Uber CEO Travis Kalanick announced on Tuesday that he will take a leave of absence from the ride-sharing company he co-founded. The move coincided with the release of former Attorney General Eric Holder's report on allegations of harassment throughout Uber's ranks. Uber released the list of recommendations provided by Holder's law firm, saying the company's board of directors will adopt all of the changes. In an email to employees, Kalanick said he needs to take time off to grieve after the loss of his mother, who died in a boating accident late last month, and "to reflect, to work on myself, and to focus on building out a world-class leadership team." "The ultimate responsibility, for where we've gotten and how we've gotten here rests on my shoulders," Kalanick wrote.

Pure Storage (NYSE: PSTG), the market's leading independent all-flash data platform vendor for the cloud era, today announced Pure1 META, it's Artificial Intelligence (AI) platform for delivering on the vision of self-driving storage. Pure1 META is delivers global predictive intelligence by collecting and analyzing over 1 trillion array telemetry data points per day and enables effortless management, analytics and support. Pure1 META represents a major breakthrough in enterprise artificial intelligence and machine learning. Through the new Workload DNA generated by Pure1 META, customers will be able, for the first time in the industry, to predict both capacity and performance and get intelligent advice on workload deployment, interaction and optimization. With Pure1 META, Pure Storage continues to advance in its vision of delivering self-driving storage.

Created by a team of Stanford psychologists and AI experts, Woebot uses brief daily chat conversations, mood tracking, curated videos, and word games to help people manage mental health. Scientists who recently looked at text-chat as a supplement to videoconferencing therapy sessions observed that the texting option actually reduced interpersonal anxiety, allowing patients to more fully disclose and discuss issues shrouded in shame, guilt, and embarrassment. Yesterday, Darcy and a team of co-authors at Stanford published a peer-reviewed study in the Journal of Medical Internet Research, Mental Health that randomized 70 college students and asked them to engage with Woebot or a self-help e-book for two weeks. But using those results to claim it can significantly reduce depression may expose Woebot to legal liabilities that bots in supporting roles have managed to avoid.

Big Data analytics, machine learning, and other emerging artificial intelligence (AI) technologies have, in a very short time, become astonishingly good at helping companies see, and react to, patterns in data they would otherwise have missed. More and more, however, these new patterns carry difficult ethical choices. Not every connection between data points needs to be made, nor does every new insight need to be used. Consider these embarrassing real-world examples': Similarly, Microsoft had a mortifying experience in early 2016 with "Tay," a chatbot intended to be a fun experiment in training an AI to understand conversational language. However, when trolls coordinated their efforts on Twitter and in messaging apps GroupMe and Kik, they were able to teach Tay to respond to them in appallingly racist ways, forcing Microsoft to take the AI offline after just 16 hours. Artificial intelligence has already progressed to the point that we're already asking it to automate not just business processes, but ethical choices.

It was a striking story. "Machine Bias," the headline read, and the teaser proclaimed: "There's software used across the country to predict future criminals. And it's biased against blacks." ProPublica, a Pulitzer Prize–winning nonprofit news organization, had analyzed risk assessment software known as COMPAS. It is being used to forecast which criminals are most likely to reoffend.

Medical-robotics maker Myomo Inc. has completed its initial public offering and is now set to become the first company to list on a major U.S. exchange through a little-used provision of federal law known as Reg A . The Cambridge, Mass.-based company, which makes orthotic devices for people with upper-body paralysis, raised approximately $8 million in its offering, according to its underwriter TriPoint Global Equities.

There exist many problem domains where the interpretability of neural network models is essential for deployment. Here we introduce a recurrent architecture composed of input-switched affine transformations - in other words an RNN without any explicit nonlinearities, but with input-dependent recurrent weights. This simple form allows the RNN to be analyzed via straightforward linear methods: we can exactly characterize the linear contribution of each input to the model predictions; we can use a change-of-basis to disentangle input, output, and computational hidden unit subspaces; we can fully reverse-engineer the architecture's solution to a simple task. Despite this ease of interpretation, the input switched affine network achieves reasonable performance on a text modeling tasks, and allows greater computational efficiency than networks with standard nonlinearities.

Uber didn't immediately respond to The Atlantic's request for comment on Sunday. Uber has suffered several high-profile resignations and terminations in recent months. In May, Uber fired Anthony Levandowski, a star engineer and the central figure in a high-profile legal battle over self-driving cars. His termination was tied to a federal lawsuit in which Waymo--the self-driving car company that spun out of Google--is accusing Uber and Levandowski of stealing its design secrets. An Uber spokesperson told The Atlantic that Uber had been pressing Levandowski to help with its internal investigation of the matter for months, but that he did not meet a deadline set for him.

Proposals are welcome for the International Conference on Artificial Intelligence and Information, which will be held at the Faculty of Arts, University of Porto (Portugal) on December 5, 6 and 7, 2017. The official language is English. Graduate students, junior researchers and senior scholars are welcome to submit their work. Abstract submission: We invite submission for a 30 minute presentation (followed by 10 minute discussion). An extended abstract of approximately 250-500 words should be prepared for blind review and include a cover page with full name, institution, contact information and short bio.

Video continues to be a powerful way to capture human rights abuses around the world. Videos posted to social media can be used to hold perpetrators of gross violations accountable. But video footage poses a "Big Data" challenge to human rights organizations. Two billion smartphone users means almost as many video cameras. This leads to massive amounts of visual content of both suffering and wrong-doing during conflict zones.