Researchers said Norman's dark responses illustrate the harsh reality of machine learning.

Big data and its component, AI, are taking many industries by storm. The benefits of big data are far too significant for virtually any industry to ignore.

In a'national strategy for artificial intelligence', prepared to give the country an edge in this area, Niti Aayog suggested ways to promote adoption of …

In order to drive awareness of the benefits and understand the challenges of AI (such as on ethics[1] and legal issues), IMDA is engaging key stakeholders including government, industry, consumers and academia to collaboratively shape the Government's plans for the AI ecosystem. Such discourse will inform the Government's ongoing plans to support Singapore as a hub for AI development and innovation, and help Singapore to effectively respond to global developments. These initiatives complement IMDA's current suite of business and talent programmes to develop a vibrant AI ecosystem and position Singapore as a leading hub for AI. An Advisory Council on the Ethical Use of AI and Data will be appointed by the Minister for Communications and Information to advise and work with IMDA in the areas of responsible development and deployment of AI. The Advisory Council will assist the Government to develop ethics standards and reference governance frameworks and publish advisory guidelines, practical guidance, and/or codes of practice for the voluntary adoption by the industry.

If you already understand the underlying system, then machine learning maybe not be the best approach. You would do better using the physical equations for the system, and then only use parameter estimation in cases where you don't know one or more of the parameters. A physical model will be far more general than an ML model. The ML model will likely overfit to the cases you give it, and even if you manage to fix that, it will fail when it sees something qualitatively new. The physical equations will generalize to any scenario no matter what it looks like, so long as the assumptions are resonably respected.

The strange, creepy world of "deepfakes," videos (often explicit) with the faces of the subjects replaced by those of celebrities, set off alarm bells just about everywhere early this year. And in case you thought that sort of thing had gone away because people found it unethical or unconvincing, the practice is back with the highly convincing "Deep Video Portraits," which refines and improves the technique. To be clear, I don't want to conflate this interesting research with the loathsome practice of putting celebrity faces on adult film star bodies. But this application of technology is clearly here to stay and it's only going to get better -- so we had best keep pace with it so we don't get taken by surprise. Deep Video Portraits is the title of a paper submitted for consideration this August at SIGGRAPH; it describes an improved technique for reproducing the motions, facial expressions, and speech movements of one person using the face of another.

We can't stop Nature when it unleashes its fury in the form of volcanoes, earthquakes, storms and avalanches, but we can use technology to warn us of imminent danger - and save lives. As the sun sets over Lake Victoria, Africa's largest lake, tens of thousands of fishermen ready themselves to head out on the water for the night, fishing mostly for tilapia and Nile perch. As they push off, they know they are risking their lives - some of them may never be seen again. Lake Victoria - a lake so big it straddles Uganda, Tanzania and Kenya - is notorious for its deadly storms. At this time of year, strong winds, rain, lightning and huge waves are a regular occurrence.

O'Reilly and Microsoft are excited bring you a new e-book on AI, titled A Developer's Guide to Building AI Applications. This book, which is clearly developer-focused, walks you through the process of building intelligent cloud-based bots, and makes relevant code samples available from GitHub. As you know, AI is accelerating the digital transformation of every industry on the planet. It is our goal to allow developers and organizations of all stripes to be able to use AI successfully to augment human ingenuity and create the next generation of intelligent apps. Through this new e-book, Anand Raman and Wee Hyong Tok of Microsoft provide a comprehensive roadmap for developers to build their first AI-infused application.

While great progress has been made recently in automatic image manipulation, it has been limited to object centric images like faces or structured scene datasets. In this work, we take a step towards general scene-level image editing by developing an automatic interaction-free object removal model. Our model learns to find and remove objects from general scene images using image-level labels and unpaired data in a generative adversarial network (GAN) framework. We achieve this with two key contributions: a two-stage editor architecture consisting of a mask generator and image in-painter that cooperate to remove objects, and a novel GAN based prior for the mask generator that allows us to flexibly incorporate knowledge about object shapes. We experimentally show on two datasets that our method effectively removes a wide variety of objects using weak supervision only.