AWS DeepRacer VS Sabaki

Generative Artificial Intelligence (GenAI) is a type of artificial intelligence that can generate text, images, or other media using generative models. AWS offers a range of services for building and scaling generative AI applications, including Amazon SageMaker, Amazon Rekognition, AWS DeepRacer, and Amazon Forecast. AWS has also invested in developing foundation models (FMs) for generative AI, which are... - Source: dev.to / 3 months ago

I haven't used it, but I've heard good things about AWS' DeepRacer. It's supposed to be an all-in-one place to start for this kind of work. Source: 6 months ago

AWS DeepRacer is a service offered by Amazon Web Services (AWS) that combines machine learning, cloud computing, and robotics to provide a platform for learning and experimenting with reinforcement learning. - Source: dev.to / 8 months ago

Some other toy-scale self-driving car projects which come with simulators in case someone cannot get the hardware: 1. Duckietown: https://www.duckietown.org/ from ETH Zurich, comes with a MOOC with all material. 2. MuSHR: https://mushr.io/ from Sid Srinivasa’s group at UW. 3. F1TENTH: https://f1tenth.org/ probably the most popular, regularly heads physical competitions, sometimes at popular robotics conferences.... - Source: Hacker News / 12 months ago

I don't think I'll spend too much time writing about the history of deepracer, or what it is. You can read up on it on AWS website https://aws.amazon.com/deepracer/. - Source: dev.to / over 1 year ago

I've been using ChatGPT since launch and constantly seeking out examples of how others have been using it. A few years ago I started using KataGo with Sabaki to improve my go-playing abilities. I've known about token embeddings in neural networks before ChatGPT was a twinkle in OpenAI's eye. I was there, but I haven't seen everything you've seen, so please show me. If the truth is that ChatGPT has canned responses... Source: about 1 year ago

It's a feature with sabaki, to make it look resemble a real board more. Source: about 1 year ago

That said, if you can download some sgfs and view them in a tool like [sabaki]((https://sabaki.yichuanshen.de/), you can try and match the score that the computer reports. You can get SGFs from here - other sources are available. Be sure to find games which were won on points. You can't count a game won by resignation. Source: over 1 year ago

It's a shame because KGS would benefit greatly from a modern client. I think at this point writing a new client from scratch would be preferable, or maybe taking something like [Sabaki](https://sabaki.yichuanshen.de/) and turning it into a KGS client might be viable. Speaking of which, Sabaki is a good option for those looking to contribute to an open source project. Source: over 1 year ago

You can also just download pre-trained models. Get those set up and then install Sabaki (https://sabaki.yichuanshen.de/) and connect it to your KataGo... Instant (ok, a few hours probably if it's your first time setting it up) superhuman Go AI. There's even an npm package you can use to process SGF files and automatically score moves as good/questionable/bad + generate variations that were better choices:... - Source: Hacker News / over 2 years ago