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    Home Unlabelled Self-Driving Cars OpenPilot vs Toyota TSS 2.0 and a good example of how bad these factory assist systems really are.

    Self-Driving Cars OpenPilot vs Toyota TSS 2.0 and a good example of how bad these factory assist systems really are.

    November 25, 2019

    Self-Driving Cars OpenPilot vs Toyota TSS 2.0 and a good example of how bad these factory assist systems really are.

    OpenPilot vs Toyota TSS 2.0 and a good example of how bad these factory assist systems really are.

    Posted: 25 Nov 2019 04:34 AM PST

    Tesla's large-scale fleet learning

    Posted: 24 Nov 2019 11:39 PM PST

    Tesla has approximately 650,000 Hardware 2 and Hardware 3 cars on the road. Here are the five most important ways that I believe Tesla can leverage its fleet for machine learning:

    1. Automatic flagging of video clips that are rare, diverse, and high-entropy. The clips are manually labelled for use in fully supervised learning for computer vision tasks like object detection. Flagging occurs as a result of Autopilot disengagements, disagreements between human driving and the Autopilot planner when the car is fully manually driven (i.e. shadow mode), novelty detection, uncertainty estimation, manually designed triggers, and deep-learning based queries for specific objects (e.g. bears) or specific situations (e.g. construction zones, driving into the Sun).
    2. Weakly supervised learning for computer vision tasks. Human driving behaviour is used as a source of automatic labels for video clips. For example, with semantic segmentation of free space.
      3. Self-supervised learning for computer vision tasks. For example, with depth mapping.
      4. Self-supervised learning for prediction. The future automatically labels the past. Uploads can be triggered when a HW2/HW3 Tesla's prediction is wrong.
      5. Imitation learning (and possibly reinforcement learning) for planning. Uploads can be triggered by the same conditions as video clip uploads for (1). With imitation learning, human driving behaviour automatically labels either a video clip or the computer vision system's representation of the driving scene with the correct driving behaviour. (DeepMind recently reported that imitation learning alone produced a StarCraft agent superior to over 80% of human players. This is a powerful proof of concept for imitation learning.) ​

    (1) makes more efficient/effective use of limited human labour. (2), (3), (4), and (5) don't require any human labour for labelling and scale with fleet data. Andrej Karpathy is also trying to automate machine learning at Tesla as much as possible to minimize the engineer labour required.

    These five forms of large-scale fleet learning are why I believe that, over the next few years, Tesla will make faster progress on autonomous driving than any other company.

    Lidar is an ongoing debate. No matter what, robust and accurate computer vision is a must. Not only for redundancy, but also because there are certain tasks lidar can't help with. For example, determining whether a traffic light is green, yellow, or red. Moreover, at any point Tesla can deploy a small fleet of test vehicles equipped with high-grade lidar. This would combine the benefits of lidar and Tesla's large-scale fleet learning approach.

    I tentatively predict that, by mid-2022, it will no longer be as controversial to argue that Tesla is the frontrunner in autonomous driving as it is today. I predict that, by then, the benefits of the scale of Tesla's fleet data will be borne out enough to convince many people that they exist and that they are significant.

    Did I miss anything important?

    submitted by /u/strangecosmos
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    Driverless car groups look past the engineering challenge

    Posted: 25 Nov 2019 07:32 AM PST

    Waymo is asking for your questions on Twitter

    Posted: 25 Nov 2019 12:14 PM PST

    Why have Tesla steered away from sensors and more to cameras?

    Posted: 25 Nov 2019 02:26 AM PST

    So I was looking at the way Tesla does FSD versus other ways such as Waymo, Google, Uber, etc.

    What's the benefit to Tesla using cameras over other types of sensors?

    submitted by /u/Rumbuck_274
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    Uber self-driving car crash: The role of automation complacency

    Posted: 25 Nov 2019 06:46 AM PST

    Reserve a CyberTruck and Profit?

    Posted: 24 Nov 2019 08:43 PM PST

    Elon musk has stated that the value of a car that can be fully autonomous will be worth 100k - 200k.

    Elon Musk has stated that Tesla will reach full autonomy in 2020 and will have 1,000,000 Robo-Taxis on the road.

    Elon Musk has stated that the price of FSD will increase over time as features become available.

    Reserving a CyberTruck today, locking in the price of FSD now will bring profit. If Elon Musk is correct on his timeline, or even a year off, the value of the CyberTruck should have already appreciated by the time it starts production in late 2021 & late 2022.

    Agree or Disagree?

    submitted by /u/LT-JamieJones
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