Google Cloud TPU VS Looker

Google Cloud TPU Reviews

Looker Reviews

Google Cloud TPU mentions (5)

• Pathways Language Model (Palm): 540B Parameters for Breakthrough Perf

  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

• The AI Research SuperCluster

  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

• Stadia's future includes running the backend of other streaming platforms, job listing reveals

  Actually, that's done with TPUs which are more efficient: https://cloud.google.com/tpu. Source: almost 3 years ago

• Nvidia CEO: Ethereum Is Going To Be Quite Valuable, Transactions Will Still Be A Lot Faster

  TPU training uses Google silicon and is thus a true deep learning alternative to Nvidia. Source: almost 3 years ago

• Server Question

  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

Looker mentions (14)

• edit home page to add folder section

  Then in the "foldername" you can have 5 folders, each one for each of the groups. This means that when group1 enters looker.com, his default page will be the "foldername", which contains group1folder (he cannot see the rest of the folders if you have set the permissions correctly for each folder). Source: about 1 year ago

• Stars, tables, and activities: How do we model the real world?

  Even if you want to make Wide Tables, combining fact and dimensions is often the easiest way to create them, so why not make them available? Looker, for example, is well suited to dimensional models because it takes care of the joins that can make Kimball warehouses hard to navigate for business users. - Source: dev.to / over 1 year ago

• dbt for Data Quality Testing & Alerting at FINN

  We take daily snapshots of test results, aggregate them, and send Looker dashboards to the appropriate teams. - Source: dev.to / about 2 years ago

• I'm a dev ID 10 T please help me

  Dashboard: I like to use Datastudio because it's easy (just like using google sheets), but you can also try out Looker. Source: over 2 years ago

• The Data Stack Journey: Lessons from Architecting Stacks at Heroku and Mattermost

  For Growth and larger, I would recommend Looker. The only reason I wouldn't recommend it for the smaller company stages is that the cost is much higher than alternatives such as Metabase. With Looker, you define your data model in LookML, which Looker then uses to provide a drag-and-drop interface for end-users that enables them to build their own visualizations without needing to write SQL. This lets your... - Source: dev.to / over 2 years ago