How WriteUp.AI Runs Behind The Scenes

WriteUp.AI is my newest project. There's a lot of technical components that happened behind the scenes, so it deserves a deep dive into a lot of the technical architecture and mistakes I made along the way. 

Note: This article link is a temporary placeholder since I normally spend 40+ hours on each of these writeups. Some of my previous articles that been well-received are

In this blog article, I'm going to detail everything I learned while building WriteUp.AI a tool that uses cutting edge ML AI articles to help people write. I estimated it would take me about three weeks to build it, it ended up taking two months as I kept on adding one more feature. During this, I learned a lot about deploying ML. It should be finished this in the next week or so, but I wanted to list out all the topics I outlined to write.

  • A Quick Recap of Tech Architecture
  • Three Weeks in Peru 
  • The 90/90 Rule
  • Overengineered or Overutilized?
  • Inference And Other Scary ML Slang Terms Explained
  • K80s, V100s or P100s? (And the envy of TPUs)
  • Thompson’s Rule of Telescopes (How ML-Ops is never straight forward …)
  • Container This … Container That … Wait, where’s my video card?
  • What do you mean out of memory?!
  • Bad States with Large Tensors Leads To Other Odd Problems
  • I've Entered Cloud Prison
  • Things I Tried That Didn't Quite Work Out (Hint: Everything)
    • I had to rewrite the backend and microservice architecture twice ...
  • I Thought I’d Learn More About Neural Networks … 
  • Testing Out Autoscaling with Async
  • Shortening Feedback Cycles with Automation
  • Finding Bottlenecks: CPU, GPU, or Memory? 
  • Google Cloud Regions. Pick one or pick all?
  • Battle of the Feature Creep 
  • Making Difficult Decisions Between TensorFlow Serve, Kubernetes, TorchScript and Other Model Deployment Questions
  • TorchScript Performance Speedup (And Other Optimizations)
  • Measuring Inference Times with Cascade Lake Vs V100
  • Measure Twice, Cut Once? No. You Should Get Faster at Cutting.
  • Special Thanks To 
    • Lot of my friends helped me test this and improve the UX.
  • Why PyTorch? Why TensorFlow?
  • Dealing with Burnout

I'll alert the subscribers on the mailing list when I'm done, or just come back to this article in a week or-so. Thanks!

Contact: Please feel free to email me at [email protected] or tweet @shekkery.
Finale: Writing quality articles is hard. Getting traffic is even harder. Thank you for sharing!

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