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You could say a lot of things about AWS, but among the cloud platforms (and I've used quite a few) AWS takes the cake. It is logically structured, you can get through its documentation relatively easily, you have a great variety of tools and services to choose from [from AWS itself and from third-party developers in their marketplace]. There is a learning curve, there is quite a lot of it, but it is still way easier than some other platforms. I've used and abused AWS and EC2 specifically and for me it is the best.
Based on our record, Amazon AWS seems to be a lot more popular than Machine Box. While we know about 486 links to Amazon AWS, we've tracked only 5 mentions of Machine Box. 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.
Reminds me of Machine Box (http://machinebox.io). Source: over 3 years ago
Thank you :) I did that to teach dogโs breed to an AI. If you donโt know machine box yet : Https://machinebox.io It seems really cool and easy to use. Source: about 4 years ago
I think you should go 5 Pi X 5 Jetson Nanoโs I havenโt seen many people offloading the Nanoโs GPU functionality for ML similar to this Serverless style of product. https://machinebox.io/. Source: almost 5 years ago
For face recognition - CompreFace. Disclaimer - I created it, as an alternative you can use MachineBox, but it's not open source and has limits. Also, I think, you will use some software to control the system, e.g. Frigate or Home Assistant, I think this repository can be useful for you. Source: about 5 years ago
If you have a really simple application, you can just save the encodings into the files. If not - it's better to use a database. SQL is ok. But for the best results, I would suggest using milvus.io, as it was created for saving vectors and finding the distances (I haven't tried it, though). If your final goal is not to learn face recognition basics, you can just use free ready to use solutions like CompreFace... Source: about 5 years ago
In conclusion, Cloudflare Workers and AWS Lambda are two popular edge computing solutions that offer a range of benefits, including reduced latency, improved performance, and enhanced security. By understanding the key differences between these solutions, businesses can make informed decisions about which one to use. Whether you're building a real-time analytics application or a serverless API, Cloudflare Workers... - Source: dev.to / 24 days ago
> but it's still a singleton instance, so where do you run it? Most hardware doesn't give you enough uptime for what you need here, because what you actually needed was a re-architecture for distribution / failover / whatever, and while you could ask your LLM to do that you aren't going to run your bank on the result. If only we had a way to solve these issues with tools capable of running Rust programs in that... - Source: Hacker News / about 2 months ago
Not because infrastructure isn't important. It is. Not because Amazon Web Services (AWS) is a bad platform. It isn't. - Source: dev.to / 2 months ago
The AWS S3 documentation covers all of these in detail. The configuration takes about an hour to get right the first time and rarely needs changes after. - Source: dev.to / 3 months ago
The first pattern is direct-to-storage. The client uploads chunks directly to an object storage service like Amazon S3 using pre-signed URLs. The application server creates the upload session and grants permission but never sees the file bytes. This pattern scales well because the application servers do not handle the upload bandwidth. - Source: dev.to / 3 months ago
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