As announced, you will receive dedicated AWS credits for training your models for the challenge.
Please read below to see how you can claim the $50 AWS credits for yourself or for your team This is the first set of credits that we are releasing, out of a total of $50,000 AWS credits available for training your RL agents.
Eligibility
You (or your team) must have made at least one successful submission to the challenge. Read on to understand credit availability for each round:
We are distributing the credits in 2 stages:
Currently for warm-up and Round 1, you only need to have made a successful submission to claim the $50 credit.
A successful submission is equivalent to the baseline that we have provided or better on any of the three metrics specified in the challenge.
Please request new credits once you have exhausted the $50 credit and provide proof of exhaustion of credits as well.
Credits will be available until we exhaust $25,000 credits.
For Round 2, you will need to report an increment in your previous score to receive more credits. (Stay tuned for more details)
How to redeem?
Please share the following as a reply to this thread to receive your code.
Team name (if relevant):
Submission id:
A brief intro about you (Us and the participants would love to know what brought you to this challenge!):
We will be sending out the AWS credits every alternative day after verifying the details. After receiving your code, you can go to this website and claim your credits.
The codes are valid until May 31st, 2022
On AWS you can select an on-demand g4dnxlarge instance with a GPU required for running the simulator. We have benchmarked against T4s which takes ~12 hours for 1 training run or the baseline to converge.
I have been following Roborace since the beginning of the project and always wanted to work on it. Although, I was never able to start learning ML/AI. When I saw this challenge I thought to myself that this is the time to start learning because the things that I’d learn through this challenge would directly manifest into skills that I’ll need to break into this industry.
The post doesn’t let me edit, so adding some more information here:
On AWS you can select an on-demand g4dnxlarge instance with a GPU required for running the simulator. We have benchmarked against T4s which takes ~12 hours for 1 training run or the baseline to converge.
I am a AI software engineer from china. I have developed some NLP, CV applications, and now I want to learn more about RL. This challenge is so FUN that I’d like to take this as a starting point.
With my mate, we are currently studying IT and are willing to learn more on AI. My mate is besides really interested in autonomous driving. We are diving in the challenge to improve our skills and knowledges on the subject and try to do our best to develop a convincing model.
Studied physics and then AI/ML/Control at KTH, Sweden. I love building self-learning systems, it is so rewarding to build a system that learns to solve a task by itself. First time building such systems for learning something safely. In previous projects, I let the agent run wild
Our team is working on Autonomous Driving technology and we mostly deal with supervised learning and computer vision. We wanted to explore more on the RL domain and so we signed up for this challenge.
I’m a researcher in Computer Vision, and I’m currently working on my PhD focused on multiagent deep reinforcement learning. I’m interested in applying deep learning to solve the general problem of autonomous driving, and I’m interested in exploring reinforcement learning and deep learning.
Our team is working on Autonomous Driving technology and we mostly deal with supervised learning and computer vision. We wanted to explore more on the RL domain and so we signed up for this challenge.
I don’t have a team name,
My submission id is #171215
I’m an interested student from CMU MCDS. I’ve been wanting to get cracking on some of these open data science challenges for some time, and I’m finally going to start!
Learn to Race Challenge!
This is the first set of credits that we are releasing, out of a total of $50,000 AWS credits available for training your RL agents.
Eligibility
How to redeem?
We will be sending out the AWS credits every alternative day after verifying the details. After receiving your code, you can go to this website and claim your credits.
