A main purpose of the study is to investigate evolution of phenotypes, not just genomes--- i.e. how the functions and capabilities of bacteria change over generations due to evolution. Just showing there was a change in the genetic sequence doesn't do that, since it might be a change that isn't expressed.
For large publishers, printing/binding/shipping/warehousing costs these days don't run more than $1-3 per book, so it's not too surprising that the e-books would only be discounted a few dollars.
Ten times 65,000 e-books sold per week in the U.S. equates to about 34 million per year. Sales are really that high? Is this including magazines and newspaper, or just actual books?
Not sure there is a solid one. There are multiple factors at work, which interact with each other and all have gray areas. Time commitment often comes up, but some people play Bejeweled for absurdly compulsive amounts of time per week. Time commitment per session might be one, though perhaps perceived time commitment per session is a better one. Some might just be cultural factors--- "hardcore games" tend to have all sorts of non-gameplay related markers like fantasy or shooter themes that mark them as targeted to specific groups. When you change those, as with Spore, you get a different audience, even when you still have a really long game typical in many ways of the "hardcore" category.
On the whole I think it's basically incoherent as a solid distinction, though it comes up often enough that there must be something to it. The first research I know of trying to pin it down better is Jesper Juul's new book on the subject, which among other things tries to sift some data from a bunch of interviews with self-described "casual" and "hardcore" gamers about what traits each of them thinks the two labels implies. It might be interesting to have a richer vocabulary to talk about it, though, since it's clearly more than a single hardcore---casual axis.
I agree, and don't think it's anywhere near the science/CS-education bottleneck either. It's true that it can be useful to work with some non-trivial data even in relatively early education: sifting through a few thousand records for patterns, testing hypotheses on them, etc., can lead to a way of thinking about problems that is hard to get if you're working only toy examples of 5 data points or something. But I think there's very little of core science education that needs to be done at "internet-scale". If we had a generation of students who solidly grasped the foundations of the scientific method, of computing, of statistics, of data-processing, etc., but their only flaw was that they were used to processing data on the orders of a few megabytes, and needed to learn how to scale up bigger--- well that'd be a good problem for us to have.
Apart from very specific knowledge, like actually studying scaling properties of algorithms to very-large data sets, I don't see much core science education even benefiting from huge data sets. If your focus in a class isn't on scalability of algorithms, but on something else, is there any reason to make students deal with an unwieldy 30 TB of data? Even "real" scientists often do their exploratory work on a subset of the full data set.
C++ has a lot of properties, but "simple" is hardly one of them. It's got so much stuff munged into it that the spec contains literally hundreds of pages special-casing bad interactions between features, and it takes a gigantic effort just to determine the type of an expression. Parsing C++ is actually not only not context-free, but undecidable, in general. It takes a heroic effort to determine whether A f(B,C); is a function declaration, or a call to a constructor. Static resolution rules are horrifically complex. The interaction of templates with everything else in the language is riddled with pitfalls. Etc.
It definitely lowers the bar at how good you have to be, but I'm not sure it makes it irrelevant. Just the overhead of putting computations into some sort of container (thunks of some sort) and getting them back out can get absurd if the computations turn out to be, say, smaller than 100 instructions.
They're pretty close to equivalent statements, though, since the major studios are such a large percentage of the total job market. If you're getting your grads hired somewhere, that somewhere is likely to be, in large part, Electronic Arts, UbiSoft, Activision/Blizzard, Microsoft Game Studios, etc.
The thing that's always killed this idea (along with automatic parallelization even on the same machine) is that the overhead of figuring out what's worth distributing, and the additional overhead from mistakes (accidentally distribute trivial computations), often swamps the gains from the multiple processors banging away on it simultaneously. Determining statically what's worth distributing is very hard, since solving it properly is undecidable (basically equivalent to the halting problem), and even solving it in a significant enough subset of cases to be useful has proved difficult. It looks like this project is monitoring dynamically to determine what to distribute, which seems likely to be more fruitful, although historically that approach has suffered from the overhead of the monitoring (like always running your code with debugging instrumentation turned on).
I certainly hope he has a breakthrough vs. past approaches, or it could just be that advances in a lot of areas of technology have given him a better substrate on which to build things that naturally mitigates lots of the problems these things used to have (automatic parallelization research started probably ahead of its time, back in the 1970s, so that most academic stuff was killed off by the 1990s after no really knock-down results emerged). It's not entirely clear to me what the killer advance is, though. The particular variety of portable continuations? A good way of easily monitoring computations? Something that makes the data-dependency analysis particularly easy?
It depends what you count as "game design". CMU's ETC gets a lot of its grads hired, though it's a masters program, and a large proportion of people there have CS bachelors' degrees already. UC Santa Cruz gets its game-design/CS grads hired also, but it's in the CS department and more of a "game-flavored CS" degree than a game-design degree. Even the more humanities-oriented game-design programs seem to be having some success, but their graduates tend to get hired as designers or artists rather than programmers.
The GP's post doesn't really make any sense, though. The people at major studios working on network-architecture problems are of course network-architecture people, not game designers. In some cases they might not even really know much about game design, beyond what they've needed to learn to deal with the network architecture.
They claim they calibrated the model against historical data, so the searchprevalence relationship at least has some validity. The relationship between searches and prevalence of infection might be different in the current situation than in previous years, of course, but they didn't just make a base assumption that searches=prevalence, but rather estimated the relationship from data.
This isn't new; if anything, mandatory vaccination laws have become much more lenient in the United States than they used to be. In the early 20th century, 11 states had fully mandatory vaccination laws, not just "must get vaccinated as a condition of attending public schools" or "must be vaccinated as a condition of working in certain occupations" sorts of things. Rather, it was a requirement for living in the jurisdiction that you must be vaccinated. Massachusetts's mandatory smallpox vaccination law was upheld by the Supreme Court in Jacobson v. Commonwealth of Massachusetts in 1905, which is still the main precedent on the subject.
That's not the case if large portions of the economy are controlled by corporations that are all doing that. In theory, it might be possible for me to live and eat without ever dealing with a major corporation, but in practice it's nearly impossible to do. If anything, I see taxation by government as much preferable to de-facto taxation by corporations, since at least I have a vote in the former, and the sums are usually lower.
In most socialized systems, like France's, you do have a choice. So that's an argument against Canada's unusual system, not against socialized medicine in general.
Actually, you do have exactly that in a capitalist system. Most large corporations are run this badly, or worse. There's a reason there's an incestuous web of shared directors across Fortune 500 companies, many of whom hire out jobs to each other or to consulting firms connected with those directors or other senior management.
Unfortunately, the corporate world works exactly the same way. Given a choice between a solution that's reasonably priced, and a hideously expensive solution that involves shady consulting companies, 9 out of 10 Fortune 500 companies will pass the buck on to an overpriced consulting firm, which recommends (surprise!) the overpriced consulting solution.
I'd prefer they chose a sensible venue based on the location of the relevant parties, witnesses, and/or evidence. For example, they could sue in Florida, where they're located; or in New York, the North American headquarters of Toyota; or in Kentucky, the location of Toyota's American R&D facilities. But why Marshall, Texas? What can they point to in Marshall, Texas that makes it uniquely suited to serve as a venue for this case?
Slashdot Mirror
A main purpose of the study is to investigate evolution of phenotypes, not just genomes--- i.e. how the functions and capabilities of bacteria change over generations due to evolution. Just showing there was a change in the genetic sequence doesn't do that, since it might be a change that isn't expressed.
Did you miss the "ten times"?
For large publishers, printing/binding/shipping/warehousing costs these days don't run more than $1-3 per book, so it's not too surprising that the e-books would only be discounted a few dollars.
Ten times 65,000 e-books sold per week in the U.S. equates to about 34 million per year. Sales are really that high? Is this including magazines and newspaper, or just actual books?
Not sure there is a solid one. There are multiple factors at work, which interact with each other and all have gray areas. Time commitment often comes up, but some people play Bejeweled for absurdly compulsive amounts of time per week. Time commitment per session might be one, though perhaps perceived time commitment per session is a better one. Some might just be cultural factors--- "hardcore games" tend to have all sorts of non-gameplay related markers like fantasy or shooter themes that mark them as targeted to specific groups. When you change those, as with Spore, you get a different audience, even when you still have a really long game typical in many ways of the "hardcore" category.
On the whole I think it's basically incoherent as a solid distinction, though it comes up often enough that there must be something to it. The first research I know of trying to pin it down better is Jesper Juul's new book on the subject, which among other things tries to sift some data from a bunch of interviews with self-described "casual" and "hardcore" gamers about what traits each of them thinks the two labels implies. It might be interesting to have a richer vocabulary to talk about it, though, since it's clearly more than a single hardcore---casual axis.
I agree, and don't think it's anywhere near the science/CS-education bottleneck either. It's true that it can be useful to work with some non-trivial data even in relatively early education: sifting through a few thousand records for patterns, testing hypotheses on them, etc., can lead to a way of thinking about problems that is hard to get if you're working only toy examples of 5 data points or something. But I think there's very little of core science education that needs to be done at "internet-scale". If we had a generation of students who solidly grasped the foundations of the scientific method, of computing, of statistics, of data-processing, etc., but their only flaw was that they were used to processing data on the orders of a few megabytes, and needed to learn how to scale up bigger--- well that'd be a good problem for us to have.
Apart from very specific knowledge, like actually studying scaling properties of algorithms to very-large data sets, I don't see much core science education even benefiting from huge data sets. If your focus in a class isn't on scalability of algorithms, but on something else, is there any reason to make students deal with an unwieldy 30 TB of data? Even "real" scientists often do their exploratory work on a subset of the full data set.
Its launches are all in Asia too.
Although, the European Space Agency's launches are all in South America...
C++ has a lot of properties, but "simple" is hardly one of them. It's got so much stuff munged into it that the spec contains literally hundreds of pages special-casing bad interactions between features, and it takes a gigantic effort just to determine the type of an expression. Parsing C++ is actually not only not context-free, but undecidable, in general. It takes a heroic effort to determine whether A f(B,C); is a function declaration, or a call to a constructor. Static resolution rules are horrifically complex. The interaction of templates with everything else in the language is riddled with pitfalls. Etc.
It definitely lowers the bar at how good you have to be, but I'm not sure it makes it irrelevant. Just the overhead of putting computations into some sort of container (thunks of some sort) and getting them back out can get absurd if the computations turn out to be, say, smaller than 100 instructions.
They're pretty close to equivalent statements, though, since the major studios are such a large percentage of the total job market. If you're getting your grads hired somewhere, that somewhere is likely to be, in large part, Electronic Arts, UbiSoft, Activision/Blizzard, Microsoft Game Studios, etc.
The thing that's always killed this idea (along with automatic parallelization even on the same machine) is that the overhead of figuring out what's worth distributing, and the additional overhead from mistakes (accidentally distribute trivial computations), often swamps the gains from the multiple processors banging away on it simultaneously. Determining statically what's worth distributing is very hard, since solving it properly is undecidable (basically equivalent to the halting problem), and even solving it in a significant enough subset of cases to be useful has proved difficult. It looks like this project is monitoring dynamically to determine what to distribute, which seems likely to be more fruitful, although historically that approach has suffered from the overhead of the monitoring (like always running your code with debugging instrumentation turned on).
I certainly hope he has a breakthrough vs. past approaches, or it could just be that advances in a lot of areas of technology have given him a better substrate on which to build things that naturally mitigates lots of the problems these things used to have (automatic parallelization research started probably ahead of its time, back in the 1970s, so that most academic stuff was killed off by the 1990s after no really knock-down results emerged). It's not entirely clear to me what the killer advance is, though. The particular variety of portable continuations? A good way of easily monitoring computations? Something that makes the data-dependency analysis particularly easy?
It depends what you count as "game design". CMU's ETC gets a lot of its grads hired, though it's a masters program, and a large proportion of people there have CS bachelors' degrees already. UC Santa Cruz gets its game-design/CS grads hired also, but it's in the CS department and more of a "game-flavored CS" degree than a game-design degree. Even the more humanities-oriented game-design programs seem to be having some success, but their graduates tend to get hired as designers or artists rather than programmers.
The GP's post doesn't really make any sense, though. The people at major studios working on network-architecture problems are of course network-architecture people, not game designers. In some cases they might not even really know much about game design, beyond what they've needed to learn to deal with the network architecture.
If the influenza pandemic will kill off Extreme Programming, now that's something I can get behind.
They claim they calibrated the model against historical data, so the searchprevalence relationship at least has some validity. The relationship between searches and prevalence of infection might be different in the current situation than in previous years, of course, but they didn't just make a base assumption that searches=prevalence, but rather estimated the relationship from data.
This isn't new; if anything, mandatory vaccination laws have become much more lenient in the United States than they used to be. In the early 20th century, 11 states had fully mandatory vaccination laws, not just "must get vaccinated as a condition of attending public schools" or "must be vaccinated as a condition of working in certain occupations" sorts of things. Rather, it was a requirement for living in the jurisdiction that you must be vaccinated. Massachusetts's mandatory smallpox vaccination law was upheld by the Supreme Court in Jacobson v. Commonwealth of Massachusetts in 1905, which is still the main precedent on the subject.
That analogy doesn't make any sense. If all cars were made by one company, they would be a monopoly, for the reasons you cite.
That's not the case if large portions of the economy are controlled by corporations that are all doing that. In theory, it might be possible for me to live and eat without ever dealing with a major corporation, but in practice it's nearly impossible to do. If anything, I see taxation by government as much preferable to de-facto taxation by corporations, since at least I have a vote in the former, and the sums are usually lower.
In most socialized systems, like France's, you do have a choice. So that's an argument against Canada's unusual system, not against socialized medicine in general.
Actually, you do have exactly that in a capitalist system. Most large corporations are run this badly, or worse. There's a reason there's an incestuous web of shared directors across Fortune 500 companies, many of whom hire out jobs to each other or to consulting firms connected with those directors or other senior management.
Unfortunately, the corporate world works exactly the same way. Given a choice between a solution that's reasonably priced, and a hideously expensive solution that involves shady consulting companies, 9 out of 10 Fortune 500 companies will pass the buck on to an overpriced consulting firm, which recommends (surprise!) the overpriced consulting solution.
It's starting to look more and more like it's going to be my generations plastic.
I, too, look forward to the giant raft of entangled nanoparticles polluting the middle of the Pacific.
There's nothing wrong with complaining about monopolies.
It might be worth pointing to the mission site or project site at NASA.
Yahoo has about twice as many daily unique visitors as Facebook, so I'm not so sure about the "fewer eyes" part.
I'd prefer they chose a sensible venue based on the location of the relevant parties, witnesses, and/or evidence. For example, they could sue in Florida, where they're located; or in New York, the North American headquarters of Toyota; or in Kentucky, the location of Toyota's American R&D facilities. But why Marshall, Texas? What can they point to in Marshall, Texas that makes it uniquely suited to serve as a venue for this case?