Over the last 18 months, we’ve witnessed a fundamental shift in the AI landscape. We have gone from asking models for information to giving them the keys to our systems. This move from “Generative” to “Agentic” AI is not just a technical upgrade; it is a massive change in our organisational risk profile. The Singapore […]
I keep hearing the same dismissal from technical leaders and executives when the topic of AI in the development cycle comes up. They point to issues with code quality, the introduction of security vulnerabilities, or logic that simply doesn’t hold up under pressure. They claim that because a Large Language Model currently performs like a
Scaling Governance for AI Read More »
If there is one mantra that has defined the last decade of tech, it is “move fast and break things.” And looking at the Australian ecosystem right now, we are certainly moving fast. But I worry we are about to break the wrong things. There is a dangerous disconnect playing out in our sector. On
The Governance Blindspot: Mistaking Recklessness for Speed Read More »
While Python dominates the experimental phase of machine learning, it often hits a ceiling when deployed in production environments where milliseconds matter. A recent article from Whole Tomato dives into why industries like autonomous vehicles, high-frequency trading, and robotics are building their ML pipelines directly in C++ and CUDA. This guide walks through the architecture
Building High-Performance AI/ML Pipelines with C++ and CUDA Read More »
Embarcadero has released an important patch for RAD Studio 13 that updates the Smart CodeInsight AI integration to support the latest Anthropic Claude models. Why is this update needed? Claude recently deprecated some of the models previously supported by RAD Studio. This patch addresses the necessary API and JSON data mapping changes to keep your
RAD Studio 13: New Patch for Smart CodeInsight and Claude Read More »
The conversation around AI in test automation is often filled with hype, but what does its implementation look like in practice? This post from Ranorex outlines their pragmatic, problem-first approach. Instead of chasing buzzwords, their focus is on how AI can solve the most persistent challenges in testing, particularly the significant time and effort spent
AI in Test Automation: Beyond the Hype Read More »
RAD Studio 13 introduced the SmartCore AI Components, an important new foundational element for integrating the power of LLMs into your VCL and FireMonkey applications. In this practical webinar, Malcolm Groves from Code Partners will work through multiple AI-enabled applications to get you up to speed on how these components work, and how you might
Webinar : Integrating AI into your RAD Studio Applications Read More »