Ben Khalesi writes about where artificial intelligence, consumer tech, and everyday technology intersect for Android Police. With a background in AI and Data Science, he’s great at turning geek speak ...

TensorFlow has become the most popular tool and framework for machine learning in a short span of time. It enjoys tremendous popularity among ML engineers and developers. According to the Hacker News ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More At Google’s inaugural TensorFlow Dev Summit in Mountain View, California, ...

Deep learning is changing our lives in small and large ways every day. Whether it’s Siri or Alexa following our voice commands, the real-time translation apps on our phones, or the computer vision ...

A subcategory of machine learning, deep learning uses multi-layered neural networks to automate historically difficult machine tasks—such as image recognition, natural language processing (NLP), and ...

In the dynamic world of machine learning, two heavyweight frameworks often dominate the conversation: PyTorch and TensorFlow. These frameworks are more than just a means to create sophisticated ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Soroosh Khodami discusses why we aren't ready ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Google’s DeepMind artificial intelligence (AI) research group today ...

As more and more new late 2020 MacBook Airs and MacBook Pros land in users' hands, don't be surprised to see the pile-up of news and reports about their impressive performance. That has always been ...

Overview NumPy and Pandas form the core of data science workflows. Matplotlib and Seaborn allow users to turn raw data into ...

CDNN2 enables localized, deep learning-based video analytics on camera devices in real time. This significantly reduces data bandwidth and storage compared to running such analytics in the cloud, ...