AI startup Anthropic's claim of automating COBOL modernization sent IBM's stock plummeting, wiping billions off its market value. The decades-old language, still powering critical systems, faces a ...

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

Living human neurons were trained to play Doom, extending the long-running engineering benchmark into biological computing.

Two days to a working application. Three minutes to a live hotfix. Fifty thousand lines of code with comprehensive tests.

A biocomputer powered by lab-grown human brain cells has leveled up from Pong to Doom. While nowhere ready to handle the video game shooter’s most challenging levels, researchers at Cortical Labs in ...

Discover OpenFang, the Rust-based Agent Operating System that redefines autonomous AI. Learn how its sandboxed architecture, pre-built "Hands," and security-first design outperform traditional Python ...

No code, no problem ...

Researchers at a Melbourne start-up have taught their “biological computer” made from living human brain cells to play Doom.

Its use results in faster development, cleaner testbenches, and a modern software-oriented approach to validating FPGA and ASIC designs without replacing your existing simulator.

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

There are three critical areas where companies most often go wrong: data preparation and training, choosing tools and specialists and timing and planning.

Anthropic's Claude Sonnet 4.6 matches Opus 4.6 performance at 1/5th the cost. Released while the India AI Impact Summit is on, it is the important AI model ...