- Today’s top AR news: The first AR app for asthma sufferers.
- Today’s top AI/machine learning news: 20 tech startups and their patents.
- Today’s top computer vision/machine vision news: Machine vision and early detection of diabetic eye disease.
- The first AR app for asthma sufferers.
- How AR brought old Beijing back to life.
- AR project at Bodleian Library in Oxford.
- App shows what life will be like when the world’s ice melts.
- A look at 20 tech startups, some using AI, AR, and CV.
- Machine learning experts parse Amazon basin ecology data.
- Revenue planning with machine learning.
- Machine-time analytics on Wall Street.
- Machine learning shows when to zap brain to boost memory.
- Google to display smarter ads with machine learning.
- ML-enabled condition monitoring solution for electric, mechanical devices.
- Novel machine learning technique for measuring sleep patterns.
- AI anti-fraud service.
- Elon Musk outlines how he’ll merge AI and human brain.
- Start-up uses AI tech for breast cancer screening.
- 6 AI startups in Africa.
- AI can accurately predict future heart disease, strokes.
- Augmented Reality
- How Augmented Reality Brought Old Beijing Back to Life (Sixth Tone)
- Mundipharma Launches First Augmented Reality App to Help Asthma Sufferers (Yahoo! Finance)
- Launch of augmented reality project is set to bring new life to the Bodleian Library (Experience Oxfordshire)
- This App Shows You What Life Will Be Like When The World’s Ice Melts (Fast Company)
- Artificial Intelligence/Machine Learning
- Planet enlists machine learning experts to parse a treasure trove of Amazon basin data (TechCrunch)
- Bizible Debuts Revenue Planning Product With Machine Learning (Demand Gen Report)
- Future View of HPC on Wall Street: Machine-Time Analytics (Enterprise Tech), Rated: A
- Machine learning shows exactly when to zap brain to boost memory (New Scientist)
- Google Leans On Machine Learning And Scale For Smarter Display Ads (ad exchanger)
- Bluvision Announces Machine Learning-enabled Condition Monitoring Solution for All Types of Electric and Mechanical Devices (Yahoo! Finance)
- Researchers use novel machine learning technique to measure sleep patterns (News-Medical)
- Easy Solutions Launches Artificial Intelligence Anti-Fraud Service (Yahoo! Finance)
- Elon Musk Just Outlined How He’ll Merge The Human Brain and AI (Futurism)
- A Look Inside 20 Stealth Startups (CB Insights)
- This start-up uses artificial intelligence tech for breast cancer screening (Business-Standard)
- 6 artificial intelligence startups in Africa to look out for (VentureBurn)
- Artificial intelligence can accurately predict future heart disease and strokes, study finds (University of Nottingham)
- Computer Vision/Machine Vision
- IBM Machine Vision Technology Advances Early Detection of Diabetic Eye Disease Using Deep Learning (PR Newswire)
- Cadence Tensilica Vision P-Series DSPs are Industry’s First Imaging/Vision DSPs Certified by Khronos as OpenVX 1.1 Conformant (PR Newswire)
- Xilinx Showcases Vision Guided Machine Learning with reVISION (PR Newswire)
Since January, however, augmented reality (AR) technology has been allowing people to travel back in time and appreciate the graceful beauty of the Nine Old Gates. Now, anyone changing lines at Xizhimen Station or on board the special AR train running along Line 2 is treated to a series of photographs of the gates themselves.
When people scan these pictures with the Baidu mobile app and turn on the AR function, all kinds of historic scenes showing the lives of ordinary Beijingers appear on their smartphones. The app also features spoken descriptions of the history of each gate, as well as literary allusions that have been made to the gates throughout history.
We needed to train machines to recognize blurry, low-resolution photographs that were more than a century old; to discover the subtle differences among these pictures; to perform this in spite of the overlapping effects of different angles, different levels of lighting, and the complex environment of Beijing’s subway; and then to bring all of this into our mobile app’s AR function.
To showcase the technology we’re currently working on, we used Baidu’s Simultaneous Localization and Mapping (SLAM) to activate a triggering mechanism that occurs when the user arrives at Zhengyangmen. In simple terms, this technology enables a computer to use sensors — such as cameras, lasers, and gyroscopes — to estimate the user’s position in an unknown environment while simultaneously constructing a map of the surrounding area through which they can move.
An innovative digital health initiative developed out of Mundipharma’s Regional Head Office in Singapore employing augmented reality technology to address errors in inhaler use among Asthma sufferers as part of a new and personalised approach to Asthma management has been launched.
breatherite™, a free app developed by Mundipharma, is the first digital health platform to utilise augmented reality together with a range of smartphone sensors, delivering a personal asthma management solution with a focus on correcting errors in inhaler technique.
The app engages the front-facing camera for facial mapping, the accelerometer and gyrometer to track inhaler preparation, the microphone to analyse inhalation and exhalation, along with augmented reality to visualise correct inhaler orientation and head alignment. Together, these features assess, and correct inhaler use as part of a unique interactive experience.
Launch of augmented reality project is set to bring new life to the Bodleian Library (Experience Oxfordshire)
Oxford is one of twelve of England’s historic cities which have collaborated to develop an innovative augmented reality (AR) product that is set to bring heritage to life. The ground-breaking new AR experience launched on March 31st to celebrate English Tourism Week. It consists of an app and videos that transports the user back in time to unveil the hidden lives of some of history’s most fascinating characters at the Bodleian Library.
The premise of the app is to capture significant historic moments in time whilst providing tourists the opportunity to explore England’s most historic cities.
Called After Ice, the app detects your location and allows you to visualize the effects of climate change through augmented reality by overlaying an image of yourself in your current environment with water-level projections.
When I open After Ice in New York and hold my phone up to my face, I see a gentle wave of water rolling somewhere right over my head. Occasionally, a fish swims past. The app tells me that at 79% of total melt, sea level will be at 208 feet above current levels in my neighborhood; at 100% melt, sea level is expected to rise as much as 263 feet.
Artificial Intelligence/Machine Learning
Planet enlists machine learning experts to parse a treasure trove of Amazon basin data (TechCrunch)
The hope is that by releasing this data and hosting this competition, Planet can encourage academics and researchers worldwide to apply advances in machine learning that have been put to great use in efforts like facial recognition and detect, to this pressing ecological problem.
The goal is to see if competitors can come up with new ways to monitor these situations with machine learning tools created to make sense of the data.
Bizible Debuts Revenue Planning Product With Machine Learning (Demand Gen Report)
Bizible announced it has launched a revenue planning solution that incorporates machine learning capabilities. The new solution, which relies on proprietary algorithms, enables B2B marketers to do channel mix modeling and forecasting dynamically using historical data and various “what if scenarios.”
Future View of HPC on Wall Street: Machine-Time Analytics (Enterprise Tech), Rated: A
“Machines are actually making decisions in sub-10 microseconds now…,” said Donal Byrne, CEO of Corvil, at the recent HPC for Wall Street conference in New York, “so that means a machine can make a decision on the order of a million times faster than we can as humans. We’ve seen this movie play out over the last five years.”
With HFT machines operating at volumes and speeds beyond human’s ability to track, there has emerged a new problem straight out of the alarmist’s view of AI: the need for machines to monitor machines.
The solution, Byrne contended, is what he calls “machine-time analytics,” a new way for humans to make sense of machine decisions and actions occurring at these machine timescales. Machine-time analytics is the ability to analyze the actions and decision of machines at the timescale and granularity with which they act.
First: a trusted source of detailed data. “If the data is of poor quality, if it’s summarized, or if it’s the wrong data, then you’re going to get garbage out.” Byrne contends that network data is the best source to tap into because it captures all trading activity.
Second: an accurate view of time, which means that all trading actions are time-stamped to an exacting degree.
Third: the application of advanced machine learning algorithms to analyze trading activity.
Fourth: continuous, streaming tracking of all activity on the trading platform.
Machine learning shows exactly when to zap brain to boost memory (New Scientist)
First, the team recorded the brain signals of the volunteers while they learned items from a list, and later as they tried to recall those items. They then applied machine learning methods to this brain signal data, enabling them to predict if a person’s efforts to commit something to memory would later prove successful, based on the state of their brain at the time.
The team next ran further recall tests, during which they delivered random jolts of electricity to the participants while they were trying to memorise test items. They compared the effects of jolting someone during two different brain states – the pattern of signals linked to being likely to later remember something, and the pattern linked to being more likely to have a memory lapse.
Smart display campaigns are accessible via AdWords and reach more than 3 million GDN sites and apps on GDN now.
Beta testers like hotel search platform trivago have seen conversions increase an average of 20% across the board compared to standard display campaigns priced at the same CPA.
But Google’s goal is to bring these media and creative capabilities together in a single workflow while ramping up its use of machine learning in ads.
Bluvision Announces Machine Learning-enabled Condition Monitoring Solution for All Types of Electric and Mechanical Devices (Yahoo! Finance)
Bluvision, a part of HID Global, announced their advanced, device agnostic, Condition Monitoring solution at Hannover Messe, 2017 – the World’s largest manufacturing industrial technology trade fair. The new solution uses machine learning and Artificial Intelligence (A.I.) to predict motor and equipment failure. The solution tracks an asset’s multiple states of motion and develops a performance profile, using Bluvision’s end-to-end platform – sensor beacons, BLE to WiFi (BluFi) gateways and Bluvision’s cloud solution, Bluzone. Depending on an asset’s health, user-defined real-time alerts can be set up to communicate not only the asset’s current status but also if that asset’s health is degrading and is predicted to need attention.
Osaka University researchers have designed new technology that uses machine learning to model a personal sleep pattern based on the sounds made during sleep. Because the sounds can be recorded at home with no fancy devices, it is expected that doctors using this technology could diagnose patients under normal sleeping conditions, which is expected to lead to better treatment.
Easy Solutions Launches Artificial Intelligence Anti-Fraud Service (Yahoo! Finance)
Easy Solutions, the Total Fraud Protection company, today unveiled its new Detect TA Artificial Intelligence (AI) Fraud Assessment Service for banks and other financial institutions. Artificial Intelligence delivers a competitive edge to any business that leverages it effectively, and it is already being applied by leading financial institutions to improve fighting fraud.
In early engagements, organizations have seen up to 195 percent increase in fraud detection rates using machine learning models developed from the service.
Just a few weeks ago, details leaked asserting that Musk is backing a brain-computer interface venture that was founded in order to allow humans to keep up with the advancements made in machine intelligence. At the time of the leak, the company – called Neuralink – was still in the earliest stages of development.
Since the computing powers of AI are expected to surpass that of humans in rather quick order, the neural lace is meant to push our cognitive performance to a level that is comparable to that of AI.
A Look Inside 20 Stealth Startups (CB Insights)
The company’s patent activity focuses mainly on refining Magic Leap’s VR/AR products with a “see-through head mounted display” and VR or AR “headsets having adjustable interpupillary distance.”
The patent for “using historical attributes of a user for virtual or augmented reality rendering” is aimed at decreasing latency when rendering new objects in a virtual world. Notes in this document indicate that high latency when rendering virtual objects can cause users discomfort, queasiness, etc. and that keeping latency low improves user experience. To that end, the company is attempting to use historical user information about head movements to improve head tracking and develop “predictive head tracking.”
Zoox’s patents suggest that one mission of the billion-dollar company is to develop a system that will interconnect all their vehicles to keep them moving smoothly.
Tyto apparently wants to bring your doors and windows into the modern era and let you control these electronically as well, like with the connected window below.
Aquifi is focusing a lot on technologies not just to scan, map, and rapidly reconstruct a 3D world with 2D cameras, but also for users to possibly interface with that world using head movements and gestures and incorporate the use of “wearable glasses.”
Startups are famous for thinking outside the box and Sympara is attacking the debilitating condition of hypertension in an unorthodox way: with an external device and a smartphone. We can see from their patents that they intend to have users attach a specialized device to their chests that administers a therapeutic session of low-level electrical impulses aimed at modulating their blood pressure.
But Xiant Technologies thinks there’s still room for improvement, with patents revealing that they are developing lighting systems aimed at the burgeoning ag tech space to help improve outputs for plants and chickens. Claims around their lighting system include that it can produce larger chickens and possibly earlier sexual maturity, which would allow them to make eggs and reproduce earlier. For plants, the company indicates that the lighting system would be used as a fundamental controller of plant activity, aimed at speeding up growth times and increasing yields.
Syntilla Medical appears to be working on that with a device referred to in their patents as an “implantable head located radiofrequency coupled neurostimulation system for head pain,” and references helping ease migraine pain elsewhere in the documents. Apparently it would deliver targeted neurostimulation on demand and features both an implanted device inside the user’s head and an external receiver on the outside (clipped to the ear or secured in another way). This receiver would possibly be connected to a smartphone, according to one image. An intelligent device that could interface with the implant could conceivably allow it to adjust the neurostimulation to precise degrees, track usage, and allow stats to be interpreted by users and medical professionals to determine efficacy and more.
Elira aims to help users connect with their stomachs via an adhesive dermal patch with a built-in electrode that could help them curb their appetites and eat less. The digital health company’s patents cover the development of a miniature device that would affect the user’s digestive system and “[increase the] delay in the gastric emptying time,” which could conceivably help users feel fuller longer and eat less.
Whereas the mythological Odin plucked out his own eye in exchange for knowledge, this startup is using their knowledge to insert specialized therapeutic implants into patient’s eyes. Their unique system creates a multi-layer optical implant which, once inserted into the “sub-Tenon’s space of the eye and provides sustained release of the therapeutic agent during the treatment or prevention of the disorder of the eye.”
This start-up uses artificial intelligence tech for breast cancer screening (Business-Standard)
Bangalore-based startup Niramai is using a combination of machine learning, artificial intelligence, and cloud-based screening to tackle the problem of access and cost of breast cancer screening.
Niramai is an acronym for Non-Invasive Risk Assessment with Machine-learning and Artificial Intelligence. It uses a low-cost device that takes high-resolution thermal images which require no radiation. Artificial intelligence is applied to the images on the cloud to detect breast cancer. This provides an alternative to traditional mammography, which requires expensive equipment and experienced radiographers. The startup claims that its patented Thermalytix technology using thermography can detect tumors five years earlier than mammography or clinical exams.
South African startup DataProphet last year received a significant investment of an undisclosed amount from Yellowwoods Capital Holdings to expand its international offering.
Among the applications the startup has designed are a conversational agent for inquiries and a solution to detect emotion via image which has been integrated into a game for major Japanese publisher Bandai Namco.
Founded in 2011 by Dayne and Ryan Falkenberg (pictured here) and Mark Pederson, the Stellenbosch-based company (Clevva) uses virtual advisors on artificial intelligence platforms to advise sales and technical consultants.
Founded by Benji Meltzer and James Paterson (pictured left and right, respectively) in 2014, Cape Town based Aerobotics develops AI systems for drones.
The company uses AI to assist farming consultants in South Africa, Australia and the UK to analyse processed maps and extract actionable information to identify problem areas in crops such as wheat, macadamia nuts, citrus and sugar cane. This enables the company to develop variable rate fertilisation application maps and predict the yield of crops.
Nigerian startup Kudi.ai has developed a chatbot which allows users to make payments and send money to friends and family in Nigeria via messaging.
Stockshop.co.za offers a number of artificial intelligence solutions to financial institutions such as banks and insurance companies.
These include a conversational user interface (a bot in its infancy) that match-makes available financial consultants or brokers with client leads. The startup has also developed a bot interface that completes real-time identity verification checks on behalf of banks and financial institutions in line with requirements under the Financial Intelligence Centre Act (FICA).
Nigerian startup Aajoh uses artificial intelligence to help individuals that send a list of their symptoms via text, audio and photographs, to diagnose their medical condition.
Artificial intelligence can accurately predict future heart disease and strokes, study finds (University of Nottingham)
The team of primary care researchers and computer scientists compared a set of standard guidelines from the American College of Cardiology (ACC) with four ‘machine-learning’ algorithms – these analyse large amounts of data and self-learn patterns within the data to make predictions on future events – in this case, a patient’s future risk having of heart disease or a stroke.
Computer Vision/Machine Vision
IBM Machine Vision Technology Advances Early Detection of Diabetic Eye Disease Using Deep Learning (PR Newswire)
IBM (NYSE: IBM) this week released the results of new research using deep learning and visual analytics technology to advance early detection of diabetic retinopathy (DR)1. The results, which classify the degree of severity of the disease in an eye image, exceed other currently published research efforts for severity classification using deep learning and pathology insights.
The research found that a new method created by the IBM team achieved an accuracy score of 86 percent in classifying the severity of the disease across the five levels recognized on the international clinical DR scale (no DR; mild; moderate; severe; proliferative DR). By being able to quickly and accurately identify both the presence and severity of diabetic eye disease, this research could potentially help doctors and clinicians have a better view of disease progression and determine treatment.
Based on more than 35,000 eye images accessed via EyePACS, the IBM technology was trained to identify lesions such as micro-aneurysms, haemorrhages and exudates to indicate damage of the retina’s blood vessels and assess both the presence and severity of the disease. The novel method for classifying the severity level of DR combines deep learning techniques, convolutional neural networks (CNN), with a dictionary-based learning to incorporate DR specific pathologies.
Cadence Tensilica Vision P-Series DSPs are Industry’s First Imaging/Vision DSPs Certified by Khronos as OpenVX 1.1 Conformant (PR Newswire)
Cadence Design Systems, Inc. (NASDAQ: CDNS) today announced that the Cadence® Tensilica® Vision P-Series DSPs are the first imaging/vision DSPs to pass Khronos™ Group’s conformance tests for the OpenVX™ 1.1 specification. Application developers can now take advantage of Tensilica Vision P5/P6 functionality without detailed knowledge of the hardware architecture and still achieve high performance. This enables faster development of computer vision and imaging applications on Tensilica Vision P-Series DSPs being deployed in applications processors for mobile, automotive, drone, security, augmented reality/virtual reality (AR/VR) and other markets.
Xilinx, Inc. (NASDAQ: XLNX) will showcase its new reVISION™ stack for vision guided machine learning applications at the Embedded Vision Summit 2017. Through in-booth demonstrations and paper presentations, Xilinx and global channel distribution partner, Avnet, will show how Xilinx’s tools, libraries and methodologies infuse machine learning, computer vision, sensor fusion and connectivity into vision guided intelligent systems. Visit Xilinx at the Embedded Vision Summit 2017, May 1-3, at the Santa Clara Convention Center.
Xilinx and Avnet In-Booth Demonstrations
- Deep Learning, Computer Vision and Sensor Fusion – Presented by Xilinx
This demonstration runs three major complex algorithms commonly used in autonomous systems today, Convolutional Neural Network (CNN), Dense Optical Flow and Stereo Vision, all in a single Zynq® UltraScale+™ MPSoC device.
- Avnet Sensor Fusion Acceleration with Xilinx reVISION Stack – Presented by Avnet
This demonstration features the PicoZed™ Embedded Vision Kit and Xilinx® reVISION™ stack, highlighting sensor fusion – Visible (PYTHON-1300-C) + Thermal (FLIR LEPTON), and filters including Sobel, Optical Flow and Image Fusion.
- Developing Advanced Machine Vision Systems Using Only Software Defined Environments
Monday, May 1 from 11:15-11:45AM, Summit Track – Enabling Technologies
Presented by Nick Ni, Senior Product Manager for SDSoC and Embedded Vision at Xilinx and Vinod Kathail, Distinguished Engineer at Xilinx
- Caffe to Zynq: State-of-the-Art Machine Learning Inference Performance in Less Than 5 Watts
Monday, May 1 from 10:45-11:15AM, Summit Track – Enabling Technologies
Presented by Nick Ni, Senior Product Manager for SDSoC and Embedded Vision at Xilinx and Vinod Kathail, Distinguished Engineer at Xilinx