Abstract: Real-world data streams, such as news articles and social media posts, are dynamic and nonstationary, creating challenges for real-time structured representation via knowledge graphs, where ...

Among other things, launching AIModels.fyi ... Find the right AI model for your project - https://aimodels.fyi ...

Deploying ultra-large models on-premise has historically required massive GPU clusters, high-speed interconnects like NVLink/NVSwitch, and intensive cooling systems — resulting in prohibitive cost and ...

For years, the way large language models handle inference has been stuck inside a box — literally. The high-bandwidth RDMA networks that make modern LLM serving work have confined both prefill and ...

The butterfly bypass from the RotorQuant paper: TurboQuant applies a d×d Walsh-Hadamard Transform (butterfly network with log₂(d) stages across all 128 dimensions). PlanarQuant/IsoQuant apply ...

A large language model that is trained using AI outputs can inherit undesirable behaviours, even if they are not directly referenced in the training data. Work this year has shown that AI models that ...

Abstract: Conventional semantic communication systems require training task-specific semantic encoders on each user device and corresponding decoders on the server for every client, resulting in ...