COBOL is in the headlines again, and this time it is because of artificial intelligence (AI) – sparking conversations with tools emerging that claim t.

Explore the leading data orchestration platforms for 2026 with quick comparisons, practical selection tips, and implementation guidance to keep your data pipelines reliable and scalable.

Designing and deploying DSPs FPGAs aren’t the only programmable hardware option, or the only option challenged by AI. While AI makes it easier to design DSPs, there are rising complexities due to the ...

Technology partnership equips engineering and legal teams with new capabilities to manage IP risks from AI coding ...

While Anthropic’s Claude Code grabbed headlines, IBM has been deploying its own generative AI solution, Watsonx Code Assistant for Z, designed to modernize the very mainframes it built. Unlike general ...

Mercury 2 introduces diffusion LLMs to text, delivering 10x faster speeds for AI agents and production workflows without sacrificing reasoning power.

Implements all corresponding Python data structure interfaces while significantly improving performance through targeted optimizations. Users can choose the most suitable data structure type based on ...

Docker is a widely used developer tool that first simplifies the assembly of an application stack (docker build), then allows for the rapid distribution of the resulting executabl ...

By way of definition, AWS Strands is a model-driven framework (i.e. one that uses high-level designs to automatically generate code, which is often used for streamlining complex software development ...

Coursiv sponsors Python Software Foundation, supporting the open-source language powering 80% of AI tools used by ...

Abstract: Programming language source code vulnerability mining is crucial to improving the security of software systems, but current research is mostly focused on the C language field, with little ...

Python is a language that seems easy to do, especially for prototyping, but make sure not to make these common mistakes when ...