Everybody wants a slice of the fresh AI pie, and Asus is offering regular folks the chance to run their own AIs locally.
Quantization plays a crucial role in deploying Large Language Models (LLMs) in resource-constrained environments. However, the presence of outlier features significantly hinders low-bit quantization.
Abstract: While generative large language models exhibit robust capabilities in multi-task scenarios, they struggle with fine-grained semantic understanding tasks, particularly for languages lacking ...
Explore how neuromorphic chips and brain-inspired computing bring low-power, efficient intelligence to edge AI, robotics, and ...
Abstract: Large pre-trained models (LPMs) provide essential technical support for downstream Artificial Intelligence (AI) tasks spawning under the intelligent evolution of wireless networks. Using ...
As AI automates the work that once trained junior lawyers, firms must rethink how capability is built. New simulation-led and AI-enabled training models may offer a better path forward. For decades, ...
The quality of the latent space in visual tokenizers (e.g., VAEs) is crucial for modern generative models. However, the standard reconstruction-based training paradigm produces a latent space that is ...
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