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Autonomous DeLorean drives sideways to move forward

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Re: Autonomous DeLorean drives sideways to move forward

#51

Post by spockz »

Animats wrote: post #41
sillysaurusx wrote: post #35

Earlier quoted context omitted.

I would highly recommend https://www.youtube.com/watch?v=PYylPRX6z4Q as a way of framing the problem. It seems like our options for ML are currently: self-play, dataset fitting, or human feedback. It's possible to solve any problem that can fit into one of those molds. (Unfortunately the opposite is true: if a problem doesn't fit into those categories, it seems very hard to solve with any form of ML.) But, now that I…

One approach is that you have a semi-traditional control system, which has integrators, filters, adders, etc. All these components have tuning parameters, and tuning complex controllers is hard. But once you get them tuned, they behave in a reasonably predictable way. The machine learning part is used to get a predictor. You operate the thing and train a model of what will happen for various inputs. The machine learn…

So what is the difference of using this approach with exploring the set of inputs to find the optimal one using a search algorithm like A* or the many different ones?

I’ve been struggling to find where machine learning starts and what is just good old statistics (used in data mining for ages) and search algorithms like A*.

Re: Autonomous DeLorean drives sideways to move forward

#52

Post by allovernow »

mjburgess wrote: post #48
allovernow wrote: post #43

Earlier quoted context omitted.

>The trouble with pure neural net controllers is that they sometimes do something totally bogus for some data point within the normal input space. That's not OK in control systems. Is that actually true? Everything we do at work with neural nets seems to indicate continuity. We do stuff with mathematical simulations and imagelike processing. Latent space for auto encoders tend to be smoothly varying throughout the ra…

It's not a continuity problem. It's that "bogus" is defined with respect to what it should do, and that criteria requires a working understanding of the environment which isn't present in the model. If you had all possible images of all possible roads in all possible (lighting, weather,..) conditions, etc. then the ideal behaviour is just a function from all inputs to all desired actions. In the absence of this infin…

>Any model which has no explicit understanding of the causal behaviour of an environment is going to misbehave for one of those unseen data points (eg. an unseen road in a weather/lighting/etc. condition

I disagree. That sounds like an older interpretation of behavior of simple deep nets like the inception family. My experience with auto encoders and GANs is such that the nets can and unquestionably do interpolate between training data points. What's more, the latent spaces display order reflecting logic - much in the way that you can perform arithmetic on BERT encodings in what amounts to a form of logic. This is the where SOTA is now and I think it's a strong step towards AI, though we're still far from it.

The trick is in understanding the boundaries in high dimensional space that your training data represents. So there is some degree of covering all your bases, so to speak, and that requires a new kind of intuition. These are very exciting times in tech/ML.

Re: Autonomous DeLorean drives sideways to move forward

#53

Post by tempestn »

dharmab wrote: post #40
jamestimmins wrote: post #9

So is the general idea that by removing the automated controls, which normally limit drift so human drivers don't lose control, they're able to gather data at the extremes of car handling? I'm curious how this would be applied in the real world. It almost seemed to suggest that a self-driving car would operate with those stability controls turned off, allowing it operate evasive maneuvers that would be impossible in…

Drifting is objectively less effective and safe than normal manuevering and braking. Drifting as a sport exists to look cool and stylish. It's like figure skating with cars. (There is one exception- off road racing on loose surfaces requires drifting. But driving that way off road is only useful for speed at the expense of safety and reliability.)

Another exception of a sort, and I believe the one this research is meant to address, is when the drift is initiated unintentionally. Say you hit a patch of black ice mid-corner, for example. This kind of work can expand the envelop of the control system to encompass these scenarios.

Re: Autonomous DeLorean drives sideways to move forward

#54

Post by tempestn »

sudhirj wrote: post #31
saagarjha wrote: post #7

I was half expecting a Toyota Sprinter Trueno and Eurobeat. Pop references aside, though, what is this useful for? I thought cars were designed to not skid normally due to ABS?

ABS is a very human-centric system the tries to keep the car controllable under low traction, often by sacrificing something aspect of movement. The neural nets here throw all that out of the window, and control the car with direct physics, without being once or twice removed from reality. The video also has some very interesting points about how the AI should be able to control the acceleration and braking on each w…

That, and also ABS only prevents the wheels from locking (much) under braking. It doesn't help you if you enter a corner too fast, or hit a patch of ice, or stab the throttle too early on exit, etc. Traction control helps with the last of those scenarios, and modern stability control can start to help with others. But as you said, this system would theoretically be able to go straight to the most effective inputs in any given situation, since it doesn't have to deal with a human driver in the loop.

Re: Autonomous DeLorean drives sideways to move forward

#55

Post by grecy »

I genuinely hope Tesla get a 2020 Roadster to lap the Nurburgring on autopiliot with nobody inside. If it lives up to promises, it will easily set the all time lap record as the fastest vehicle ever.

It will be an interesting time when a $200k production car can whip the pants of a multi-million dollar F1 racecar.

Re: Autonomous DeLorean drives sideways to move forward

#56

Post by abcpassword »

grecy wrote: post #55

I genuinely hope Tesla get a 2020 Roadster to lap the Nurburgring on autopiliot with nobody inside. If it lives up to promises, it will easily set the all time lap record as the fastest vehicle ever. It will be an interesting time when a $200k production car can whip the pants of a multi-million dollar F1 racecar.

F1 could go faster. They’re limited by the regulations. Literally “formula” cars.

Re: Autonomous DeLorean drives sideways to move forward

#57

Post by mjburgess »

allovernow wrote: post #52
mjburgess wrote: post #48

Earlier quoted context omitted.

It's not a continuity problem. It's that "bogus" is defined with respect to what it should do, and that criteria requires a working understanding of the environment which isn't present in the model. If you had all possible images of all possible roads in all possible (lighting, weather,..) conditions, etc. then the ideal behaviour is just a function from all inputs to all desired actions. In the absence of this infin…

>Any model which has no explicit understanding of the causal behaviour of an environment is going to misbehave for one of those unseen data points (eg. an unseen road in a weather/lighting/etc. condition I disagree. That sounds like an older interpretation of behavior of simple deep nets like the inception family. My experience with auto encoders and GANs is such that the nets can and unquestionably do interpolate be…

Again you're treating this as-if its a problem of finding a sufficiently smooth function over data points.

The problem is that the right behaviour is not a model fitted to that data. It isn't "fitted" at all.

When I turn the thermostat the temperature in the room increases. If the thermostat is broken, the temperature does not. The predicting the effect of the thermostat on the room requires intervening in the room to find out if it is broken; it requires having a model of the room, of the thermostat, etc.

No system that is not in direct causal contact with its environment can adapt to it. The system -- as it is in contact --- needs to be explicitly modelling the causally relevant features of that environment.

This isn't a statistical problem. You cannot learn a function over images to actions because the environment is absent from those images.

An infinite number of 2D images contain no 3D information. An infinite number of 3D images contain no skeletons (ie., inner-structure of objects). An infinite number of images of object pieces contain no information on object behaviour. An infinite number of videos of an object behaving contains no information of its behaviour when broken. An infinite number of videos of all possible breakages in all existing environments contains no information about behaviour in new environments.

Animals solve this problem by playing with objects, building models of those objects (their causal properties, ie., how they interact with other objects). That requires being-in an environment and explicitly modelling it.

There cannot be a "non-bogus" system arrived at via ML. Statistics itself is deficient in providing tools to design systems that "do what they should".

Any paradigm which makes the cartesian assumption that "behaviour is a function of data" is necessarily incapable of intelligent adaptation. Environments "as data" are infinities.

ie., For statistics to work you need all the relevant variables of an environment to make the "correct decision", and all the data needed to train against those. That's infinite.

The "child on road" column isn't going to be fed into the machine. The machine does not, and cannot, even model what a "child" is. Patterns among fractions of infinites is not a basis for saftey (, nor for intelligence).

Re: Autonomous DeLorean drives sideways to move forward

#58

Post by kart23 »

grecy wrote: post #55

I genuinely hope Tesla get a 2020 Roadster to lap the Nurburgring on autopiliot with nobody inside. If it lives up to promises, it will easily set the all time lap record as the fastest vehicle ever. It will be an interesting time when a $200k production car can whip the pants of a multi-million dollar F1 racecar.

Theres no way a tesla roadster is beating the current record holder, the 919 evo. The roadster would be magnitudes heavier, plus it wouldn't have the aero for the downforce.

https://youtu.be/PQmSUHhP3ug

Re: Autonomous DeLorean drives sideways to move forward

#59

Post by yobananaboy »

metaphor wrote: post #49
yobananaboy wrote: post #20

Earlier quoted context omitted.

On top of that, there's the deadman's switch on the console that stops the car if the driver releases it. Would definitely pay to ride in something like this.

It's an e-stop button (probably NFPA 79 Cat 0 implementation), not dead man's switch. This timestamp[1] clearly depicts an air gap between fingers and button while maneuvering. [1] https://youtu.be/3x3SqeSdrAE?t=74

Hah you're right. That makes more sense, the other angles looked like he was holding it down the entire time. Thanks :D

Re: Autonomous DeLorean drives sideways to move forward

#60

Post by grecy »

kart23 wrote: post #58
grecy wrote: post #55

I genuinely hope Tesla get a 2020 Roadster to lap the Nurburgring on autopiliot with nobody inside. If it lives up to promises, it will easily set the all time lap record as the fastest vehicle ever. It will be an interesting time when a $200k production car can whip the pants of a multi-million dollar F1 racecar.

Theres no way a tesla roadster is beating the current record holder, the 919 evo. The roadster would be magnitudes heavier, plus it wouldn't have the aero for the downforce. https://youtu.be/PQmSUHhP3ug

Obviously we have to take it with a grain of salt, though Elon said it will. So far we've heard of an 8.8 sec quarter and 0-60mph in 1.9s. The chief designer also said it will better all publicly announced numbers.
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