Microsoft

LLM can Read Spectrogram: Encoder-free Speech-Language Modeling

Recent speech-aware large language models (Speech-LLMs) rely on a pre-trained speech encoder to convert audio into semantic-rich representations consumable by LLM. In this work, instead, we explore: ...
AOL

Tensordyne Claims Massive Speed and Power Improvement Over Nvidia

If simulations are to be believed, startup Tensordyne's new AI chip could crush the performance of market leader Nvidia in terms of energy efficiency and latency for inferencing. The company just sent ...
IEEE

Temporal Convolutional and Fusional Transformer Model With Bi-LSTM Encoder-Decoder for Multi-Time-Window Remaining Useful Life Prediction

Abstract: Health prediction is crucial for ensuring reliability, minimizing downtime, and optimizing maintenance in industrial systems. Remaining Useful Life (RUL) prediction is a key component of ...
GitHub

VapourSynth filter for exemplar-based video colorization using CMNET2.

Colorizes black-and-white clips by propagating color from reference frames using the CMNET2 deep learning model with a sliding permanent-memory window.
Hacker

Evaluating RAG Systems: Why Answer Quality Is Not Enough

I'm a Senior Applied Scientist at Amazon with over 10 years of experience building production-scale ML/AI systems. A RAG system is not just an LLM with extra context. It is a retrieval, ranking, ...
IEEE

DMFNet: Spatio-Temporal Multi-Scale Fusion with Dual Encoder-Decoder for Optical Remote Sensing Image Change Detection

Abstract: Convolutional neural networks (CNNs) have achieved significant success in optical remote sensing image change detection (CD). However, they still face two major challenges that limit the ...