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Comment Re:With the best will in the world... (Score 1) 486

I know /. is US centric, but to me the real problem is "plugging in in their garage". Individual garages with a plug are not so common in Europe.

The EV might be ok for the american suburbs where everyone has a big house with a garage, but for for european ones where almost everyone live in apartments where you park your car either in the stress or on some parking lots.

Comment Re:We can learn from this (Score 1) 163

We have to accept that it is in our biology, but civilization is impossible without trying to curb it.

It is also in our nature to kill, steal, and maim. Should we then say: "Well, apparently we should allow that or even cater for it."?
The answer is no.

That's exactly the reply I was hoping to get, and you should be moded up.

Comment Re:We can learn from this (Score 3, Interesting) 163

Why is it broken? These rules are the consequence of human behavior at a global scale. As long as the global human behavior is to increase the maximum individual achievable wealth, instead of increasing some sort of minimum collective value, I bet you will see these kind of rules emerging. Which means they are not broken, but rather a good solution to the problem.

I was born in East-Germany, where people did a pacific revolution to free themselves from a dictatorship. That's what your history book says. The truth is, people wanted to have the opportunity to get rich which is not possible in a socialist country. Some of them did eventually, but the vast majority is now poorer than they were before, having a high unemployment rate, mini-jobs with low income, etc. Are people happier by now? Frankly, I'm not sure. But as soon as basic needs are fulfilled (home, food, day activity), people tend to be very sad if they don't see any opportunity of growth. So maybe they are indeed happier by now, even if basic needs are less achieved.

You have to accept that we are a competitive species, not a collaborative one. We may do things together, but only in the perspective of self-fulfillment. It's as if individual growth is hard-coded in our genes. Maybe not you, certainly not me, but in average, yes.

Comment Facepalm (Score 1) 486

This kind of useless paper is exactly why idiots should not be allowed in computer science. They even give the explanation in the paper and still draw to bad conclusion. To me, it should be renamed "Bad programming habit performs worse than very bad performing habit in the absence of knowledge about the tool used".

Comment Re:Good. (Score 4, Interesting) 198

They'll likely convince some people to continue with public transportation, which would be a victory, even if small.

Probably not. We are voting this Sunday. My guess is that people will be so upset not to be allowed to take their car tomorrow, that they will vote for the very first idiot that will promise to ban the measure. Usually, these idiots are right wing extremists.

I'm not very optimistic. Mankind is greedy by nature and probably can't understand the logic of environment preservation as long as it generates a net individual loss.

Comment Re: Foxconn Factories' Future: Fewer Humans, More (Score 1) 187

Weren't people saying the same sort of things when the "assembly line" was first invented? After all, the main purpose of the "assembly line" was to make the same amount of stuff with fa fewer workers than had been needed previously.

I'm not saying this will be next year or so, and I'm not sure the parent post was meant to be exact with respect to the timeline. But, yeah, it's the kind of global direction we're heading towards. The ultimate goal is to replace of work done by humans by work done by machines, simply because we're lazy. that and the fact that capitalism is about gaining the benefits of someone else's work because you own the business. If owning robot overlords can assure you all you ever need without working, it's obvious everybody will want these, but only the most fortunate will afford it, leaving the rest of us in misery.

Oddly, we seem to have managed to get past the introduction of the assembly line without the sort of problems you're predicting - humanity is still here, its population is still growing, and technology is still advancing.

Isn't population growing mainly due to latency? Many second order systems simply overshoot before stabilizing. The mentality we have is still stuck in the post WWII era, were growth was over 5% every year and you could make plenty of kids without worrying for the future. I won't count on humanity to be something else than a pure reacting system, which means it will always adjust too late, contrarily to a predicting system (which is what individuals can be).

Comment Re: Foxconn Factories' Future: Fewer Humans, More (Score 2) 187

Although the way it's written is brutal and arrogant, I think it is the closest to what will happen. The more I look at it, the more it seems the future will look like "the Dancers at the End of Time" by M. Moorcock. It is either that, which means a brutal decrease of the unneeded population, or the end of technological advancement or the end of humanity.

Comment Re:Do they actually work well now? (Score 1) 45

Last time I looked there was no application of ANNs which couldn't be solved more efficiently by other algorithms ... and the best ANNs used spiking neurons with Hebbian learning which are not amenable to efficient digital implementation.

Is it possible that last time you checked was a long time ago? Deep neural networks are again all the rage now (i.e. huge teams working with them at Facebook and Google) because

  1. (1) They have resulted in a significant performance improvement over previously state-of-the-art algorithms in many application tasks,
  2. (2) Although they are computation-heavy, they are amenable to massive parallelization (modern computational power is probably the main reason why they have improved singificantly with respect to ANNs of the 80-90s, given that the main architecture itself has not changed a lot, except possibly for the "convolution" trick which effectively introduces hard-coded localization and spatial invariance).

To be fair, it always seems to me that (1) and (2) are very closely related. CNNs that won recent computer vision benchmarks are the only methods that used so much processing power so far. Not that they're less efficient than other, tough. It's just that I would love to see other methods with that many engineering, tunning, dedicated computational power and how they compare.
Also, not that when it comes to classification, the standard is to throw the last layer and train a linear SVM on the penultimate layer, which also show that CNNs alone are not enough.

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