Michael Levin's Blog – February 2011 Archive (3)

Demo and Startup City

Demo is a conference that showcases new ideas. The idea is that people with startup ideas get 6 minutes to pitch their ideas. What's the payoff for them? Investors, of course. What's the payoff for us? There's a website with a live feed and we can watch the action on the web! Surf to www.demo.com today beginning at 9:00AM PST and be a…

Continue

Added by Michael Levin on February 28, 2011 at 8:00am — No Comments

The Making of Swampcast





The Making of Swampcast ::: A video documenting the history and production of Swampcast, a podcast about "Software development, emerging technology and everything else!"

 

Contact Mike at http://www.codetown.us/profile/MichaelLevin

 

Subscribe to Swampcast at www.swampcast.com and on iTunes at… Continue

Added by Michael Levin on February 25, 2011 at 11:00am — No Comments

Net Neutrality ::: Updated!

"The Federal Communications Commission appears poised to pass a controversial set of rules that broadly create two classes of Internet access, one for…

Continue

Added by Michael Levin on February 23, 2011 at 4:30pm — 7 Comments

Monthly Archives

2025

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

Happy 10th year, JCertif!

Notes

Welcome to Codetown!

Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.

When you create a profile for yourself you get a personal page automatically. That's where you can be creative and do your own thing. People who want to get to know you will click on your name or picture and…
Continue

Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.

Looking for Jobs or Staff?

Check out the Codetown Jobs group.

 

Enjoy the site? Support Codetown with your donation.



InfoQ Reading List

Article: Engineering Speed at Scale — Architectural Lessons from Sub-100-ms APIs

Sub‑100-ms APIs emerge from disciplined architecture using latency budgets, minimized hops, async fan‑out, layered caching, circuit breakers, and strong observability. But long‑term speed depends on culture, with teams owning p99, monitoring drift, managing thread pools, and treating performance as a shared, continuous responsibility.

By Saranya Vedagiri

Uber Moves from Static Limits to Priority-Aware Load Control for Distributed Storage

Uber engineers detailed how they evolved their storage platform from static rate limiting to a priority-aware load management system. The approach protects Docstore and Schemaless, Uber’s MySQL-based distributed databases, by colocating control with storage, prioritizing critical traffic, and dynamically shedding load under overload conditions.

By Leela Kumili

Building Software Organisations Where People Can Thrive

Continuous learning, adaptability, and strong support networks are the foundations for thriving teams, Matthew Card mentioned. Trust is built through consistent, fair leadership and addressing toxic behaviour, bias, and microaggressions early. By fostering growth, psychological safety, and accountability, people-first leadership drives resilience, collaboration, and performance.

By Ben Linders

Google DeepMind Introduces ATLAS Scaling Laws for Multilingual Language Models

Google DeepMind researchers have introduced ATLAS, a set of scaling laws for multilingual language models that formalize how model size, training data volume, and language mixtures interact as the number of supported languages increases.

By Robert Krzaczyński

Presentation: Foundation Models for Ranking: Challenges, Successes, and Lessons Learned

Moumita Bhattacharya discusses the evolution of Netflix’s ranking systems, from the multi-model architecture to a Unified Contextual Recommender (UniCoRn). She explains how they built a task-agnostic User Foundation Model to capture long-term member preferences. Learn how they solve system challenges like high-throughput inference and the tradeoff between relevance and personalization.

By Moumita Bhattacharya

© 2026   Created by Michael Levin.   Powered by

Badges  |  Report an Issue  |  Terms of Service