Abstract: Long-term electrocardiogram (ECG) signal monitoring necessitates a large amount of memory space for storage, which affects the transmission channel efficiency during real-time data transfer.

Multi-agent systems, designed to handle long-horizon tasks like software engineering or cybersecurity triaging, can generate up to 15 times the token volume of standard chats — threatening their ...

TensorFlow Compression (TFC) contains data compression tools for TensorFlow. You can use this library to build your own ML models with end-to-end optimized data compression built in. It's useful to ...

Glioblastoma, the deadliest primary brain tumor in adults, exerts physical forces on surrounding brain tissue, leading to neuronal damage. In the present study, by applying multiple model systems, we ...

ESET researchers provide details on a previously undisclosed China-aligned APT group that we track as PlushDaemon and one of its cyberespionage operations: the supply-chain compromise in 2023 of VPN ...

As sequencing becomes more accessible, there is an acute need for novel compression methods to efficiently store sequencing files. Omics analytics can leverage sequencing technologies to enhance ...

HANDS ON If you hop on Hugging Face and start browsing through large language models, you'll quickly notice a trend: Most have been trained at 16-bit floating point of Brain-float precision. FP16 and ...

In this work, we propose a novel view that treats inducing temporal action abstractions as a sequence compression problem. To do so, we bring a subtle but critical component of LLM training pipelines ...

In this article on Mamba, we’ll explore how this innovative state-space model (SSM) revolutionizes sequence modeling. Developed by Albert Gu and Tri Dao, Mamba is distinguished for its efficiency in ...