Systems | Development | Analytics | API | Testing

Train your own AI model: Know the Buts and Hows

Have you ever wondered how apps like Google Maps predict traffic, or how Netflix knows exactly what you want to watch next? Or better yet, how can chatbots (like ChatGPT!) carry on conversations almost like humans? The magic behind it all? AI models. But what exactly is an AI model? Is it some complex algorithm sitting in a dark server room somewhere? Or is it the new digital brain behind today’s smartest tools? In simple terms, AI models are like trained minds.

Nearly half of testers struggle with AI's learning curve

AI is transforming testing—but not without its challenges. According to the State of Software Quality Report 2025, 46% of testers cite the lack of skilled personnel or the steep learning curve as major barriers to adopting AI in software testing. In this insightful message, we highlight one of the most pressing issues in the QA space: while AI has immense potential to drive efficiency and quality, teams are struggling to fully capitalize on it due to limited expertise.

Confluent unites batch and stream processing for faster, smarter agentic AI and analytics

On Confluent Cloud for Apache Flink®, snapshot queries combine batch and stream processing to enable AI apps and agents to act on past and present data. New private networking and security features make stream processing more secure and enterprise-ready.

EP 24 | Why AI Agents Are the Future of Enterprise AI with Cloudera's Abhas Ricky

AI agents are quickly becoming one of the most powerful tools in the enterprise AI toolkit. According to Cloudera’s latest Agentic AI Survey, 96% of enterprises plan to expand their use of AI agents. But what’s driving this surge, and how can organizations turn hype into results? In this episode of The AI Forecast, host Paul Muller sits down with Abhas Ricky, Chief Strategy Officer at Cloudera, to explore the real momentum behind agentic AI. From healthcare to telecom, Abhas unpacks how AI agents are already transforming operations with speed, intelligence, and autonomy.

Why You Need An Ai Code Checker

Imagine waking up to an email from a junior developer: I just wrote 1,000 lines of flawless code in under an hour! Impressive? Absolutely. Suspicious? Maybe. Thanks to AI tools like GitHub Copilot, ChatGPT, Cursor and Claude, writing code has never been faster. But as AI-generated code floods repositories, classrooms, and businesses, a critical question arises: How do we know if code was written by a human or an AI?

How eXalt Built a Secure and Scalable ChatGPT Alternative with Koyeb

eXalt is a French consulting firm with over 1200 consultants and offices in Paris, New York, London, Madrid, Lisbon, Brussels, and throughout France. They specialize in Finance and Tech, offering expertise in data science, cybersecurity, software development and IT infrastructure, project and product management, and more. When eXalt consultants are on assignment, they often need fast, reliable access to a ChatGPT-like tool to help with research and problem-solving.