The next paper from our reading group is by Forrest N. Iandola, Matthew W. Moskewicz, Khalid Ashraf, Song Han, William J. Dally and Kurt Keutzer. This paper introduces a small CNN architecture called "SqueezeNet" that achieves AlexNet-level accuracy on ImageNet with 50x fewer parameters. As you may have noticed with one of our recent posts we're really interested in learning more about the compression of neural network architectures and this paper really stood out. It's no secret that much of deep learning is tied up in the hell that is parameter tuning. This paper makes a case for increased study into the area of convolutional neural network design in order to drastically reduce the number of parameters you have to deal with.

The symptoms of post-traumatic stress disorder include uncontrolled memories of a traumatic event, anxiety and panic--"hyperarousal" is the technical term--depression, avoiding anything that's a reminder of the event, self-destructive behavior, and more. It's the only psychiatric disorder where people are pretty sure of the cause: emotionally traumatic events, from the death of a loved one to an experience of fear or violence. By some estimates 5 to 10 percent of all US adults have PTSD, more women than men. Wars in Afghanistan, Iraq, and other places US troops are deployed put those numbers even higher among people in the military and veterans. But the biology of PTSD--neurological changes, elevated or depressed levels of something a blood test could pick up, genetic vulnerabilities--is … multifactorial.

The FDA approved the country's first human-interacting autonomous robot for hospitals on Thursday. The RP-VITA, made by iRobot (best known to consumers as the makers of the Roomba) and InTouch Health, is a human-sized telepresence robot which allows doctors to remotely interact with hospital patients. The robot can navigate hospital corridors autonomously, while medical professionals talk and interact with patients through a special iPad app. The Food and Drug Administration has given the RP-VITA full 510(k) clearance for hospital use.

A courageous boy from New Jersey received a letter of support from NASA after he applied for the role of planetary protection officer. Jack Davis, 9, applied for NASA's new position that was listed this week in hopes of finding help to protect the Earth against aliens. In official terms, the position involves the assistance with the'avoidance of organic-constituent and biological contamination in human and robotic space exploration'. Jack Davis, 9, applied for NASA's planetary protection officer new position that was listed this week in hopes of finding help to protect the Earth against aliens It adds that'space flight missions may intentionally or unintentionally carry Earth organisms and organic constituents to the planets or other solar system bodies'. Jack was one of the first applicants to apply, writing an adorable letter explaining why he was qualified for the job. 'My name is Jack Davis and I would like to apply for the planetary protection officer job,' he said in the letter.

Japanese technology company SoftBank Group Corp. has reported a 98 percent drop in its April-June profit on losses stemming from investments in the Chinese e-commerce company Alibaba. SoftBank said Monday its quarterly net profit was 5.5 billion yen ($50 million), down from 254 billion yen the previous year. Quarterly sales added 3 percent to 2.19 trillion yen ($20 billion). The Tokyo-based company's operating profit, which highlights core operations, logged a 50 percent increase year-on-year as its U.S. mobile carrier Sprint boosted profitability. Softbank, which sells the Pepper robot, did not give an annual forecast, which is not unusual for the company.

Researchers developed a "cognitive-computational model of human norms in a representation that can be coded into machines," according to DARPA's website. Further, a smart algorithm has been developed that "allows machines to learn norms in unfamiliar situations drawing on human data," the weapons developing agency said. If smart robots are ever to become "trustworthy collaborators with human partners," they will need to obey basic intuitive norms about human interaction. According to the Pentagon's account, they've completed a significant -- if mostly confidential -- breakthrough in philosophy: training robots to recognize value judgments like good and bad, right and wrong. These human faculties are critical for until-now strictly human tasks like planning, setting goals and organizing, and will be incorporated, at least on a basic level, into the robots of the future.

University of Washington researchers at the UW Graphics and Image Laboratory have developed new algorithms that turn audio clips into a realistic, lip-synced video, starting with an existing video of that person speaking on a different topic. As detailed in a paper to be presented Aug. 2 at SIGGRAPH 2017, the team successfully generated a highly realistic video of former president Barack Obama talking about terrorism, fatherhood, job creation and other topics, using audio clips of those speeches and existing weekly video addresses in which he originally spoke on a different topic decades ago. Realistic audio-to-video conversion has practical applications like improving video conferencing for meetings (streaming audio over the internet takes up far less bandwidth than video, reducing video glitches), or holding a conversation with a historical figure in virtual reality, said Ira Kemelmacher-Shlizerman, an assistant professor at the UW's Paul G. Allen School of Computer Science & Engineering. This beats previous audio-to-video conversion processes, which have involved filming multiple people in a studio saying the same sentences over and over to try to capture how a particular sound correlates to different mouth shapes, which is expensive, tedious and time-consuming. The new machine learning tool may also help overcome the "uncanny valley" problem, which has dogged efforts to create realistic video from audio.

Nervous about the thought of your connected car falling victim to hacks, especially when self-driving cars hit the streets in earnest? So is the British government -- it just issued tougher guidelines for the security of networked vehicles. It wants security to be part of the design process across every partner involved, even at the board of directors' level, and for companies to keep cars updated throughout their lifespans. UK officials also call for a "defence-in-depth" strategy that minimizes vulnerabilities (such as by walling off systems to limit the damage of a hack), and very limited use of personal data that gives you control over what the car transmits. The government has also reiterated its hopes to build a "new framework" for self-driving car insurance, making it clear who pays when an autonomous vehicle crashes.

It's just something that I think, anything that represents--that is a risk to the public deserves at least insight from the government because one of the mandates of the government is the public well-being. And that insight is different from oversight, so at least the government should have insight to understand what's going on, and then decide what rules are appropriate to ensure public safety.That is what I'm advocating for. I'm not advocating for that we stop the development of AI, or any of the sort of straw man, hyperbole things that have been written. I do think there are great benefits to AI. We just need to make sure that they're indeed benefits, and we don't do something really dumb.

What is supervised machine learning and how does it relate to unsupervised machine learning? In this post you will discover supervised learning, unsupervised learning and semis-supervised learning. Supervised and Unsupervised Machine Learning Algorithms Photo by US Department of Education, some rights reserved. The majority of practical machine learning uses supervised learning. Supervised learning is where you have input variables (x) and an output variable (Y) and you use an algorithm to learn the mapping function from the input to the output.