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Based on our record, Minio seems to be a lot more popular than Apple Machine Learning Journal. While we know about 156 links to Minio, we've tracked only 6 mentions of Apple Machine Learning Journal. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
The meta-data and model artifacts from experiment tracking can contain large amounts of data, such as the training model files, data files, metrics and logs, visualizations, configuration files, checkpoints, etc. In cases where the experiment tool doesn't support data storage, an alternative option is to track the training and validation data versions per experiment. They use remote data storage systems such as S3... - Source: dev.to / 10 days ago
> When it gets too out of hand, people will paper it over with a new, simpler abstraction layer, and the process starts again, only with a layer of garbage spaghetti underneath. I'm pretty happy that there are S3 compatible stores that you can host yourself, that aren't insanely complex. MinIO: https://min.io/ SeaweedFS: https://github.com/seaweedfs/seaweedfs Of course, many will prefer hosted/managed solutions... - Source: Hacker News / 23 days ago
Here are the basic steps to getting a minio tenant deployed inot kubernetes. There are some pre-requisites tasks to be deployed (and will not be covered in this article) including. - Source: dev.to / 2 months ago
I'd throw minio [1] in the list there as well for homelab k8s object storage. [1] https://min.io/. - Source: Hacker News / 5 months ago
Can you just append the data to a blob using something like the s3 blob api? AWS, Azure and Minio https://min.io/ all support it. That way you don't have to reinvent the wheel. Source: 9 months ago
For your reference, Apple's pages for Machine Learning for Developers and for their research. The Apple Neural Engine was custom designed to work better with their proprietary machine learning programs -- and they've been opening up access to developers by extending support / compatibility for TensorFlow and PyTorch. They've also got CoreML, CreateML, and various APIs they are making to allow more use of their... Source: about 1 year ago
We even host annual poster sessions of those PhD intern’s work while at our company, and it’ll give you an idea of the caliber of work. It may not be as great as Nvidia, Stryker, Waymo, or Tesla (which are not part of MAANG but I believe are far more ahead in CV), but it’s worth of considering. Source: about 1 year ago
They have something for ML: https://machinelearning.apple.com. - Source: Hacker News / about 2 years ago
They're more subtle about it, I think. https://machinelearning.apple.com/ Some of the papers are pretty good. I don't disagree with your sentiment in aggregate, though. Source: about 2 years ago
Siri is not where it needs to be because Apple refuses to mine user data to enrich it. They also are very hesitant to allow researchers to publish their breakthroughs which makes recruitment very hard. Although this is changing https://machinelearning.apple.com/. - Source: Hacker News / about 2 years ago
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