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Tesla is often said to have a massive lead in self-driving data thanks to having equipped all its cars with sensors early on and collecting real-world data from a fleet that now includes over a million vehicles.
The automaker is able to use the extensive data set to improve its neural nets powering its suite of Autopilot features, and it ultimately believes it will lead to full self-driving capability.
However, that data is a lot more valuable when it is “labeled” – meaning that the information in the images collected by the fleet is being tagged with information, such as vehicles, lanes, street signs, etc.
If the images are properly labeled – for example, if you can consistently recognize a speed sign and label it as such – you can feed a bunch of different images of different speed signs to a computer vision neural net in order to be able to recognize them.
Labeling has been a focus of Tesla’s Autopilot team.
Andrej Karpathy, Tesla’s head of AI and computer vision, revealed last year that Tesla only has “a few dozen” engineers working on neural networks, but they have a “huge” team working on labeling.
Tesla is trying to automate a lot of the labeling in order to be able to use a lot of the data that is being collected by the fleet.
Last year, Tesla CEO Elon Musk said that drivers are effectively labeling just by driving through intersections:
Essentially, the driver when driving and taking action is effectively labeling — labeling reality — as they drive and [make] them better and better. I think this is an advantage that no one else has, and we’re quite literally orders of magnitude more than everyone else combined.
But Tesla also has employees manually labeling data to be fed to its neural net.
Tesla looking to hire data labelers in Buffalo
Now we learn that Tesla is expanding the team to Buffalo, New York, where the automaker operates Gigafactory New York.
The company announced on LinkedIn a few days ago:
Tesla describes the role in the job listing:
“Labeled data is the critical ingredient for training powerful Deep Neural Networks, which help drive the Tesla vehicles autonomously. In this role you will work with a user interface to label images for cars, lanes, street signs, etc.”
The automaker listed some of the responsibilities of a data labeler:
You will use the Autopilot labeling interface to label images critical to training our deep neural networks.
You will interact with the computer vision engineers on the Autopilot team to help us improve on the design of an efficient labeling interface.
You will be expected to gain basic computer vision and machine learning knowledge to better understand how the labels are used by our learning algorithms, as this will allow you to make more judgement calls on difficult edge cases that might come up during labeling.
Glassdoor lists a salary of $22 per hour for a data labeler at Tesla, but that was based on reports from people in that position in California.
Tesla inherited Gigafactory New York from its acquisition of SolarCity and with it comes a deal with the state to create a certain number of jobs and maintain a level of investment in the region.
This deal has been somewhat hard to fulfill for Tesla after several changes of the plan for the factory, which was first supposed to produce solar panels.
That plan originally failed and was replaced with a deal with Panasonic to produce solar modules for Tesla at the factory, but that deal also ended last year.
Now Tesla instead produces solar roof tiles and Supercharger stations at the factory.
https://electrek.co/2021/02/08/tesl...ilot-neural-nets-images-gigafactory-new-york/
FTC: We use income earning auto affiliate links. More.
The automaker is able to use the extensive data set to improve its neural nets powering its suite of Autopilot features, and it ultimately believes it will lead to full self-driving capability.
However, that data is a lot more valuable when it is “labeled” – meaning that the information in the images collected by the fleet is being tagged with information, such as vehicles, lanes, street signs, etc.
If the images are properly labeled – for example, if you can consistently recognize a speed sign and label it as such – you can feed a bunch of different images of different speed signs to a computer vision neural net in order to be able to recognize them.
Labeling has been a focus of Tesla’s Autopilot team.
Andrej Karpathy, Tesla’s head of AI and computer vision, revealed last year that Tesla only has “a few dozen” engineers working on neural networks, but they have a “huge” team working on labeling.
Tesla is trying to automate a lot of the labeling in order to be able to use a lot of the data that is being collected by the fleet.
Last year, Tesla CEO Elon Musk said that drivers are effectively labeling just by driving through intersections:
Essentially, the driver when driving and taking action is effectively labeling — labeling reality — as they drive and [make] them better and better. I think this is an advantage that no one else has, and we’re quite literally orders of magnitude more than everyone else combined.
But Tesla also has employees manually labeling data to be fed to its neural net.
Tesla looking to hire data labelers in Buffalo
Now we learn that Tesla is expanding the team to Buffalo, New York, where the automaker operates Gigafactory New York.
The company announced on LinkedIn a few days ago:
Tesla describes the role in the job listing:
“Labeled data is the critical ingredient for training powerful Deep Neural Networks, which help drive the Tesla vehicles autonomously. In this role you will work with a user interface to label images for cars, lanes, street signs, etc.”
The automaker listed some of the responsibilities of a data labeler:
You will use the Autopilot labeling interface to label images critical to training our deep neural networks.
You will interact with the computer vision engineers on the Autopilot team to help us improve on the design of an efficient labeling interface.
You will be expected to gain basic computer vision and machine learning knowledge to better understand how the labels are used by our learning algorithms, as this will allow you to make more judgement calls on difficult edge cases that might come up during labeling.
Glassdoor lists a salary of $22 per hour for a data labeler at Tesla, but that was based on reports from people in that position in California.
Tesla inherited Gigafactory New York from its acquisition of SolarCity and with it comes a deal with the state to create a certain number of jobs and maintain a level of investment in the region.
This deal has been somewhat hard to fulfill for Tesla after several changes of the plan for the factory, which was first supposed to produce solar panels.
That plan originally failed and was replaced with a deal with Panasonic to produce solar modules for Tesla at the factory, but that deal also ended last year.
Now Tesla instead produces solar roof tiles and Supercharger stations at the factory.
https://electrek.co/2021/02/08/tesl...ilot-neural-nets-images-gigafactory-new-york/
FTC: We use income earning auto affiliate links. More.
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