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Michael Levin's Blog – January 2015 Archive (6)
Phone Software Entrepreneurs? Under 30 Forbes List
Forbes published an under 30 tech list featuring entrepreneurs who've made it big. Read about it …
Added by Michael Levin on January 27, 2015 at 12:30pm — No Comments
Getting Started With Android
Interested in Android programming? Here's a nice, recent article at Lifehacker outlining good, free resources to get you going. http://lifehacker.com/i-want-to-write-android-apps-where-do-i-start-1643818268 ;
Added by Michael Levin on January 22, 2015 at 11:05am — No Comments
Pay What You Want: Back-End Developer Course Bundle
Added by Michael Levin on January 20, 2015 at 10:23am — No Comments
Speak at OSCON!
Here's a message from O'Relly about OSCON 2015:
We're deep into planning OSCON 2015 and we've got some exciting news: OSCON is changing. We're no longer beating the drum and…
ContinueAdded by Michael Levin on January 9, 2015 at 11:47am — No Comments
O'Reilly Solid Conference CFP closes 1/20!
The O'Reilly Solid conference is in San Diego in June and it's all about the merging of HW/SW for the IoT. Want to get involved? The Call for Papers is open and there are loads of benefits in giving a presentation for an O'Reilly conference., Take it from me! It's a great thing to do for the community and you learn a ton…
ContinueAdded by Michael Levin on January 9, 2015 at 9:30am — No Comments
How to Use SQL, Hadoop, Drill, REST, JSON, NoSQL, and HBase in a Simple REST Client
Our friend Carol just published this article.
SQL will become one of the most prolific use cases in the Hadoop ecosystem, according to Forrester Research. Apache Drill is an open source SQL query engine for big data exploration. REST services and clients have emerged as popular technologies on the Internet. Apache HBase is a hugely popular Hadoop NoSQL…
ContinueAdded by Michael Levin on January 7, 2015 at 1:45pm — No Comments
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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.
Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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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 VedagiriUber 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 KumiliBuilding 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 LindersGoogle 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 KrzaczyńskiPresentation: 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
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