Picture: military interrogators are talking to a local man they suspect of helping to emplace roadside bombs. The man denies it, even as they show him photos of his purported accomplices. But an antenna in the interrogation room is detecting the man's heartbeat as he looks at the pictures. A UK research team is using radio waves to pick up subtle changes in heart rhythm and then, using an advanced AI called a neural network, understand what those signals mean -- in other words, what the subject is feeling. It's a breakthrough that one day might help, say, human-intelligence analysts in Afghanistan figure out who represents an insider threat.

It is also doing the function of making people aware of the potential that artificial intelligence and machine learning hold.

AI-enabled synthetic media is being used as a tool for manipulating real emotions and capturing user data by genealogy service MyHeritage, which has just launched a new feature -- called "deep nostalgia" -- that lets users upload a photo of a person (or several people) to see individual faces animated by algorithm. The Black Mirror-style pull of seeing long-lost relatives -- or famous people from another era -- brought to a synthetic approximation of life, eyes swivelling, faces tilting as if they're wondering why they're stuck inside this useless digital photo frame, has led to an inexorable stream of social shares since it was unveiled yesterday at a family history conference… This is my great-grandmother, Kathleen. I've always felt so close to her even though she died when I was 2 years old. This #DeepNostalgia video brought tears to my eyes to see her move, almost like seeing her as she was posing for this photo. MyHeritage's AI-powered viral marketing playbook with this deepfakery isn't a complicated one: They're going straight for tugging on your heart strings to grab data that can be used to drive sign-ups for their other (paid) services.

A new plan by Amazon to use artificial intelligence (AI) to dub films could spell the end for voiceover actors. The technology giant has patented a system that would see computers learn the voices of Hollywood stars such as Tom Cruise by studying their films. Amazon's computer systems could then automatically generate foreign language versions without any need for voiceover actors to dub the audio. The company used the example of "The Last Samurai" as an example use of the technology in its patent filing. By analysing how Cruise sounds in other films such as "Mission Impossible" and "Rain Man," Amazon could recreate his lines from "The Last Samurai" in French or Polish while still sounding recognisable.

A new study that measures how humans perceive artworks generated by artificial intelligence, alongside artworks created by humans, has concluded that a majority of people basically can't tell the difference. Published in the journal Empirical Studies in the Arts by researcher Harsha Gangadharbatla, the study was inspired by the sale of "Edmond de Belamy", an AI-generated portrait by the creative studio Obvious. Hailed as "the future", the artwork fetched around ten times the average price for a male artist at auction (and 20 times more than artworks by women), going for $432,500 at Christie's in 2018. The hype around "Edmond de Belamy" wasn't an isolated occurrence, either. In a 2017 study that asked people to compare a selection of AI artworks and actual Art Basel pieces, people mostly preferred the artworks created by machines.

Multi-label audio tagging consists of assigning sets of tags to audio recordings. At inference time, thresholds are applied on the confidence scores outputted by a probabilistic classifier, in order to decide which classes are detected active. In this work, we consider having at disposal a trained classifier and we seek to automatically optimize the decision thresholds according to a performance metric of interest, in our case F-measure (micro-F1). We propose a new method, called SGL-Thresh for Surrogate Gradient Learning of Thresholds, that makes use of gradient descent. Since F1 is not differentiable, we propose to approximate the thresholding operation gradients with the gradients of a sigmoid function. We report experiments on three datasets, using state-of-the-art pre-trained deep neural networks. In all cases, SGL-Thresh outperformed three other approaches: a default threshold value (defThresh), an heuristic search algorithm and a method estimating F1 gradients numerically. It reached 54.9\% F1 on AudioSet eval, compared to 50.7% with defThresh. SGL-Thresh is very fast and scalable to a large number of tags. To facilitate reproducibility, data and source code in Pytorch are available online: https://github.com/topel/SGL-Thresh

Artificial intelligence (AI) is doing what the tech-world Cassandras have been predicting for some time: It is sending out curve balls, leaving a trail of misadventures and tricky questions around the ethics of using synthetic intelligence. Sometimes, spotting and understanding the dilemmas AI presents is easy, but often it is difficult to pin down the exact nature of the ethical questions it raises. We need to heighten our awareness around the changes that AI demands in our thinking. If we don't, AI will trigger embarrassing situations, erode reputations and damage businesses. Two years ago, Amazon abandoned the AI tool it used to recruit employees.

REUTERS: Alphabet Inc's Google will change procedures before July for reviewing its scientists' work, according to a town hall recording heard by Reuters, part of an effort to quell internal tumult over the integrity of its artificial intelligence (AI) research. In remarks at a staff meeting last Friday, Google Research executives said they were working to regain trust after the company ousted two prominent women and rejected their work, according to an hour-long recording, the content of which was confirmed by two sources. Teams are already trialing a questionnaire that will assess projects for risk and help scientists navigate reviews, research unit Chief Operating Officer Maggie Johnson said in the meeting. This initial change will roll out by the end of the second quarter, and the majority of papers will not require extra vetting, she said. Reuters reported in December that Google had introduced a "sensitive topics" review for studies involving dozens of issues, such as China or bias in its services.

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