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cloud-computer-vision's Introduction

# [louis030195.com](https://louis030195.com) ๐Ÿค”

Carbon-based intelligence ๐Ÿ’.

๐Ÿ”— Links

๐ŸŒŠ My memory stream

Here is a list of Louis brain diet & outputs:

๐Ÿ‘‹ Favourite daily quotes from readwise.io/@louis

That your strength as a rationalist is your ability to be more confused by fiction than by reality.

Harry Potter and the Methods of Rationality

Eliezer Yudkowsky

The most valuable knowledge is always discovered last: but the most valuable knowledge consists of methods.

The Will to Power

Friedrich Wilhelm Nietzsche

Putting together the initial team, creating the culture, and instilling the mission and values into the team are all like designing and building the initial product.

Tren Griffin - A Dozen Lessons for Entrepreneurs

2017, Columbia University Press

### ๐Ÿง  Recent entropy generated by my [brain](https://brain.louis030195.com) โ„น๏ธ some of my latest thoughts, written in obsidian.md notes
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  • Readwise/Podcasts/The Knowledge Project with Shane Parrish - 193 โ€” Dr. Jim Loehr โ€” Change the Stories You Tell Yourself.md
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  • README.md
  • Readwise/Articles/Peter Kazanjy - Founding Sales The Early Stage Go-to-Market Handbook.md
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  • Readwise/Articles/Peter Kazanjy - Founding Sales The Early Stage Go-to-Market Handbook.md
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    ๐Ÿ“š Books Louis is reading

    โœ Recent book reviews

    Anything that align with your interest? Let's have a 15-30 min remote coffee:

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    cloud-computer-vision's People

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    cloud-computer-vision's Issues

    Pipeline optimization

    Input pubsub triggered too many times
    Upload 200 frames =>

    Screenshot from 2019-08-23 18-02-17

    Obviously the firsts triggers push everything in the Pub/Sub queue, then the function is called ~200 times for nothing, would it be better to switch to a http / pubsub trigger from back API calling just once after multiple files have been uploaded ?

    AI Platform - batch predictions quota

    File "/env/local/lib/python3.7/site-packages/google/cloud/functions/worker.py", line 383, in run_background_function _function_handler.invoke_user_function(event_object) File "/env/local/lib/python3.7/site-packages/google/cloud/functions/worker.py", line 217, in invoke_user_function return call_user_function(request_or_event) File "/env/local/lib/python3.7/site-packages/google/cloud/functions/worker.py", line 214, in call_user_function event_context.Context(**request_or_event.context)) File "/user_code/main.py", line 100, in batch_prediction print('Response', batch_predict(PROJECT_ID, body)) File "/user_code/main.py", line 68, in batch_predict response = request.execute() File "/env/local/lib/python3.7/site-packages/googleapiclient/_helpers.py", line 130, in positional_wrapper return wrapped(*args, **kwargs) File "/env/local/lib/python3.7/site-packages/googleapiclient/http.py", line 855, in execute raise HttpError(resp, content, uri=self.uri) googleapiclient.errors.HttpError: <HttpError 429 when requesting https://ml.googleapis.com/v1/projects/wildlife-247309/jobs?alt=json returned "Quota failure for project wildlife-247309. The project is already using 80 CPU cores for batch prediction. This job additionally requires 10 CPU cores, which in total would exceed the allowed maximum of 72 cores. To read more about Cloud ML Engine quota, see https://cloud.google.com/ml-engine/quotas.">

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