Notes about Rust’s ownership model. Specific care taken to document vocabulary usage.

A collection of vim-related things I have found myself looking up more than once.

It turns out the problem was my third-party router, but I had some trouble testing it at first.

Some unresearched, opinionated thoughts on making brainstorms as good as possible.

Summary

InfoQ: Meta Has Developed an AITemplate Which Transforms Deep Neural Networks into C++ Code

Meta created a Python framework called AITemplate that improves inference performance for deep neural networks by:

• transforming and optimizing the graph
• converting code to C++

Some notes on how people are defining MLOps and what general principles we can draw from that.

• O’Reilly book by Ted Dunning and Ellen Friedman
• The book is free, because they are hoping it will serve as good marketing material for MapR Convergent Data Platform.
• Focuses on the larger issue of “Machine Learning is more than just developing a model and getting it into production.”
• Talks about the need for a holistic approach to the cross-cutting concerns of ML that we will call “machine learning logistics” and “model management.”
• Talks about the whole system from start to finish
• The book may be a bit dated, as it was published in 2017.
• The book itself provides useful content. It’s not just marketing material. Every now and then, you see “tools like MapR Convergent Data Platform”, etc.

Chapter 02

• Logistics and model management need to be flexible to handle many different use cases and scenarios.
• But you don’t want it to be so complicated that it is also a hindrance to people getting work done.

Ingredients of the Rendezvous Approach

• “The rendezvous architecture takes advantage of data streams and geo-distributed stream replication to maintain a responsive and flexible way to collect and save data, including raw data, and to make data and multiple models available when and where needed.”
• “The design strongly supports ongoing model evaluation and multi-model comparison. It’s a new approach to managing models that reduces the burden of logistics while providing exceptional levels of monitoring so that you know what’s happening.”

Machine Learning Logistics Book

Chapter 1

Intro

• “Model management” is a term for the holistic view of the entire machine learning system.
• It’s not the cool part of Machine Learning, but it’s extremely important.
• New practitioners are going to need some practical advice on this matter.

Reading

How I Motivate Myself to Write

Tools

• Craft Docs