Codetown
Codetown ::: a software developer's community
Jim Clarke's Blog (3)
JavaFX and SteelSeries gauges using FXML
Gerrit Grunwald, aka @hansolo_ on twitter, has just ported his Swing based gauges and meters framework known as SteelSeries to JavaFX as part of the JFXtras-lab project. I can't tell you how many times since Java AWT first came out, that I have had to use meters…
ContinueAdded by Jim Clarke on June 25, 2012 at 9:30pm — No Comments
JavaFX 2.2 Canvas
One of the cool new features of the JavaFX 2.2 developer preview release is a new Canvas node that allows you to do free drawing within an area on the JavaFX scene similar to the HTML 5 Canvas. You can download this release for Windows, Mac, and Linux from JavaFX Developer Preview.
Being adventurous, I decided to take the JavaFX Canvas for a spin around the block. In doing…
ContinueAdded by Jim Clarke on June 3, 2012 at 8:11pm — No Comments
GroovyFX, Getting started.
Dean Iverson and I have been working on an open source project called GroovyFX that provides a Groovy binding that sits on the new JavaFX 2.0 platform. Dean has written a good blog on how to get started with GroovyFX here. It is already a little dated, but if you ignore the JavaFX build numbers and just download the…
ContinueAdded by Jim Clarke on September 27, 2011 at 4:51pm — No Comments
Latest Blog Posts
Most Popular Blog Posts
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.
Looking for Jobs or Staff?
Check out the Codetown Jobs group.
InfoQ Reading List
Presentation: How to Unlock Insights and Enable Discovery Within Petabytes of Autonomous Driving Data
Kyra Mozley discusses the evolution of autonomous vehicle perception, moving beyond expensive manual labeling to an embedding-first architecture. She explains how to leverage foundation models like CLIP and SAM for auto-labeling, RAG-inspired search, and few-shot adapters. This talk provides engineering leaders a blueprint for building modular, scalable vision systems that thrive on edge cases.
By Kyra MozleyArticle 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 Kumili
© 2026 Created by Michael Levin.
Powered by
