AI Models Push Memory Limits, Language Models Get Smarter at Citations, and Thai AI Catches Up to Global Standards

Today's tech breakthroughs showcase how AI is becoming both more powerful and more accessible, with new innovations allowing models to process massive amounts of text and generate more reliable citations. In a significant development for global AI equity, researchers demonstrate how smaller languages can achieve sophisticated AI capabilities with limited resources, potentially democratizing advanced AI technology beyond English-speaking regions. Links to all the papers we discussed: InfiniteHiP: Extending Language Model Context Up to 3 Million Tokens on a Single GPU, Skrr: Skip and Re-use Text Encoder Layers for Memory Efficient Text-to-Image Generation, SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models, Can this Model Also Recognize Dogs? Zero-Shot Model Search from Weights, An Open Recipe: Adapting Language-Specific LLMs to a Reasoning Model in One Day via Model Merging, EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents

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