AT&T's chief data officer shares how rearchitecting around small language models and multi-agent stacks cut AI costs by 90% at 8 billion tokens a day.

Pinterest launched a next-generation CDC-based database ingestion framework using Kafka, Flink, Spark, and Iceberg. The system reduces data availability latency from 24+ hours to 15 minutes, processes ...

Announcing the Fabricate Data Agent, synthetic data generation via agentic AI. Plus, Structural's Custom Categorical is now AI-assisted, and Model-based Custom Entities are coming to Textual!

If you’ve ever done Linux memory forensics, you know the frustration: without debug symbols that match the exact kernel version, you’re stuck. These symbols aren’t typically installed on production ...

SQL will continue to serve as the lingua franca but the world of data will speak in graphs, vectors, LLMs too– and relational databases will stay but not in the same chair. Here’s why?

Backend development is mainly defined by the library used to develop it. Choosing modern, optimized Node.js libraries directly impacts scal ...

Researchers call this context rot: as an AI system processes more information, irrelevant details clutter its working memory. The result can be less accurate responses, higher costs, and a gradual ...

Turns out the factory of the future doesn't just need a software update... it needs a crash mat. Hangzhou-based Unitree Robotics says it will ship up to 20,000 humanoid robots in ...

Unlock the power of event-driven architecture with AWS's innovative pattern for Amazon RDS SQL Server. This approach decouples database events from processing, enhancing scalability and responsiveness ...

Microsoft SQL Server installation is simple when system requirements and edition choices are planned.Choosing the right authentication mode, such as ...

Alibaba unveiled Qwen3.5, an open-weight, 397-billion-parameter mixture-of-experts model that only wakes up 17 billion neurons per prompt. The payoff? You get 60% lower inference ...

Deploy AI-managed automations from local runs to production using Trigger.dev monitoring and error handling to reduce workflow failures.