AI Weekly 23 Feb 2018

Hi! New AI Weekly is here! This week brought us couple very interesting papers from Baidu, Google and OpenAI, all of them are really worth reading! There are also cool videos to watch, especially the series published by Institute for Pure & Applied Mathematics provides lot of useful knowledge. That’s not all of course… just enjoy your weekend reading other AI news and don’t forget to share it with your friends 


10 BREAKTHROUGH TECHNOLOGIES 2018 – Dueling neural networks. Artificial embryos. AI in the cloud. MIT Technology Review prepared annual list of the 10 technology advances they think will shape the way we work and live now and for years to come.

A Dozen Times Artificial Intelligence Startled The World – The best uses of Generative Models and how they work.

Google’s new AI algorithm predicts heart disease by looking at your eyes – Scientists from Google and its health-tech subsidiary Verily have discovered a new way to assess a person’s risk of heart disease using machine learning. By analyzing scans of the back of a patient’s eye, the company’s software is able to accurately deduce data, including an individual’s age, blood pressure, and whether or not they smoke. This can then be used to predict their risk of suffering a major cardiac event — such as a heart attack — with roughly the same accuracy as current leading methods.


New Deep Learning Techniques (Lectures) – Institute for Pure & Applied Mathematics

2018 Isaac Asimov Memorial Debate: Artificial Intelligence – Isaac Asimov’s famous Three Laws of Robotics might be seen as early safeguards for our reliance on artificial intelligence, but as Alexa guides our homes and automated cars replace human drivers, are those Three Laws enough? Neil deGrasse Tyson, Frederick P. Rose Director of the Hayden Planetarium, hosts and moderates a lively discussion about how A.I. is opening doors to limitless possibilities, and if we’re ready for them. The 2018 Isaac Asimov Memorial Debate took place at the Museum on February, 13, 2018.

Visibility and Monitoring for Machine Learning Models – Josh Willis, an engineer at Slack, spoke at our January MeetUp about testing machine learning models in production.


Easily Build a Neural Net for Breast Cancer detection – a simple tutorial to train a neural network by reading data from a CSV


The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation – This paper forecasts how malicious actors could misuse AI technology, and potential ways we can prevent and mitigate these threats.

Assessing Cardiovascular Risk Factors with Computer Vision – Using deep learning algorithms trained on data from 284,335 patients, Google Researchers were able to predict CV risk factors from retinal images with surprisingly high accuracy for patients from two independent datasets of 12,026 and 999 patients.

A Closed-form Solution to Photorealistic Image Stylization – Photorealistic image style transfer algorithms aim at stylizing a content photo using the style of a reference photo with the constraint that the stylized photo should remains photorealistic. While several methods exist for this task, they tend to generate spatially inconsistent stylizations with noticeable artifacts. In addition, these methods are computationally expensive, requiring several minutes to stylize a VGA photo. In this paper, authors present a novel algorithm to address the limitations.

Neural Voice Cloning with a Few Samples – In this study, Baidu Research focus on two fundamental approaches for solving the problems with voice cloning: speaker adaptation and speaker encoding. Both techniques can be adapted to a multi-speaker generative speech model with speaker embeddings, without degrading its quality. In terms of naturalness of the speech and similarity to the original speaker, both demonstrate good performance, even with very few cloning audios.


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