Category: LLM
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Kimi K2 Thinking: China’s New Contender in the LLM Reasoning Race
Moonshot AI’s Kimi K Thinking: reasoning-focused open MoE boosting China’s AI momentum with efficient, deployable, multipolar rivalry
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Bridging Context Engineering in AI with Requirements Engineering
How AI-driven context engineering can transform requirements: dynamic, multimodal scenario generation and proactive need inference.
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Transformers Are Injective: Why Your LLM Could Remember Everything (But Doesn’t)
Transformers may be injective and invertible: hidden activations can reconstruct inputs—big gains for interpretability, major privacy risks.
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LLM-Guided Image Editing: Embracing Mistakes for Smarter Photo Edits
Apple’s MGIE uses LLM-guided text editing that learns from imperfect edits, making photo retouching conversational, faster and more creative.
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The Neural Junk-Food Hypothesis
LLM ‘brain rot’: training on junk short, high-engagement posts erodes reasoning, safety, and behavior—data quality wins.