Re: OT?: AI, learning networks and pattern recognition (was: Apples actual response to the Flash issue)
Dear all, i think it is all said. Please stop this annoying discussion. This list is called use-revolution, so maybe we can come back to this again. Thank you! Matthias Am 03.05.2010 um 07:47 schrieb Randall Lee Reetz: Why don't you ask the guys at adobe if their content is really aware. -Original Message- From: Ian Wood revl...@azurevision.co.uk Sent: Sunday, May 02, 2010 9:27 PM To: How to use Revolution use-revolution@lists.runrev.com Subject: OT?: AI, learning networks and pattern recognition (was: Apples actual response to the Flash issue) Now we're getting somewhere that actually has some vague relevance to the list. On 2 May 2010, at 22:39, Randall Reetz wrote: I had assumed your questions were rhetorical. If I ask the same questions multiple times you can be sure that they're not rhetorical. When I say that software hasn't changed I mean to say that it hasn't jumped qualitative categories. We are still living in a world where computing exists as pre-written and compiled software that is blindly executed by machines and stacked foundational code that has no idea what it is processing, can only process linearly, all semantics have been stripped, it doesn't learn from experience or react to context unless this too has been pre-codified and frozen in binary or byte code, etc. etc etc. Hardware has been souped up. So our little wrote tricks can be made more elaborate within the substantial confines mentioned. These same in-paradigm restrictions apply to both the software users slog through and the software we use to write software. As a result, these very plastic machines with mercurial potential are reduced to simple players that react to user interrupts. They are sequencing systems, not unlike the lead type setting racks of Guttenburg-era printing presses. Sure we have taught them some interesting seeming tricks – if you can represent something as digital media, be it sound, video, multi-dimentional graph space, markup – our sequencer doesn't know enough to care. So for you, for something to be 'revolutionary' it has to involve a full paradigm shift? That's a more extreme definition than most people use. Current processors are capable of 6.5 million instructions per second but are used less than a billionth of available cycles by the standard users running standard software. From a pedantic, technical point of view, these days if the processor is being used that little then it will ramp down the clock speed, which has some environmental and practical benefits in itself. ;-) As regards photo editing software, anyone aware of the history of image processing will recognize that most of the stuff seen in photoshop and other programs was proposed and executed on systems long before some guys in france democratized these algorithms for consumer use and had their code acquired by adobe. It used to be called array arithmetic and applied smoothly to images divided up into a grid of pixels. None of these systems see an image for its content except as an array of numbers that can be crunched sequentially like a spread sheet. It was only when object recognition concepts were applied to photos that any kind of compositional grammar could be extracted from an image and compared as parts to other images similarly decomposed. This is a form of semantic processing and has its parallels in other media like text parsers and sound analysis software. You haven't looked up what content-aware fill *is*, have you? It's based on the same basic concepts of pattern-matching/feature detection that facial recognition software is based on but with a different emphasis. To paraphrase, it's not facial recognition that you think is the only revolutionary feature in photography in twenty years, it's pattern- matching/detection/eigenvectors. A lot of time and frustration would have been saved if you'd said that in the first place. Semantics opens the door to the building of systems that understand the content they process. That is the promised second revolution in computation that really hasn't seen any practical light of day as of yet. You're jumping too many steps here - object recognition concepts are in *widespread* use in consumer software and devices, whether it's the aforementioned 'focus-on-a-face' digital cameras, healing brushes in many different pieces of software, feature recognition in panoramic stitching software or even live stitching in some of the new Sony cameras. Semantic processing of content doesn't magically enable a computer to initiate action. Data mining really isn't semantically mindful, simply uses statistical reduction mechanisms to guess at the existence of the location of pattern ( a good first step but missing the grammatical hierarchy necessary
RE: OT?: AI, learning networks and pattern recognition (was: Apples actual response to the Flash issue)
Why don't you ask the guys at adobe if their content is really aware. -Original Message- From: Ian Wood revl...@azurevision.co.uk Sent: Sunday, May 02, 2010 9:27 PM To: How to use Revolution use-revolution@lists.runrev.com Subject: OT?: AI, learning networks and pattern recognition (was: Apples actual response to the Flash issue) Now we're getting somewhere that actually has some vague relevance to the list. On 2 May 2010, at 22:39, Randall Reetz wrote: I had assumed your questions were rhetorical. If I ask the same questions multiple times you can be sure that they're not rhetorical. When I say that software hasn't changed I mean to say that it hasn't jumped qualitative categories. We are still living in a world where computing exists as pre-written and compiled software that is blindly executed by machines and stacked foundational code that has no idea what it is processing, can only process linearly, all semantics have been stripped, it doesn't learn from experience or react to context unless this too has been pre-codified and frozen in binary or byte code, etc. etc etc. Hardware has been souped up. So our little wrote tricks can be made more elaborate within the substantial confines mentioned. These same in-paradigm restrictions apply to both the software users slog through and the software we use to write software. As a result, these very plastic machines with mercurial potential are reduced to simple players that react to user interrupts. They are sequencing systems, not unlike the lead type setting racks of Guttenburg-era printing presses. Sure we have taught them some interesting seeming tricks if you can represent something as digital media, be it sound, video, multi-dimentional graph space, markup our sequencer doesn't know enough to care. So for you, for something to be 'revolutionary' it has to involve a full paradigm shift? That's a more extreme definition than most people use. Current processors are capable of 6.5 million instructions per second but are used less than a billionth of available cycles by the standard users running standard software. From a pedantic, technical point of view, these days if the processor is being used that little then it will ramp down the clock speed, which has some environmental and practical benefits in itself. ;-) As regards photo editing software, anyone aware of the history of image processing will recognize that most of the stuff seen in photoshop and other programs was proposed and executed on systems long before some guys in france democratized these algorithms for consumer use and had their code acquired by adobe. It used to be called array arithmetic and applied smoothly to images divided up into a grid of pixels. None of these systems see an image for its content except as an array of numbers that can be crunched sequentially like a spread sheet. It was only when object recognition concepts were applied to photos that any kind of compositional grammar could be extracted from an image and compared as parts to other images similarly decomposed. This is a form of semantic processing and has its parallels in other media like text parsers and sound analysis software. You haven't looked up what content-aware fill *is*, have you? It's based on the same basic concepts of pattern-matching/feature detection that facial recognition software is based on but with a different emphasis. To paraphrase, it's not facial recognition that you think is the only revolutionary feature in photography in twenty years, it's pattern- matching/detection/eigenvectors. A lot of time and frustration would have been saved if you'd said that in the first place. Semantics opens the door to the building of systems that understand the content they process. That is the promised second revolution in computation that really hasn't seen any practical light of day as of yet. You're jumping too many steps here - object recognition concepts are in *widespread* use in consumer software and devices, whether it's the aforementioned 'focus-on-a-face' digital cameras, healing brushes in many different pieces of software, feature recognition in panoramic stitching software or even live stitching in some of the new Sony cameras. Semantic processing of content doesn't magically enable a computer to initiate action. Data mining really isn't semantically mindful, simply uses statistical reduction mechanisms to guess at the existence of the location of pattern ( a good first step but missing the grammatical hierarchy necessary to work towards a self optimized and domain independent ability to detect and represent salience in the stacked grammar that makes up any complex system. Combining pattern-matching with adaptive systems, whether they be neural networks or something else is another matter
RE: OT?: AI, learning networks and pattern recognition (was: Apples actual response to the Flash issue)
I can see how the word revolution in the context of this list has acquired so anemic and castrated a meaning. I am sorry. Next time, I will use a word that means all the way around, or when a king is replaced by a democracy. time. -Original Message- From: Ian Wood revl...@azurevision.co.uk Sent: Sunday, May 02, 2010 9:27 PM To: How to use Revolution use-revolution@lists.runrev.com Subject: OT?: AI, learning networks and pattern recognition (was: Apples actual response to the Flash issue) Now we're getting somewhere that actually has some vague relevance to the list. On 2 May 2010, at 22:39, Randall Reetz wrote: I had assumed your questions were rhetorical. If I ask the same questions multiple times you can be sure that they're not rhetorical. When I say that software hasn't changed I mean to say that it hasn't jumped qualitative categories. We are still living in a world where computing exists as pre-written and compiled software that is blindly executed by machines and stacked foundational code that has no idea what it is processing, can only process linearly, all semantics have been stripped, it doesn't learn from experience or react to context unless this too has been pre-codified and frozen in binary or byte code, etc. etc etc. Hardware has been souped up. So our little wrote tricks can be made more elaborate within the substantial confines mentioned. These same in-paradigm restrictions apply to both the software users slog through and the software we use to write software. As a result, these very plastic machines with mercurial potential are reduced to simple players that react to user interrupts. They are sequencing systems, not unlike the lead type setting racks of Guttenburg-era printing presses. Sure we have taught them some interesting seeming tricks if you can represent something as digital media, be it sound, video, multi-dimentional graph space, markup our sequencer doesn't know enough to care. So for you, for something to be 'revolutionary' it has to involve a full paradigm shift? That's a more extreme definition than most people use. Current processors are capable of 6.5 million instructions per second but are used less than a billionth of available cycles by the standard users running standard software. From a pedantic, technical point of view, these days if the processor is being used that little then it will ramp down the clock speed, which has some environmental and practical benefits in itself. ;-) As regards photo editing software, anyone aware of the history of image processing will recognize that most of the stuff seen in photoshop and other programs was proposed and executed on systems long before some guys in france democratized these algorithms for consumer use and had their code acquired by adobe. It used to be called array arithmetic and applied smoothly to images divided up into a grid of pixels. None of these systems see an image for its content except as an array of numbers that can be crunched sequentially like a spread sheet. It was only when object recognition concepts were applied to photos that any kind of compositional grammar could be extracted from an image and compared as parts to other images similarly decomposed. This is a form of semantic processing and has its parallels in other media like text parsers and sound analysis software. You haven't looked up what content-aware fill *is*, have you? It's based on the same basic concepts of pattern-matching/feature detection that facial recognition software is based on but with a different emphasis. To paraphrase, it's not facial recognition that you think is the only revolutionary feature in photography in twenty years, it's pattern- matching/detection/eigenvectors. A lot of time and frustration would have been saved if you'd said that in the first place. Semantics opens the door to the building of systems that understand the content they process. That is the promised second revolution in computation that really hasn't seen any practical light of day as of yet. You're jumping too many steps here - object recognition concepts are in *widespread* use in consumer software and devices, whether it's the aforementioned 'focus-on-a-face' digital cameras, healing brushes in many different pieces of software, feature recognition in panoramic stitching software or even live stitching in some of the new Sony cameras. Semantic processing of content doesn't magically enable a computer to initiate action. Data mining really isn't semantically mindful, simply uses statistical reduction mechanisms to guess at the existence of the location of pattern ( a good first step but missing the grammatical hierarchy necessary to work towards a self optimized and domain independent ability to detect and represent salience in the stacked
Re: OT?: AI, learning networks and pattern recognition
On 3 May 2010, at 06:47, Randall Lee Reetz wrote: Why don't you ask the guys at adobe if their content is really aware. So your only response to someone taking the time to go through your email in a serious manner and discuss the topics included is to take a pot-shot and not respond to any of the points? Yep, put me down as another person who's putting your email address into the spam filter as a troll. Ian ___ use-revolution mailing list use-revolution@lists.runrev.com Please visit this url to subscribe, unsubscribe and manage your subscription preferences: http://lists.runrev.com/mailman/listinfo/use-revolution
Re: OT?: AI, learning networks and pattern recognition
what is happening on my list :-( I stay away for a couple of days and all things break loose... tesc tesc tesc... Now, I've just devised the perfect solution for this! Now, Revolution powered list monitor software will scan every email and assign a Revolution Content Rate factor to it, if it has a high RCR number, it will simply go thru, if its RCR is too low, then you will be driven to the Quality Center and the system will request that you solve an engine bug. If/When you solve it, then, your mail will go thru. The bugs will be assigned using a simple algorithm where the severity or age of the bug is inversely proportional to the RCR value of the email. So that if you rate quite low on RCR you will be given the most old powerful engine bugs to solve. I hope you all understand that this is for the good of the community and we'll benefit from it, if the low RCR rate continues like what I've been seeing here, I grok that we'll solve all the engine bugs plus port the engine to Haiku, Solaris (again), FreeBSD (again), Android (Android is the new black) in about a week. If some user reaches ZERO KRCR, which stands for 0 Kelvin Revolution Content Rate which is really absolute zero RCR, he will be given flight tickets to Switzerland and a big dossie on the LHC and the task to prevent it from destroying the world. If he ever solves all CERN bugs, we'll ship our hero to SETI and then after that small taks, he'll go to Redmond to solve Windows and throw chairs at Ballmer. PS: This message has an RCR of 2, so I've been given a Bug to solve, but since QA center is down, I am yet to know which one. On Mon, May 3, 2010 at 7:17 AM, Ian Wood revl...@azurevision.co.uk wrote: On 3 May 2010, at 06:47, Randall Lee Reetz wrote: Why don't you ask the guys at adobe if their content is really aware. So your only response to someone taking the time to go through your email in a serious manner and discuss the topics included is to take a pot-shot and not respond to any of the points? Yep, put me down as another person who's putting your email address into the spam filter as a troll. Ian ___ use-revolution mailing list use-revolution@lists.runrev.com Please visit this url to subscribe, unsubscribe and manage your subscription preferences: http://lists.runrev.com/mailman/listinfo/use-revolution -- http://www.andregarzia.com All We Do Is Code. ___ use-revolution mailing list use-revolution@lists.runrev.com Please visit this url to subscribe, unsubscribe and manage your subscription preferences: http://lists.runrev.com/mailman/listinfo/use-revolution
Re: OT?: AI, learning networks and pattern recognition
Andre Garzia wrote: PS: This message has an RCR of 2, so I've been given a Bug to solve, but since QA center is down, I am yet to know which one. It's back up again, so get to work. :) -- Jacqueline Landman Gay | jac...@hyperactivesw.com HyperActive Software | http://www.hyperactivesw.com ___ use-revolution mailing list use-revolution@lists.runrev.com Please visit this url to subscribe, unsubscribe and manage your subscription preferences: http://lists.runrev.com/mailman/listinfo/use-revolution
Re: OT?: AI, learning networks and pattern recognition
LOL :-) Le 3 mai 2010 à 15:13, Andre Garzia a écrit : what is happening on my list :-( I stay away for a couple of days and all things break loose... tesc tesc tesc... Now, I've just devised the perfect solution for this! Now, Revolution powered list monitor software will scan every email and assign a Revolution Content Rate factor to it, if it has a high RCR number, it will simply go thru, if its RCR is too low, then you will be driven to the Quality Center and the system will request that you solve an engine bug. If/When you solve it, then, your mail will go thru. The bugs will be assigned using a simple algorithm where the severity or age of the bug is inversely proportional to the RCR value of the email. So that if you rate quite low on RCR you will be given the most old powerful engine bugs to solve. I hope you all understand that this is for the good of the community and we'll benefit from it, if the low RCR rate continues like what I've been seeing here, I grok that we'll solve all the engine bugs plus port the engine to Haiku, Solaris (again), FreeBSD (again), Android (Android is the new black) in about a week. If some user reaches ZERO KRCR, which stands for 0 Kelvin Revolution Content Rate which is really absolute zero RCR, he will be given flight tickets to Switzerland and a big dossie on the LHC and the task to prevent it from destroying the world. If he ever solves all CERN bugs, we'll ship our hero to SETI and then after that small taks, he'll go to Redmond to solve Windows and throw chairs at Ballmer. PS: This message has an RCR of 2, so I've been given a Bug to solve, but since QA center is down, I am yet to know which one. On Mon, May 3, 2010 at 7:17 AM, Ian Wood revl...@azurevision.co.uk wrote: On 3 May 2010, at 06:47, Randall Lee Reetz wrote: Why don't you ask the guys at adobe if their content is really aware. So your only response to someone taking the time to go through your email in a serious manner and discuss the topics included is to take a pot-shot and not respond to any of the points? Yep, put me down as another person who's putting your email address into the spam filter as a troll. Ian ___ use-revolution mailing list use-revolution@lists.runrev.com Please visit this url to subscribe, unsubscribe and manage your subscription preferences: http://lists.runrev.com/mailman/listinfo/use-revolution -- http://www.andregarzia.com All We Do Is Code. ___ use-revolution mailing list use-revolution@lists.runrev.com Please visit this url to subscribe, unsubscribe and manage your subscription preferences: http://lists.runrev.com/mailman/listinfo/use-revolution -- Pierre Sahores mobile : (33) 6 03 95 77 70 www.wrds.com www.sahores-conseil.com ___ use-revolution mailing list use-revolution@lists.runrev.com Please visit this url to subscribe, unsubscribe and manage your subscription preferences: http://lists.runrev.com/mailman/listinfo/use-revolution
OT?: AI, learning networks and pattern recognition (was: Apples actual response to the Flash issue)
Now we're getting somewhere that actually has some vague relevance to the list. On 2 May 2010, at 22:39, Randall Reetz wrote: I had assumed your questions were rhetorical. If I ask the same questions multiple times you can be sure that they're not rhetorical. When I say that software hasn't changed I mean to say that it hasn't jumped qualitative categories. We are still living in a world where computing exists as pre-written and compiled software that is blindly executed by machines and stacked foundational code that has no idea what it is processing, can only process linearly, all semantics have been stripped, it doesn't learn from experience or react to context unless this too has been pre-codified and frozen in binary or byte code, etc. etc etc. Hardware has been souped up. So our little wrote tricks can be made more elaborate within the substantial confines mentioned. These same in-paradigm restrictions apply to both the software users slog through and the software we use to write software. As a result, these very plastic machines with mercurial potential are reduced to simple players that react to user interrupts. They are sequencing systems, not unlike the lead type setting racks of Guttenburg-era printing presses. Sure we have taught them some interesting seeming tricks – if you can represent something as digital media, be it sound, video, multi-dimentional graph space, markup – our sequencer doesn't know enough to care. So for you, for something to be 'revolutionary' it has to involve a full paradigm shift? That's a more extreme definition than most people use. Current processors are capable of 6.5 million instructions per second but are used less than a billionth of available cycles by the standard users running standard software. From a pedantic, technical point of view, these days if the processor is being used that little then it will ramp down the clock speed, which has some environmental and practical benefits in itself. ;-) As regards photo editing software, anyone aware of the history of image processing will recognize that most of the stuff seen in photoshop and other programs was proposed and executed on systems long before some guys in france democratized these algorithms for consumer use and had their code acquired by adobe. It used to be called array arithmetic and applied smoothly to images divided up into a grid of pixels. None of these systems see an image for its content except as an array of numbers that can be crunched sequentially like a spread sheet. It was only when object recognition concepts were applied to photos that any kind of compositional grammar could be extracted from an image and compared as parts to other images similarly decomposed. This is a form of semantic processing and has its parallels in other media like text parsers and sound analysis software. You haven't looked up what content-aware fill *is*, have you? It's based on the same basic concepts of pattern-matching/feature detection that facial recognition software is based on but with a different emphasis. To paraphrase, it's not facial recognition that you think is the only revolutionary feature in photography in twenty years, it's pattern- matching/detection/eigenvectors. A lot of time and frustration would have been saved if you'd said that in the first place. Semantics opens the door to the building of systems that understand the content they process. That is the promised second revolution in computation that really hasn't seen any practical light of day as of yet. You're jumping too many steps here - object recognition concepts are in *widespread* use in consumer software and devices, whether it's the aforementioned 'focus-on-a-face' digital cameras, healing brushes in many different pieces of software, feature recognition in panoramic stitching software or even live stitching in some of the new Sony cameras. Semantic processing of content doesn't magically enable a computer to initiate action. Data mining really isn't semantically mindful, simply uses statistical reduction mechanisms to guess at the existence of the location of pattern ( a good first step but missing the grammatical hierarchy necessary to work towards a self optimized and domain independent ability to detect and represent salience in the stacked grammar that makes up any complex system. Combining pattern-matching with adaptive systems, whether they be neural networks or something else is another matter - but it's been a long hard slog to find out that this is what you're talking about. Adaptive systems themselves are also quite widespread by now, from Tivos learning what programmes you watch to predictive text on an iPhone, from iTunes 'Genius' playlists recommendations through to Siri (just bought up by Apple, as it happens). Such systems will need to work all of
