it used, such as exhaustive search to considerable depth and a huge memory of pre-computed end-games, were not options for Kasparov, yet he played essentially as well as the computer. Whatever the intelligence he used was, it was not what the computer was doing.
So the problem is that the semantic flow approach to defining AI would label both Deep Blue and my car's GPS as intelligent, and arguably also the car itself for merely moving from A to B (at least when the automatic parallel parking feature is in use.) To get around this problem, the term 'weak AI' was introduced, with the distinction that 'weak AI' is not generalizable.
If you take my approach, and consider intelligence to be an attribute of the way in which something is done, rather than of either the actor or the action, then you get more directly to a similar position, but without the confusion you get whenever the strong/weak distinction is not made, and one party says AI is a solved problem, and the other says that's nonsense.
Furthermore, the strong/weak workaround is a bit of a kludge that may be OK for these examples, but it runs into difficulties with machine learning, which is generalizable to a degree. I think it is still an open question whether machine learning has, or ever will, achieve intelligence. Consider your third example, translation. Machine learning does it (and impressively so) by a thorough (if not exhaustive) calculation over correlations in a very large sample set. Humans, however, approach it differently: we go through the intermediate step of understanding the text.
Understanding is a concept that we cannot explain, but that does not render it useless, because we understand it well enough to recognize it. The study of an AI's performance on an IQ test is relevant here, because the AI did particularly badly on questions that required understanding (the 'why' questions, as the article p
The problem with most proposed tests for intelligent computing is that not everything that humans need intelligence to perform require intelligence. For example, Gary Kasparov had to use his intelligence to play chess essentially with the same performance as Deep Blue, but nobody, especially not its developers, mistook Deep Blue for an intelligent agent.
A recent post concerned AI performance on IQ tests. The program being tested performed on average like a 4 year old, but, significantly, its performance was very uneven, and it did particularly poorly on comprehension.
Turing cannot be faulted for not anticipating the way Turing tests have been gamed. I think his basic approach is still valid; it just needs to be tweaked a bit. This is not moving the goalposts, it is a valid adjustment for what we have learned.
Would there really be a market for manipulating an opinion poll?
Yes. There are more than enough people in the world who do things because "everyone who is anyone is doing it".
True, but in other circumstances, such as a race that is polling as unexpectedly close, it might provoke more supporters of the underdog to vote. I am certain that the questions of how to game the predictions, when, and in which direction, are being actively studied.
It should be noted that in the last U.S. presidential election, partisan predictions did not seem to affect the result, and Nate Silver became famous for accurately calling it by being as objective as he could.
Google "buy twitter followers" and you will see a lot of companies dealing with this.
The WSJ article mentions 'promoted' tweets as well as tweets from the candidates' organizations, and says the researchers found that they tended to cancel out (this also suggests they were not being excluded from the study.) This study might provoke attempts to game future measurements, but fortunately, this is only about prediction, not actual voting (unless correlation actually does imply causation in this case, but there is no suggestion that it does.)
They wanted to show that... the AI-joke problem was simpler than previously thought.
If they think this work shows that, they can't have much of a sense of humor.
More seriously, I get the impression that machine learning, and especially unsupervised learning, is the latest hope of the AI community, but I don't think they have shown much reason to believe it will go beyond sophisticated mimicry, with most of the apparent progress being attributable to Moore's law. In this case, they claim that 16% of the generated jokes are considered funny by humans, and I suspect they will find it increasingly difficult to keep the hit rate improving. So far, the law of diminishing returns seems to kick in before the emergence of any behavior that goes beyond a clever imitation of intelligence.
Ok then what's the purpose of HAVING a sign-off if not to say "I understand this, think it's a good idea, approve of it, and am willing to put my name to it?" QED.
Exactly. The productive work, in contrast, consists of figuring out what is to be done and how it is to be done, and doing it. If things work out well, the sign-off itself is moot.
I know one of the IBM Admins for this job, she said Qld health signed off at every stage before going live.
By itself, sign-off is a red herring in these issues. The contractor is supposed to have the expertise to propose viable solutions before the sign-off, and then to implement them effectively. If the client went against good advice or repeatedly changed its mind, then it carries a share of the blame that can reach 100%, but you cannot establish that from the sign-offs alone (after all, the contractor also signed off on the same things at the same time.) The sign-offs are useful only as corroborating evidence for the information that is needed to determine what went wrong, which is a) who decided what, and when? and b) were the decisions effectively implemented?
While sign-offs are an important formal action in the process, they are not themselves productive, and when I see people obsessing over them, I see people in CYA mode, preparing for the assignment-of-blame phase of the project.
The entire speech is spun from speculation: "I can sit here and imagine circumstances and scenarios, but they're nothing more than imaginative." (his words).
"ConceptNet 4 did dramatically worse than average on comprehension—the ‘why’ questions.” - Robert Sloan, lead author of the study.
This comment strengthens my feeling that current AI is making progress in faking many of the accidental attributes of intelligence, but has not discovered the essence.
The development of childrens' mental abilities seems to accelerate over time, as if there is positive feedback, but this does not seem to have emerged in AI yet, especially if we factor out Moore's law. On the contrary, any given exercise in developing AI through machine learning seems to hit a wall of diminishing returns at some point. Is anyone aware of a project that has not experienced this effect?
Slashdot Mirror
Right. The authors have overlooked the fact, as shown by their own map, that, in 1347, the plague moved into Europe along a broad front: the Mediterranean coastline. I imagine that it spread along that front by ship, a good deal faster than the inland spread that the authors base their thesis on.
Furthermore, the authors summarily dismiss the effect of the disease on its spread. It was very debilitating, and a traveller on land who fell sick would be unlikely to continue his journey. The authors exaggerate the distance a sick traveller would be likey to spread the disease.
Add to this the failure of the authors to recognize that almost all land travel would be by foot (with what animals were being used for transport mostly being used to carry the baggage of foot travellers) and you have three strikes against their argument. I don't doubt that the world was less connected than than it is now, but the authors overstate their case. By overestimating the rate at which land travel would, in practice, spread the diseease, they have underestimated the amount of travel.
Isn't the energy released from a fusion reaction ALWAYS larger than the energy absorbed?
In the case of lightweight elements, the energy released by two fusing nuclei is less than the kinetic energy smashing them together, but only a small fraction of the nuclei in a pellet fuse, and most of the energy absorbed by the pellet goes into heating and ionizing the atoms that don't undergo fusion.
"Lalueza-Fox was able to isolate a small amount of Y chromosome from the inner part of the head, which is transmitted from male to male each generation."
Well, maybe. But I don't believe a chic bullshit detector is a logical possibility.
That is what it looks like in retrospect...
I recall it looking that way at the time, too. Of course, in each case, there was a lag between when the train left the station and when Microsoft realized it needed to be on it, and in that interval, it was preoccupied with the things you describe.
The tablet/touch part must hurt because, for once, they were pioneers of the software technology (albeit on a mainframe-sized surface), but then they repeated Xerox' canonical mistake (that's definitely a retrospective view - I didn't see it coming at the time. I am a curmudgeon in these matters, and for most purposes, I still find a mouse to be superior to any of its supposed replacements, including touch - Englebart was a genius.)
Microsoft usually can see the train coming long before it arrives.
In my reading of its history, Microsoft has spent a good deal of its existence catching up with one train or another. Two notable examples: GUIs and the internet.
I'm amused by the ironic juxtaposition of your post and your sig.
Oh, for fuck's sake, this argument is just awful. "Well, people SHOULD pay protection money, because otherwise anyone with enough strength might break their legs."
You must be a philosopher, because your analysis, and the course of action that you derive from it, is only valid in a possible world that we don't live in. In the real world, society incurs expenses all the time to protect itself from malicious parties. Last time I bought a car, they were still putting locks on them. If you want to get worked up over this, you should start with the defense budget of the nation you live in.
Except, as it says in TFA, the guy now "welcomes cold calls". I can see the point of slugging cold-callers with what is effectively a "fine", but once you go to the extreme of extending unsolicited calls just for the revenue, then that is just profiteering.
Personally, I just say "Please hold the line..." and put the phone under a cushion. I don't care if the underpaid caller loses on his quota: that is not my problem.
Your response targets someone who is arguably being exploited by the scheme, rather than those who instigated and profit from it.
I agree with Dishevel, and I do also use the 'please hold' response - maybe it will get me flagged as 'waste of time'. If there was an easy way to be more than a trivial inconvenience to them, I would do it.
I think that the punchline is " if the texter knows, or has special reason to know, the recipient will view the text while driving."
Agreed, and I wonder if the judges are thinking of situations such as where a company texts one of their drivers while she is on the road, especially if the company has created an environment where the driver is under pressure to respond immediately.
On the other hand, this is mainly just another revenue stream for lawyers, because you know it is going to be pursued in every case, regardless of whether it is plausible the sender knew, and the sender will have to defend against it.
The premium rate 09 lines you are talking about are separately regulated and abuse is prosecuted.
The only abuse here is the cold-calling (I am, of course, writing from an ethics point of view, which should not be confused with the legal or telco views.)
If you go back to the start of this discussion, you can see that it didn't start as a disagreement over the definition of 'intelligence'. What has happened here is that you have painted yourself into a corner where you have to use a definition of 'intelligence' that is so weak that my thermostat qualifies.
They plan to confine their activities to legal surveillance from now on.
Yeah, right.
It sounds like you want to define intelligence entirely in terms of how you do something, not in terms of what you do. But that raises a difficult question: what techniques count as "intelligence"? And how do you decide that?
It doesn't raise a difficult question - the question is difficult no matter how you look at it. Unless you are proposing that an intelligent action is defined as anything that a human does, which has a host of problems that I touched on in my previous post, then, in your approach, we face the same question when deciding which actions are intelligent.
Consider playing chess. You say that computer chess programs are not intelligent because we understand how they work, and those are different from what a human does.
Not exactly - It is not my position that AI has to work like human intelligence. The reason no extant chess program counts as intelligent is because there is clearly more to intelligent chess-playing than brute-force search, a vast memory of pre-computed partial results, and custom heuristics that are inscrutable to the agent. We can see that this is true because a) humans cannot perform the searches or memorize end-games to a degree even remotely close to what the machine is capable of, yet the best human players perform comparably to the best computers; b) if you take those capabilities from the machine, its performance crashes; and c) humans not only understand the heuristics they use, they developed them themselves.
Developing those heuristics is part of intelligent play. I believe some of Deep Blue's heuristics came from machine learning applied to a vast set of games against other programs, which is where things begin to get interesting, but it is not as if Deep Blue figured out what training it needed to do to improve itself.
You don't have to take my word for it - The developers of Deep Blue carefully and deliberately avoided describing it as intelligent.
But human chess playing is actually pretty easy to understand...
That's what an earlier generation of AI developers thought, but after a promising start, they ran into a wall of diminishing returns. It was an early example of the AI community prematurely anticipating success.
Furthermore, you glossed over the difficult bits, such as how the heuristics are developed in the first place.
And all of these techniques are ones that computer chess programs can also be programmed to use.
And yet the humans kept on winning. Deep Blue finally scraped a Pyrrhic win by brute force. The difficulty of that achievement belies your claim that chess is just a matter of a few easily-understood algorithms coupled with memorization.
You want to say that human chess players use some mysterious power called "intelligence" that is different from what computers do. But that just isn't true.
To accurately state what I think, 'mysterious' should be read as 'currently poorly understood' and 'different from what computers do' should be read as 'different from what computing has done so far.' And that I believe to be empirically true, for all the reasons I have given here and in my first post.
On the other hand, you are now arguing against the role of intelligence in chess-playing, which is the opposite of your position in your first post.
Likewise, you say that humans translate a text by "understanding" it, which you define with the Potter Stewart approach of, "We can't explain it, but we know it when we see it."
That is the nature of things that are not well understood, and you can't change that by rephrasing the problem.
But do we really know it when we see it?
You assumed you could when you chose to define an intelligent action as something that an intelligent agent does - specifically, when you decide whether an agent is intellige
Where does this end? Maybe never, since there may always exist a future test that it will fail.
However, if a system goes, say, ten years without failing, a lot of people will probably be satisfied with that.
I think that, in the situation you predict, we will find it more useful to recognize degrees of intelligence, rather than talk in pass/fail terms.
When a human does these things [play chess, translate documents, plan a route], we call it intelligence. Our judgement that they are "displaying intelligence" is not based on understanding how they did it. We therefore must accept a computer that does them as being intelligent too.
The fact that we cannot explain intelligence does add some difficulty to talking about it, and while reasonable people can disagree over this, I think the approach you use here tends to confuse two things, which you then have to separate by introducing the qualifiers 'weak' and 'strong'.
In your argument, you consider intelligence to be an attribute of an activity, such as playing chess, and then you transfer this attribute to any agent performing the activity. But how do you decide which activities are intelligent? My guess is that you do it by the human test: if humans use intelligence to perform the act, then it is an intelligent act.
There is a sort of semantic flow here, and it has formed a self-referential circle: intelligent actions bestow the quality of intelligence on the agents performing them, but the actions were bestowed the quality of intelligence in the first place by the agents performing them.
The other problem with this approach is that you still have to make a completely independent judgement of what constitutes intelligent action: if moving from A to B or eating were to be included, all animals are intelligent, and the term loses its usefulness. If you can make the distinction for a human's action, you can do it for any agent's actions without invoking semantic flow. By this analysis, we can see that intelligence is a property of the means by which things are done, not the actions themselves.
So the semantic flow approach has not helped in the definition of intelligence, but it also adds another difficulty. Out of the specific examples you give, a computer finding the best route too the airport is not considered to be AI, weak or otherwise. In the case of Deep Blue, even its developers were at pains to say it was not AI, because we know that the techniques it used, such as exhaustive search to considerable depth and a huge memory of pre-computed end-games, were not options for Kasparov, yet he played essentially as well as the computer. Whatever the intelligence he used was, it was not what the computer was doing.
So the problem is that the semantic flow approach to defining AI would label both Deep Blue and my car's GPS as intelligent, and arguably also the car itself for merely moving from A to B (at least when the automatic parallel parking feature is in use.) To get around this problem, the term 'weak AI' was introduced, with the distinction that 'weak AI' is not generalizable.
If you take my approach, and consider intelligence to be an attribute of the way in which something is done, rather than of either the actor or the action, then you get more directly to a similar position, but without the confusion you get whenever the strong/weak distinction is not made, and one party says AI is a solved problem, and the other says that's nonsense.
Furthermore, the strong/weak workaround is a bit of a kludge that may be OK for these examples, but it runs into difficulties with machine learning, which is generalizable to a degree. I think it is still an open question whether machine learning has, or ever will, achieve intelligence. Consider your third example, translation. Machine learning does it (and impressively so) by a thorough (if not exhaustive) calculation over correlations in a very large sample set. Humans, however, approach it differently: we go through the intermediate step of understanding the text.
Understanding is a concept that we cannot explain, but that does not render it useless, because we understand it well enough to recognize it. The study of an AI's performance on an IQ test is relevant here, because the AI did particularly badly on questions that required understanding (the 'why' questions, as the article p
The problem with most proposed tests for intelligent computing is that not everything that humans need intelligence to perform require intelligence. For example, Gary Kasparov had to use his intelligence to play chess essentially with the same performance as Deep Blue, but nobody, especially not its developers, mistook Deep Blue for an intelligent agent.
A recent post concerned AI performance on IQ tests. The program being tested performed on average like a 4 year old, but, significantly, its performance was very uneven, and it did particularly poorly on comprehension.
Turing cannot be faulted for not anticipating the way Turing tests have been gamed. I think his basic approach is still valid; it just needs to be tweaked a bit. This is not moving the goalposts, it is a valid adjustment for what we have learned.
In other words, a verbal commitment is worth the paper it's written on.
It is every bit as good as a written constitution.
Yes. There are more than enough people in the world who do things because "everyone who is anyone is doing it".
True, but in other circumstances, such as a race that is polling as unexpectedly close, it might provoke more supporters of the underdog to vote. I am certain that the questions of how to game the predictions, when, and in which direction, are being actively studied.
It should be noted that in the last U.S. presidential election, partisan predictions did not seem to affect the result, and Nate Silver became famous for accurately calling it by being as objective as he could.
Google "buy twitter followers" and you will see a lot of companies dealing with this.
The WSJ article mentions 'promoted' tweets as well as tweets from the candidates' organizations, and says the researchers found that they tended to cancel out (this also suggests they were not being excluded from the study.) This study might provoke attempts to game future measurements, but fortunately, this is only about prediction, not actual voting (unless correlation actually does imply causation in this case, but there is no suggestion that it does.)
They wanted to show that ... the AI-joke problem was simpler than previously thought.
If they think this work shows that, they can't have much of a sense of humor.
More seriously, I get the impression that machine learning, and especially unsupervised learning, is the latest hope of the AI community, but I don't think they have shown much reason to believe it will go beyond sophisticated mimicry, with most of the apparent progress being attributable to Moore's law. In this case, they claim that 16% of the generated jokes are considered funny by humans, and I suspect they will find it increasingly difficult to keep the hit rate improving. So far, the law of diminishing returns seems to kick in before the emergence of any behavior that goes beyond a clever imitation of intelligence.
Ok then what's the purpose of HAVING a sign-off if not to say "I understand this, think it's a good idea, approve of it, and am willing to put my name to it?" QED.
Exactly. The productive work, in contrast, consists of figuring out what is to be done and how it is to be done, and doing it. If things work out well, the sign-off itself is moot.
I know one of the IBM Admins for this job, she said Qld health signed off at every stage before going live.
By itself, sign-off is a red herring in these issues. The contractor is supposed to have the expertise to propose viable solutions before the sign-off, and then to implement them effectively. If the client went against good advice or repeatedly changed its mind, then it carries a share of the blame that can reach 100%, but you cannot establish that from the sign-offs alone (after all, the contractor also signed off on the same things at the same time.) The sign-offs are useful only as corroborating evidence for the information that is needed to determine what went wrong, which is a) who decided what, and when? and b) were the decisions effectively implemented?
While sign-offs are an important formal action in the process, they are not themselves productive, and when I see people obsessing over them, I see people in CYA mode, preparing for the assignment-of-blame phase of the project.
The entire speech is spun from speculation: "I can sit here and imagine circumstances and scenarios, but they're nothing more than imaginative." (his words).
Much like the Iraqi WMD thing.
"ConceptNet 4 did dramatically worse than average on comprehension—the ‘why’ questions.” - Robert Sloan, lead author of the study.
This comment strengthens my feeling that current AI is making progress in faking many of the accidental attributes of intelligence, but has not discovered the essence.
The development of childrens' mental abilities seems to accelerate over time, as if there is positive feedback, but this does not seem to have emerged in AI yet, especially if we factor out Moore's law. On the contrary, any given exercise in developing AI through machine learning seems to hit a wall of diminishing returns at some point. Is anyone aware of a project that has not experienced this effect?