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Comment This time really is different. (Score 5, Insightful) 544

Once upon a time, people generated most of their value with their muscles. When machines replaced muscles, people could still generate value with their brains because machines could not replace brains. So the original Luddite scenario never materialized.

Now that machines are starting to replace brains, a growing portion of the population has a rapidly dwindling ability to generate significant economic value relative to the machines. As time passes, machines can effectively replace both the muscles and brains of more of the population.

This is also why forcing people to work fewer hours will not help. The problem is not the number of jobs available; it is the number of people who can generate more positive value in that position relative to a machine. Eventually we will all be in the position of no longer being able to be a productive member of a modern economy; everyone believes their contribution to be indispensable until the technology catches up and it isn't.

Comment Re:Does it really take so much computing power? (Score 2) 861

Actually, it is a relatively cheap computation on modern computing hardware. The specification for many modern tactical intercept systems is that the complete decision cycle has an upper bound of 20-50 milliseconds. You can do an amazing amount of computation on sensor data in that amount of time.

Remember, sophisticated multi-target tracking and engagement systems were built in the 1970s and 1980s with much less processing power than your cell phone has today.

And in fact, if you look at the chipsets used in state-of-the-art terminal guidance packages for hypersonic kinetic intercept of agile targets, they are embedded systems chips that would have been obsolete as desktop CPUs even a decade ago. Think MIPS R3000 or R4000 class CPUs and a modest DSP.

Basically, CPUs can drive computation at a much higher rate than material physics allows targets to change their behavior. We passed the threshold where computation is the bottleneck decades ago.

Comment Not an assault rifle (Score 4, Informative) 666

The SIG716 is not an "assault rifle" and you won't be "mowing" anything down with it. It is a conventional semi-automatic rifle that can be legally owned just about everywhere. Also, it is in a large caliber that makes it better suited for hunting than for rapid fire.

If the guy had been shipped a functionally equivalent hunting rifle with a classic wood stock there would not be as many ninnies getting the vapors over it. Unless Amazon has never made a shipping error before, this is a non-story.

Comment Re:Non-metallic firearms have been around a while. (Score 1) 846

Polymer and composite firearm construction was pioneered by Heckler & Koch in the 1970s and they have continuously produced lightweight composite firearms since that time. Glock is popular because it offered good price performance, not because it was particularly innovative. The construction, action, etc were copied from old firearm designs.

It is possible to build non-metallic firearms but the manufacturing would be exotic and extremely expensive.

Comment Re:Lots of coffee or caffeine = always indoors? (Score 1) 130

Perhaps those drinking 3 cups a day are more likely to be in jobs where they are virtually chained to a desk, so they rarely see the sun and thus less skin cancer.

Prior studies on animal models have produced similar reductions in skin cancer associated with caffeine; the result in the article is not surprising. For example, here is a skin cancer study done with caffeine and mice:

http://www.sciencedaily.com/releases/2012/04/120403142328.htm

No mice were chained to a desk for this study. I recall other studies done based on topical application of caffeine (rather than ingestion) with good results but I am too lazy to google them.

Comment Re:Lets Stick to Software Patents (Score 1) 126

There is no such thing as a "software patent". There are a few entirely unrelated classes of patent that are lazily bundled together under the rubric of "software patent". A business method patent or "...on the Internet" or "...on a computer" patent are very different beasts from fundamental machinery or algorithm patents. From a patent policy and theory standpoint, these different cases are essentially unrelated.

The lack of precision is part of the reason there is not a cohesive movement to reform patents in this area. A reasonable solution for one class may not be a reasonable solution for another yet many reform proponents are throwing all into the same bucket. To people with legitimate patent interests who are amenable to reform, the scorched earth of deeming everything remotely associated with computing as "non-patentable", whether people realize it or not, seems unreasonable and gets in the way of getting everyone to agree on reasonable reforms to the individual patent classes. Discussions of patent reform policy require more nuance than many people are willing to give it.

Comment Java is poor for memory-intensive codes (Score 5, Interesting) 611

There is definitely movement away from Java and toward C/C++ for some types of software. Applications bottlenecked by memory performance, like databases and high-performance codes, will often be faster than a language like Java by integer factors. When people assert that Java is about as fast as C/C++ they are talking about code like tight, CPU-bound loops. However, Java is wasteful of memory and CPU cache lines in a way that C/C++ is not under normal circumstances which has a significant adverse impact on the performance of some codes.

On recent processors, memory performance is a bigger bottleneck than CPU performance for performance-sensitive codes. The throughput of CPUs has grown faster than our ability to keep those CPUs fed from memory. In the supercomputing world this started to become evident years ago; memory benchmarks like STREAM became more closely correlated with real-world performance than CPU benchmarks like LINPACK for a great many algorithms. The resurgence of C/C++ is partly driven by this reality since it makes memory optimization relatively straightforward and you can receive large gains relative to Java for modest effort.

A smaller but also important driver away from Java is the GC. The increasing focus on "real-time" and predictable latency for applications like analytics and database engines is complicated when Java's garbage collector is inserted in the middle. This is a chronic point of pain for some applications.

I developed Java for years but my latest project (a real-time analytical database engine) is being written in C++ for the above reasons, among others. Writing high-performance applications of this type is actually pretty painful in Java because you end up doing unnatural things in the language to even approach the efficiency of conventional C++. Anecdotally, many of our C++ developers were doing Java until recently so the statistic does not surprise me.

Comment Not really necessary in the US (Score 2) 70

The US is awash in privately funded technology R&D toward exascale computing. While there is government funding, it is somewhat superfluous to the extent that US has a huge, well-funded private sector obsessed with massively scaling just about everything vaguely related to computing. That whole Internet-scale computing thing.

The US is hardly disadvantaged by the government not spending money on exascale computing. The US government does not need to compensate for the absence of private investment.

Comment "video games and special effects"? (Score 4, Insightful) 292

Say what? Is this what average people think programmers and software engineers do? Do they think the kids won't catch on that the reality does not look anything like that?

I have nothing against programming as a part of standard education. It is likely beneficial on multiple levels, not just because it teaches a useful skill but because it forces you to reason about and analyze systems in a somewhat rigorous way.

My issue is that they are apparently faking the real rewards at a very superficial level which generates little value in practice. You won't train a generation of great computer scientists by doing a bait and switch, and history suggests that really great computer scientists are rarely motivated by their ability to do parlor tricks for the adoring masses. Like with many other technical disciplines, the deep elegance that makes it rewarding requires long and serious study that most of society will never really appreciate except in a very indirect way.

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