axis-aws-rekognition
determined
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axis-aws-rekognition | determined | |
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2 | 10 | |
1 | 2,844 | |
- | 3.3% | |
1.8 | 9.9 | |
over 2 years ago | 6 days ago | |
Go | Go | |
GNU General Public License v3.0 only | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
axis-aws-rekognition
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Boosting the assembly process with AWS serverless & Axis camera
For us, this is a big step towards bringing AWS into our assembly process to enable other use cases with the same setup, at the same time, gain quick wins for us. To support the community and the speed of transformation at manufacturers, we will also release our POC (proof of concept) code at GitHub that brings the powerful OCR function from Rekognition and the result delivered over MQTT together with powerful cameras. With some simple code changes, you could quickly get the object Rekognition with thousands of supported objects/scenes and custom labels to train it for your own object detection with a few images.
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AWS open source news and updates No.41
axis-aws-rekognition Lezgin Bakircioglu got in touch this week to tell me about this project and how they are integrating AI services such as AWS Rekognition into the Axis range of cameras in order to do OCR. He has put together this blog post, Boosting the assembly process with AWS serverless & Axis camera to help you understand how this all fits together. This is still experimental, so get in touch with Lezgin if you think this is something you would like to contribute to.
determined
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Open Source Advent Fun Wraps Up!
17. Determined AI | Github | tutorial
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ML Experiments Management with Git
Use Determined if you want a nice UI https://github.com/determined-ai/determined#readme
- Determined: Deep Learning Training Platform
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Queueing/Resource Management Solutions for Self Hosted Workstation?
I looked up and found [Determined Platform](determined.ai), tho it looks a very young project that I don't know if it's reliable enough.
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Ask HN: Who is hiring? (June 2022)
- Developer Support Engineer (~1/3 client facing, triaging feature requests and bug reports, etc; 2/3 debugging/troubleshooting)
We are developing enterprise grade artificial intelligence products/services for AI engineering teams and fortune 500 companies and need more software devs to fill the increasing demand.
Find out more at https://determined.ai/. If AI piques your curiosity or you want to interface with highly skilled engineers in the community, apply within (search "determined ai" at careers.hpe.com and drop me a message at asnell AT hpe PERIOD com).
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How to train large deep learning models as a startup
Check out Determined https://github.com/determined-ai/determined to help manage this kind of work at scale: Determined leverages Horovod under the hood, automatically manages cloud resources and can get you up on spot instances, T4's, etc. and will work on your local cluster as well. Gives you additional features like experiment management, scheduling, profiling, model registry, advanced hyperparameter tuning, etc.
Full disclosure: I'm a founder of the project.
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[D] managing compute for long running ML training jobs
These are some of the problems we are trying to solve with the Determined training platform. Determined can be run with or without k8s - the k8s version inherits some of the scheduling problems of k8s, but the non-k8s version uses a custom gang scheduler designed for large scale ML training. Determined offers a priority scheduler that allows smaller jobs to run while being able to schedule a large distributed job whenever you need, by setting a higher priority.
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Cerebras’ New Monster AI Chip Adds 1.4T Transistors
Ah I see - I think we're pretty much on the same page in terms of timetables. Although if you include TPU, I think it's fair to say that custom accelerators are already a moderate success.
Updated my profile. I've been working on DL training platforms and distributed training benchmarking for a bit so I've gotten a nice view into the GPU/TPU battle.
Shameless plug: you should check out the open-source training platform we are building, Determined[1]. One of the goals is to take our hard-earned expertise on training infrastructure and build a tool where people don't need to have that infrastructure expertise. We don't support TPUs, partially because a lack of demand/TPU availability, and partially because our PyTorch TPU experiments were so unimpressive.
[1] GH: https://github.com/determined-ai/determined, Slack: https://join.slack.com/t/determined-community/shared_invite/...
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[D] Software stack to replicate Azure ML / Google Auto ML on premise
Take a look at Determined https://github.com/determined-ai/determined
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AWS open source news and updates No.41
determined is an open-source deep learning training platform that makes building models fast and easy. This project provides a CloudFormation template to bootstrap you into AWS and then has a number of tutorials covering how to manage your data, train and then deploy inference endpoints. If you are looking to explore more open source machine learning projects, then check this one out.
What are some alternatives?
amazon-s3-presigned-urls-aws-sam - For more serverless learning resources, visit https://serverlessland.com/.
ColossalAI - Making large AI models cheaper, faster and more accessible
cfn-diagram - CLI tool to visualise CloudFormation/SAM/CDK stacks as visjs networks, draw.io or ascii-art diagrams.
Dagger.jl - A framework for out-of-core and parallel execution
ha-mqtt-iot - A simple configurable MQTT client that allows actions to be taken or values be reported from a PC
aws-virtual-gpu-device-plugin - AWS virtual gpu device plugin provides capability to use smaller virtual gpus for your machine learning inference workloads
aws-sdk-js-v3 - Modularized AWS SDK for JavaScript.
acaps - Axis System Integration ACAP
goofys - a high-performance, POSIX-ish Amazon S3 file system written in Go
awslambdahandler - Linter for AWS Lambda handler
alpa - Training and serving large-scale neural networks with auto parallelization.