Tech Xplore

New RoboReward dataset and models automate robotic training and evaluation

The advancement of artificial intelligence (AI) algorithms has opened new possibilities for the development of robots that ...
winbuzzer.com

Google Unveils TensorFlow 2.18 with Optimized Workflows for AI Model Development

Google has released TensorFlow 2.18, bringing significant enhancements including full support for NumPy 2.0 and a revised approach to CUDA through Hermetic builds. TensorFlow is an open-source machine ...
GitHub

Subclassing a model, writing a custom train_step, and distributed training in Tensorflow

Multi-GPU in Keras/Tensorflow: https://keras.io/examples/generative/wgan_gp/ I should point out that on my native machine, I'm logically splitting an RTX Ada A6000 ...
CNX Software

DeGirum ORCA M.2 and USB Edge AI accelerators support Tensorflow Lite and ONNX model formats

I’ve just come across an Atom-based Edge AI server offered with a range of AI accelerator modules namely the Hailo-8, Blaize P1600, Degirum ORCA, and MemryX MX3. I had never heard about the last two, ...
GitHub

How can I use the custom generator to train a TensorFlow model on SageMaker?

I am trying to train a TensorFlow custom classification model using a custom data generator on SageMaker Studio. However, the notebook did not utilize the GPU to train the model. My instance type: I ...
IEEE

TensorFlow to Cloud FPGAs: Tradeoffs for Accelerating Deep Neural Networks

Abstract: We present the first open-source TensorFlow to FPGA tool capable of running state-of-the-art DNNs. Running TensorFlow on the Amazon cloud FPGA instances, we provide competitive performance ...