How YouTube's Recommendation Algorithm Works

by Alex Giamas on  Sep 23, 2016

In a recent paper published by Google, YouTube engineers analyzed in greater detail the inner workings of YouTube’s recommendation algorithm. The paper was presented on the 10th ACM Conference on Recommender Systems last week in Boston. In this news item we analyze how YouTube uses deep learning to operate one of the largest and most complex recommendation systems in industry.

IBM Creates Artificial Neurons from Phase Change Memory for Cognitive Computing

by Srini Penchikala on  Sep 13, 2016

A team of scientists at IBM Research in Zurich, have created an artificial version of neurons using phase-change materials to store and process data. These phase change based artificial neurons can be used to detect patterns and discover correlations in Big Data (real-time streams of event based data) and unsupervised machine learning at high speeds using very little energy.

TensorFlow Learns Cucumber Selection and Classification

by Dylan Raithel on  Sep 08, 2016

Cucumber farmer with embedded systems engineering background teaches TensorFlow neural network to mimic his cucumber-farming family’s classification and selection skills for automation.

DeepMind AI Program Increases Google Data Center Cooling Power Usage Efficiency by 40%

by Dylan Raithel on  Jul 28, 2016

DeepMind Sensor data captured from Google data centers yield a 40% increase in data center power usage efficiency and an overall site-wide 15% power usage efficiency gain using an AI program similar to an earlier game-like program of theirs that had learned how to play Atari games.

Facebook Open-Sources Deep Learning Project Torchnet

by Dylan Raithel on  Jul 27, 2016 1

Facebook Artificial Intelligence Research laboratory open-sources the Torchnet project to package and optimize boiler plate deep learning code for reuse and plugin-ability.

Google Details New TensorFlow Optimized ASIC

by Dylan Raithel on  May 23, 2016

The machine learning and engineering communities weigh in on news of Google's new TensorFlow optimized processor, the TPU and possibly influence several industry leaders in the hardware space like Intel and Nvidia.

Open Sourcing Artificial Intelligence Research

by Jonathan Allen on  Apr 27, 2016

Today OpenAI, a non-profit artificial intelligence research company founded by InfoSys and Amazon Web Services, announced a beta for OpenAI Gym. Gym is a Python based toolkit for developing and comparing reinforcement learning (RL) algorithms offered under the MIT license.

Collision: Online Harassment and Machine Learning

by David Iffland on  Apr 27, 2016

Online harassment is a serious issue, one that the engineers and designers behind the keyboard don't always think about when building software. Machine learning is become more prevalent but as more technology companies take advantage of it, they risk alienating their users even more by presenting content that isn't actually relevant.

Google Cloud Machine Learning and Tensor Flow Alpha Release

by Dylan Raithel on  Apr 18, 2016

Late last month Google released an alpha version of their TensorFlow (TF) integrated cloud machine learning service as a response to a growing need to make their Tensor Flow library to run at scale on the Google Cloud Platform (GCP). Google describes several new feature sets around making TF usage scale by integrating several pieces of the GCP like Dataproc, a managed Hadoop and Spark service.

Databricks Integrates Spark and TensorFlow for Deep Learning

by Dylan Raithel on  Mar 12, 2016

Since announcements late last year about Google open-sourcing TensorFlow, the company’s open-source library for machine learning, and previous coverage at InfoQ, the data-science community has had an opportunity to try out TensorFlow for their own projects.

Microsoft Azure IoT Hub Reaches General Availability

by Kent Weare on  Feb 14, 2016

Microsoft has recently announced its Azure IoT Hub offering has reached general availability (GA). This is a follow-up release to the public preview that Microsoft provided in October of last year. InfoQ previously covered the public preview announcement as part of the Azure Con event coverage.

How Airbnb Uses Net Promoter Score to Predict Guest Rebooking

by Srini Penchikala on  Feb 02, 2016 1

Net Promoter Score (NPS) is a customer loyalty metric used to determine the likelihood that a customer will return to a company's website or use their service again. Airbnb uses NPS extensively in measuring the customer loyalty, as a more effective measurement to determine the likelihood that a customer will return to book again or recommend the company to their friends.

Riley Newman on How Airbnb Uses Data Science

by Jérôme Serrano on  Jan 10, 2016

Riley Newman, head of data science at Airbnb, recently published an article describing how the Californian startup defines and uses data science. He explains that data can be seen as the voice of the customers, and data science as an act of interpretation. He also details several initiatives that have been particularly important for scaling data science.

Facebook Open Sourcing AI Hardware Design

by Alex Giamas on  Dec 21, 2015

Facebook recently announced open sourcing hardware design for its custom designed Open Rack compatible hardware. Attributing advances in Machine Learning and Artificial Intelligence to richer data sets and more powerful GPU-based systems, Facebook is unveiling its next generation systems code-named “Big Sur”, after the synonymous location in California.

DMTK, a Machine Learning Toolkit from Microsoft

by Abel Avram on  Nov 13, 2015

About the same time Google announced open sourcing TensorFlow, Microsoft has pushed to GitHub DMTK, a Distributed Machine Learning Toolkit. While Google has released a one-machine version of TensorFlow, DMTK runs on a cluster of machines.

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