China attempted to censor Google’s AI beating its Go champion

China’s state censors tried hard to prevent citizens from watching Google’s artificial intelligence beat the nation’s Go champion.

The nation’s internet censorship gained the nickname “The Great Firewall” for its strict control over what content can be viewed. Most people’s go-to for search queries, Google, is unable to be accessed in the country for example, at least without circumvention. Citizens often use Baidu’s search engine instead.

Competence in sports is a matter of national pride for many, but it’s taken extra seriously in China where it continues to be seen as a kind of status symbol. Go in particular is a 2,000-year-old game which remains largely unchanged. The idea that a computer would (and did) beat Go champion Ke Jie appears to have been enough for state censors to intervene and block live streams of the event.

As reported by the China Digital Times, the censorship notice dictates: “Regarding the Go match between Ke Jie and AlphaGo, no website, without exception, may carry a live stream.” Where a live stream had been announced in advance, the notice demanded the announcement be immediately withdrawn.

Ke Jie was once enthusiastic about his chances and said “Bring it on!” when the AlphaGo AI beat South Korean champion Lee Sedol with a 4-1 victory. Now, however, Ke Jie has vowed never to play against AlphaGo again.

Some websites cleverly skirted the ban with a recreation of the game being played move-by-move on their own Go boards. For viewers outside China, Google has posted the matches on their YouTube channel for all to view.

AlphaGo is powered by the DeepMind AI which Google acquired in 2014. The AI continues to self-improve by playing millions of games against itself.

Are you surprised the state decided to censor the event? Share your thoughts in the comments. Latest from the homepage

Opinion: What makes a smart home truly smart?

Opinion What makes a smart home smart? An increasing number of companies want to know the answer to that question. According to a recent report from Harbor Research, “the smart home market is gaining substantial momentum, with an estimated 900 million smart devices existing in households across the world today.”

At the most basic level, a smart home is one that has sensor-enabled products that are part of the Internet of Things (IoT), plus a way to make use of the IoT data generated by the sensors. Of course, in the real world it’s a bit more complex than that.

For starters, there are three types of sensors:

  • Basic sensors are the most numerous. They are battery-powered and inexpensive, and they typically detect a single function, such as on/off, or measure a single value, such as temperature.
  • Dynamic sensors generally have multiple outputs and are more intelligent than basic sensors. They cost more, and smart homes might use one or a few dynamic sensors for functions such as energy management or smart irrigation.
  • Intelligent sensors are contextually aware. They are used in beacons, geofences, and many video-based applications. Intelligent sensors know who a user is, where they are in space and time, and what is happening around them.

Using a combination of sensor types is the first step to making a home smart. But using the IoT data the sensors generate is where the real smarts kick in.

The smartness of a smart home depends largely on its level of data integration. The greater the integration, the more value to the home’s residents, the more they’re likely to adopt additional connected devices, and the more benefits to you as a manufacturer.

As with sensors, increased complexity of integrations translates into increased intelligence. In single-device integration, one device talks to one app. You can get remote control and monitoring of that one device, including push notifications and alarms. But it’s hard to integrate with sensors. Not much smarts at this level. 

Device-to-device integration typically involves sensors. At this level, one sensor-enabled device can trigger an action in another sensor-enabled device, automatically. Currently, most of these interactions are between devices from a single manufacturer or through a retailer gateway. Integrated systems, meanwhile, are where the smart home begins to really take shape. Sensors integrated into the system enable interconnected, multi-manufacturer IoT solutions such as those supporting Amazon Alexa, Apple HomeKit, or Nest.

The ultimate level of integration results in intelligent learning systems, which can apply pattern matching (for example, every day Dad comes home between 5 and 5:30 pm and turns on the TV to ESPN) to trigger automated actions (when Dad enters the home, the geofence turns on the TV and sets it to the ESPN channel). Intelligent learning systems can also analyze and respond to individual user preferences, such as preloading different preferences into the coffee maker so that you and your partner each get the coffee you like the way you like it, without configuring or interacting with the coffee maker.

Other characteristics of smart home solutions include:

  • Security and privacy technologies to keep both IoT products and users’ personal data safe from hackers
  • Mechanisms for making sure that smart home systems can operate even if the network connection is lost
  • Easy installation, setup, and access to the available smart home features
  • Interoperability among devices from different manufacturers

The Harbor Research note also says: “We believe one of the biggest challenges that lies ahead for manufacturers looking to enter or expand in the residential market is their engineers’ lack of skills and technical expertise for creating smart home products and how much this will slow market development.”

Unless you already have teams of specialised IoT engineers on staff, with tons of real-world IoT experience, your best bet for getting the most value from the smart home market is to start with robust IoT platform technology. Latest from the homepage

INRIX has a solution to make connected vehicles and road networks safer

INRIX supplies real-time traffic data to six of the eight top car manufacturers, but now it’s moving from efficiency to safety with the launch of its latest solution.

The Safety Alerts product suite consists of INRIX Dangerous Slowdowns, INRIX Incidents, and INRIX Road Weather. Each of the products collects real-time data from all the newfangled connected cars hitting the roads and, in combination with other sources, utilise the information to help drivers around the world.

“INRIX has long been focused on making driving not only more efficient, but also safer. INRIX Safety Alerts is an innovative next step to proactively use massive amounts of big data to make connected vehicles and smart cities safer for everyone,” said Mark Daymond, chief technology officer at INRIX. “Drivers, fleet operators and city planners now have a real-time solution for visibility into ever-changing road conditions.”

Real-time data collected from one vehicle could be transmitted to others using INRIX’s services to warn them of dangerous conditions along their route. The information can also be used by agencies to improve their road networks and prevent accidents by focusing efforts in areas that have become a higher risk over time.

Iowa’s Department of Transportation (DoT) is the first agency to utilise one of INRIX’s new Safety Alerts product suite to monitor, measure and manage the state’s road network.

“Drivers in Iowa, like many others around the world, are regularly confronted with traffic, and tackling congestion is a top priority for us. Secondary collisions at the queue is a problem plaguing roadways worldwide that also needs solving,” explained Scott Marler, director of traffic operations at Iowa DOT. “We are using Dangerous Slowdowns and other INRIX services to keep drivers safe and congestion at a minimum.”

The complete Safety Alerts suite includes:

  • INRIX Dangerous Slowdowns – a newly launched service in INRIX XD Traffic that helps prevent back-of-queue, rear-end collisions where rapidly forming congestion creates a situation that requires advanced driver awareness. Based on real-time data from vehicles on the road, the location-based notifications warn drivers and transportation agencies of sudden reductions in speed or stopped traffic on the roadway.

  • INRIX Incidents – keeps drivers and transportation planners informed about congestion, accidents, and construction on the road. Using more than 400 data sources, Incidents provides the most comprehensive and accurate global dataset of anomalous roadway conditions. According to an independent study by Frost & Sullivan, INRIX Traffic had a 100% detection rate of the recorded incidents, followed distantly by competing services.

  • INRIX Road Weather – the first service to use real-time and predictive atmospheric data to give drivers advance warning of dangerous weather-related road conditions tied to individual road segments. Unlike other services, Road Weather provides drivers with critical information about the roads themselves, including the type of precipitation, surface condition (including hard-to-detect black ice) and visibility. The identification of hazardous road conditions can also be utilised by transportation officials for real-time management of road networks or advanced maintenance planning.

Inrix supplies driving intelligence services for companies and agencies including Audi, BMW, Ford, Mercedes-Benz, Toyota, more than 60 U.S. Departments of Transportation, the U.K. Highways Agency, and the Denmark Road Authority.

The company has two consumer apps currently available for smartphones. INRIX Traffic is a crowdsourced navigation app which can circumvent traffic and predict conditions ahead of time, while INRIX ParkMe is only available on iOS but allows users to find and pay for parking ahead of arrival.

Are you impressed with INRIX Safety Alerts? Share your thoughts in the comments. Latest from the homepage

Qualcomm says it is shipping more than one million chips per day for the IoT

Qualcomm Technologies has announced that it currently ships more than one million chips per day into a wide range of connected applications.

The company is using its technical expertise to design platforms that help customers commercialize IoT products quickly and cost-effectively in areas including wearables, voice and music, connected cameras, robotics and drones, home control and automation, home entertainment, and commercial and industrial IoT, according to the press materials.

Qualcomm Technologies has its grip in IoT spanning across various networks. For instance, the company’s wearables platforms have been adopted in more than 150 wearable designs, and over 80% of Android Wear smartwatches launched or announced are based on Snapdragon Wear 2100. In smart homes, more than 125 million TVs, home entertainment and other connected home products from leading brands have shipped using Qualcomm Technologies’ connectivity chips. MDM9206 is purposely developed for IoT applications and is commercially available today.

To address this wide variety of network, form factors and requirements in the IoT, Qualcomm Technologies offers one of the broadest portfolios of chips and platforms, including mobile, multimedia, cellular, Wi-Fi and Bluetooth system-on-chips. These solutions include comprehensive software with platform-specific applications and APIs, as well as support for multiple communication protocols, operating systems and cloud services.

Qualcomm Technologies is making available over 25 production-ready reference design platforms through a network of original design manufacturers for products including voice-enabled home assistants, connected cameras, drones, VR headsets, lighting, appliances and smart hubs/gateways to further help manufacturers develop IoT devices quickly and cost-effectively. Latest from the homepage

How a pharmaceutical supply chain company is taking advantage of the Internet of Things

In 2014, during a routine check from the Ministry of Health in the U.S., it was found that only 55 percent of vaccines were stored and transported in the temperature conditions that ensured the medication maintained its quality. To put that into perspective, every baby born receives vaccines to prevent diseases such as small pox and measles. If only 55 percent of those vaccinations maintain safety requirements, that creates a situation where a majority of babies don’t get the quality dosage and medication they need to protect them from diseases.

To overcome this challenge, organizations are turning to technology. More specifically, the Internet of Things (IoT) is making it possible to ensure the safer transportation and delivery of medications. Dutch pharmaceutical services company, AntTail, is paving the way for building innovative IoT applications that more effectively track the conditions of medications while in transit.  

The team at AntTail built an IoT application using the Mendix low-code application development platform. The application collects sensor data from medication shipments to provide information on temperature, as well as send push notifications to patients with reminders on when to take the medication.

One of the barriers for creating IoT apps is the requirement of many disparate technologies. AntTail uses a central router as a hub for all of the sensors, collecting the data when there is a connection and storing the data when there is no connection to ensure that no data is lost. The Router uses Vodafone’s Managed IoT Connectivity Platform as a way to connect to AWS, and has a Java service running that puts the data into Hadoop.

Hadoop is a means to store all of the data, but it is not complete without the context needed to make smart business decisions. AntTail uses Mendix to add context to the data by assigning roles to each sensor. The app takes into account where the sensor is being used in order to determine the role and assign a trigger.

For example, some sensors are assigned the role of “Last Mile” because they travel from the pharmacy to the patient. These sensors monitor not only the temperature the medication is being stored in, but also the adherence, making sure the patient takes the medication. The sensor is triggered when the patient opens the package and deactivates itself.

Other sensors are placed in warehouses and must be up and running 24/7; if no data is being collected and the sensor is offline for more than 30 minutes, an alarm profile is set up to notify the caretaker. Basic shipments also carry sensors that start at point A and deactivate when they get to point B in order to trigger a notification that the shipment has made it to its destination.

The app can visualize all of these sensors and evaluate the data for any triggers. AntTail uses the REST services module from the Mendix app store to access the full power of JSON-based REST APIs. The module serves three goals: consuming services, publishing services and synchronizing data between apps by combining consume and publish. By using the native REST service, AntTail’s customers can access the data quickly to make important business decisions in real-time.

“It’s lightning fast; I get 10,000 records in less than a second,” says Mark Roemers, CEO and Co-Founder of AntTail.

As a result, there has been a 99 percent success rate in tracking and alarming, keeping the medicine at proper temperatures and patients taking the medicine at the prescribed intervals due to reminders from the app.

Mark says that the next steps for AntTail are to take the app mobile. They are already in the process of building out their mobile apps in order to provide proactive notifications 24/7. For the warehouse manager, this means that even when he is not in front of his computer he will be able to receive notifications if a sensor reports an excursion and can act immediately. With the mobile solution, patients, pharmacists and logistics customers can access and interpret the sensors’ data from anywhere at any time. Latest from the homepage

Intel’s big bets on autonomous driving unveiled: “Unwavering confidence” in success

Intel has opened the doors to its Silicon Valley Innovation Center for Autonomous Driving and, with a slew of partners in tow, gave further insight into its push towards the connected car space.

Among the announcements was a reveal of one of the first highly automated vehicles developed in partnership with BMW and Mobileye, which Intel acquired for $ 15.3 billion in March, alongside demonstrating with Ericsson. over the air data moving across a 5G network between the car and the cloud.

The company also opened its Advanced Vehicle Lab, which alongside labs in Arizona, Germany, and Oregon will research the requirements and technologies needed to power self-driving vehicles, from artificial intelligence (AI) to supporting cloud services, while the Autonomous Garage Labs will focus more on the tools and testing side.

Doug Davis, senior vice president and general manager of the automated driving group at Intel, penned an editorial outlining his passion for the project, saying he postponed his retirement to lead the initiative.

“The chance to solve one of the most complex technology challenges of our time, the opportunity to help the auto industry reinvent transportation, the potential to save a million lives every year – those things are unlike anything I’ve done before,” he wrote.

“I have unwavering confidence that Intel will succeed in autonomous driving”, he added. “We have an astounding breadth and depth of experience and the world’s finest technology toolkit to apply to this challenge. We have tapped resources from across the company and have added experienced talent from the automotive industry. Our teams are operating in high gear and will deliver the necessary technology breakthroughs.”

In July last year, BMW, Intel and Mobileye announced plans to bring self-driving vehicles onto the road by 2021 through a common platform. The companies outlined their strategy to come up with solutions which continually went up the scale of automation, from level 3 (‘eyes off’), to level 4 (‘mind off’) and then eventually to level 5, ‘driver off’, when a human is not required inside the vehicle. Davis added that plans were afoot to bring the platform to market for other OEMs and tier one suppliers.

Davis also riffed on the importance of AI in autonomous vehicle development. “Mastering AI both inside the car and in the data centre will be essential to the autonomous driving data challenge,” he wrote. “Here it’s important to remember that autonomous driving isn’t a game. When cars are thinking and acting without human intervention, they must be able to do so in a safe and trustworthy way.”

Plenty of research is taking place, and plenty of data is being collected to gauge what autonomous cars should do in certain situations. The MIT’s ‘moral machine’ program, which gives participants the choice between “the lesser of two evils”, such as killing two passengers or five pedestrians, is an example of this. As Davis noted: “If all we needed was a supercomputer to handle the autonomous driving data challenge, our work would be done.”

Intel’s acquisition of Mobileye showed how seriously the firm was taking this sector, particularly, as this publication pointed out, the difference in price compared to the $ 8.9bn Samsung is paying for Harman. “The faster we can deliver autonomous driving technology and take humans out of the driver’s seat, the faster we can save lives,” wrote Davis. “It’s that’s simple – and that important…and I am confident Intel will not only succeed in helping our partners put self-driving cars on the roads, we will do so in the fastest, smartest way possible.”

You can take a look at the full list of announcements here.

Picture credits: Intel Latest from the homepage

Actility acquires Abeeway for greater IoT location services

Actility, an IoT and M2M solutions provider, has acquired geolocation system specialist Abeeway with the aim to provide a best in class portfolio of IoT location services to support service providers and solution vendors across a wide range of industry sectors.

Abeeway, already a market leader in tracking devices, offers on-demand geolocation, movement alerts or geofencing that use GPS signals to determine their location, but energy-efficient LoRaWAN communication to pass that location to a tracking application. Hence, in comparison with trackers using cellular networks, they offer much longer battery life.

The key innovation developed by Abeeway, providing a powerful competitive advantage to Actility location services, is an assisted GPS technology specifically optimised for LoRaWAN, which allows fewer satellites to be used for a fix and reduces the GPS lock time to a few seconds. The power required for both GPS signal acquisition and processing is reduced: this combination results in a dramatic increase in battery life, by an order of magnitude versus existing GPS location technology.

ThingPark Location services will be accessible through APIs – when combined with the bidirectional capability of the LoRaWAN link – will allow developers to manage geolocation according to the needs of their application.

Olivier Hersent, Actility founder and CTO, said: “The unique advantage of our platform is its ability to serve a huge variety of use cases by combining different location technologies including network-based TDoA location, GPS and A-GPS, Bluetooth beacons and wi-fi ‘sniffing.’” Latest from the homepage

Connected car shipments will hit 70 million by 2022, says Frost & Sullivan

A new report titled “Global Connected Car Market Outlook, 2017” by Frost & Sullivan forecasts global connected car shipments will increase from around 25 million to almost 70 million units by 2022.

According to the report, automotive suppliers – considering the potential in data explosion – are attempting to capture and sell car data by leveraging their software and hardware platforms. While over-the-air (OTA), human-machine interface (HMI) and connected services generate direct revenue streams, Big Data analytics will help save costs and accelerate returns on investments (ROI) for automotive original equipment manufacturers (OEMs).

Frost & Sullivan mobility analyst Siddhanth Kumaramanickavel, said: “A notable example of cross-industry collaboration is the integration of virtual assistants such as Amazon Alexa into the vehicle. This allows non-automotive players to invest in connected homes and cars. Companies like Maluuba, iNAGO, Promptu, Sensory and Baidu also are working on offering natural speech assistants, AI-enabled speech assistants, and voice biometrics to automotive manufacturers.”

The adoption of 4G LTE has increased connected car uptake and widened the subscriber base for telematics services. On the other hand, retention rates following free trials remain low. In order to attract more buyers, car manufacturers are experimenting with new service models such as product-as-a-service. Commission-based and transaction volume-based models will define revenue streams as businesses move toward this model.

Kumaramanickavel noted: “As North America and Europe are generating ROI from connected, automated and mobility-related services, OEMs are focusing on introducing the same experience in emerging regions.”

Another report titled “Connected Car Devices Market – Global Forecast to 2021” by Research and Markets projects the global connected car devices to grow at a CAGR of 16.3% to $ 57.15 billion by 2021. According to the report, the Asia-Pacific region is projected to witness the highest CAGR in the period. Latest from the homepage

AI falls on the final furlong in predicting Kentucky Derby winner

The Kentucky Derby, one of the three races which make up the Triple Crown in US horse racing, was won over the weekend by Always Dreaming, the 9-2 favourite which came home by 2 ¾ lengths in cool and damp conditions. Yet for one company which placed its collective AI efforts on predicting the runners and riders correctly, Always Dreaming did not feature in their winners’ enclosure – despite getting the result spot on last year.

Unanimous AI, founded in 2015, offers what it calls ‘swarm AI’ technology which “amplifies human intelligence, empowering groups to harness their collective knowledge, wisdom and intuition by forming real-time AI systems,” in the company’s own words.

In other words, Unanimous AI aims to build a ‘super expert’ harnessing human capabilities with machine data usage. Partnering with TwinSpires, a horse racing betting firm, the aim was for not just a combination of individual race picks from the experts, but building an super expert and having them ‘think together’ as a real-time swarm moderated by AI algorithms.

Last year, the company made headlines by correctly predicting the superfecta – the top four horses in exact order – at odds of 542 to 1. This time round, the company’s picks were Classic Empire, which finished 4th, McCraken (8th), and Irish War Cry (10th). Always Dreaming was ranked fourth by its system, while Lookin at Lee, a 32-1 outsider, confounded the experts by finishing second – with the odds of the superfecta as a result being a whopping 76,000 to 1.

Prior to this year’s race, the company, led by Louis Rosenberg, was confident yet cautious about its chances. “While predicting sports always involve a large element of chance, Unanimous AI taps the intelligence of groups and evokes the best possible prediction based on the available information,” he said. “We have seen this work in a wide range of fields, from forecasting movie box office to predicting the price of Bitcoin. We are excited to see how these handicappers do against one of the most unpredictable of events.”

This time around, the post-mortem was more circumspect, although the company noted the odds were more significantly against them this time around, as well as adding it had still placed more horses than the average individual expert.

“The swarming process amplified the intelligence of the experts, boosting the average performance from 1.6 horses correct up to 2.0 horses correct. That means the experts would have been better off, as a group, going with the swarm than going with their own individual picks,” the company noted. “But without 32-1 Lookin at Lee in anyone’s forecast, the players’ pool missed out on the massive superfecta.”

You can read the full post from Unanimous AI here. Latest from the homepage

YoBike chooses Bristol for its ‘Uber-like’ bike-sharing launch

YoBike, a new app-based bike-sharing service, has chosen Bristol as its European launch city in the startup’s bid to make local transport more sustainable and convenient.

While bike-sharing schemes have seen rollouts not just in the UK but around the world; most require users to pick up and deposit bikes at set locations around the city. YoBike takes a smarter and more convenient approach with bikes able to be locked up (and picked up by other users) in any legal and safe location.

Our fleet of bikes will help Bristol meet its target for becoming a greener city

Built-in digital locks allow users to discover and unlock the bikes via YoBike’s app on iOS or Android and pay for the desired usage time. A bike can be rented for £1 per hour, 24 hours for £5, or an annual commuter pass is available for just £39 which allow for two, one-hour-long rides per day.

Similar business models to YoBike are popular in Asia but it’s the first time such a bike-sharing scheme is available in the UK. While most other schemes, including the so-called ‘Boris Bikes’ in London, offer heavy and clunky bikes – YoBike promises high-quality aluminium-alloy bikes which require minimal maintenance due to features such as punctureless tires.

YoBike has partnered with Bristol charity Life Cycle which trains prisoners in mechanic skills

If a bike goes missing after it’s been properly locked, YoBike will not charge the previous user and the bike should be able to be located using a built-in GPS. A number of measures have been implemented to deter thieves including a siren which goes off if the bikes are tampered with and custom-made parts which are useless to private bikes.

“Anyone who steals these bikes will be disappointed,” said YoBike UK CEO Michael Qian. “There’s really not much you can sell for use on other bikes and the bright yellow bikes themselves are so recognisable it would be very difficult to sell them on in one piece.”

300 of the bikes are set to be delivered to Bristol in May and will rise to more than 500 before the end of the month. Opening the app earlier today showed a wide selection of parking spots but not many bikes yet available:

“Our fleet of bikes will help Bristol meet its target for becoming a greener city, combatting congestion and setting an inspiring example to other cities across the UK”, comments Qian. “YoBike wants to promote and facilitate safe cycling, which is affordable and convenient for people living and working in the city”.

The company’s app is easy-to-use and offers some fun but useful stats including calories burned and the amount of carbon emissions saved.

Bristol is often considered to be an environmentally-conscious city and was awarded the European Green Capital award in 2015, but poor transport links have also led to it being among the most congested. YoBike will appeal to both denizens looking to live greener lifestyles and those just looking for cheaper and more convenient transportation options.

YoBike has partnered with a Bristol charity Life Cycle which trains prisoners in mechanic skills on how to strip down, repair, and rebuild bikes, with the aim of achieving City & Guilds accredited qualifications in Cycle Mechanics. Prisoners from HMP Bristol Prison will help with the maintenance of YoBike’s bikes following their initial launch phase.

Further adding to YoBike’s smart city credentials, the company is working with Drayson Technologies to add CleanSpace environmental sensors to the bikes. Usage data will be shared with local government to assist with future resource planning and congestion initiatives.

What are your thoughts on YoBike’s bike-sharing scheme? Let us know in the comments. Latest from the homepage