Plausible. But I’ve learned any prognostications on complex systems are far more likely to be wrong than right. Looking forward to connecting these dots in hindsight.

Fun network diagram of data for The Office. Made with my son! medium.com/@ccolsonbball/… #TheOffice #DataScience

I always appreciated the Stitch Fix Algorithms team's willingness to invest in amazing internal tools. Ariadne: building a custom observability UI for personalized search multithreaded.stitchfix.com/blog/2023/06/1…

The graphics on Netflix's tech blog have leveled-up. Good content too. netflixtechblog.com/detecting-scen…

Pretty much any metrics layer, etl, or feature store would benefit from this.

Broccoli might be my favorite fractal.

Hamilton in action (a technology that spun out of the Stitch Fix algorithms team). blog.dagworks.io/p/containerize… #DataScience #LLMs

Mind blown. I just realized that iPhone and MacBooks can share a copy buffer. Copy on one, paste to the other. How long has that been there?

Expressing PySpark Transformations Declaratively with Hamilton blog.dagworks.io/p/expressing-p…

Very appreciative to Wes McKinney and so many others that help evolve this space. So many of us stand on your shoulders while focusing on the mere application of these technologies and receiving the kudos for the value they generate. Thank you! vldb.org/pvldb/vol16/p2… #datascience

RIP Netflix DVD. A long run.

So many companies say they are okay with failure but they still behave in ways which discourages risk-taking and innovation. In Amy Edmondson new book she articulates the different types of failures which gives us with the vocabulary to adjust and embrace the right kind of

Great article featuring Bob Sutton and huggyrao on "addition sickness": the unnecessary rules, procedures, communications, tools, and roles that seem to inexorably grow, stifling productivity and creativity.

Gorgeous visualization. Effective too. Coneys so much more than text alone. NYTimes always does a nice job. nytimes.com/interactive/20…

Good framing on the tradeoff between moving fast and shipping high quality code. In a data science context, I believe one needs to lean towards 'fast' in the short-term in order to learn more quickly and allay uncertainty. But, once value is found, we need refactor to achieve a

I appreciate chatGPT's humility in admitting mistakes.

Must be fun to be a PhD student right now. So many adjacent possibilities surface now that foundational models are available. Cool paper on the relationships between objects in an image. arxiv.org/pdf/2402.19474… #AI #computervision

Working in companies shouldn't be so hard. Even when we all want the same things, we trip over bad process and unnecessary coordination. At the same time, other things can be too easy and we do things we later regret. Learn how to smartly work with friction. The Friction Project:

One of my heroes. Thank you for all the contributions to knowledge

Find me on Bluesky: ecolson.bsky.social. Love all things data science, machine learning, AI, and management there of.