Introducing AI.GENERATE_TABLE: creating structured data from gen AI models in BigQuery
AI.GENERATE_TABLE() in BigQuery lets you convert unstructured data into a structured table based on the provided prompt and table schema.
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Modern Software Development For Today's Systems & Applications
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.
Agentic AI and the Future of Software Testing: A Q&A with Angie Jones
Explore how this emerging technology is changing and evolving the software development and testing fields.
Unlock AI: Faster Data Insights for All (No Code)
Steffen Hoellinger, CEO of Airy, details how they use AI and data streaming to increase developer productivity and enable a self-serve data experience for business users.
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.
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?
DreamFactory MCP explainer (Enterprise AI)
Watch how DreamFactory's MCP Server allows for natural language queries of your direct database with a high level of accuracy. Additionally, RBAC ensures data governance by making sure only the correct data is exposed to certain users based on their roles.
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.
Memory in AI Agents: What You Need to Know
AI agents are learning to remember, and that changes everything. Memory is what allows AI agents to go beyond one-off answers. It helps them retain context, learn from past interactions, and make more thoughtful, personalized decisions over time. In today’s episode, our AI Product Strategist, Ayesha Amjad, breaks down the critical role of memory in agentic AI systems.