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I think you must mean that you don't know an academic expert who thinks we're close. The teams at Tesla must think it's achievable in the next few years.

by jfoster 10y ago

ams6110 10y ago
Or they want you to think that.
- Matthias247 10y ago
  Or it's the marketing team and not the engineering team :-)
jayjay71 10y ago
Well I also used to work with the team that's now at Uber (I worked at the National Robotics Engineering Center which is where they got almost all of their initial 40 engineers), and some of the guys I used to work with went to Google as well as Tesla. Tesla has a retention problem - their top engineers regularly quit every few years. Google lost nearly their entire team working on self-driving cars because Sergey insisted on making a fully self-driving vehicle instead of rolling out incremental levels of autonomy. If you're only reading article after article hyping the technology instead of talking to the people actually building it, of course you're going to believe the journalists instead of the engineers. I don't know anybody actually writing the code that thinks we're close. Of course the PR teams and managers are going to hype everything up - that's their job.
- laichzeit0 10y ago
  Excuse my rather hand-waving explanations below but I'm not an expert in this field. The guys you spoke to, was this before or after they went to Google/Uber? As I understand the approach at Tesla would be (a) collecting an enormous amount of real-world driving data that possibly others are not or have not done yet, (b) do as little "coding" as possible, but rather take a deep-learning approach. I.e. the "algorithm" gets better the more data you throw at it, it doesn't depend on human intelligence, but rather on how much data you collect. Similar to how Google Translate got so good (it's not good because of any linguistic model or because a team of linguists "coded" it, it's just good because of the sheer amount of data it was trained on). (c) they have enough money to throw at any hardware requirements for a platform that could train on such an amount of data. Are the conditions above not different perhaps from what you experienced whilst working at NREC and perhaps different from the way you guys approached autonomous-driving? I'm trying to think from Elon Musk first-principles. If it was technically possible, what are all the lego blocks you need to go about building this?
  - jayjay71 10y ago
    That certainly seems like the idea for Tesla - collect all the data from the cars in real-world condition and use it for training. I think it's brilliant. Time will tell to see how well they can leverage that data. Having a better sensor suite would certainly make it easier though. It's a lot easier to interpret LIDAR (it basically makes a 3D map for you) than it is to interpret a camera (you have to figure out how to turn 2D into 3D). My skepticism is in the leap towards a fully autonomous vehicle, safe for driving on real roads in harsh conditions. Very few people have attempted anything in bad weather yet, although Ford has actually done some work on it. If we are talking about incremental improvements - sure that will happen constantly. What I'm saying is I don't believe you're going to get into a car without a driver anytime soon.
    - kneel 10y ago
      Tesla has been recording driving data, sensor data, and GPS data for years. They already have a system in place for machine learning driving data. This combined with their sensors is IMO a great basis for fully autonomous cars. Tesla is planning to have their factory produce 500,000 cars in 2018. Even if they only meet half of that they'll still be collecting a lot of data. I would guess most major cities and freeways will have full autonomous support by 2019.
      - jayjay71 10y ago
        I'll give you 10 to 1 odds on that if you want to bet.
    - missbit 10y ago
      Driving in snow is simple. Just hit the brakes hard whenever you are uncertain.
  - Matthias247 10y ago
    I think the comparison to google translate is interesting. How much confidence do you have that a translation by google translate is correct? How would you compare the complexity of translating documents between various languages to the complexity of driving a car in arbitrary environments and situations. And the most interesting think: Would you trust your life on google translate? At least in the sense that it does not corrupt the meaning of a translated text (small errors ok)?

I think you must mean that you don't know an academic expert who thinks we're close. The teams at Tesla must think it's achievable in the next few years.

by jfoster 10y ago

I think you must mean that you don't know an academic expert who thinks we're close. The teams at Tesla must think it's achievable in the next few years.

ams6110 10y ago

Or they want you to think that.

Matthias247 10y ago
Or it's the marketing team and not the engineering team :-)

jayjay71 10y ago

Well I also used to work with the team that's now at Uber (I worked at the National Robotics Engineering Center which is where they got almost all of their initial 40 engineers), and some of the guys I used to work with went to Google as well as Tesla. Tesla has a retention problem - their top engineers regularly quit every few years. Google lost nearly their entire team working on self-driving cars because Sergey insisted on making a fully self-driving vehicle instead of rolling out incremental levels of autonomy. If you're only reading article after article hyping the technology instead of talking to the people actually building it, of course you're going to believe the journalists instead of the engineers. I don't know anybody actually writing the code that thinks we're close. Of course the PR teams and managers are going to hype everything up - that's their job.

laichzeit0 10y ago
Excuse my rather hand-waving explanations below but I'm not an expert in this field. The guys you spoke to, was this before or after they went to Google/Uber? As I understand the approach at Tesla would be (a) collecting an enormous amount of real-world driving data that possibly others are not or have not done yet, (b) do as little "coding" as possible, but rather take a deep-learning approach. I.e. the "algorithm" gets better the more data you throw at it, it doesn't depend on human intelligence, but rather on how much data you collect. Similar to how Google Translate got so good (it's not good because of any linguistic model or because a team of linguists "coded" it, it's just good because of the sheer amount of data it was trained on). (c) they have enough money to throw at any hardware requirements for a platform that could train on such an amount of data. Are the conditions above not different perhaps from what you experienced whilst working at NREC and perhaps different from the way you guys approached autonomous-driving? I'm trying to think from Elon Musk first-principles. If it was technically possible, what are all the lego blocks you need to go about building this?
- jayjay71 10y ago
  That certainly seems like the idea for Tesla - collect all the data from the cars in real-world condition and use it for training. I think it's brilliant. Time will tell to see how well they can leverage that data. Having a better sensor suite would certainly make it easier though. It's a lot easier to interpret LIDAR (it basically makes a 3D map for you) than it is to interpret a camera (you have to figure out how to turn 2D into 3D). My skepticism is in the leap towards a fully autonomous vehicle, safe for driving on real roads in harsh conditions. Very few people have attempted anything in bad weather yet, although Ford has actually done some work on it. If we are talking about incremental improvements - sure that will happen constantly. What I'm saying is I don't believe you're going to get into a car without a driver anytime soon.
  - kneel 10y ago
    Tesla has been recording driving data, sensor data, and GPS data for years. They already have a system in place for machine learning driving data. This combined with their sensors is IMO a great basis for fully autonomous cars. Tesla is planning to have their factory produce 500,000 cars in 2018. Even if they only meet half of that they'll still be collecting a lot of data. I would guess most major cities and freeways will have full autonomous support by 2019.
    - jayjay71 10y ago
      I'll give you 10 to 1 odds on that if you want to bet.
  - missbit 10y ago
    Driving in snow is simple. Just hit the brakes hard whenever you are uncertain.
- Matthias247 10y ago
  I think the comparison to google translate is interesting. How much confidence do you have that a translation by google translate is correct? How would you compare the complexity of translating documents between various languages to the complexity of driving a car in arbitrary environments and situations. And the most interesting think: Would you trust your life on google translate? At least in the sense that it does not corrupt the meaning of a translated text (small errors ok)?