xAI Workers Revolt: The Controversial “Skippy” Project That Asked Employees to Give Grok a Face
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Smarter Prompts, Smarter AI: Claude’s Guide to Getting It Right the First Time
In an era where artificial intelligence has become integral to daily workflows, the art of effective prompting has emerged as ...
Meta Snubs the EU’s AI Guidelines: A Tech Giant’s Stand Against European Regulation
The Standoff Begins Meta has drawn a line in the sand. The social media giant has refused to sign the ...
Fake Obama Arrest Video Shared by Trump Sparks Outrage and Legal Debate
President Posts Deepfake Arrest Video Amid Intelligence Community Accusations President Donald Trump ignited a political controversy Sunday night when he ...
Qwen3-235B-A22B-Instruct-2507 Review: How Alibaba’s Latest LLM Achieves 95% on ZebraLogic and Supports 119 Languages
TLDR Qwen3-235B-A22B-Instruct-2507 represents a groundbreaking advance in large language model technology. With 235 billion parameters, a powerful Mixture of Experts ...
China Dives Deep: The Revolutionary Underwater Data Centers Powering AI’s Future
China is making waves in the tech world. The country has launched an ambitious underwater data center project that could ...
NVIDIA Expands CUDA to RISC-V: A Game-Changing Move for AI Computing
The tech world just witnessed a seismic shift. NVIDIA announced that its powerful CUDA platform will now support RISC-V processors. ...
Solar Pro 2 vs Kimi K2 vs DeepSeek R1: The Ultimate 2025 Open-Source LLM Comparison Guide
TLDR This article presents an exhaustive comparative analysis of three cutting-edge open-source large language models (LLMs) that have shaped the ...
Solar Pro 2: Redefining Efficiency, Performance, and Versatility in Open-Source LLMs
In a landscape where large language models (LLMs) continually push the boundaries of artificial intelligence, the recent release of Solar ...
Scaling Laws for Optimal Data Mixtures – Paper Summary
TL;DR “Scaling Laws for Optimal Data Mixtures” proposes a breakthrough framework that replaces costly trial-and-error data selection with principled scaling ...
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