AI Weekly 23 September 2018

Hi! New AI Weekly is here! Enjoy your weekend reading AI news and don’t forget to share it with your friends 😉

GENERAL

Machine-learning system tackles speech and object recognition, all at once – MIT computer scientists have developed a system that learns to identify objects within an image, based on a spoken description of the image. Given an image and an audio caption, the model will highlight in real-time the relevant regions of the image being described. http://news.mit.edu/machine-learning-image-object-recognition-0918

AI Company Accused of Using Humans to Fake Its AI – It’s a common fear that artificial intelligence could steal our jobs, but in the case of one of China’s leading voice recognition companies, it might be more of a case of humans taking work from AI. On Friday, iFlytek was hit with accusations that it hired humans to fake its simultaneous interpretation tools, which are supposedly powered by AI. https://www.sixthtone.com/news/1002956/ai-company-accused-of-using-humans-to-fake-its-ai-

This AI Predicts Obesity Prevalence—All the Way from Space – A research team at the University of Washington has trained an artificial intelligence system to spot obesity—all the way from space. The system used a convolutional neural network (CNN) to analyze 150,000 satellite images and look for correlations between the physical makeup of a neighborhood and the prevalence of obesity. https://singularityhub.com/2018/09/17/this-ai-predicts-obesity-prevalence-all-the-way-from-space/

Machine Learning Confronts the Elephant in the Room – A visual prank exposes an Achilles’ heel of computer vision systems: Unlike humans, they can’t do a double take. https://www.quantamagazine.org/machine-learning-confronts-the-elephant-in-the-room-20180920/

LEARNING

Efficient tuning of online systems using Bayesian optimization – Facebook relies on a large suite of backend systems to serve billions of people each day. Many of these systems have a large number of internal parameters. For example, the web servers that power Facebook use the HipHop Virtual Machine (HHVM) to serve requests, and HHVM has dozens of parameters that control the just-in-time compiler. As another example, machine learning systems are used for a variety of prediction tasks. These systems typically involve multiple layers of predictive models, with a large number of parameters for determining how the models are linked together to yield a final recommendation. Such parameters must be carefully tuned through the use of live, randomized experiments, otherwise known as A/B tests. Each of these experiments may take a week or longer, and so the challenge is to optimize a set of parameters with as few experiments as possible. https://research.fb.com/efficient-tuning-of-online-systems-using-bayesian-optimization/

The Trinity Of Errors In Financial Models: An Introductory Analysis Using TensorFlow Probability https://medium.com/tensorflow/the-trinity-of-errors-in-financial-models-an-introductory-analysis-using-tensorflow-probability-9fdefb4d283d?linkId=57092143

Introducing the Model Optimization Toolkit for TensorFlow – a suite of techniques that developers, both novice and advanced, can use to optimize machine learning models for deployment and execution. https://medium.com/tensorflow/introducing-the-model-optimization-toolkit-for-tensorflow-254aca1ba0a3?linkId=57036398

PROGRAMMING

A New TensorFlow Hub – a platform to publish, discover, and reuse parts of machine learning modules in TensorFlow. https://medium.com/tensorflow/a-new-tensorflow-hub-web-experience-c804496e99f3

PAPERS

Understanding Neural Arithmetic Logic Units – DeepMind recently released a new paper titled, Neural Arithmetic Logic Units (NALU). It’s an interesting paper that solves an important problem in Deep Learning, teaching neural networks to count. Surprisingly, although neural networks have been able to achieve state of the art results in many tasks such as categorizing lung cancer, they struggle with simpler tasks, like counting numbers. https://medium.com/tensorflow/understanding-neural-arithmetic-logic-units-11b0f85c1d1d?linkId=57139321

RESOURCES

A planetary-scale platform for Earth science data & analysis – Earth Engine’s public data archive includes more than forty years of historical imagery and scientific datasets, updated and expanded daily. https://developers.google.com/earth-engine/datasets/

A planetary-scale platform for Earth science data & analysis – Earth Engine’s public data archive includes more than forty years of historical imagery and scientific datasets, updated and expanded daily. https://developers.google.com/earth-engine/datasets/

2018-09-23T22:02:05+00:00

Hello World

Hi, this website is focused on Artificial Intelligence, hopefully you will find something interesting for you.

Recent Posts