Google’s ATLAS study reveals how languages help each other in AI training, offering scaling laws and pairing insights for better multilingual models.

The additions let data teams ask progressive, context‑aware questions in natural language while enabling developers to deploy governed analytics agents across applications via unified API endpoints.

Google has renamed its open-source ZetaSQL project to GoogleSQL, unifying the branding for the SQL dialect, analysis, and parsing libraries.

Maybe your wishes will come true? AI Ultra subscribers will be able to create and explore interactive AI-generated worlds.

Teradata (NYSE: TDC) today announced the availability of its foundational enterprise-grade Data Analyst AI agent on Google Cloud Marketplace, enabling organizations to integrate advanced analytics and ...

What's Up Docker shows which Docker containers need updates, tracks versions, and lets you manage them safely through a ...

Cuts out the Azure middleman with multi-year deal for 'tighter alignment' Snowflake plans to spend as much as $200 million ...

In 2026, artificial intelligence skills sit on the short list for promotions in analytics, product, and operations. Teams want people who can frame the right problem, choose workable models, and ...

Hands-on learning is praised as the best way to understand AI internals. The conversation aims to be technical without ...

Systems Development Engineer Ravi Kiran Reddy Bommareddy eliminated vendor dependencies and manual bottlenecks across Amazon's fulfillment network, proving scal ...

Google Gemini cheat sheet with key features, how the models work, where it’s available on web, Android, iOS, Workspace, plus pricing and setup steps.

NotebookLM Review: Bring Your Own Sources to This Ultrapractical Google AI Tool ...