8 articles found
AI-augmented architecture isn’t about replacing architects, it’s about transforming them into curators of machine-readable knowledge. Here’s why most teams are getting it wrong.
Chinese AI labs like Z.AI and Qwen didn’t just catch up to US models, they weaponized efficiency under sanctions to dominate open-source AI. The data tells a story of unintended consequences.
A deep technical analysis of an 8x Radeon 7900 XTX build running local LLM inference at 192GB VRAM, exposing the cost-performance gap between DIY consumer hardware and cloud AI infrastructure.
Debunking the myth that Google’s Gemma models are lagging behind, and exploring how their multilingual capabilities are quietly dominating the AI landscape.
Google’s C2S-Scale 27B, built on Gemma, generated a novel cancer hypothesis that’s already been experimentally validated. The era of AI-driven discovery has begun.
Why trusting third-party AI providers might be costing you more than just money, including up to 14% performance degradation.
Google’s new language extraction tool promises structured data from messy text, but developers are discovering it’s more complicated than advertised.
Stanford’s new lecture series reveals the mathematical foundations most AI tutorials skip – here’s what makes it different
