Roundup 10/19/2016

Machine learning (ML) and deep learning (DL) content from the past 24 hours. Filtered by hand, culled of hype, lightly seasoned with snark.


— Daniel Gutierrez interviews Jim McHgh of NVIDIA’s Deep Learning Group, who says he wants to collaborate with Databricks to integrate the BIDMach machine learning library with Spark.

— At its annual Symposium, Gartner says that CIOs are set to lead the development of a new “civilization architecture” based on AI and machine learning. Uh-huh. There’s enough hot air in that room to melt the polar icecaps.

— Meanwhile, Gartner announces the top ten strategic technology trends for 2017, and machine learning is right up there at #1 on the list.

— Ginny Rometty, who has presided over a 20% decline in revenue, earnings and market value at IBM, gets her ghostwriter to voice some platitudes about AI.


— Serdar Yegualp describes Microsoft’s big bet on FPGAs, explains the potential of FPGAs for machine learning, notes that existing machine learning software generally does not support FPGA acceleration.

— Meanwhile, however, Baidu announces that it will accelerate its machine learning applications with Xilinx FPGAs.

— Xilinx is on a roll. TeraDeep announces a fast deep learning solution that leverages Xilinx FPGAs.

— Aaron Tilley speculates that Apple plans to use a mysterious FPGA chip in the Apple iPhone 7 for AI.

Methods and Techniques

— Scott Zoldi, FICO’s Chief Analytics Officer offers some advice on keeping predictive models current.

— Patrick Gray offers a rubric to determine whether your business needs AI.


— In The Stack, Martin Anderson describes CNNdroid, an open source library that runs GPU-accelerated convolutional neural networks on Android devices.

— Microsoft releases two R packages for data scientists. Separately, MSFT releases LightGBM, a fast Gradient Boosting Machine, to GitHub.

— Fujitsu announces the development of a technology to monitor traffic conditions with image processing and machine learning.

— Trend Micro launches new security software with embedded machine learning.

Autonomous Vehicles

— In MIT Technology Review, Carol Reiley explains how deep learning powers the self-driving car.

— Kunal Khullar maps the timeline for the Apple Car.

— In TechRepublic, Hope Reese describes what Ford is doing with big data.


— In HBR, Oren Danieli explain how to hire people with algorithms. They don’t talk about firing people, but you can bet that someone is using algorithms for that as well.

— Healogics and NLPLogix partner to develop machine learning applications to help clinicians treat wounds.


— Viscovery, a deep learning and AI platform, lands $10 million in funding.

— Adtech leader Varick Media Management announces an update to its campaign management platform, with two new ML-driven services to optimize bids and placement.

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