Nvidia stock plunges 3% as Meta considers ditching the chip giant's GPUs for Google's tensor processing units in data centers, while Google's new Gemini 3 AI model trained entirely on its own TPUs threatens Nvidia's 90% stranglehold on the AI chip market.
Elon Musk's xAI secures massive $15 billion funding round at $230 billion valuation, closing December 19th despite Musk previously denying such reports on X, as AI investment frenzy continues with rivals OpenAI and Anthropic also raising billions.
Major tech giants including OpenAI, Meta, and Google DeepMind are adopting Lean4, a mathematical proof verification programming language that eliminates AI hallucinations by requiring formal verification of every statement, with early results showing AI success rates jumping from 12% to 60% despite scalability challenges.
Luma AI secures $900 million in funding at a $4 billion valuation, with CEO Amit Jain claiming their Ray3 reasoning model outperforms OpenAI's Sora as the visual content generation startup plans to build a massive 2-gigawatt compute cluster and expand aggressively into India and emerging markets.
Google launches Gemini 3 AI model with record-breaking 1501 Elo score, featuring new Deep Think reasoning mode that achieves 45.1% on ARC-AGI-2 benchmarks and rolls out today across Google Search, Gemini app, and new Antigravity development platform.
ByteDance launches Depth Anything 3, a groundbreaking AI model that transforms any visual input into accurate 3D geometry using a single transformer backbone, dramatically outperforming previous models across depth estimation and 3D generation tasks while offering open-source access with multiple variants and interactive tools.
AI experts remain divided on whether large language models demonstrate genuine intelligence or merely sophisticated pattern recognition, as these systems successfully tackle complex problems like Math Olympiad questions while working with word-embedded knowledge, though multimodal AI models face greater skepticism due to their pixel-based processing methods.
Researchers discover that AI models dramatically switch between accurate and false responses based solely on how questions are phrased, with 'think step by step' prompts triggering correct factual recall while 'give answer in one word' instructions activate shallow processing circuits that frequently generate hallucinated information.
Baidu launches M100 and M300 AI chips set to debut in 2026 and 2027 respectively, directly challenging Nvidia's market dominance as China pushes for technological independence with domestic processors promising over 50% performance improvements.
Groundbreaking research reveals that AI language models wastefully activate their entire networks for social reasoning tasks while actually using only a tiny specialized subset of parameters, creating massive inefficiency compared to human brains and pointing toward revolutionary energy-saving AI designs.