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General Purpose Reinforcement Learning, Speech Tech Gets More Human, and Mobile Devices LLMs
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Today's tech landscape sees major breakthroughs as researchers unveil new AI models that can process unprecedented amounts of text while making speech generation more natural than ever. As these advances reshape how machines understand and communicate with humans, a parallel revolution in mobile computing shows how complex AI systems are being streamlined for the devices in our pockets, potentially transforming how we interact with technology in our daily lives. Links to all the papers we discussed: Baichuan-Omni-1.5 Technical Report, Qwen2.5-1M Technical Report, Towards General-Purpose Model-Free Reinforcement Learning, ARWKV: Pretrain is not what we need, an RNN-Attention-Based Language Model Born from Transformer, Emilia: A Large-Scale, Extensive, Multilingual, and Diverse Dataset for Speech Generation, iFormer: Integrating ConvNet and Transformer for Mobile Application
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