Lenovo'sThinkSystem SR680a V4doesn't just perform—it explodes with AI power, thanks to Nvidia'sB200GPUs. We're talking4nmchips with a mind-boggling208 billion transistors. Boost? Try11x...

Meta's Llama4models, Scout and Maverick, strut around with17B active parametersunder a Mixture of Experts architecture. But deploying onGoogle Cloud's Trillium TPUsor A3 GPUs? That's become a breeze with new, fine-tuned recipes. Utilizing tools likeJetStreamandPathways? It means zipping through infe..

Amazon'sCEO sounds the alarm: AI is gearing up to decimate office jobs. He urges employees to sharpen their skills or risk getting the axe, all while Amazon unleashes a cavalcade of over1,000generative AI projects...

AI model collapsecould hit hard with synthetic data in play. Picturepre-2022 dataas the “low-background steel” savior for pristine datasets. The industry squabbles over thetrue fallout, while researchers clamor for policies that keep data unsullied. The worry? AI behemoths might lock everyone else o..

Welcome to the jungle of customer support automation, fueled byAmazon BedrockandLangGraph. These tools juggle the circus act of ticket management, fraud sleuthing, and crafting responses that could even fool your mother. Integration with the likes ofJiramakes for a dynamic duo. Together, they tackle..

The Gemini Agent Network Protocol introduces powerful AI collaboration with four distinct roles. Leveraging Google’s Gemini models, agents communicate dynamically for improved problem-solving...

Amazon Alexa floundered amid brittle systems: a decentralized mess where teams rowed in opposing directions, clashing product and science cultures in tow...

Reinforcement-Learned Teachers (RLTs)ripped through LLM training bloat by swapping "solve everything from ground zero" with "lay it out in clear terms." Shockingly, a lean 7B model took down hefty beasts likeDeepSeek R1. These RLTs flipped the script, letting smaller models school the big kahunas wi..

3FSisn't quite matching its own hype. Yes, it boasts a flashy8 TB/s peak throughput, but pesky network bottlenecks throttle usage to roughly 73% of its theoretical greatness. Efficiency’s hiding somewhere, laughing. A dig intoGraySortshows storage sulking on the sidelines, perhaps tripped up by CRAQ..

FrontierLarge Reasoning Models (LRMs)crash into an accuracy wall when tackling overly intricate puzzles, even when their token budget seems bottomless.LRMsexhibit this weird scaling pattern: they fizzle out as puzzles get tougher, while, curiously, simpler models often nail the easy stuff with flair..