This summer I was invited to take part in the 2018 NASA Frontier Development Lab, along with a small team including Michele Sasdelli (University of Adelaide), and a pair of planetary scientists, Megan Ansdel (University of California at Berkeley) and Hugh Osborn (Laboratoire d'Astrophysique de Marseille). Our team composed of both machine learning and planetary scientists, was challenged over the course of 8 weeks to combine our expert knowledge in order to improve the methods behind one of the most exciting frontiers of science: exoplanet discovery. Here I discuss some of the challenges of applying machine learning to real-world scientific data, in particular noisy and sparse periodic time-series data. Our knowledge of exoplanets, or planets that exist outside our Solar System, has advanced drastically over the last few decades. In fact, until relatively recently one could have called exoplanets a theoretical concept.

I t wasn't long ago that technology was a topic only discussed among techies. In fact, technology was an elective course in many graduate school programs until very recently. Today, technology is part of our daily lives so it's not surprising that technology is very much a part of any industry. It's also not surprising to see the direction technology has taken. It has evolved from a way to communicate with each other and store important information, to a way to interact with each other, express ourselves and manage our lives. The drive to monetize our personal information for the purpose of creating the latest and greatest target marketing algorithm has paved the way for artificial intelligence or AI. Google was a pioneer and early adopter of this type of AI, gathering information about our interest based on our searches and pairing businesses and products we would likely use. It is this type of AI that brings customers to businesses like an arranged marriage. Collection of data through cloud-based applications originally created for business solutions slowly evolved for consumer convenience for everything from banking to entertainment. Amassing raw data to create solutions for everyday activities helped to speed the process of AI for the birth of AI. Had we not partaken in taking information once only saved on our desktops and placing it on cloud servers, AI may not have evolved into the presence of daily life today. Years ago, reluctance and lack of understanding of how digital information is used kept many people who are not computer savvy from partaking in this community. Today, thanks to companies like Facebook and Amazon, people readily share their information with companies with a basic trust that the information will only be used for the purpose intended. This is why, even though the information is occasionally breached, we are so willing to join communities like Citizens app and Waze which use crowd sourcing for the collective purpose of helping each of its participants. Crowd sourcing applications can then place ads as a form of revenue, though not all do. This rather invasive, though passive, business model hones in on our inherent need to share information in order to benefit from the information shared by others.

Cybersecurity has been continuously evolving, not just as a hot topic for discussion but as the mainstream challenge and priority for a large number of organizations. Recently, we have seen several cyberattack incidents turning into global epidemic events, such as WannaCry (May 2017; damaging 200,000 computers across 150 countries), Petya/NotPetya (June 2017; $10 billion damage estimated), Mirai (Oct 2016; initial level impact on 300,000 insecure IoT-devices worth $100 million, further variants and consequences still getting unveiled). And even on the corporate front, the world has witnessed several massive breach incidents, including Yahoo (2013-14; impacting 3 billion users), Equifax (July 2017; impacting 150 million U.S. citizens), and Aadhaar (Aug 2017 to Jan 2018, 1.1 billion Indian citizens impacted), just to name a few. With every passing day, cybercriminals are learning and adopting new and innovative methods of attack. To withstand such attacks, security agencies also need to ramp up their game. Besides the established players, there are a large number of startups using advanced techniques like machine learning and artificial intelligence to prevent such cyberattacks.

If there is one thing the general public is familiar with when the use of artificial intelligence than it is facial recognition. Whether it is opening their mobile phone or the algorithms Facebook uses to find eyes or other parts of a face in images, facial recognition has become a standard. But now scientists dealing with complex questions like the composition of the universe are starting to use a modified version of the'standard' facial recognition in an attempt to discover how much of the dark matter there is in the universe and where it is possibly located. As Digital Trends and Futurity note in their reports on the subject, "physicists believe that understanding this mysterious substance is necessary to explain fundamental questions about the underlying structure of the universe." It is the researchers gathered in Alexandre Refregier's group at the Institute of Particle Physics and Astrophysics at ETH Zurich, Switzerland that has started to use deep neural network methods that lie behind facial recognition to develop new, special tools to attempt to discover what is still a secret of the universe for us. As Janis Fluri, one of the researchers working on the project told Digital Trends, "The algorithm we [use] is very close to what is commonly used in facial recognition," adding that"the beauty of A.I. is that it can learn from basically any data.

Additional operational enablement can be achieved by using technologies like AI to improve how operational and technology teams engage with security. For example, using technology available today, the time required to complete routine security processes can be reduced significantly by using AI to automate resource- or time-intensive aspects of these processes. For operational teams, improvements in security process efficiency reduce the friction associated with following security requirements. Developments in AI technology are expected to unlock more opportunities to improve cybersecurity operations and support the balance of risk and return.

Missile could strike U.S. withing 30 minutes; retired Army Gen. Anthony Tata reacts. China's Communist Party marked 70 years in power Tuesday with a military parade showcasing the country's global ambitions and advancements in weapons technology. Trucks carrying nuclear missiles designed to evade U.S. defenses, a supersonic attack drone and other products of a two-decade-old weapons development effort rolled through Beijing as soldiers marched past President Xi Jinping and other leaders on Tiananmen Square. Fighter jets flew over spectators who waved Chinese flags. The display highlighted Beijing's ambition for strategic influence to match its status as the second-largest global economy, even as Xi's government suppresses dissent that illustrates the tensions between a closed, one-party dictatorship and a rapidly evolving society.

Sengupta: Thank you so much for having me today. I'm really excited to be in San Francisco. I don't get to come here that often, which is strange because I live in Los Angeles, but I do like to come whenever I can. For my talk today, I'm going to talk about the future of transportation, specifically on the things that I worked on that I think are kind of the up and coming thing, the thing that I'm working on now and what's going to happen in the future. I think part of my career has always been about just doing fun and exciting new things and all my degrees are in aerospace engineering, ever since I was a little kid, I loved science fiction. I actually am a Star Trek person versus a Star Wars person, but I knew since I was a little kid that I wanted to be involved in the space program, so that's why I decided to go the aerospace engineering route and I wanted to build technology. I got my Ph.D. in plasma propulsion systems. Has anyone heard of the mission called Dawn that's out in the main asteroid belt? My Ph.D. research actually was developing the ion engine technology for that mission. It actually flew and got it to a pretty cool place out in the main asteroid belt looking at Vesta and Ceres. I did that for about five years and then I kind of felt like I had done everything I could possibly do on that front, from a research perspective. My management asked me if I wanted to work on the next mission to Mars. There's very few engineers in the space program who'd be like, "No, I'm just not interested in that." And they're like, "We want you to do the supersonic parachute for it."

The Food and Drug Administration has issued new guidelines on how it will regulate mobile health software and products that use artificial intelligence to help doctors decide how to treat patients. The guidelines, contained in a pair of documents released Thursday morning, clarify the agency's intent to focus its oversight powers on AI decision-support products that are meant to guide treatment of serious or critical conditions, but whose rationale cannot be independently evaluated by doctors. Unlock this article by subscribing to STAT Plus and enjoy your first 30 days free! STAT Plus is STAT's premium subscription service for in-depth biotech, pharma, policy, and life science coverage and analysis. Our award-winning team covers news on Wall Street, policy developments in Washington, early science breakthroughs and clinical trial results, and health care disruption in Silicon Valley and beyond.

Those bemoaning the amount of spam in their email account's inbox (offers of suspiciously cheap Rolexes, notifications of windfalls, requests to help transfer funds from African states) may not be aware that spam exists for one reason: it works. In a similar way, because the profits from successful cybercrime are very healthy, specific individuals and organizations will always spend time and effort learning clever exploits and methods, because, on occasion, those methods work. Cybercrime is therefore here to stay, and because both end-users and cyber specialists are becoming better educated as to attackers' methods, the threat landscape will not only shift constantly but also become more complex, as methods used by bad actors will become more – although this is not intended as a compliment – intelligent. In general, companies of all sizes have deployed a combination of three cybersecurity measures. The first is a suite of pre-programmed (albeit occasionally updated) databases of known threats: their signatures, techniques, and modus operandi.

The global threat of fraud shows no signs of slowing down. Losses related to fraud are valued at $14.7 billion, according to the most recent DataVisor Fraud Index Report. As fraudsters become increasingly aggressive, new global regulations and solutions are being deployed to keep consumers, merchants and banks safe. In the latest Digital Fraud Tracker, PYMNTS highlights the fraud trends and patterns that regulators are closely monitoring, as well as the solutions -- including artificial intelligence (AI) and machine learning (ML) -- that are being deployed to shift the anti-fraud effort from defense to offense. Fraud has become particularly problematic in the United Kingdom, where last year card-based losses increased by 19 percent compared to the previous year.