The face is just a wrapper - a receipient wouldn't have the same bone structure, behavior/expressions (raised eyebrows, winks, scowls), eyes, ways of moving mouth and lips (speech, etc) as the donor.
Remember also that the police do facial reconstruction from bare skulls and get recognisable results - the bone structure is a VERY large part of what makes you look like you do.
To have a GUI scale in that way (appear same but higher resolution on higher resolution display) you really need more than abstract coordinates (not float vs integer - abstract resolution independent vs pixel based). You also need a stroke (vs pixel) based graphics library like Apple's Quartz (display PDF).
Nope - you can crop all but the central region of a photo, change it from sepia to B/W and place it on a new background and it'll still find it. How do I know? - I tried it, and also read their FAQ.
I'm guessing that currently color shifts match as long as the luminance information doesn't change too much, but their FAQ doesn't specifically say how they match and eliminate match candidates.
Given their target market, they're not going to want to make matching too forgiving (i.e get too many false positives), but presumably they may make the degree/type of match more configurable in future versions (at least for paying customers). You might want to have a tight match criteria in an automated notify-me-whenever-matches-appear scenario, but looser searches when done interactively (e.g. show me the top 10 best matches, however good/bad the matches are).
The article appears to suggest that it is that good, if you can take a photo on your phone of a painting, and then find an article on that painting...
If you read their FAQ, it says it's not designed to work for that type of thing - it's for searching for instances & lightly photoshopped variations of specific pictures, not searching for pictures with similar content. i.e. if you searched for a picture of a tree it'd return any instances of that specific picture, not other pictures of that tree or pictures of other trees.
It seems to be meant more as a copyright protection tool than a semantic search tool, and seems to do what it claims very well from what I've tested.
I write code for Telecom test systems that need to run 24x7 processing highly varying requests from dozens of different client systems. Our system consists of dozens of different processes/components per host, with multiple hosts all invoking components on each other as needed (all via CORBA). There are very many paths that any request can take through our system.
In this environment we log VERY heavily since each request is close to unique and we need to be able to determine the path it took through the system, and why it did, and what happened, in the event of any bug report. Some of the haviest used modules can produce close to 1GB of log per day per host - upto a couple hundred lines of logging information per request per process that it passes thru. We use a custom printf-like log library written in C++ (that auto rotates the log files based on various criteria), a custom tail utility for dealing with the large log files (tail a log file from a given timestamp - done instantly via binary search on the timestamps) and a daily cron job to compress the older log files and move any older than 5 days off the production servers to someplace with more storage.
Not sure how not only you but a bunch of moderators all failed to read the article... The camera light DID go on, which is one of the things that drew her attention.
One of the new problems was that the computer's built-in camera light came on every time she was near the machine.
If the "spy" software was smart it might have been able (depending on camera hardware/firmware) to have been able to turn the light off, but seeing as it didn't the point is rather moot!
A quick scan of TFA doesn't reveal the heritage of Aurora, but the emphasis on web publishng vs viewing, and even the name, both immediately bring to mind the (ancient, but continuously updated) W3C editor/browser Amaya:
Presumably selection for intelligence is bidirectionally related to occupying the evolutionary niche of a generalist.
Once you are a generalist by behaviour then additional intelligence becomes adaptive.
The initial step onto that feedback cycle (from more behaviorally limited to generalist) may have been either by necessity due to change of environment/competetors (with only the more generalist/intelligent DNA surviving), or maybe opportunity/discovery (e.g. ape discovering shellfish as a food source, taking them outside of their normal environment).
The first point [The would-be AI programs must be free to rewrite portions of themselves] is the most difficult. It is *not* easy to take pieces out of two programs and build a third program that does things that both do.
You're assuming that the intelligence is in the code, but a more reasonable place for it to be is the data (essentially data connections/relationships), and Google is already in the business of storing data relationships. "All" that needs to change is that they'd have to change to a scheme where it was the data relationships, not their code, that determined the processing to do...
There is a continuous spectrum of processing architectures from traditional code driven to cutting edge data driven techniques. The example you give is just one point on that spectrum. Not a very interesting point.
The fact that given system is using a neural net doesn't in of itself define where it exists on that code driven-data driven spectrum. With a neural net it's the connection architecture that defines the processing that is being effected by pumping data through it, and of course if the connection architecture is largely or wholely fixed than all you are doing by "training" it is indeed just parameterizing a pre-chosen model or mapping.I use the scare quotes around "training" since the training/running dichotomy is artificial - more useful neural nets learn/adapt continuously as data is pumped through them, and don't make the distinction.
The more interesting type of neural networks are ones where it's not just connection strengths in a pre-determined connection (processing) scheme that are being created by the data, but the connections themselves. i.e. neural networks where it is the data itself that is largely defining the network and hence the processing performed. Our own neo-cortex is a good example. Sure the (genetically determined) "blank slate" high level architecture does constrain what types of things (data relationships) it may learn, but it would be absurd to say that at birth we're pre-programmed to play chess or code in C++ - the level of generality that the initial architecture enables is so huge that it makes more sense to say that we are data driven and that our ability to play chess is essentially determined by our exposure to chess playing. You could draw a parallel to a CPU where the built-in data processing rules (instruction set) are so general that it's really the input data (instruction stream) that defines what the CPU does - it's not meaningful to say that the CPU design has constrained/determined what the CPU can do.
Neural nets are just one example of (potentially) data driven design where the data, not code, determines what processing is performed. Another trivial example would be a using a genetic algorithm to write programs - in this type of setup it'd be meaningless to say that the software developer had specified what the (evolving) program was attempting to do, let alone how it did it - that would be determined at run time by how the evolving programs were ranked (the competition part of a genetic algorithm)... If you ranked them on their ability to play checkers then they'd evolve to play checkers, if you ranked them to play noughts-and-crosses, then they'd evolve to play that - totally outside of the control of the programmer.
The only way for a robot to grow past its programming is to add the capability to do so. And simply having a system scan data and find correlations isn't going to be enough. There needs to be an action taken on the discovered correlations, and beyond that the actions need to be reprocessed back into the system in a feedback loop. And even further, it is necessary for the program to identify patterns and make intelligent decisions based on those patterns, but the intelligence necessary to make those decisions must come from external sources. I.e. the programmer.
That's only partially true.
1) Past a certain point of capability a robot/AI doesn't need to be externally/human programmed to grow past its programming - it can do it itself.
2) It's conceivable, and not outside the realm of reasonable possibility, that someone could **accidently** make a system become intelligent and far more autonomous than they intended. Consider that our neo-cortex is responsible for most if not all of what we call intelligence (& cognition), yet the neo-cortex is really an incredibly simple repetetive structure - it's just the connections (which self-organize from the input data) that are complex. Consider what would happen if Google, maybe thinking they were just implementing some form of data self-organization or clustering, happended to accidently build something functionally equivalent to the the cortical method of doing it...
3) Of course if a system did become intelligent (essentially was autonomously learning from the data it was exposed to), we'd still have control over it in the physical sense. We'd control the power switch, we'd control whether we made it mobile or gave it actuators, we'd control whether we gave it sensors. For the cat to be truly out of the bag we'd have to get to the point of the movie "AI" where the robots have been created and exist in uncontrollably large numbers.
The appearance of intelligence is not intelligence. A recommendations system or search engine may appear intelligent, but the part of the system that processes information "intelligently" was programmed by a person who understood the process. The computer is merely following directions.
That not true in general. It's only true for old fashioned "code forward" computing where your code is specifying what to do with the data. With connectionist approaches, genetic computing, etc (and natural evolution), it's often the data not the code that is in control, and techniques like this are usually used specifically because you don't know how to "intelligently" solve the problem, so you instead, in essence, feed the data into an architecture where it organizes itself.
Let's also note that even though in a software system a genetic algoritm is explicitly coded, that in nature it's not. You'll not find "the evolutionary algorithm" anywhere in any form in nature. Evolution is just the emergent behavior what happens when the necessary pre-conditions (parallelism, shared resources/competition, imperfect inheritence) exist. A reasonable way to view using the same approach in software is that you also are not really providing an algorithm - you are just setting up the preconditions/environment that will result in what you want happening, without you being aware or specifying how it is going to happen.
They don't break out the CPU power usage - those figures are for the **entire computer**.
Idle Nano=59.2 Atom=56.4
Load Nano=77.5 Atom=60.1
If we assume that the bulk of the load vs idle power difference is due to CPU power usage, then we have the Atom using approx. 4W more under load, and the Nano using 18W more.
Whatever it's total power draw, the Atom is evidently much more miserly.
Can someone please clue me in as to what a plasmoid is? What are the differences between a plasmoid and a regular application? Why would I want to use, say, a folder view plasmoid rather than a regular file browsing app?
Jim Carey is also dating (and has been for a long time) Jenny McCarthy (of ex. MTV fame), who's son is autistic, and who praises Carey's bond with her son. I'd be very surprised if his opinion isn't well informed.
I understand that many people feel that software patents are so broken they should be thrown out.
The purpose of patents is meant to be to encourage innovation by protecting investment in innovation, but by that standard the concept of software patents is indeed broken.
Software is not like other fields where innovation occurs relatively infrequently and often at considerable cost of time and money. In the software field, there are two contradictory forces at play that capture the essence of the field:
1) Writing software is an inherently creative / innovative process. Every day you are innovating - sometimes coming up with a design takes longer than others, but innovation is essentially a daily and cheap process.
2) Software inherently requires reuse. As the realities of design patterns (formalized or not) and libraries attest, even programming languages themselves, software is inherently about applying a limited set of tools and approaches to solving the unique task at hand.
Consequently, and correspondingly:
1) Software doesn't need patent protection because innovation is not an optional investment - it is a fundamental daily practice part of the field.
2) Software is hampered by protecting "innovation" (i.e. other's software designs) since it is the nature of software that at a certain level of abstraction there are only so many ways of doing things and so many types of functionality that are needed (design patterns and libraries). If software patents are allowed it is inevitable that other software developers, on a daily basis, will need to keep redesigning the wheel, since all software needs wheels. Look at the GNU compiler set as an example - there are only so many types of code optimization techniques that make sense, and due to the patent office having allowed these "wheels" to be patented, every compiler designer, GNU team included, need to find less optimal and obvious ways of doing optimization than the obvious approaches that suggest themselves though the normal discipline of software design.
Something this small is always going to be blown about by the slightest of air currents anyway, so you need to be able to compensate for lack of 100% control. Same deal for real-life dragonflies, butterflies and even birds (even seen them trying to fly against a strong wind?), but this doesn't prevent any of these from being able to get where they want to and land on flowers, bits of grass or whetever. You just need appropriate control software.
A dragonfly (both real ones and this one - did you watch the videos?) is a lot move maneuverable (can change direction on a dime) than a plane, and also for covert applications not going to draw attention since it really does look like a dragonfly and the only noise is the flapping wings.
I'm not even sure that the aerodynamics of plane would scale to this small, but this thing demonstrably does, and real-life dragonflys prove that this design does indeed work at smaller scales such as the 5cm they are targetting for the next iteration.
Latin is certainly the language of the bible, despite the book being originally written in greek.
That would depend on where you lived, and what date you are talking about. The eastern part of the Roman empire was Greek speaking, and the western half was Latin speaking. When Constantine I had 50 copies (a significant effort) of the bible made c.330AD, they would have been in Greek - this was not a translation project. Also remember that written copies of the bible were extrememly scarce and would have only been read by a small number of scholars and early church fathers. Most 4th, and even 5th, century "Christians" were quite unclear about what exactly the new religion believed in, and saw no incompatability in also clinging to belief in the sun god Sol Invictus (as recorded and bemoaned by Pope Leo I c.450AD).
The earliest latin translations, and proliferation therof, of the bible start around the end of the 4th century with the translation of St. Jerome (based on the Hebrew original, not the Greek Septaguint) which became known as the Vulgate.
1) No, it's not the Septaguint, because the Septaguint is the old testament (aka Jewish Torah), whereas the main interest in the Codex Sinaiticus is that it is (maybe - in contention with the Codex Vaticanus) the oldest new testament, although it does also contain part of the old testament. Other copies of the old testament (e.g. dead sea scrolls) are much older.
2) The new testament canon was not decided upon at the (1st) Council of Nicea - it was provably already established before then, and the "procedings" of the Council still survive (as do writings about it by participant Eusebius). There are many persistent and untrue internet myths about the Council of Nicea.
3) It may in fact be exactly the same version of the new testament as existed in the time of roman emperor Constantine I (who convened the Council of Nicea) - given that it may well date to his time (although **precise** dating unknown), it may be one of the 50 copies of the bible that Constantine is recorded (by Eusebius) to have had produced.
jumping in wasn't too hard when the first thing you looked at after bootup was the Basic interpreter.
Get off my lawn you whippersnapper!
I started with a NASCOM-1 1MHz 2K RAM (1K for you, 1K for the "monitor" program) Z80 kit in 1978. When I finished soldering it together the only thing I got after bootup was a prompt at which you could enter hex bytes (after you hand assembled your program on paper) to a chosen memory address.
I'd actually consider this approach for someone learning about computers today. Buy an Apple II off eBay ($20 or so) and start programming in assembler. Write an interrupt driver serial driver or something that interacts directly with the hardware. There are too many kids nowadays who may know how to program in some modern scripting language, or maybe even in C/C++, but still don't really have an intimate knowledge of how computers work at the lowest level.
Slashdot Mirror
The face is just a wrapper - a receipient wouldn't have the same bone structure, behavior/expressions (raised eyebrows, winks, scowls), eyes, ways of moving mouth and lips (speech, etc) as the donor.
Remember also that the police do facial reconstruction from bare skulls and get recognisable results - the bone structure is a VERY large part of what makes you look like you do.
To have a GUI scale in that way (appear same but higher resolution on higher resolution display) you really need more than abstract coordinates (not float vs integer - abstract resolution independent vs pixel based). You also need a stroke (vs pixel) based graphics library like Apple's Quartz (display PDF).
Nope - you can crop all but the central region of a photo, change it from sepia to B/W and place it on a new background and it'll still find it. How do I know? - I tried it, and also read their FAQ.
I'm guessing that currently color shifts match as long as the luminance information doesn't change too much, but their FAQ doesn't specifically say how they match and eliminate match candidates.
Given their target market, they're not going to want to make matching too forgiving (i.e get too many false positives), but presumably they may make the degree/type of match more configurable in future versions (at least for paying customers). You might want to have a tight match criteria in an automated notify-me-whenever-matches-appear scenario, but looser searches when done interactively (e.g. show me the top 10 best matches, however good/bad the matches are).
The article appears to suggest that it is that good, if you can take a photo on your phone of a painting, and then find an article on that painting...
If you read their FAQ, it says it's not designed to work for that type of thing - it's for searching for instances & lightly photoshopped variations of specific pictures, not searching for pictures with similar content. i.e. if you searched for a picture of a tree it'd return any instances of that specific picture, not other pictures of that tree or pictures of other trees.
It seems to be meant more as a copyright protection tool than a semantic search tool, and seems to do what it claims very well from what I've tested.
Seems to work too!
I tried it on a pic and it came back not with the original but one where my search image had been:
1) Changed from sepia to B/W, AND
2) Had the central oval shaped region retained, and the rest replaced with some photoshopped frame.
I was impressed.
I write code for Telecom test systems that need to run 24x7 processing highly varying requests from dozens of different client systems. Our system consists of dozens of different processes/components per host, with multiple hosts all invoking components on each other as needed (all via CORBA). There are very many paths that any request can take through our system.
In this environment we log VERY heavily since each request is close to unique and we need to be able to determine the path it took through the system, and why it did, and what happened, in the event of any bug report. Some of the haviest used modules can produce close to 1GB of log per day per host - upto a couple hundred lines of logging information per request per process that it passes thru. We use a custom printf-like log library written in C++ (that auto rotates the log files based on various criteria), a custom tail utility for dealing with the large log files (tail a log file from a given timestamp - done instantly via binary search on the timestamps) and a daily cron job to compress the older log files and move any older than 5 days off the production servers to someplace with more storage.
Not sure how not only you but a bunch of moderators all failed to read the article... The camera light DID go on, which is one of the things that drew her attention.
One of the new problems was that the computer's built-in camera light came on every time she was near the machine.
If the "spy" software was smart it might have been able (depending on camera hardware/firmware) to have been able to turn the light off, but seeing as it didn't the point is rather moot!
A quick scan of TFA doesn't reveal the heritage of Aurora, but the emphasis on web publishng vs viewing, and even the name, both immediately bring to mind the (ancient, but continuously updated) W3C editor/browser Amaya:
http://www.w3.org/Amaya/
Presumably selection for intelligence is bidirectionally related to occupying the evolutionary niche of a generalist.
Once you are a generalist by behaviour then additional intelligence becomes adaptive.
The initial step onto that feedback cycle (from more behaviorally limited to generalist) may have been either by necessity due to change of environment/competetors (with only the more generalist/intelligent DNA surviving), or maybe opportunity/discovery (e.g. ape discovering shellfish as a food source, taking them outside of their normal environment).
The first point [The would-be AI programs must be free to rewrite portions of themselves] is the most difficult. It is *not* easy to take pieces out of two programs and build a third program that does things that both do.
You're assuming that the intelligence is in the code, but a more reasonable place for it to be is the data (essentially data connections/relationships), and Google is already in the business of storing data relationships. "All" that needs to change is that they'd have to change to a scheme where it was the data relationships, not their code, that determined the processing to do...
There is a continuous spectrum of processing architectures from traditional code driven to cutting edge data driven techniques. The example you give is just one point on that spectrum. Not a very interesting point.
The fact that given system is using a neural net doesn't in of itself define where it exists on that code driven-data driven spectrum. With a neural net it's the connection architecture that defines the processing that is being effected by pumping data through it, and of course if the connection architecture is largely or wholely fixed than all you are doing by "training" it is indeed just parameterizing a pre-chosen model or mapping.I use the scare quotes around "training" since the training/running dichotomy is artificial - more useful neural nets learn/adapt continuously as data is pumped through them, and don't make the distinction.
The more interesting type of neural networks are ones where it's not just connection strengths in a pre-determined connection (processing) scheme that are being created by the data, but the connections themselves. i.e. neural networks where it is the data itself that is largely defining the network and hence the processing performed. Our own neo-cortex is a good example. Sure the (genetically determined) "blank slate" high level architecture does constrain what types of things (data relationships) it may learn, but it would be absurd to say that at birth we're pre-programmed to play chess or code in C++ - the level of generality that the initial architecture enables is so huge that it makes more sense to say that we are data driven and that our ability to play chess is essentially determined by our exposure to chess playing. You could draw a parallel to a CPU where the built-in data processing rules (instruction set) are so general that it's really the input data (instruction stream) that defines what the CPU does - it's not meaningful to say that the CPU design has constrained/determined what the CPU can do.
Neural nets are just one example of (potentially) data driven design where the data, not code, determines what processing is performed. Another trivial example would be a using a genetic algorithm to write programs - in this type of setup it'd be meaningless to say that the software developer had specified what the (evolving) program was attempting to do, let alone how it did it - that would be determined at run time by how the evolving programs were ranked (the competition part of a genetic algorithm)... If you ranked them on their ability to play checkers then they'd evolve to play checkers, if you ranked them to play noughts-and-crosses, then they'd evolve to play that - totally outside of the control of the programmer.
Maybe because it's not relevant?
Despite the provocative "the machine is us/ing us" title, all it is saying is that:
1) Seperation of content and presentation (= HTML & CSS) frees non-techies to provide content
2) Web 2.0 user controlled tagging means that non-techies are also providing the structure/links
That's all - no processing or intelligence forming going on here, just non-techies creating the web (of data).
The only way for a robot to grow past its programming is to add the capability to do so. And simply having a system scan data and find correlations isn't going to be enough. There needs to be an action taken on the discovered correlations, and beyond that the actions need to be reprocessed back into the system in a feedback loop. And even further, it is necessary for the program to identify patterns and make intelligent decisions based on those patterns, but the intelligence necessary to make those decisions must come from external sources. I.e. the programmer.
That's only partially true.
1) Past a certain point of capability a robot/AI doesn't need to be externally/human programmed to grow past its programming - it can do it itself.
2) It's conceivable, and not outside the realm of reasonable possibility, that someone could **accidently** make a system become intelligent and far more autonomous than they intended. Consider that our neo-cortex is responsible for most if not all of what we call intelligence (& cognition), yet the neo-cortex is really an incredibly simple repetetive structure - it's just the connections (which self-organize from the input data) that are complex. Consider what would happen if Google, maybe thinking they were just implementing some form of data self-organization or clustering, happended to accidently build something functionally equivalent to the the cortical method of doing it...
3) Of course if a system did become intelligent (essentially was autonomously learning from the data it was exposed to), we'd still have control over it in the physical sense. We'd control the power switch, we'd control whether we made it mobile or gave it actuators, we'd control whether we gave it sensors. For the cat to be truly out of the bag we'd have to get to the point of the movie "AI" where the robots have been created and exist in uncontrollably large numbers.
The appearance of intelligence is not intelligence. A recommendations system or search engine may appear intelligent, but the part of the system that processes information "intelligently" was programmed by a person who understood the process. The computer is merely following directions.
That not true in general. It's only true for old fashioned "code forward" computing where your code is specifying what to do with the data. With connectionist approaches, genetic computing, etc (and natural evolution), it's often the data not the code that is in control, and techniques like this are usually used specifically because you don't know how to "intelligently" solve the problem, so you instead, in essence, feed the data into an architecture where it organizes itself.
Let's also note that even though in a software system a genetic algoritm is explicitly coded, that in nature it's not. You'll not find "the evolutionary algorithm" anywhere in any form in nature. Evolution is just the emergent behavior what happens when the necessary pre-conditions (parallelism, shared resources/competition, imperfect inheritence) exist. A reasonable way to view using the same approach in software is that you also are not really providing an algorithm - you are just setting up the preconditions/environment that will result in what you want happening, without you being aware or specifying how it is going to happen.
They don't break out the CPU power usage - those figures are for the **entire computer**.
Idle Nano=59.2 Atom=56.4
Load Nano=77.5 Atom=60.1
If we assume that the bulk of the load vs idle power difference is due to CPU power usage, then we have the Atom using approx. 4W more under load, and the Nano using 18W more.
Whatever it's total power draw, the Atom is evidently much more miserly.
Can someone please clue me in as to what a plasmoid is? What are the differences between a plasmoid and a regular application? Why would I want to use, say, a folder view plasmoid rather than a regular file browsing app?
Jim Carey is also dating (and has been for a long time) Jenny McCarthy (of ex. MTV fame), who's son is autistic, and who praises Carey's bond with her son. I'd be very surprised if his opinion isn't well informed.
Just because none has been provided, doesn't mean that none exists.
Proof may even exist without the guy making these claims being aware of it. It's not obvious that his knowledge is first hand.
I understand that many people feel that software patents are so broken they should be thrown out.
The purpose of patents is meant to be to encourage innovation by protecting investment in innovation, but by that standard the concept of software patents is indeed broken.
Software is not like other fields where innovation occurs relatively infrequently and often at considerable cost of time and money. In the software field, there are two contradictory forces at play that capture the essence of the field:
1) Writing software is an inherently creative / innovative process. Every day you are innovating - sometimes coming up with a design takes longer than others, but innovation is essentially a daily and cheap process.
2) Software inherently requires reuse. As the realities of design patterns (formalized or not) and libraries attest, even programming languages themselves, software is inherently about applying a limited set of tools and approaches to solving the unique task at hand.
Consequently, and correspondingly:
1) Software doesn't need patent protection because innovation is not an optional investment - it is a fundamental daily practice part of the field.
2) Software is hampered by protecting "innovation" (i.e. other's software designs) since it is the nature of software that at a certain level of abstraction there are only so many ways of doing things and so many types of functionality that are needed (design patterns and libraries). If software patents are allowed it is inevitable that other software developers, on a daily basis, will need to keep redesigning the wheel, since all software needs wheels. Look at the GNU compiler set as an example - there are only so many types of code optimization techniques that make sense, and due to the patent office having allowed these "wheels" to be patented, every compiler designer, GNU team included, need to find less optimal and obvious ways of doing optimization than the obvious approaches that suggest themselves though the normal discipline of software design.
Something this small is always going to be blown about by the slightest of air currents anyway, so you need to be able to compensate for lack of 100% control. Same deal for real-life dragonflies, butterflies and even birds (even seen them trying to fly against a strong wind?), but this doesn't prevent any of these from being able to get where they want to and land on flowers, bits of grass or whetever. You just need appropriate control software.
A dragonfly (both real ones and this one - did you watch the videos?) is a lot move maneuverable (can change direction on a dime) than a plane, and also for covert applications not going to draw attention since it really does look like a dragonfly and the only noise is the flapping wings.
I'm not even sure that the aerodynamics of plane would scale to this small, but this thing demonstrably does, and real-life dragonflys prove that this design does indeed work at smaller scales such as the 5cm they are targetting for the next iteration.
Latin is certainly the language of the bible, despite the book being originally written in greek.
That would depend on where you lived, and what date you are talking about. The eastern part of the Roman empire was Greek speaking, and the western half was Latin speaking. When Constantine I had 50 copies (a significant effort) of the bible made c.330AD, they would have been in Greek - this was not a translation project. Also remember that written copies of the bible were extrememly scarce and would have only been read by a small number of scholars and early church fathers. Most 4th, and even 5th, century "Christians" were quite unclear about what exactly the new religion believed in, and saw no incompatability in also clinging to belief in the sun god Sol Invictus (as recorded and bemoaned by Pope Leo I c.450AD).
The earliest latin translations, and proliferation therof, of the bible start around the end of the 4th century with the translation of St. Jerome (based on the Hebrew original, not the Greek Septaguint) which became known as the Vulgate.
Well...
1) No, it's not the Septaguint, because the Septaguint is the old testament (aka Jewish Torah), whereas the main interest in the Codex Sinaiticus is that it is (maybe - in contention with the Codex Vaticanus) the oldest new testament, although it does also contain part of the old testament. Other copies of the old testament (e.g. dead sea scrolls) are much older.
2) The new testament canon was not decided upon at the (1st) Council of Nicea - it was provably already established before then, and the "procedings" of the Council still survive (as do writings about it by participant Eusebius). There are many persistent and untrue internet myths about the Council of Nicea.
http://faculty.cua.edu/pennington/Canon%20Law/Nicea/CouncilNicea.html
http://www.tertullian.org/rpearse/nicaea.html
3) It may in fact be exactly the same version of the new testament as existed in the time of roman emperor Constantine I (who convened the Council of Nicea) - given that it may well date to his time (although **precise** dating unknown), it may be one of the 50 copies of the bible that Constantine is recorded (by Eusebius) to have had produced.
jumping in wasn't too hard when the first thing you looked at after bootup was the Basic interpreter.
Get off my lawn you whippersnapper!
I started with a NASCOM-1 1MHz 2K RAM (1K for you, 1K for the "monitor" program) Z80 kit in 1978. When I finished soldering it together the only thing I got after bootup was a prompt at which you could enter hex bytes (after you hand assembled your program on paper) to a chosen memory address.
I'd actually consider this approach for someone learning about computers today. Buy an Apple II off eBay ($20 or so) and start programming in assembler. Write an interrupt driver serial driver or something that interacts directly with the hardware. There are too many kids nowadays who may know how to program in some modern scripting language, or maybe even in C/C++, but still don't really have an intimate knowledge of how computers work at the lowest level.
Steve Jobs is definately a creative entrepreneur, but he is also a lucky one.
Nah... the failure rate for startups is phenomenal, but Jobs:
- Made a success Apple (maybe luck there - right place, right time - but also the right product)
- Made a success of NeXT (at least sufficiently so to sell it for boatloads of cash, and much of the tech lives on)
- Made a success of Pixar
- Came back to Apple when it was failing, turned it around, and introduced: iMac, OS/X, iPod, ITunes, iPhone ...
That's a heck of a string of "luck"! ;-)
Incidently I'm not a fanboy - never owned a Mac - but you've got to give the man his due.