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Based on our record, AWS Glue should be more popular than Google Cloud TPU. It has been mentiond 13 times since March 2021. 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.
AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy to prepare and load data for analysis. It helps bridge the gap between our MongoDB Atlas data and the services we'll use for recommendation. - Source: dev.to / about 2 months ago
AWS Glue is a fully managed extract, transform, and load (ETL) service provided by Amazon Web Services (AWS). It is designed to make it easy for users to prepare and load their data for analysis. AWS Glue simplifies the process of building and managing ETL workflows by providing a serverless environment for running ETL jobs. - Source: dev.to / 3 months ago
It is serverless data integration service to allow you to easily scale your workloads in preparing data and moving transformed data into a target location. - Source: dev.to / 10 months ago
So in the next post, we'll do that: We'll take what we've done here, add a few more components with Pulumi and AWS Glue, and wire it all up with a few magical lines of Python scripting. - Source: dev.to / over 1 year ago
Once it's in a Data Lake then you have different options depending on the analytics you need. For more advanced constant analytics then you could look into Amazon Kinesis Data Analytics instead of Firehose to S3, but for Ad-Hoc queries then this is where Glue and Athena come in. - Source: dev.to / over 1 year ago
According to https://cloud.google.com/tpu, each individual TPUv3 has 420 Teraflops, and TPUv4 is supposed to double that performance, so if that guess is correct, it should take a few seconds to do inference. Quite impressive really. - Source: Hacker News / about 2 years ago
You can also rent a cloud TPU-v4 pod (https://cloud.google.com/tpu) which 4096 TPUv-4 chips with fast interconnect, amounting to around 1.1 exaflops of compute. It won't be cheap though (excess of 20M$/year I believe). - Source: Hacker News / over 2 years ago
Actually, that's done with TPUs which are more efficient: https://cloud.google.com/tpu. Source: over 2 years ago
TPU training uses Google silicon and is thus a true deep learning alternative to Nvidia. Source: almost 3 years ago
The server choice really depends on how much CPU and RAM the requests take, how many users will be hitting the server, etc. You can start with a $5/month Digital Ocean server (or AWS or Google) and see if that works for you. Or you can outsource the server administration to Amazon or Google if you don't want to deal with it or need specialized tpu hardware. Source: about 3 years ago
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