Kaldi, an open-source speech recognition toolkit, has been updated with integration with the open-source TensorFlow deep learning library. Developers Yishay Carmiel and Hainan Xu of Seattle-based ...

In the realm of machine learning frameworks, there’s no one-size-fits-all solution. PyTorch and TensorFlow offer distinct advantages that cater to different aspects of the machine learning workflow.

And TensorFlow underpins the applied machine learning APIs for Google Cloud Natural Language, Speech, Translate, and Vision. Data flow graphs are directed acyclic graphs that describe a ...

In the spirit of open-source code, Google hopes that access and use by researchers, engineers and even hobbyists will result in even better machine learning capabilities in the future.

TensorFlow is a Python-friendly open source library for developing machine learning applications and neural networks. Here's what you need to know about TensorFlow.

Machine learning (ML), the most common form that AI takes today, relies on huge masses of data to train models. So an ML-enabled file system seems like a no-brainer. Here's the first one.

Google uses TensorFlow to train its neural networks faster and improve products, but is looking for a developer boost. By open-sourcing TensorFlow, Google is looking to make its machine learning ...

TensorFlow also divorces Google's machine learning workflow from its monolithic company codebase, meaning that it's now possible for outsiders to meaningfully contribute to the project.

This enables more reliable performance in any environment. TensorFlow lite drives home the point that Google cares about the nexus of AI and mobile devices.

According to the TensorFlow site, Google open sourced the project to help standardize machine learning systems. “Research in this area is global and growing fast, but lacks standard tools ...