Technology

Odds and Ends #4

Kops, podcasts, and Milvus.

  • I just discovered kops, apparently an excellent way to deploy and manage Kubernetes clusters on the cloud. Since managing a k8s cluster seems to be a full-time job at the best of times, I’m interested to see if this really does make it much easier.
  • I have a very mild case of podcast addiction, and am always looking for something great to add to my collection of subscriptions. Nikita Voloboev has published a very interesting list of podcasts. I have tried a few of the ones I didn’t already know, and they are excellent.
  • Speaking of podcasts, I highly recommend The Dropout, the result of a three-year investigation by ABC News into the fraud perpetrated by Elizabeth Holmes and her company Theranos.
  • Milvus is a welcome new addition to the space of vector search. Vector similarity search is extremely useful any time you are dealing with high-dimensional embeddings, and it has been my observation that thinking about embeddings often leads to new and interesting opportunities quite orthogonal to the original use case for which the embeddings were produced.
Read more: Odds and Ends #4

Odds and Ends #3

Karothek, Jupyter on K8s, and more.

  • My former colleagues at Blue Yonder (now part of JDA) have introduced Kartothek, software for managing tables stored as parquet files.
  • A great set of documentation on going zero to JupyterHub with Kubernetes.
  • A related piece from Jim Crist on installing JupyterHub on an existing Hadoop cluster.
  • An interesting paper interoducing PATE from a couple of years ago that had passed me by. PATE stands for Private Aggregation of Teacher Ensembles, and is a method for doing semi-supervised transfer learning from private data.
Read more: Odds and Ends #3

Odds and Ends #2

Information theory, an AI Playbook, and Traces.

Read more: Odds and Ends #2