Hardly a conclusive or thorough study - were it really double-blind, some subjects should have heard two 128 Kb/s tracks, while others heard two 256 Kb/s tracks, and there should have been a "no difference" option.
If you had RTFA, you would have know that there was a "no difference" option.
New Belgium Brewery, most famous for Fat Tire and Sunshine, produce 10% of their electricity using the methane that is produced from bacteria feeding off of their waste water.
If so you should know that the Mac doesn't exactly sleep like a normal PC might; it apparently keeps the CPU running to some degree
Incorrect. Power to the CPU is cut off, but power is kept on for the RAM. From Apple's site:
The Operating System uses the power management hardware to shut down power to the CPU, the ROM, and some of the control logic. Sufficient power is maintained to the RAM so that no data is lost
A good start would be to not use tape.
I don't know what actual the percentage of tape failures is (and they're not telling), but in my own experience it's pretty high.
Hard disks and PCs are cheap enough that every movie could have its own little RAID array somewhere.
Tape is much cheaper than disc. A 3592 tape will hold 700GB worth of data, for a fraction of the cost of disc. Also, tape is more reliable than disc, if being used for long term storage, where the tape is not frequently used. From http://www.research.ibm.com/journal/rd/474/hellman .html
In addition, tape has two major advantages over HDD. The first is the ability to remove a cartridge to a completely separate location for safekeeping, and the second is the stability of the storage media over time. Tape is considerably more stable over long periods (years) of inactive time, whereas HDD mechanisms must be activated periodically (every few months) to maintain viability.
OK, so now that Google has admitted to copying the sohu.com pinyin database... exactly how did they get a copy in the first place? Is there a publicly available file for personal use or was there some sort of web scraping or what?
I suspect that there's more to this story that we're not hearing.
Exactly. Reading 95% of the comments for this story and yesterday's story, everyone seems to think that this is about stealing code. This is about Google using the same data to train an algorithm. Both algorithms make the same mistakes because they were trained using the same data, which contained incorrectly labled information. It is whether or not this data was publicly available that is the issue.
For (a horribly contrived) example: Lets say that I write some hand writing recognition software using a neural-net. In order to train my software, I use a large database of handwriting samples that I have found on the web. However, the person that compiled this database made the mistake of labeling all of the sample images of the letter 'n' as the letter 'q', and all of the images of the letter 'q' are labeled as the letter 'n'. Person B comes along and uses the same data set to train a naïve-Bayes classifier. Guess what? Both algorithms will make the same mistakes when it comes to the letters 'n' and 'q'. Not because I stole code from Person B, but because we used the same training data.
I'm not defending Google at all here. If they stole the data from Sohu, they should get in trouble. Based on the fact that Google is in the web-mining business, I would guess that they just grabbed this data off of the net, and someone forgot to think about if they had the right to use it.
Just media sensationalism to me. Jane Goodall observed chimps "fishing" for ants with twigs quite some time ago. Some of these chimps fashioned the twigs so as to work better. From where I sit, this is just as fantastic as having a chimp fashioning a larger twig to hunt with. Nothing new here except an over active media trying to make something out more out of old news.
Luckily for you, today I launched a new site http://www.slashvertisement.com/, dedicated to helping Internet entrepreneurs obtain stories on slashdot. My first interview is with Mark Fletcher.
This is the primary service the RIAA members still provide, and still can. They could position themselves as P2P search engines and filters, picking through songs available on the various P2P networks, and rating music based on their evaluations and your preferences. Note that they're not offering up the tunes themselves. The tunes they're listing are out there somewhere on the Net; Google would find them, too, if you typed in the right filename. All the label's search site would do is present what they warrant to be quality music that you're likely to enjoy. This would, of course, be a subscription service -- say USD$7.95/month. What you'd be paying for is not the music, but the recommendations.
So, then would it become illegal to tell your friend about a band that you learned about through the RIAA's website? Could I legally post a list of my favorite bands, even if that list just happened to coincide heavily with the RIAA's?
My attempts to install Ubuntu or Yellow Dog on an iMac G3 were a nightmare.
I'm a lifelong computer geek, and I'm having a hard time installing Linux. My experiences could be bad luck, but this suggests to me that Linux isn't ready for Average User.
You know, to be fair - the G3 was introduced in 1998, shipped with 3 gigs of disk and 32MB of RAM. I wouldn't benchmark Windows off of that...
So what do you do with with people like me, I wonder, who support open source and make the leap, only to find they have to waste days and nights of their life for weeks on end trying to do the simplest things. I was prepared to learn a new way of doing things, but it seems that Linux does the complicated things superbly well, but the simple things incredibly badly
Yeah..., you know, that's why you see all of these people on here laughing when people talking about installing Linux on their grandparent's computer.
Recently have been some recent stories on Slashdot claiming that Vista would downgrade the quality of audio and video for every application in a machine where protected content was running. One of the stories painted a scary scenario where a 'medical IT worker who's using a medical imaging PC while listening to audio/video played back by the computer' would have his medical images 'deliberately degraded'.
"Completely ridiculous rumor debunked, proves DRM is benevolent," states person unfamiliar with logic.
Seriously, is anyone that is even slightly aware of the state-of-the-art pattern recognition algorithms surprised? This is a case of popular culture leading people to believe that pattern recognition software is ahead of where it is. Every semester, PHD and masters students at literally 100's of universities try their hands at this (not to mention industry researchers/professors). People have been studying the top techniques used in this field for years, and there is no suggestion yet that this problem is remotely solved.
Believe me, a hashtable is used as the most pitiful of strawmen. Do yourself a favor, research topics like face recognition and face detection, it is an interesting topic. Look at the methods that are commonly used. If you have an idea that no one had tried, by all means, post it. To people familiar with the subject, this is akin to flying cars. That doesn't mean that is won't be solved first, it just means that the top industry/university results are very poor. Similar to how we can levitate a vehicle, but a national flying car program is laughable.
Say a classification algorithm has a 96% failure rate (far better than the best of these systems under realistic conditions):
If you sample 1,000,000 videos, 40,000 will be classified incorrectly. Let's pretend that magically YouTube only screens these videos. That is an awful lot of employees checking for false positives and false negatives. Given present technology, it is predictable that this would be the case.
Several months from now, you will see another story about how pattern recognition isn't able to classify the web 100% or some other notion. Read up on the topic and set the record straight.
Wow, it sounds like you could get a free PHD at any university in the world. Perhaps you'd like to share your method with us. Principle Components Analysis, Semi-Naive Bayes Classifier, compare pixel values with a histogram;) (maybe after applying a Hough transform)? Stop press, stop press!!!
I find this outlook somewhat humerous. I studied computer vision as a grad student, and yet whenever a face recognition story is posted on slashdot, sure enough, all of the +5 comments reflect Hollywood misconceptions. Digging through the articles, I generally find that people with real experience in the computer vision field have their comments relegated to a 1 status.
I have two first generation iPods that I've inherited from various people. Both still work fine. I just got a new 80 gig, not because my first gens died, but because I got sick of having to swap out songs whenever I wanted to listen to different music.
I understand people experience problems with every gen music player, but I just want to state that there are still first gen players out there running without a hitch. I imagine I won't use them anymore, due to the bulk and lack of capacity, but I imagine they will be pretty cool to have in about 10 years.
A Master's level education will prepare you to think critically and introduce you to research in a specific area. I'm not so certain that a Master's Degree is a more broad experience than a gaming degree. For instance, I have my Master's in Computer Vision. While at school I studied mostly computer graphics, biological vision, and pattern analysis. Outside of Computer Science, I studied statistics and linear algebra, areas that are useful in Computer Vision. Although I did have time to dabble in Software Engineering subjects that interested me, I would say that my education was mostly focused on a particular area. I saw much of the same in my peers, who studied Computer Security, Software Engineering, Networking, etc.
Although my area of study was focused, I imagine that I learned many of the same skills that Master's in other unrelated fields learn. The ability to critically analyze research, conduct research, and write research.
It has always puzzled me to an extent when I meet people who are pursuing a "general" Master's degree, with no specific area of study, and in many cases, no thesis. Is this any different then just prolonging the undergraduate experience? Also, before choosing a school, ask yourself if you will be working with researchers that are studying exactly what you are interested in. You're going to be spending a lot of time with them.
I don't know if it's at all related, but some people have a bump on the back of their head, and I've read before that those with the bump are generally more intelligent than those without. It has a name, can't remember, but I think it was some German word.
Would it be safe to say you don't possess said bump?
Slashdot Mirror
New Belgium Brewery, most famous for Fat Tire and Sunshine, produce 10% of their electricity using the methane that is produced from bacteria feeding off of their waste water.
Exactly. Reading 95% of the comments for this story and yesterday's story, everyone seems to think that this is about stealing code. This is about Google using the same data to train an algorithm. Both algorithms make the same mistakes because they were trained using the same data, which contained incorrectly labled information. It is whether or not this data was publicly available that is the issue.
For (a horribly contrived) example: Lets say that I write some hand writing recognition software using a neural-net. In order to train my software, I use a large database of handwriting samples that I have found on the web. However, the person that compiled this database made the mistake of labeling all of the sample images of the letter 'n' as the letter 'q', and all of the images of the letter 'q' are labeled as the letter 'n'. Person B comes along and uses the same data set to train a naïve-Bayes classifier. Guess what? Both algorithms will make the same mistakes when it comes to the letters 'n' and 'q'. Not because I stole code from Person B, but because we used the same training data.
I'm not defending Google at all here. If they stole the data from Sohu, they should get in trouble. Based on the fact that Google is in the web-mining business, I would guess that they just grabbed this data off of the net, and someone forgot to think about if they had the right to use it.
Seriously, is anyone that is even slightly aware of the state-of-the-art pattern recognition algorithms surprised? This is a case of popular culture leading people to believe that pattern recognition software is ahead of where it is. Every semester, PHD and masters students at literally 100's of universities try their hands at this (not to mention industry researchers/professors). People have been studying the top techniques used in this field for years, and there is no suggestion yet that this problem is remotely solved.
Believe me, a hashtable is used as the most pitiful of strawmen. Do yourself a favor, research topics like face recognition and face detection, it is an interesting topic. Look at the methods that are commonly used. If you have an idea that no one had tried, by all means, post it. To people familiar with the subject, this is akin to flying cars. That doesn't mean that is won't be solved first, it just means that the top industry/university results are very poor. Similar to how we can levitate a vehicle, but a national flying car program is laughable.
Say a classification algorithm has a 96% failure rate (far better than the best of these systems under realistic conditions):
If you sample 1,000,000 videos, 40,000 will be classified incorrectly. Let's pretend that magically YouTube only screens these videos. That is an awful lot of employees checking for false positives and false negatives. Given present technology, it is predictable that this would be the case.
Several months from now, you will see another story about how pattern recognition isn't able to classify the web 100% or some other notion. Read up on the topic and set the record straight.
Wow, it sounds like you could get a free PHD at any university in the world. Perhaps you'd like to share your method with us. Principle Components Analysis, Semi-Naive Bayes Classifier, compare pixel values with a histogram ;) (maybe after applying a Hough transform)? Stop press, stop press!!!
You haven't been laid in six years? Ouch!
I find this outlook somewhat humerous. I studied computer vision as a grad student, and yet whenever a face recognition story is posted on slashdot, sure enough, all of the +5 comments reflect Hollywood misconceptions. Digging through the articles, I generally find that people with real experience in the computer vision field have their comments relegated to a 1 status.
I have two first generation iPods that I've inherited from various people. Both still work fine. I just got a new 80 gig, not because my first gens died, but because I got sick of having to swap out songs whenever I wanted to listen to different music. I understand people experience problems with every gen music player, but I just want to state that there are still first gen players out there running without a hitch. I imagine I won't use them anymore, due to the bulk and lack of capacity, but I imagine they will be pretty cool to have in about 10 years.
A Master's level education will prepare you to think critically and introduce you to research in a specific area. I'm not so certain that a Master's Degree is a more broad experience than a gaming degree. For instance, I have my Master's in Computer Vision. While at school I studied mostly computer graphics, biological vision, and pattern analysis. Outside of Computer Science, I studied statistics and linear algebra, areas that are useful in Computer Vision. Although I did have time to dabble in Software Engineering subjects that interested me, I would say that my education was mostly focused on a particular area. I saw much of the same in my peers, who studied Computer Security, Software Engineering, Networking, etc.
Although my area of study was focused, I imagine that I learned many of the same skills that Master's in other unrelated fields learn. The ability to critically analyze research, conduct research, and write research.
It has always puzzled me to an extent when I meet people who are pursuing a "general" Master's degree, with no specific area of study, and in many cases, no thesis. Is this any different then just prolonging the undergraduate experience? Also, before choosing a school, ask yourself if you will be working with researchers that are studying exactly what you are interested in. You're going to be spending a lot of time with them.
... I guess now we don't like SLES. Shoddy security, I've heard.
They must have meant "Turing it on."