4 biggest voices who helped shape artificial intelligence technology

There is a version of the artificial intelligence story that some may say began with ChatGPT, or perhaps with the smartphone, ...
The Brown Daily Herald

With new technology, paralyzed patients can communicate by thinking about typing

For people experiencing paralysis, communication often means spelling out words one letter at a time by using their eyes to ...

Deep learning reveals how auditory cortex neurons split up natural sound coding

Over the past decades, computer scientists have introduced numerous artificial intelligence (AI) systems designed to emulate the organization and functioning of networks of neurons in the brain.

We analyzed Philly street scenes and identified signs of gentrification using machine learning trained on longtime residents’ observations

Researchers are using machine learning models to identify gentrification in imagery. Community insights help keep the models ...
AI Business

Cohere Unveils Open Source Speech Model for Edge Devices

Cohere launched an open source speech recognition model, Transcribe, that's small enough to be deployed at the edge.
Times Union

Arrow Bank buying Utica bank with deep Adirondack ties

GLENS FALLS — The parent company of Arrow Bank in Glens Falls announced on Thursday that it is acquiring Utica-based Adirondack Bank in an $89.1 million deal. Adirondack Bank dates back to 1898, when ...
marktechpost

How to Design Complex Deep Learning Tensor Pipelines Using Einops with Vision, Attention, and Multimodal Examples

In this tutorial, we walk through advanced usage of Einops to express complex tensor transformations in a clear, readable, and mathematically precise way. We demonstrate how rearrange, reduce, repeat, ...
IEEE

Enhancing Cybersecurity with Deep Learning: A Comparative Study of CNN and RNN for IDS

Abstract: The design and development of intrusion detection systems (IDS) are also widely used to implement deep learning approaches in the field of cybersecurity. Deep-learning techniques are ...
GitHub

RNN-DAS: A New Deep Learning Approach for Detection and Real-Time Monitoring of Volcano-Tectonic Events Using Distributed Acoustic Sensing

RNN-DAS is an innovative Deep Learning model based on Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) cells, developed for real-time Volcano-seismic Signal Recognition (VSR) using ...
digitalmarketreports

Minkang Zhang Improves Medical Image Recognition Through RNN Optimization and Deep Learning Integration

The exponential increase in medical imaging data has intensified the need for accurate and efficient diagnostic analysis. Conventional methods often fail to process large volumes of dynamic images ...