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Phone Software Entrepreneurs? Under 30 Forbes List
Forbes published an under 30 tech list featuring entrepreneurs who've made it big. Read about it here.
I heard about it because one of the guys is a neighbor's grandson. We were chatting while he walked his dog and he told me his grandson made the list. It fires me up to read stuff like this. Yes, there are millions of aspiring entrepreneurs out there. Some use Kickstarter, also a great read. I can't tell you how many times I tried a new idea and fell on my face. Sometimes, it makes some money or an impact. Sometimes it crashes and burns. But, as you can see with this article you've got to keep trying! As a great friend Serge Beauregard* liked to say, you've only got so many heartbeats.
What do you think? Got some ideas/case studies/fish that got away stories to share?
* The Serge Beauregard Swampcast is number 43 here: https://itunes.apple.com/us/podcast/swampcast/id283428946?mt=2# ;
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Happy 10th year, JCertif!
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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
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By Saranya VedagiriUber Moves from Static Limits to Priority-Aware Load Control for Distributed Storage
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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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