June 2012 Blog Posts (4)

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…

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Added by Jim Clarke on June 25, 2012 at 9:30pm — No Comments

Simple example of Using Spring+JAXRS+MongoDB

FYI,

I will be expanding on it later, but might be an interesting read for some...

http://jackietutorial.blogspot.com/2012/06/springmongodbwebspherejaxrsmaven-part-1.html

Added by Jackie Gleason on June 18, 2012 at 4:01pm — No Comments

JCertif 2012 - Call For Paper : The biggest Java/Andoid Community Event in Africa !!

JCertif 2012 Call for Papers Now Open -- http://www.jcertif.com!

As some of you already know. The next edition of JCertif is coming and will take place on September 03th-09th in Brazzaville, Congo.

If you have an interesting presentation idea, we want to hear from…

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Added by Max Bonbhel on June 7, 2012 at 12:48am — 1 Comment

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…

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Added by Jim Clarke on June 3, 2012 at 8:11pm — No Comments

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InfoQ Reading List

How Grab Optimizes Image Caching on Android with Time-Aware LRU

To improve image cache management in their Android app, Grab engineers transitioned from a Least Recently Used (LRU) cache to a Time-Aware Least Recently Used (TLRU) cache, enabling them to reclaim storage more effectively without degrading user experience or increasing server costs.

By Sergio De Simone

Google Researchers Propose Bayesian Teaching Method for Large Language Models

Google Research has proposed a training method that teaches large language models to approximate Bayesian reasoning by learning from the predictions of an optimal Bayesian system. The approach focuses on improving how models update beliefs as they receive new information during multi-step interactions.

By Daniel Dominguez

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By Renato Losio

DoorDash Builds LLM Conversation Simulator to Test Customer Support Chatbots at Scale

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By Leela Kumili

Netflix Uncovers Kernel-Level Bottlenecks While Scaling Containers on Modern CPUs

Engineers at Netflix have uncovered deep performance bottlenecks in container scaling that trace not to Kubernetes or containerd alone, but into the CPU architecture and Linux kernel itself.

By Craig Risi

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