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April 2015 Blog Posts (2)
JavaOne
Folks,
Perhaps this is old news for you, but JavaOne San Francisco registration is live. Various saving options are available leading up to the conference, and to take advantage of the current US$600 in savings registration needs to be completed by May 31st, 2015 (11:59pm PT).
I encourage you to read through the registration options by visiting the JavaOne registration site:…
Added by Michael Levin on April 24, 2015 at 11:00am — No Comments
An Inside Look at the Components of a Recommendation Engine
Recommendation engines help narrow your choices to those that best meet your particular needs. In this post, we’re going to take a closer look at how all the different components of a recommendation engine work together. We’re going to use collaborative filtering on movie ratings data to recommend movies. The key components are a collaborative filtering algorithm in Apache Mahout to build and train a machine learning model,…
ContinueAdded by Carol McDonald on April 13, 2015 at 9:14am — 1 Comment
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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
C++26: Reflection, Memory Safety, Contracts, and a New Async Model
The C++26 standard draft is now complete, reports Herb Sutter, long-time C++ expert and former chair of the ISO C++ standards committee. The finalized draft introduces reflection, enhances memory safety without requiring code rewrites, adds contracts with preconditions and postconditions alongside a new assertion statement, and establishes a unified framework for concurrency and parallelism.
By Sergio De SimoneMeta Reports 4x Higher Bug Detection with Just-in-Time Testing
Meta introduces Just-in-Time (JiT) testing, a dynamic approach that generates tests during code review instead of relying on static test suites. The system improves bug detection by ~4x in AI-assisted development using LLMs, mutation testing, and intent-aware workflows like Dodgy Diff. It reflects a shift toward change-aware, AI-driven software testing in agentic development environments
By Leela KumiliCNCF Warns Kubernetes Alone Is Not Enough to Secure LLM Workloads
A new blog from the Cloud Native Computing Foundation highlights a critical gap in how organizations are deploying large language models (LLMs) on Kubernetes: while Kubernetes excels at orchestrating and isolating workloads, it does not inherently understand or control the behavior of AI systems, creating a fundamentally different and more complex threat model.
By Craig RisiAnthropic Introduces Agent-Based Code Review for Claude Code
Anthropic has introduced a new Code Review feature for Claude Code, adding an agent-based pull request review system that analyzes code changes using multiple AI reviewers.
By Daniel DominguezPresentation: Speed at Scale: Optimizing the Largest CX Platform Out There
Matheus Albuquerque shares strategies for optimizing a massive CX platform, moving from React 15 and Webpack 1 to modern standards. He discusses using AST-based codemods for large-scale migrations, implementing differential serving with module/nomodule, and leveraging Preact to shrink footprints. He explains how to balance cutting-edge performance with strict legacy browser constraints.
By Matheus Albuquerque
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