An Australian man acquitted of murder last month after his Tinder date plummeted off a balcony to her death faced new criticism after he acknowledged in a TV interview that the woman had screamed "no" a reported 33 times before she fell. "Yeah, she was certainly trying to make a lot of noise," Gable Tostee commented in the interview, which aired on the Nine Network's "60 Minutes." Critics also lashed out after The Courier Mail claimed Tostee was paid a six-figure sum for the interview. A senior detective called it "disgusting". The detective continued, "There's a lot of anger among police about this. Of course we respect the court's decision to find him not guilty but for him to now do a paid interview after everything this poor girl's family has been through, is horrific."

Following his acquittal of murder in the death of his Tinder date Warriena Wright, Australian man Gable Tostee has managed to offend several people. Tostee, 30, is scheduled to appear on an episode of "60-Minutes on the Nine Network" set to air Sunday in which he shares details about the woman's death, BBC News reported Monday. Tostee and Wright, 26, met through the popular dating app while the woman was in New Zealand for vacation. The two returned to his apartment where their argument turned physical. Tostee reportedly locked the woman on the balcony, where she later fell to her death. Following a week-long trial that took place in October, Tostee was found not guilty of manslaughter and murder in Wright's death.

Binary is the story of a man who must decide between saving his artificially intelligent girlfriend or a human woman during a crucial space voyage, causing him to question what love really means. Binary will be a 20-minute, live-action short film. Ryker - Loyal and naive, Ryker grew up in the working class. When he falls in love with an artificially intelligent woman, Seline, he struggles with whether to prioritize his love or his fellow human. Seline - An advanced form of artificial intelligence, appearing human, Seline has been programmed with the capacity to love. She must convince Ryker and Natalie her love is as valuable as human love.

The artificial intelligence (AI) currently being developed is largely benevolent. It can mimic the way humans think, complete menial and repetitive tasks, and more. But that doesn't prevent people from being afraid of AI, thinking it will take away jobs or eventually turn Terminator into a documentary. Somebody thought AI wasn't scary enough, and did something to change that. Researchers from MIT and Australia's CSIRO have created AI that actively warps pictures into scary nightmare fuel.

The Commonwealth Scientific and Industrial Research Organisation (CSIRO) has signed on for a pair of Nvidia DGX-1 3U boxes to serve as a platform for applying machine learning to its science. Angus Macoustra, acting deputy CIO and executive manager for Scientific Computing at CSIRO, said the boxes would be used for medical image analysis, nano-material modelling, genome analysis, astronomy, and space science. In the realm of space science, Macoustra said machine learning can help with hunting for the signature of pulsars. "Two thirds of all known pulsars discovered in the world have actually been observed on the Parkes radio telescope, and CSIRO holds close to 40 years of data collected from that instrument," Macoustra said during the GTCx Australia conference on Tuesday. "Machine learning gives us mechanisms to interrogate that data and it is the belief of our scientists that there are still a number of unknown pulsars locked up in these data sets that span the past 40 years."

Waiopehu College pupils, from left, Kate Nicholson, Niko Tofa and Sammy Heyward. More than 100 teens have explored the ever-evolving world of artificial intelligence. The 130 budding young scientists, from Freyberg High School, Manawatu College and Waiopehu College, learned about the benefits and difficulties faced in a technology-rich future at a conference in Levin on Friday. Mechanical masseuses and construction robots that could work in all weather conditions and give workers a sleep-in were among ideas the pupils – aged 11 to 13 – came up with for the future. Centre for Science and Citizenship founders Dr Deborah Stevens, left, and Dr Lynne Bowyer.

An upcoming TV interview with the Australian man acquitted of the murder of a New Zealand woman during a Tinder date has met with an online backlash. Gable Tostee, 30, was charged after Warriena Wright, 26, fell in 2014 from his balcony in Queensland's Gold Coast. After a high-profile, week-long trial last month, a jury found him not guilty of murder and manslaughter. The Nine Network's 60 Minutes programme has arranged the exclusive interview which will air on 13 November. "I restrained her to stop her from attacking me," Mr Tostee said in a preview of the interview.

Analyses performed using Spark of brain activity in a larval zebrafish: embedding dynamics of whole-brain activity into lower-dimensional trajectories. The growth of data volumes in industry and research poses tremendous opportunities, as well as tremendous computational challenges. As data sizes have outpaced the capabilities of single machines, users have needed new systems to scale out computations to multiple nodes. As a result, there has been an explosion of new cluster programming models targeting diverse computing workloads.1,4,7,10 At first, these models were relatively specialized, with new models developed for new workloads; for example, MapReduce4 supported batch processing, but Google also developed Dremel13 for interactive SQL queries and Pregel11 for iterative graph algorithms. In the open source Apache Hadoop stack, systems like Storm1 and Impala9 are also specialized. Even in the relational database world, the trend has been to move away from "one-size-fits-all" systems.18 Unfortunately, most big data applications need to combine many different processing types. The very nature of "big data" is that it is diverse and messy; a typical pipeline will need MapReduce-like code for data loading, SQL-like queries, and iterative machine learning. Specialized engines can thus create both complexity and inefficiency; users must stitch together disparate systems, and some applications simply cannot be expressed efficiently in any engine. In 2009, our group at the University of California, Berkeley, started the Apache Spark project to design a unified engine for distributed data processing. Spark has a programming model similar to MapReduce but extends it with a data-sharing abstraction called "Resilient Distributed Datasets," or RDDs.25 Using this simple extension, Spark can capture a wide range of processing workloads that previously needed separate engines, including SQL, streaming, machine learning, and graph processing2,26,6 (see Figure 1).

The overall goal is to target treatment specifically to each individual so that clinical outcomes for that individual are optimized. One direction of attack is to use patient data to discover decision rules which specify the treatment to use as a function of a vector of features from the patient. Regression and classification are important statistical tools for estimating such rules based on either observational data or data from a randomized trial, and machine learning can help with this because of its ability to artfully handle high dimensional feature spaces with potentially complex interactions.

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. The 2016 U.S. Robotics Roadmap was released this week; it's a massive document authored by 150 roboticists that's intended to help frame and guide research and policy decisions with the goal of solving societal problems in the United States. We'll be taking a closer look at it, but here's a 30-minute summary from lead editor Henrik Christensen: The legged robot ANYmal can support disaster relief teams with safer search and rescue operations. With its advanced locomotion capabilities, ANYmal can operate in rough outdoor environments, crawl through pipes, and access buildings over steps and stairs.