- Today’s top AR news: Sandia uses AR to train people on security.
- Today’s top AI/machine learning news: Facebook combats race discrimination with machine learning.
- Today’s top computer vision/machine vision news: 3 CV technologies that aid people with low or no vision.
- Sandia uses AR to train people on security.
- Why engineers should care about AR.
- Local grill hopes AR sparks brand loyalty.
- 12 AR apps for education.
- Digital Catapult launches program for AR startups.
- Facebook uses machine learning to combat racial discrimination in advertising.
- SentinelOne makes ML enhancement to next-gen endpoint protection platform.
- Druva fights ransomware with machine learning.
- Bixby on S8 speaks more languages than Google’s assistant.
- How criminals use AI and machine learning.
- Machine learning and deep learning guide: Part I
- Cloudera, Intel speed up ML workloads with Apache Spark.
- AI at UMass & Northwestern.
- Google Android Wear 2.0 update puts AI inside wristwatch.
- Cosabella credits AI with 60% jump in lingerie revenue.
- Researchers predict remission, relapse in AML patiens with machine learning.
- Android Things Developer Preview 2 adds TensorFlow for machine learning on IoT devices.
- AI gives weapons greater autonomy.
- Augmented Reality
- Sandia adding virtual layer of security (Biz Journals)
- Why Should Engineers Care About Augmented Reality? (Electronic Design)
- MOE’S SOUTHWEST GRILL HOPES AUGMENTED REALITY SPARKS BRAND LOYALTY (Loyalty360)
- 12 augmented reality apps (eSchool News)
- Digital Catapult launches programme for virtual, mixed and augmented reality startups (CBR Online)
- Artificial Intelligence/Machine Learning
- SentinelOne Makes Major Machine Learning Enhancement to Its Next-Generation Endpoint Protection Platform (Marketwired)
- Druva Applies Machine Learning to Combat Ransomware (IT Business Edge)
- Samsung’s Bixby on the S8 may speak more languages than Google’s Assistant (PhoneArena)
- How criminals use Artificial Intelligence and Machine Learning (betanews)
- Deep Learning and Machine Learning Guide: Part I (DZone)
- Cloudera And Intel Speed Up Machine Learning Workloads With Apache Spark, Intel® Math Kernel Library Integration (EconoTimes)
- Connected vehicles in Ohio, artificial intelligence with UMass, Nortthwestern (NetworkWorld)
- Google Android Wear 2.0 update puts artificial intelligence inside your wristwatch (The Sun)
- Lingerie Brand Cosabella Credits Artificial Intelligence With 60 Percent Revenue Jump (GeoMarketing)
- Researchers develop computer machine-learning model to predict remission or relapse in AML patients (News-Medical)
- Facebook introduces machine learning to combat racial discrimination in ads (PRWeek)
- Android Things Developer Preview 2 adds TensorFlow for machine learning on IoT devices (9to5Google)
- Artificial Intelligence giving weapons greater autonomy (Defense Systems)
- Computer Vision/Machine Vision
- Asteroid mining project to image drilling in space (IMV Europe)
- Three technologies improving quality of life for those with low vision, blindness (Bel Marra Health)
- How UK startup Metail is using computer vision to change the retail industry (TechWorld)
- Smart Manufacturing Looks to Advances in 3D Machine Vision (Machine Design)
Sandia adding virtual layer of security (Biz Journals)
Sandia National Laboratories is adding augmented reality to its security toolbox, using it to train personnel around the world on how to guard their nuclear assets.
AR enhances training on how to prevent theft and sabotage of the facility’s products. The virtual headsets, in use at the labs since April, give students a form of X-ray vision so they can see first-hand how protecting the lab’s nuclear material works — without being in the same building.
Why Should Engineers Care About Augmented Reality? (Electronic Design)
Why should engineers care about augmented reality? I posed this question and more to Scope AR’s Scott Montgomerie. Scott is the co-founder and CTO of Scope AR, a vendor that’s making augmented reality a reality.
Montgomerie: For starters, sending in experts from afar or constantly having to repair issues that were never fully resolved is time-consuming and expensive, often times creating downtime that costs in the millions. With complex tasks, phone (or even video) calls don’t cut it, leaving lots of room for error and providing little opportunity for creating future efficiencies. However, with this more natural method of communication using augmented reality, field workers or those local to the issues can address a problem on equipment or machinery as if they had the knowledge of the engineer who created it. In the meantime, they can ensure they covered off on each step with backup systems all the while leaving a trail of analytics for future use.
On Tuesday, Moe’s Southwest Grill launched its second in-store Augmented Reality (AR) poster titled “Bacon Blues,” which is the latest installment of the brand’s nationwide rollout of in-restaurant worlds of art featuring foodscapes — stunning landscapes crafted with Moe’s fresh ingredients by Carl Warner.
Losacco: The objective of the Augmented Reality integration as part of the Rockin’ Rewards loyalty app and new in-store wall art is creating a new way to connect with our fans outside of a transactional experience. The universe of mobile apps is very competitive and there needs to be additional value of use for consumers to share their phone storage with a brand. The Rockin’ Rewards loyalty app was intentionally intended to be an extension of the overall Moe’s experience and this is the first part of delivering that tie-in. Each piece of wall art (Foodstock and Bacon Blues) allow our loyal fans to find fun Easter eggs inspired by influential moments in music history. The Moe’s culture is rooted in music which is delivered through the “Dearly Departed” playlist and Rockin’ fun environment.
Our fans can be entertained when dining in each restaurant by interacting and unlocking fun Easter eggs in the wall art. In the new Bacon Blues poster, fans can even play various instruments and a harmonica through their phone.
12 augmented reality apps (eSchool News)
The Brain AR App: Examines the layers of the head from skin, muscle and skull down to the inner areas of the brain.
Amazing Space Journey: Students explore the solar system, sun, planets and satellites in detail. They also observe and learn about the planets’ position and orbit.
Anatomy 4D: This app provides an interactive 4D experience of human anatomy.
Elements 4D: These augmented reality chemistry blocks come to life, and students can produce different chemical reactions by combining two elements.
Augmentor has been launched by Digital Catapult, a programme designed to support early stage tech businesses developing applications in virtual, mixed and augmented reality technologies.
Successful Augmentor applicants will get the chance to work at Digital Catapult’s centre in London where they will have full access to a state-of-the-art Immersive Lab.
Artificial Intelligence/Machine Learning
SentinelOne Makes Major Machine Learning Enhancement to Its Next-Generation Endpoint Protection Platform (Marketwired)
SentinelOne, the company transforming endpoint security by delivering real-time protection powered by machine learning and dynamic behavior analysis, today announced the Deep File Inspection (DFI) engine, a significant new feature to its next-generation endpoint protection platform. The DFI engine identifies and prevents the execution of advanced threats and performs powerful, on-access static analysis to uncover and block file-based malware prior to execution and without any dependence on signatures.
Built with the same advanced machine learning technology that drives the company’s award-winning behavior-based detection capabilities, the DFI engine earned SentinelOne EPP top scores across several validation test reports from AV Comparatives and AV-TEST, making it the first certified AV replacement for MacOS.
Druva Applies Machine Learning to Combat Ransomware (IT Business Edge)
Today, Druva announced it is employing machine learning algorithms across its cloud service to continually assess the unique attributes of changes being made across various file types to make it easier to identify abnormal deletions, unusual modifications and updates, and an atypical number or large number of file creations.
In fact, Korean media is now reporting that Bixby will understand 7-8 languages at launch, including Korean and Chinese. That’s more than the five spoken languages of Google’s Assistant on the Pixel phones, but less than the Siri roster.
Attackers use AI and ML to take the results from one tool and then allow the other tools to “learn” about the finding and use it against other systems. As an example, if a one tool finds a password, that tool can feed the information to another tool or bot that may conduct the exploitation of one or many systems using the discovered password.
Advice and Recommendations
- Use defense in depth mechanisms to defend against automated/AI-based attacks.
- Utilize Security Information and Event Management (SIEM) to evaluate log data from systems and protection mechanisms.
- Ensure that all systems require users to use strong passwords comprised of alpha, numeric, and special characters.
- Shut down unnecessary services on all systems.
Step 1 is to learn the languages of ML and DL. C and C++ are strong in DL and Python is everywhere — so learning Python is very critical.
Step 2 is to start picking up machine learning frameworks like MXNet, which is now in Apache.
Step 3 is to get your data. Apache Olingo for Open Data Protocol lets you read OData and Open Data sources, which is helpful.
Step 4 is a to dive deep into TensorFlow.
Spark is still the choice for running distributed jobs on Hadoop for multiple workloads (i.e., Graph, Batch, Streaming, SQL, ML, DL).
Cloudera And Intel Speed Up Machine Learning Workloads With Apache Spark, Intel® Math Kernel Library Integration (EconoTimes)
Cloudera, the global provider of the fastest, easiest, and most secure data management, analytics and machine learning platform built on the latest open source technologies, today announced a jointly tested solution with Intel to advance capabilities for machine learning (ML) and artificial intelligence (AI) workloads. Benchmark tests on Cloudera with Apache Spark and the newly released Intel® Math Kernel Library (Intel® MKL), demonstrate the combined offering can advance machine learning performance over large data sets in less time and with less hardware. This helps organizations accelerate their investments in next generation predictive analytics.
Lexalytics, a Boston-based text analytics software and services provider, has established what it’s calling Magic Machines AI Labs at its office in Amherst to collaborate with the University of Massachusetts Amherst’s Center for Data Science and Northwestern University’s Medill School of Journalism, Media and Integrated Marketing Communications.
With UMass (which counts Lexalytics CEO Jeff Catlin among its grads), Lexalytics will work with faculty and students in areas such as analyzing, visualizing and exploiting data, and overall, making the AI building process easier.
Google has unveiled the second generation of its smartwatch software, which will place artificial intelligence (AI) in the company’s wearables for the first time.
Lingerie Brand Cosabella Credits Artificial Intelligence With 60 Percent Revenue Jump (GeoMarketing)
The specific tools Cosabella has been using include Emarsys’s Automation, Predict Web Extend, Smart Insight and CRM Ads products.
Since the integration of that platform, Cosabella says it has seen a doubled its email subscriber list. In turn, that has led to “email-driven” revenues by more than 60 percent compared to 2015. The roll out of the Emarsys platform is the next big step in Cosabella’s move into AI integration during 2017.
Researchers develop computer machine-learning model to predict remission or relapse in AML patients (News-Medical)
Researchers have developed the first computer machine-learning model to accurately predict which patients diagnosed with acute myelogenous leukemia, or AML, will go into remission following treatment for their disease and which will relapse.
The computer was trained using bone marrow data and medical histories of AML patients, as well as blood data from healthy individuals. Cases about which the computer had no information were evaluated by the algorithm by applying knowledge about similar cases in the database. The computer was then able to predict remission with 100 percent accuracy. Relapse was correctly predicted in 90 percent of relevant cases.
On Wednesday, Facebook outlined the steps it has taken to do so. In a blog post, the platform said it has updated its advertising policies, introduced a new section to educate advertisers about the policy, and will begin to roll out machine learning technology to identify housing, employment, or credit ads that discriminate against ethnicity.
Using machine learning technology, Facebook will be able to distinguish ads that offer housing, employment, or credit opportunities to check whether they go against the new ad policy.
Following a rebrand of Google’s IoT OS last December, a new developer preview of Android Things is available with bug fixes and other features based on developer feedback. The most notable addition is the ability to run TensorFlow for on-device machine learning and computer vision.
Leveraging the vast development familiarity with Google’s dominant mobile OS, the Internet of Things platform aims to allow any Android developer to quickly build smart home devices using known Android APIs and Google services.
Artificial Intelligence giving weapons greater autonomy (Defense Systems)
Those efforts are thought to be a response to the Navy’s Long Range Anti-Ship Missile, or LRASM, scheduled to be deployed as early as next year to counter aggressive Chinese military moves in the South China Sea. LRASM is believed to have semiautonomous capabilities that use AI technology to counter electronic defenses and reach designated targets without the use of standard navigation aids.
For now, AI capabilities for “intelligent” cruise missiles appear to be restricted to evading electronic countermeasures and other threats, navigating independent of the Global Positioning System and bypassing enemy ships not on target lists.
Computer Vision/Machine Vision
Asteroid mining project to image drilling in space (IMV Europe)
Wroclaw vision systems specialist Scanway supplied a vision-based measuring chamber for the DREAM project, the aim of which is to produce a chart of the particles that are ejected while the rock is drilled.
The measurement setup consists of a laser line projected parallel to the rock, and a camera – the MvBlueLynx-X smart camera from Matrix Vision – detecting particles passing through the laser line. The data captured will be analysed after the flight.
The MvBlueLynx-X camera was chosen because of its small size and weight. The device is a highly integrated embedded platform, with digital inputs and outputs that can be programmed independently.
Three technologies improving quality of life for those with low vision, blindness (Bel Marra Health)
Co-Robotic Cane: A co-robotic cane is currently being developed by Dr. Chang Ye of the University of Arkansas, Little Rock to aid those with low vision in maneuvering indoors. There is existing GPS-based technology available to help people find a location, such as a building, but it isn’t useful for finding and navigating specific rooms within a structure. The cane functions by providing feedback about the user’s environment, using a 3D camera and a motorized roller tip to drive the cane forward for the user to follow. The cane also stores preloaded floor plans that can be accessed through voice recognition, though Ye hopes to have the cane capable of downloading a building’s floor plans through Wi-Fi upon entry.
Robotic Glove: Dr. Ye is also working on a robotic glove to help the user locate and use small objects and doorknobs. The fingerless glove uses a camera and speech recognition to identify an object, then guides the hand’s movements through tactile prompts.
Crosswalk App: Dr. James Coughlan and his team at the Smith-Kettlewell Eye Research Institute have created an app for smartphone users that emits auditory signals to help the user identify a crossing location and stay within the lines of a crosswalk. Through the use of GPS, computer vision, and a geographic information system, the app is able to find the location where the user is standing, locate crosswalks and stoplights, and identify if there are any disruptions to the intersection such as construction or uneven surfaces. The combination of these technologies can work to guide the user safely through the crosswalk.
The eventual solution was to simplify the process by digitising garments in 2.5 dimensions instead of 3D. Adeyoola explained: “So starting with a sample we digitise against ground truth, which is a mannequin, and then based on the standard elements of how the garment changes into different sizes we use software to deform and warp that garment based not just on how it changes shape but the underlying shape of the person under the garment.”
Metail would essentially become the photography department for a retailer, using its warping software to reduce the amount of photos required to digitise a garment.
“So we needed to be able to do the photography in a way that we supply some sort of rig to go into their supply chain,” he explained. “So it could be operated where the garments are, because the samples are gold dust and that is where you need to do the photography.”
Eventually Adeyoola wants Metail to “be wherever anyone is having a conversation about fashion”. What he means is, by digitising the world’s garments a user could be reading Vogue magazine, scan the dress and see it on the MeModel, share it on Facebook and buy it on Amazon, all from their phone.
Smart Manufacturing Looks to Advances in 3D Machine Vision (Machine Design)
To make the image one can use the single point method (which provides the location of where an object is located in a 3D space,) or the more familiar process (using a cloud of points where every point in the image represents an XYZ coordinate). The points would be the ridges of the structured body rather than the pixels that comprise that image. In a point cloud, you have to combine the data to get a result.
Just like your eyes, using multiple cameras allows you triangulate points in space. Correspondence problems for stereo imaging for non-textured images like a tablecloth are solved by using structured lighting. At the end, you get a 3D snapshot that can be analyzed by the image-capturing software.