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 ...

When an app needs data, it doesn't "open" a database. It sends a request to an API and waits for a clear answer. That's where FlaskAPI work fits in: building ...

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

No code, no problem ...

MiniMax M2.5 delivers elite coding performance and agentic capabilities at a fraction of the cost. Explore the architecture, ...

As Chief Information Security Officers (CISOs) and security leaders, you are tasked with safeguarding your organization in an ...

Speechify's Voice AI Research Lab Launches SIMBA 3.0 Voice Model to Power Next Generation of Voice AI SIMBA 3.0 represents a major step forward in production voice AI. It is built voice-first for ...

Learn how Zero-Knowledge Proofs (ZKP) provide verifiable tool execution for Model Context Protocol (MCP) in a post-quantum world. Secure your AI infrastructure today.

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

After building an AI prototype in six hours, John Winsor turned it into a full platform in two weeks—showing how AI is collapsing the gap between vision and execution.

Claude Sonnet 4.6 beats Opus in agentic tasks, adds 1 million context, and excels in finance and automation, all at one-fifth ...