Neuromorphic Chips and 'Brain‑Like' Computing: How Next‑Gen Chips May Change Phones, Robots, and IoT Devices

Explore how neuromorphic chips and brain-inspired computing bring low-power, efficient intelligence to edge AI, robotics, and ...

Prediction: This AI stock could deliver market-beating gains through 2030

One of the best-positioned artificial intelligence (AI) stocks for several years is undoubtedly Alphabet (NASDAQ: GOOGL) (NASDAQ: GOOG). The stock has had a strong year, but its momentum could just be ...
Hosted on MSN

Keras Vs Tensorflow — What’S The Difference And Which To Use?

In this video, we will understand what is Keras and Tensorflow. Tensorflow is a free and open-source library for machine learning and artificial intelligence. It was developed by Google. And it can be ...
GitHub

Converting PyTorch Models to TensorFlow/TFLite with Training Support for Edge Devices

I am currently working on a project that involves converting a trained PyTorch model to LiteRT and deploying to edge devices. I need the LiteRT model to have training capabilities (for all trainable ...
IEEE

Scaling TensorFlow, PyTorch, and MXNet using MVAPICH2 for High-Performance Deep Learning on Frontera

Abstract: Frontera is the largest NSF-funded cluster in the US and comprises of 8,008 nodes equipped with the latest Intel Xeon processors (Cascade-Lake). In this paper, we explore the potential of ...
marktechpost

Edge AI and It’s Advantages over Traditional AI

Edge artificial intelligence (Edge AI) involves implementing AI algorithms and models on local devices like sensors or IoT devices at the network’s periphery. This setup allows for immediate data ...
Geeky Gadgets

How to use PyTorch for Deep Learning applications – Beginners Guide

Deep learning is transforming the way we approach complex problems in various fields, from image recognition to natural language processing. Among the tools available to researchers and developers, ...