The more hopeful among these respondents cited a series of changes they expect in the next decade that could improve the tone of online life. They believe: Technical and human solutions will arise as the online world splinters into segmented, controlled social zones with the help of artificial intelligence (AI). While many of these experts were unanimous in expressing a level of concern about online discourse today many did express an expectation for improvement. These respondents said it is likely the coming decade will see a widespread move to more-secure services, applications, and platforms, reputation systems and more-robust user-identification policies. They predict more online platforms will require clear identification of participants; some expect that online reputation systems will be widely used in the future. Some expect that online social forums will splinter into segmented spaces, some highly protected and monitored while others retain much of the free-for-all character of today's platforms. Many said they expect that due to advances in AI, "intelligent agents" or bots will begin to more thoroughly scour forums for toxic commentary in addition to helping users locate and contribute to civil discussions. Jim Hendler, professor of computer science at Rensselaer Polytechnic Institute, wrote, "Technologies will evolve/adapt to allow users more control and avoidance of trolling. It will not disappear, but likely will be reduced by technological solutions."

As far-fetched as it may seem today, there are a couple of compelling reasons why some humans may one day be born without either a mother or father as we now know them, and with no other humans around to bring them up. The first is the uninhabitable Earth scenario: doomsday. This is the idea that one day our planet will not be able to support human life. This may be due to catastrophic climate change brought on by a large asteroid or comet impact, a nuclear winter following a global nuclear war or a pandemic so severe that humans do not survive. Whatever the cause of our demise, if humans want to ultimately survive and one day re-emerge, it makes sense to store the building blocks of people – ovum and sperm – ready for a resurrection of the human race once our planet is habitable again. There are already gene banks around the world that have been created to store plant seeds for just this kind of eventuality.

One sure way to find the limits of a technology is to have it become popular. Last week, Facebook announced it would hire 3,000 workers to monitor content streamed and posted on the vast social network. ServiceNow is bringing enhanced machine-learning capabilities to its Now Platform for business process automation to help customers prevent outages, automatically route service requests, and predict and benchmark IT performance.The AI capabilities will be offered through the upcoming Intelligent … Artificial intelligence is taking over parts of the recruitment process. And it's not just about jobs that are repetitive and low-skill. The robots are coming for our jobs.

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. A very clever design for a small mobile robot by Draganfly Innovations: morphing wheels allow it to climb stairs with ease. The DraganScout by Draganfly Innovations Inc. is a unique ground-based robot with the ability to morph and adapt to different application or mission needs.

Beware: Siri, Alexa and Watson will soon be watching you. Artificial intelligence, machine learning, biometrics and blockchain are just the first seeds of a revolution that will take us into an era of robo-regulators and smart regulation. Sanne Wass reports on a future that is closer than we think. She's nothing like an ordinary compliance officer; even the smartest Oxford graduate would not stand a chance against her. She knows 70 languages, and it takes her just a few minutes to investigate thousands of websites, documents, reports and legal records.

This is a curated list of medical data for machine learning. This list is provided for informational purposes only, please make sure you respect any and all usage restrictions for any of the data listed here. The National Library of Medicine presents MedPix Database of 53,000 medical images from 13,000 patients with annotations. These 1112 datasets are composed of structural and resting state functional MRI data along with an extensive array of phenotypic information. Also has clinical, genomic, and biomaker data. AMRG Cardiac Atlas The AMRG Cardiac MRI Atlas is a complete labelled MRI image set of a normal patient's heart acquired with the Auckland MRI Research Group's Siemens Avanto scanner.

This article was originally published on IEC e-Tech. Click here to view the original post. Many advances in electric self‑driving car technology and robotics are transferring across to industrial and commercial vehicles, which account for some 60% of the value of the overall electric vehicle market. In agriculture, the widening use over the next decade of autonomous hybrid or fully electric tractors, robotic machinery and drones could increase farm efficiency and revolutionize how food is produced. Although some of the technology in farming robots is similar to that of autonomous vehicles, it differs in that operations such as planting seeds, picking vegetables or fruits and localized application of pesticides have individual sensing, manipulation and processing requirements.

Support vector machines (SVMs) are an important tool in modern data analysis. Traditionally, support vector machines have been fitted via quadratic programming, either using purpose-built or off-the-shelf algorithms. We present an alternative approach to SVM fitting via the majorization--minimization (MM) paradigm. Algorithms that are derived via MM algorithm constructions can be shown to monotonically decrease their objectives at each iteration, as well as be globally convergent to stationary points. We demonstrate the construction of iteratively-reweighted least-squares (IRLS) algorithms, via the MM paradigm, for SVM risk minimization problems involving the hinge, least-square, squared-hinge, and logistic losses, and 1-norm, 2-norm, and elastic net penalizations. Successful implementations of our algorithms are presented via some numerical examples.

Twenty years ago, Stephen Goldson thought he had beaten the Argentine stem weevil, an invasive insect that was devastating New Zealand's pastures. Goldson, an entomologist, had scoured the South American countryside and come up with an efficient weevil killer: a parasitoid wasp that at first killed up to 90% of the weevils. Now, the weevil has made a comeback and an examination of decades worth of data on its abundance over years has revealed that the weevil has outevolved its parasite, which produces asexually. Now, Goldson and his colleagues are studying weevil DNA to learn the secret of this comeback.

At Search Party we are in the business of creating intelligent recruitment software. One of the problems we deal with is matching candidates and vacancies in order to create a recommendation engine. This usually requires parsing, interpreting and normalising messy, semi-/unstructured, textual data from résumés and vacancies, which is where the following come in: conditional random fields, bag-of-words, TF-IDFs, WordNet, statistical analysis, but also a lot of manual work done by linguists and domain experts for the creation of synonym lists, skill taxonomies, job title hierarchies, knowledge bases or ontologies. While these concepts are valuable for the problem we try to solve, they also require a certain amount of manual feature engineering and human expertise. This expertise is certainly a factor that makes these techniques valuable, but the question remains whether more automated approaches can be used to extract knowledge about the job space to complement these more traditional approaches.