derrickrburns

5 ms·

1.
by derrickrburns 5mo ago
Have you considered solving a different problem? What are agents trying to achieve when searching a code base? Finding seams. How about indexing seams instead?
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Front end and back end are optimizing for different things(derrickburns720047.substack.com)
1 points by derrickrburns 7mo ago|1 comments
3.
by derrickrburns 7mo ago
Find out why your design is losing users through coupled value theory and how to fix it!
4.
Generalized K-Means Clustering(github.com)
41 points by derrickrburns 1y ago|12 comments
5.
by derrickrburns 1y ago
# HackerNews Announcement ## Title Generalized K-Means Clustering for Apache Spark with Bregman Divergences ## Body (3,982 characters) I've built a production-ready K-Means library for Apache Spark that supports multiple distance funct
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Generalized K-Means Clustering for Apache Spark with Bregman Divergences(github.com)
3 points by derrickrburns 1y ago|1 comments
7.
by derrickrburns 1y ago
# HackerNews Announcement ## Title Generalized K-Means Clustering for Apache Spark with Bregman Divergences ## Body (3,982 characters) I've built a production-ready K-Means library for Apache Spark that supports multiple distance funct
8.
by derrickrburns 1y ago
The failure of the Zenobia Pay encodes much of the REAL value of Mastercard and Visa: 1. A global, enforceable rulebook + dispute court. They standardize how authorization, clearing, settlement, chargebacks, retrievals, representments, reas
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by derrickrburns 2y ago
Good writing is more important than ever. Learn how good writing can help you overcome the barriers of time and distance.
10.
Generalized K-Means Clustering(github.com)
192 points by derrickrburns 3y ago|80 comments
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by derrickrburns 3y ago
AI has sparked new interest in high dimensional embeddings for approximate nearest neighbor search. Here is a highly scalable, implementation of a companion technique, k-means clustering that uses Spark 1.1 written in Scala. Please let me
12.
by derrickrburns 3y ago
Well done!
13.
by derrickrburns 3y ago
Use chatGPT to understand dig output: Explain this : dig +human +norecurse @8.8.8.8 google.com HEADER: opcode: QUERY status: NOERROR id: 11653 flags: qr ra records: QUESTION: 1, ANSWER: 1, AUTHORITY: 0, ADDITIONAL: 1 QUESTION SE
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by derrickrburns 3y ago
Here is an analogy. Two softball players. One hits the ball 230 feet on average. The other hits the ball 210 feet on average. The homerun fence is at 220 feet. One is considered a GREAT homerun hitter. The other is considered a poor one
15.
by derrickrburns 3y ago
Here is an analogy. Two softball players. One can hit the ball an average of 230 feet, 40% of the at bats. The other can hit the ball an average of 210 feet, 40% of the at bats. The homerun wall is 220 feet. One is a GREAT homerun hitter.
16.
by derrickrburns 4y ago
Funny. I worked at AT&T Bell Labs in the 80s. All of these insights seem eerily familiar.
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by derrickrburns 4y ago
Check out Place Not Race by Sheryll Cashin for a more nuanced, intellectual discussion: https://www.amazon.com/Place-Not-Race-Opportunity-America/dp...
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by derrickrburns 4y ago
Check out Place Not Race by Sheryll Cashin for a more nuanced, intellectual discussion. https://www.amazon.com/Place-Not-Race-Opportunity-America/dp...
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Guide to Cloud-Native and Kubernetes-Ready Services(medium.com)
1 points by derrickrburns 5y ago|0 comments
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by derrickrburns 6y ago
The most important and irreplaceable asset you have is your time. Think very carefully about whom and how you spend it. You cannot get it back.
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by derrickrburns 6y ago
I deployed Gloo to production at Tidepool.org in November 2019. Rock solid tech, responsive team, excellent feature set.
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Cycle Time: A Longitudinal Look(medium.com)
1 points by derrickrburns 7y ago|0 comments
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Streaming Similarity Search for Fraud Detection(medium.com)
2 points by derrickrburns 9y ago|0 comments
24.
Building a Modern, Scalable Back End with Kubernetes(medium.com)
5 points by derrickrburns 10y ago|0 comments