A new benchmark suite for machine learning
MLPerf is a new set of benchmarks compiled by a growing list of industry and academic contributors.
Artificial Intelligence
The latest insights, ideas, and tools for building solutions that rely on machine intelligence.
Machine learning: A quick and simple definition
Get a basic overview of machine learning and then go deeper with recommended resources.
Complementary learning for AI-based predictive quality and maintenance
Using machine learning, deep learning, and cognitive computing in concert can help enterprises gain competitive edges.
Using machine learning in workload automation
Abhijit Deshpande explains how to use machine learning to identify root causes of problems in minutes instead of hours.
WTT: What the tensor?
Ron Bodkin explains what a tensor is and why you should care.
Rapid AI experimentation and innovation on Amazon Web Services
Dan Mbanga explores how accelerating AI experimentation has influenced innovations such as Amazon Alexa, Prime Air, and Go.
Bringing AI into the wild
Mary Beth Ainsworth offers an overview of SAS deep learning and computer vision capabilities that help map wildlife and scale conservation efforts around the world.
Using machine learning, the IoT, drones, and networking to reduce world hunger
Food production needs to double by 2050 to feed the world’s growing population. Jennifer Marsman details a solution that uses sensors in the soil, aerial imagery from drones, and machine learning.
Building tools for the AI applications of tomorrow
We’re currently laying the foundation for future generations of AI applications, but we aren’t there yet.
Toward the Jet Age of machine learning
Solving the challenges of efficiency, automation, and safety will require cooperation between researchers and engineers spanning both academia and industry.
Thinking beyond bots: How AI can drive social impact
A few ways to think differently and integrate innovation and AI into your company's altruistic pursuits.
Simon Moss on using artificial intelligence to fight financial crimes
Innovations that increase detection of, and response to, criminal attacks of financial systems.
Getting the most from the AI Business Summit
The AI Conference in NY will feature tutorials, conference sessions, and executive briefings to help business leaders understand and plan for AI technologies.
What happens when AI experts from Silicon Valley and China meet
Why we're taking the AI Conference to Beijing.
How to jump start your deep learning skills using Apache MXNet
The top 5 ways to immerse yourself in deep learning and MXNet.
Atif Kureishy on how enterprises are investing in AI
Leveraging the potential of AI to gain maximum ROI.
Digging into the complexity of the data labeling challenge
A look at the parallels between human and machine knowledge acquisition.
Deep learning in the enterprise
Opportunities and challenges companies will face integrating and implementing deep learning frameworks.
Build a recurrent neural network using Apache MXNet
A step-by-step tutorial to develop an RNN that predicts the probability of a word or character given the previous word or character.
Build generative models using Apache MXNet
A step-by-step tutorial to build generative models through generative adversarial networks (GANs) to generate a new image from existing images.
Building deep learning neural networks using TensorFlow layers
A step-by-step tutorial on how to use TensorFlow to build a multi-layered convolutional network.
How neural networks learn distributed representations
Deep learning’s effectiveness is often attributed to the ability of neural networks to learn rich representations of data.
Introducing capsule networks
How CapsNets can overcome some shortcomings of CNNs, including requiring less training data, preserving image details, and handling ambiguity.
Logo detection using Apache MXNet
Image recognition and machine learning for mar tech and ad tech.