Posted by James Wexler, Software Engineer, Google AI Building effective machine learning (ML) systems means asking a lot of questions. It'...
Explore the layers of a neural network with your camera.
Das RL-Framework mit dem Namen Dopamine baut auf TensorFlow auf und soll gut reproduzierbare Ergebnisse liefern.
You might have come across Judea Pearl's new book, and a related interview which was widely shared in my social bubble. In the interview, Pearl dismisses most of what we do in ML as curve fitting. Whi
As advanced machine learning algorithms are gaining acceptance across many organizations and domains, machine learning interpretability is growing in importance to help extract insight and clarity.
A hands-on example for learning the foundations of a powerful optimization framework
The importance of testing your tools, using multiple tools, and seeking consistency across various interpretability techniques.
The world’s easiest introduction to Machine Learning
Dramatic success in machine learning has led to a torrent of Artificial Intelligence (AI) applications. Continued advances promise to produce autonomous systems that will perceive, learn, decide, and
Last summer, the Defense Science Board’s report on autonomy found that investing in artificial intelligence (AI) warfare is a crucial part…
Neural Architecture Search (NAS) is an algorithm that searches for the most optimal neural network to perform a particular task on a given dataset.
The best investment you can make in your own learning is returning back to to the things you (think) you already know, and this is…
Hybrid search is a new way to use IBM Watson Assistant without some of the limitations of a traditional chatbot. This approach lets you have best of both worlds: a robust search engine, which is coupl
MLPerf is a new set of benchmarks compiled by a growing list of industry and academic contributors.
Numenta.org • Home of the HTM Community
Hierarchical temporal memory (HTM) method for unsupervised learning provides a tool which brings different strengths to the table compared to RNNs & CNNs
Keyword Extraction. Language Detection. Term Disambiguation. Semantic Comparison of Text. Semantic Filtering of tweets.
Zoubin Ghahramani discusses recent advances in artificial intelligence, highlighting research in deep learning, probabilistic programming, Bayesian optimization, and AI for data science.
Program synthesis — automatically generating a program that satisfies a given specification — is a major challenge in AI. In addition to changing the way we design software, it has the potential to re
Baidu has announced the release of ApolloScope, billed as the world's largest open source self-driving dataset. Get all the details of the release here.
IBM today announced a new Deep Learning as a Service product for AI developers from its inaugural Think conference.
This post is authored by Ilia Karmanov, Mathew Salvaris, Miguel Fierro, Danielle Dean, all Data Scientists at Microsoft.
If you’re trying to create value by using Machine Learning, you need to be using the best hardware for the task. With CPUs, GPUs, ASICs, and TPUs, things can get kind of confusing. Let's walk through
Posted by Liang-Chieh Chen and Yukun Zhu, Software Engineers, Google Research Semantic image segmentation, the task of assigning a semanti...
This AI hasn't failed — it's simply discovered 1,000 ways not to succeed.
We're working to make AI accessible by providing lessons, tutorials and hands-on exercises for people at all experience levels. Filter the resources below to start learning, building and problem-solving.
Mit künstlicher Intelligenz können Kunden des US-Startups B12 Websites erstellen. Jetzt ist die dahinterstehende Software Open Source – und könnte künftig automatisch Teams zusammenstellen.
Much research in AI lately focuses on extending the capabilities of deep learning architectures: moving beyond simple classification and pattern recognition into the realm of learning algorithmic task
Take a dive into the algorithms used in machine learning. Learn about supervised, unsupervised, and reinforcement learning, as well as the models that make them work.
TensorFlow is just one of the many open source software libraries for machine learning. In this tutorial, get an overview of TensorFlow, learn which platforms support it, and look at installation cons
Mit Tensorflow Lite veröffentlicht Google eine extrem kleine Variante seiner Machine-Learning-Bibliothek, die speziell für Mobil- und Embedded-Geräte gedacht ist.
Posted by Christopher Olah, Research Scientist, Google Brain Team and Alex Mordvintsev, Research Scientist, Google Research Have you eve...
It has the potential to revolutionize how machines "see."
AutoML automates the design of machine learning models. "Learning Transferable Architectures for Scalable Image Recognition", applies AutoML to the image classification and object detection,