Codetown
Codetown ::: a software developer's community
Zemian Deng's Groups (9)
Configuration Management SIG
8 members Latest Activity: Nov 3, 2011 Half the work of starting a project is setting it up. A large proportion is keeping it set up. We'll talk about tips and tricks, Maven, and more…
iPhone Development
40 members Latest Activity: Jan 29, 2015 iPhone development is going nuts! All the apps, all the possibilities. Objective-C is the language. The SDK is out. Shops are springing up everywhere…
Scala
5 members Latest Activity: Jul 27, 2011 Scala is a general programming language and it runs on JVM. It's a static typed language with many features that make code concise and flexible.
Build Team Town
4 members Latest Activity: Oct 6, 2009 You love Ant and other build tools. You can build an app, run a suite of tests, create a jar, deploy it. Or, you want to learn. This is your group!
Spring Town
47 members Latest Activity: Sep 21, 2019 Dependency injection. It's a smart approach. Believe that? We do! Come on in and share what you know. Ask all your Spring questions here, too!
Web2.0 Town
19 members Latest Activity: Dec 22, 2013 Web2.0 is the dynamic web. It's social networking, tag clouds, metadata, geodata, and more. We love Web2.0. There's more out there than you can…
Groovy and Grails
25 members Latest Activity: Feb 28, 2015 Using Groovy and Grails? Discuss it here.
Other Languages on the JVM Village
9 members Latest Activity: Feb 28, 2015 Love Jython? Can't get enough JRuby? Groovy? Dynamic languages on the JVM can set you free! Scala? Sure! Let us know what you think here in the Other…
JEE Town
28 members Latest Activity: Dec 11, 2012 Here's your Java Enterprise Edition group. JEE powers distributed software.
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.
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 Series - AI Assisted Development: Real World Patterns, Pitfalls, and Production Readiness
In this series, we examine what happens after the proof of concept and how AI becomes part of the software delivery pipeline. As AI transitions from proof of concept to production, teams are discovering that the challenge extends beyond model performance to include architecture, process, and accountability. This transition is redefining what constitutes good software engineering.
By Arthur CasalsHow CyberArk Protects AI Agents with Instruction Detectors and History-Aware Validation
To prevent agents from obeying malicious instructions hidden in external data, all text entering an agent's context must be treated as untrusted, says Niv Rabin, principal software architect at AI-security firm CyberArk. His team developed an approach based on instruction detection and history-aware validation to protect against both malicious input data and context-history poisoning.
By Sergio De SimoneAnthropic announces Claude CoWork
Introducing Claude Cowork: Anthropic's groundbreaking AI agent revolutionizing file management on macOS. With advanced automation capabilities, it enhances document processing, organizes files, and executes multi-step workflows. Users must be cautious of backup needs due to recent issues. Explore its potential for efficient office solutions while ensuring data integrity.
By Andrew HoblitzellTracking and Controlling Data Flows at Scale in GenAI: Meta’s Privacy-Aware Infrastructure
Meta has revealed how it scales its Privacy-Aware Infrastructure (PAI) to support generative AI development while enforcing privacy across complex data flows. Using large-scale lineage tracking, PrivacyLib instrumentation, and runtime policy controls, the system enables consistent privacy enforcement for AI workloads like Meta AI glasses without introducing manual bottlenecks.
By Leela KumiliMIT's Recursive Language Models Improve Performance on Long-Context Tasks
Researchers at MIT's CSAIL published a design for Recursive Language Models (RLM), a technique for improving LLM performance on long-context tasks. RLMs use a programming environment to recursively decompose and process inputs, and can handle prompts up to 100x longer than base LLMs.
By Anthony Alford
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