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Comment Re:Variables never being initialized an error? (Score 1) 86

"This in turn allows the compiler to find other errors such as variables that are never initialized."

Maybe a code smell but not an error, but surely this is more a function of an IDE rather than the compiler?

Once you have a list of memory locations that are never initialised it's trivial to check if those locations are ever used, which is why it's handy to have a list of variables that are never initialised. For example, you *definitely* want to catch the following error:

var x;
...(hundreds of lines later) ...
if (x>0) { ... }

AIUI, in Javascript that will generate a run-time exception (if it doesn't, it *should*!), while in typescript that will generate an error at the time of compilation, before the code ever even runs.

Comment Re:IGotCancerDoIHearAIDSGotAIDSFromTheManInTheHood (Score 1) 161

Yesterday, researchers on behalf of Microsoft said they will "solve" cancer within the next 10 years by treating it like a computer virus that invades and corrupts the body's cells. Today, Facebook CEO Mark Zuckerberg and his wife Priscilla Chan announced a $3 billion initiative to "cure all diseases."

"I see how it is. Fine. I, Jeff Bezos, pledge an end to all human suffering by sometime in the next six months."

[fineprint]Only for Prime Members[/fineprint]

Comment Re:Better equation (Score 1) 75

"Does no one else think cars + computers + network connectivity = bad?" Nope. Tesla was able to patch all their cars quickly, without asking drivers to come in to get serviced.


The patch would not have been needed had the connectivity not existed.

"Luckily, this problem that would not have existed without network connectivity was solved by using the network connectivity." Circular reasoning at its finest, folks. There would have been no patch if there was no network connectivity.

Comment Re:Hubris (Score 1) 259

Or would that depend on age? Cleaning cells at age 12 would have little effect, as mutations are fewer, but in 80+, it would result in death,

That's because cancer is a side-effect of living. When you can figure out how to prevent mutations in cell division, you would have cured cancer, but that same tech also gives immortality.

Comment Re:Think and learn like humans (Score 1) 259

The team hopes to be able to use machine learning technologies -- computers that can think and learn like humans

If your definition of a human is a retarded 4-year-old that can be trained to name colors with 75% accuracy, yes.

We're not there, we're not even close; "machine learning" is just the new buzzword in town, rising from the ashes of "big data".

Big data itself was a phoenix from the ashes of AI.

Comment Re:Quick progress (Score 1) 239

No your just being obtuse for arguments sake. A driver isn't a driver if they aren't driving. Calling them a driver is to fulfill a current regulatory requirement to have a driver... so you are arguing a chicken and an egg.

No. They have an out on that "regulatory hurdle" of having a driver in the seat - they can demonstrate the car in a variety of real-world but temporarily closed off areas. The reason you haven't seen many demonstrations of such (no precautionary driver) is because the software is not there yet. The claims have gotten louder in the last decade, but the claims are still the same - driver to provide regular corrections to the autonomous software.

They had to have someone called a driver even if they weren't driving because they required a driver.

That Tesla driver I say reading a book at the wheel certainly wasn't "driving" in any meaningful sense of the word... he was merely at the wheel... ready, sort of. Yes, that is just highway driving, but it is fully autonomous highway driving from a technical standpoint... just not a legal one yet.

Come now! You are making claims that the manufacturer disputes. It's purely a technical issue - the Tesla system is capable of doing exactly what was being done in the 90's. No more.

There is a big difference between computational power now and even just 5 years ago. With more computer power you get better image recognition in a variety of conditions. What took 8 seconds to identify a road sign on a laptop 5 or ten years ago takes 20 ms.

Sure you could autonomously drive decades ago with a truck full of computer hardware or do simple things with proximity sensors, but the envelope of capabilities is clearly getting a lot bigger and the affordability has come down well under the $100k range for a fully autonomous capable platform.

Being more affordable isn't going to complete that last bit that makes a car fully autonomous. Having more computational power isn't going to solve intractable problems, and being able to find the 10e100th prime doesn't mean that you will be able to find the (10e100 + 1)th prime in time for the heat death of the universe. Writing an algorithm that works 98% of each day doesn't mean you're almost at a 100% solution. That measurement only works for engineering, not for mathematics.

If the software problem was that easy to solve, considering the immense payoff, it would have been solved by now. Bright minds have worked on it for decades; ask them how well it is going. Don't ask the people who spent the last few years designing circuits and throwing hardware at the problem in the hope of brute-forcing a solution.

Personally, I feel that the people most likely to crack the software problem are going to be a bunch of abstract mathematicians working on something unrelated, not a bunch of engineers working incrementally towards a solution, in the same way that it was a mathematician who gave us the computer, not engineers who designed and build machines. The neural-net approach, as well, isn't suitable due to the opacity of the solution.

We need smarter algorithms instead of faster hardware, and by all accounts we don't have it.

Comment Re:Quick progress (Score 1) 239

2004 Nobody won the DARPA grand challenge... no car completed the course.

2005 5 vehicles completed the course.

2007 they switched to an urban course having to obey the rules of the road and six teams finished the course.

And prior to 2004 there were already cars being demonstrated as autonomous with minimal human input. Poster above linked to one from the 90's.

That is rapid progress.

From 2007 to 2016 we have seen pretty steady progress with commercially available features for things like automatic parking, automated braking and collision avoidance, widespread use of GPS navigation (via smartphones and built-in) and more recently the fully autonomous highway driving from Tesla (yes I've seen the people reading books while "at the wheel").

Tesla themselves say it is not autonomous. Automated braking was demonstrated in the 70's on a Volvo. You list it as some sort of breakthrough.

And Google has been pretty open in their fully autonomous car project with two different cars one based on an off the shelf lexus and another custom built electric vehicle: 1.5 million miles driven and "currently out on the streets of Mountain View, CA, Austin, TX, Kirkland, WA and Metro Phoenix, AZ"

And we are seeing Uber's autonomous efforts play out in Pittsburgh. Multiple companies, multiple projects, multiple on-street implementations that are getting better and better.

Firstly, Uber themselves say that the drivers in their autonomous cars will remain there for the foreseeable future. Their words, not mine. Secondly, you yourself pointed out that they are at the same place they were 10 years ago - that's not "getting better". There's been incremental improvements, sure, there's been more widespread takeup of the existing technologies, sure... but the state-of-the-art today in autonomous cars is basically the same as ten years ago. The cars are mostly autonomous.... up until they aren't! There's no new tech. The improvements have been tiny and incremental, and not enough to replace a human driver yet.

What people don't get is that we've seen this movie before, in the field of AI. The AI titans were 99% there with regard to thinking machines. Turned out that that 1% was unattainable. Same deal with SDC software: they may have checked off 99 out of 100 requirements for the software, but that remaining requirement (requiring corrections from an alert human at the wheel) may or may not get there.

The AI winter that followed the "we're 99% there!" AI boom was painful as many researchers had to admit that they had an intractable problem on their hands. We are currently seeing the same thing in autonomous cars: everyone is so certain that they're almost there and the remaining problems will be easy. Well, if the remaining problem was that easy, it would have been solved when it first came up in the 90's.

The problem isn't the hardware (GPS, Vision capture, distance sensor, lane detection, etc), it's the software. No company has demonstrated software-controlled cars that can function without regular human input.

And this problem isn't an easy one, which is why it hasn't been solved. The only improvements you can list came from better and more accessible hardware.

Comment Re:Excellent! (Score 1) 239

A few of your points are somewhat absurd. Having an observer in the car is irrelevant to whether the car is actually driving autonomously or not...

Those aren't observers, as you point out below...

Having someone ready to take over if the car fails is a precaution.

You are quite right - those drivers are precautions. This makes SDCs look even worse, because, as you pointed out in your previous response, we've had that for at least a decade. For a decade (or longer) we've had self-driving cars with precautionary drivers. What is happening now with Uber and the rest is, as you pointed out NOTHING NEW!

These vehicles are being driven for hundreds of thousands of miles on a variety of roads and a variety of conditions.

No, they aren't. They are being driven hundreds of thousands of miles on well-demarcated roads with occasional input from the precautionary driver.

Heck, if I recall, the DARPA grand challenge was partially on a dirt road and that was ten years ago.

That is exactly my point - there has been very little, if any, progress on self-driving cars in the last decade. If the best that can be done now is what Tesla offers, you are correct in noting that we've had this for over a decade. I'm simply noting the lack of progress. Remember Uber's press release - "The engineer in the drivers seat will remain there for the foreseeable future.".

Once again I must point out that software is deceptive in estimating. For common business-logic software which has had some 40 years of refinements, we still adhere to "the first 90% of the project takes 90% of the time, the other 10% takes another 90% of the time". This is for well-understood and previously built software!. Imagine what it is like for the stuff that has never succeeded before. You'll never know how far you are from the end.

With software, just because you implemented 9 out of 10 requirements does not mean that the last requirement is at all possible. Your last requirement might just be intractable, moreso if you're going the neural net path (hehe) as there is a lot more unknowns no matter what you trained the net on.

Comment Re:Excellent! (Score 1) 239

This is one of the things needed to get this technology legal and on the road.

Before getting this technology legal and on the road, perhaps we should focus on getting this technology? For the last five years I've been hearing that "Self-driving cars are here already", but sadly they aren't.

Okay now they are here.

Where? I see driver-assist cars, but no self-driving cars.

You mean available to purchase by consumers?

No, I meant "available at all".

Okay, not yet. But Uber is rolling out commercial service using self driving cars right now

No, they aren't - there's a human in the drivers seat.

and multiple companies apparently have fully autonomous vehicles on the public roads now.

Wrong again - no company has demonstrated a self-driving car in anything other than perfect conditions.

And acedemic/research teams have had fully self driving cars for at least ten years.

Yeah, right - and these decade-old technology is soooo undesirable that neither Uber, nor Tesla, nor Lyft offered them money for it, right? It's just sitting there, in the university

At least the Uber example has to be considered as commercial availability since this is one of the ways companies will offer self driving cars to the public, on a per trip basis. They are here.

No, they are not. Word of their imminent arrival is here. Look around - all self-driving cars need a driver in the seat. Academia has been working on this problem since at least the 90's, and they have yet to make progress. They've got a whole bunch of new sensors, but they still don't have the software ready yet.

The problem is that software is deceptive in it's complexity. Hardware is simple to gauge complexity. A hardware system that is 90% of the way there is easy to look at and figure out an ETA. A software system can't even be measured to see if it is 90% there.

For at least the last 20 years self-driving software systems were "90% there". That last 10% might just be impossible, or hard, or easy, but you can't tell, especially if you're using a neural network ('cos that is opaque even to the developers). The state of self-driving cars has not changed in the last 10 years. The announcements have.

Comment Re:Excellent! (Score 4, Insightful) 239

This is one of the things needed to get this technology legal and on the road.

Before getting this technology legal and on the road, perhaps we should focus on getting this technology? For the last five years I've been hearing that "Self-driving cars are here already", but sadly they aren't.

Okay now they are here.

Where? I see driver-assist cars, but no self-driving cars. Even Tesla (and many of slashdot regulars) point out that "autopilot" doesn't mean that the car can drive itself.

We've had the hardware to do self-driving cars for about 20 years now, and for the same amount of time very little progress was made on the software. We still don't have software that can drive a car in anything but perfect conditions, and even in perfect conditions they aren't able to do better than humans in perfect conditions.

Comment Re:And that's where you are wrong. (Score 1) 274

Once again. Tesla is full of shit. They compare 'autopilot' accident rates to all human driving. They should compare autopilot rates to human driving on divided highways. They don't because that would make them look bad.

So, have you done that? Has anyone? And if so, where's that comparison? I've looked up some related statistics but none of them speak directly to this point. Over one-third of collisions are on divided highways, for example; that suggests that in fact the comparison would not make them look bad, but I honestly don't know.

No need to go that far - they are comparing "autopilot in perfect driving conditions with a human ready to take over when the software gets it wrong" with "All human drivers, in every road condition imaginable".

You shouldn't need a book on statistics to know that the comparison of "autopilot+human+perfect conditions" with "humans+all conditions" is not a statistical comparison but a marketing one.

In short, you shouldn't need to be told that the comparison is not legitimate; it's obvious after a moment's thought.

Comment Re:Well that's wrong (Score 1) 274

In fact on average a computer will have much better visibility to the full surroundings than a human driver could, so even if "dumber" the computer is better informed and so statistically will probably make better choices.

Why would you assume that? The electronic visibility of an airplane is much better than any pilot, and yet 40 years after the invention of the "autopilot" we still do not have software that matches the pilot.

"Self-piloting" is a much much easier problem to solve than "self-driving", and yet we haven't solved that yet. I expect that 5 years after we've gotten passenger aircraft fully autonomous, we'll have self-driving cars.

But lets first see if anyone can solve the easy problem first, okay?

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