Category Archives: Internet of Things

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How the Revolutionary Mechanics of Blockchain Technology Could Serve Your Business

In the last entry in our cryptocurrency series, we explored how to secure your cryptocurrency with the right wallet. This week, we’ll take a look at the mechanics of the Blockchain across industries.

While the debate over whether Bitcoin will become the dominant cryptocurrency is far from over, the mechanics behind Bitcoin are unquestionably revolutionary. Blockchain technology has the potential to disrupt more than just currency, but industries ranging from healthcare to Wall Street.

The Blockchain is a secure ledger database shared by all parties participating in an established, distributed network of computers. The Blockchain decentralizes the process of validating transactions, allocating the duties to computers throughout the network.

Blockchain is revolutionary because it eliminates the need for a central authority, allowing for a real-time ledger that is not dependent on a single entity governing the transactions.

Imagine if in order to make changes to a text document, you had to email a colleague who would then update the document on Microsoft Word and send the updated file out to all relevant parties on the team. The updating of information would quickly become an inefficient process that is heavily dependent on the central entity (the colleague). Blockchain posits a workflow that is more like Google Docs in that it allows updates to be made in real time and shared across the network instantly without the need of a central authority. Blockchain enacts this principle by relying on computers within the network to independently validate transactions through cryptography. Thus, the validity of the ledger is determined by the many objective computers on the network rather than a single powerful entity.

The idea of decentralization can also be applied to WhatsApp, the popular messaging app that revolutionized texting and cut the cost of transactions globally. WhatsApp cut out the central authority of phone carrier companies by building the same functionality on a decentralized network (the Internet).

If you’re still confused about Blockchain, check out this awesome video by Wired breaking it down in 2 minutes:

Blockchain has already found usages in many different industries.

  • SMART CONTRACTS

Smart contracts are coded contracts embedded with the terms of an agreement. They are a method for businesses and individuals to exchange money, property, materials, or anything of value in a transparent way that avoids the services of a middleman (such as a lawyer). Smart contracts not only define the rules of an agreement, they automatically enforce the obligations provided in the terms of the contract.

Smart contracts have revolutionized the supply chain and threaten to eliminate the use of lawyers for enforcing contracts. Smart contracts and blockchain ensure data security that could also lead to the transferring of voting to an online system, potentially increasing voter turnout significantly.

  • HEALTHCARE

Within the healthcare industry, Blockchain has the potential to revolutionize data sharing between healthcare providers, resulting in more effective treatments and an overall improved ability for healthcare organizations to offer efficient care. A study from IBM showed that 56% of healthcare executives have a plan to implement a commercial blockchain solution by 2020.

  • SUPPLY CHAIN

Both within the Healthcare industry and elsewhere, blockchain is redefining supply chain management. Blockchain can provide a distributed ledger that tracks the transfer of goods and raw materials across wide-ranging geographical locations and stages. The public availability of the ledger makes it possible to trace the origin of the product down to the raw material used. For this reason, blockchain has also been applied to track organic produce supply chains.

The boon of the Internet of Things and smart objects means that blockchain technology can be extended to process data and manage smart contracts between individuals and their smart devices or even smart homes. Imagine a world where your refrigerator automatically orders eggs when it senses you are running low based on your egg eating habits. This world will be facilitated by a smart contract run on Blockchain technology embedded in an IoT device.

CONCLUSION

While the first blockchain was created for Bitcoin, applications for blockchain are constantly being implemented across industries. As Harvard Business Review smartly points out, the question in most industries is not whether blockchain will influence them, but when.

Many different cryptocurrencies are utilizing variations on Blockchain technology in order to process transactions—some of which are doing so in a more efficient manner than Bitcoin. Next week, we’ll explore the top cryptocurrencies on the market right now and which ones your business should accept.

Artificial

The Real Power of Artificial Intelligence

Technological innovations expand the possibilities of our world, but they can also shake-up society in a disorienting manner. Periods of major technological advancement are often marked by alienation. While our generation has seen the boon of the Internet, the path to a new world may be paved with Artificial Intelligence.

WHAT IS ARTIFICIAL INTELLIGENCE

Artificial intelligence is defined as the development of computer systems to perform tasks that normally require human intelligence, including speech recognition, visual perception, and decision-making. As recently as a decade ago, artificial intelligence evoked the image of robots, but AI is software not hardware. For app developers, the modern-day realization of artificial intelligence takes on a more amorphous form. AI is on all of your favorite platforms, matching the names and faces of your friends. It’s planning the playlist when you hit shuffle on Apple Music. It’s curating the best Twitter content from you based on data-driven logic that is often too complex even for the humans who programmed the AI to decipher.

MACHINE LEARNING

Currently, Machine Learning is the primary means of achieving artificial intelligence. Machine Learning is the ability for a machine to continuously improve its performance without humans having to explain exactly how to accomplish all of the tasks it has been given. Web and Software programmers create algorithms capable of recognizing patterns in data imperceptible to the human eye and alter their behavior based on them.

For example, Google’s autonomous cars view the road through a camera that streams the footage to a database that centralizes the information of all cars. In other words, when one car learns something—like an image or a flaw in the system—then all the cars learn it.

For the past 50 years, computer programming has focused on codifying existing knowledge and procedures and embedding them in machines. Now, computers can learn from examples to generate knowledge. Thus, Artificial Intelligence has already permanently disrupted the standard flow of knowledge from human to computer and vice versa.

PERCEPTION AND COGNITION

Machine learning has enabled the two biggest advances in artificial intelligence:  perception and cognition. Perception is the ability to sense, while cognition is the ability to reason. In a machine’s case, perception refers to the ability to detect objects without being explicitly told and cognition refers to the ability to identify patterns to form new knowledge.

Perception allows machines to understand aspects of the world in which they are situated and lays the groundwork for their ability to interact with the world. Advancements in voice recognition have been some of the most useful. In 2007, despite its incredibly limited functionality, Siri was an anomaly that immediately generated comparisons to HAL, the Artificial Intelligence in 2001: A Space Odyssey. 10 years later, the fact that iOS 11 enables Siri to translate French, German, Italian, Mandarin and Spanish is a passing story in our media lifecycle.

Image recognition has also advanced dramatically. Facebook and iOS both can recognize your friends’ faces and help you tag them appropriately. Vision systems (like the ones used in autonomous cars) formerly made a mistake when identifying a pedestrian once in every 30 frames. Today, the same systems err less than once in 30 million frames.

EXPANSION

AI has already made become a staple of mainstream technology products. Across every industry, decision-making executives are looking to capitalize on what AI can do for their business. No doubt whoever answers those questions first will have a major edge on their competitors.

Next week, we will explore the impact of AI on the Digital Marketing industry in the next installment of our blog series on AI.

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Everything You Need to Know About Machine Learning

A calculator can solve complex problems which would take even the most savvy mathematicians an incomparable amount of time. Artificial intelligence has become one of the most hotly debated and highly funded aspects of technology because the speed at which machines can process information yields innumerable possibilities and applications which can and will benefit humanity. One of the first popular incarnations of AI is Machine Learning.

Machine Learning is the ability for a computer to learn without being explicitly programmed. Machine learning focuses on computer programs which can identify patterns and create its own algorithms when exposed to new data. It is used in self-driving cars, in newsfeed algorithms on social media, in evaluating job candidates, in recognizing faces on your phone, and more.

The most powerful form of machine learning currently active is called “deep learning”. “Deep learning” builds a complex mathematical structure known as a neural network out of vast quantities of data. Machine learning’s ability to handle mass amounts of data makes it crucial to the advancement of IoT. The IoT collects enormous amounts of data which require computers with machine learning to recognize patterns and create algorithms.  In self-driving cars, IoT cameras and sensors in each autonomous vehicle absorb their surroundings and turn them into huge amounts of data. The data is then sent to the cloud where it is accessible to all autonomous vehicles on the road. Thus, when one self-driving car makes a mistake, all of them learn. In conjunction with the Internet of Things, machine learning will be vital to the building of a smartworld.

TOP PROGRAMMING LANGUAGES

Machine learning requires a great deal of statistical analysis; it demands an intelligent programming language which can process a number of complex issues and general paradigms.

R: Considered a statistical workhorse, R has emerged as one of the top programming languages for machine learning. R is intended for advanced users because of its complex nature and wide learning curve.

Python: A rising star for machine learning, Python is a data science book which has been in use in the manufacturing industry for awhile. Python gives users direct access to predictive analytics, making it the foremost data science language. Developers turn to Python when they are looking to frame better questions or expand the capabilities of their existing machine learning systems.

MATLAB/Octave: Millions of engineers are already using MATLAB, a matrix-based language, to analyze and develop cutting edge systems. MATLAB has emerged as the simplest way to demonstrate computational mathematics.

MACHINE LEARNING AND iOS 10

Machine learning laid much of the groundwork for the biggest upgrade in iOS 10. It is very difficult for computers to comprehend the intricacies of the human language. Machine learning has enabled iPhones to sense contextual clues with increasing confidence, improving iMessage’s ability to autocorrect and for Siri to understand the particulars of your vernacular. In the iPhone 7 camera, machine learning allows the device to separate the background from the foreground to achieve amazing portraits once possible only with DSLR cameras.

MACHINE LEARNING AND ANDROID

Google is among the dominant forces in machine learning. Much of Google Search’s prominence is owed to advances in the machine learning field. In November 2015, Google released TensorFlow, an open-source software library for machine intelligence. TensorFlow effectively simulates “deep learning” neural networks across different computer hardware and offers a straightforward way for users to train computers to perform tasks by feeding them large amounts of data.

Google uses Tensorflow in many of their internal processes, including RankBrain for information retrieval, image classification, SmartReply, and more.

MAXIMIZING MACHINE LEARNING IN MOBILE APPS

Now that mobile devices have the high productive capacity level to perform tasks to the same degree as a traditional computer, the question of what machine learning can offer apps has arisen. Large retailers like Amazon and eBay use machine learning in their mobile apps to improve customer experience with smarter product search and recommendation features, along with the ability to forecast buying trends with analytics.

While Machine Learning algorithms require a high level of programming experience and a ton of data to be effective, integrating apps with Siri & iMessage for iOS 10 allows developers to take advantage of the vast deep learning neural networks embedded into Apple’s 1st-party apps.

While the future of machine learning  on a commercial level remains to be seen outside of tech titans like Facebook, machine learning algorithms will be crucial in conjunction with the IoT in building a new SmartWorld with unparalleled predictive capabilities.

Securing Your IoT Devices Must Become a Top Priority

The Internet of Things has seen unprecedented growth the past few years. With an explosion of commercial products arriving on the marketplace, the Internet of Things has entered the public lexicon. However,  companies rushing to provide IoT devices to consumers often cut corners with regard to security, causing major IoT security issues nationwide.

In 2015, hackers proved to Wired they could remotely hack a smartcar on the highway, kill the engine and control key functions. Dick Cheney’s cardiologist disabled WiFi capabilities on his pacemaker, fearing an attack by a hacker.  Most recently, the October 21st cyber attack on Dyn brought internet browsing to a halt for hours while Dyn struggled to restore service.

Although the attack on Dyn seems to be independent of a nation-state, it has caused a ruckus in the tech community. A millions-strong army of IoT devices, including webcams and DVRs, were conscripted with a botnet which launched the historically large denial-of-service attack. Little effort has been made to make common consumers aware of the security threats posed by IoT devices. A toy Barbie can become the back door to the home network, providing access to PCs, televisions, refrigerators and more. Given the disturbing frequency of hacks in the past year, IoT security has come to the forefront of top concerns for IoT developers.

SECURING CURRENT DEVICES

The amount of insecure devices already in the market complicates the Internet of Things security problem. IoT hacks will continue to happen until the industry can shrink vulnerable devices. Securing current devices is a top priority for app developers. Apple has made an effort to combat this problem by creating very rigorous security requirements for HomeKit compatible apps.

The European Union is currently considering laws to force compliance with security standards. The plan would be for secure devices to have a label which ensures consumers the internet-connected device complies with security standards. The current EU labeling system which rates devices based on energy consumption could prove an effective template for this new cybersecurity rating system.

ISPs COULD BE THE KEY

Internet service providers could be a major part of the solution when it comes to IoT Security. Providers can block or filter malicious traffic driven by malware through recognizing patterns. Many ISPs use BCP38, a standard which reduces the process hackers use to transmit network packets with fake sender addresses.

ISPs can also notify customers, both corporate and individuals, if they find a device on their network sending or receiving malicious traffic. ISPs already comply with the Digital Millennium Copyright Act which requires internet providers to warn customers if they detect possible illegal file sharing.

With the smarthome and over 1.9 billion devices predicted to be shipped in 2019, IoT security has never been a more important issue. Cyber attacks within the US frequently claim the front page of the mainstream media. CIO describes the Dyn attacks as a wake-up call for retailers. The combination of a mass adoption of IoT and an environment fraught with security concerns means there will be big money in IoT security R & D and a potential slow-down in time-to-market pipeline for IoT products.

Will the federal government get involved in instituting security regulations on IoT devices, or will it be up to tech companies and consumers to demand security? Whatever the outcome, this past year has proved IoT security should be a major concern for developers.

Apple Brings the Internet of Things Home with HomeKit & iOS 10

Anyone engrossed in the tech scene knows the Internet of Things is one of the trendiest technology topics on the web. The IoT is shaping our world and building fortunes for innovators, futurists and top app development companies. However, in the common household, the IoT has yet to break through to the mainstream. The biggest company in the world is now looking to enact change.

Tim Cook, in his September Announcement, declared that iOS 10’s HomeKit update is the first time home automation has been integrated with a major platform. While Apple introduced HomeKit in 2014 with iOS 8, iOS 10 comes with a dedicated app called Home that controls all home automation devices.

HOME IS A HOME RUN

Home Apple App via Wareable

Home combines IoT technology with the masterful UI of iOS. Previous iterations of iOS and HomeKit required the user to manage each interface separately. So if a phone had 20 HomeKit apps, they would have 20 user interfaces to manage. The Home app unifies HomeKit apps, creating a central control center for all home automation applications.

With over 1 billion active Apple devices across the world, Home enters the market with giant global reach. Virtually every major manufacturer of home automation devices now supports HomeKit. Accessories cross all major categories, from lights and air conditioners to window shades, locks and home security. Commercial IoT companies now have massive domestic reach, and iOS users have more incentive to update their homes than ever before.

HAVE SIRI SET THE SCENE

Siri Scenes via Next Market

One of the coolest features of Home is the Siri integration. Users can control Home from both the Control Center and Siri, but Siri can work at the speed of your language. Siri’s ability to handle multiple requests means users can accomplish their ideal environmental preferences in the speed of a sentence. Apple refers to these combination commands as “scenes” and users can give “scenes” a nickname. A rambunctious user might say “Hey Siri, let’s get funky,” prompting Siri to lock the doors, dim the lights, put Barry White on the speakers at a reasonable volume and provide the most apt customized ambience for the user to rock out.

THE APPLE TV IS THE HEARTH

The fourth generation Apple TV can also act as a hub for the Home app, with the Siri Remote making it easy to control your home on the go. Apple TV’s seamless integration with HomeKit and other iOS products makes it the ultimate smart TV for a smart home, providing yet another reason for consumers to consistently buy iOS products.

BUILDING COMMERCIAL IOT FROM THE GROUND UP

The Home Automation page on the Apple website is a clear indicator of Apple’s intentions to not only be a household name, but to be the name on your household. The company already has a major market share of phones, tablets, computers, TVs and watches. They are rumored to be looking to acquire McLaren as a part of Project Titan. Apple understands that the ubiquity of the iOS platform makes them the most appealing platform for manufacturers of smart devices. Apple also announced that leading home builders, including Brookfield Residential, KB Home, Lennar Homes and R&F Properties, are integrating many HomeKit devices into new homes.

With the Apple Home potentially on the horizon, one can only wonder how much of Apple’s vision of the smarthome will be realized in the next 5-10 years.

Monetizing IoT: How the Internet of Things Builds Fortunes

A man sits in a restaurant and orders “The John Candy Burger” (a double cheeseburger with four strips of bacon and a fried egg) through a touch screen embedded into the table. As he gives the waiter his order, his smartwatch vibrates. He checks a push notification which tells him he should not order “The John Candy Burger” based on information gathered from a sensor in his body which has been monitoring his blood pressure and cholesterol among other notable health measurements in a constant stream of data for 15 years with infallible predictive capabilities. It tells him this specific cheeseburger from this specific restaurant will increase his risk of a heart attack on his daily run by 8%. He doesn’t understand how, but he accepts it the way one accepts that the earth is round and the Great Pyramid of Giza existed in 2540 BC.

In the above fictional example, the Internet of Things took the man’s order, evaluated the average nutritional content of the burger based on data gathered through sensors embedded into a smart grill, and transmitted it to the smartwatch where it analyzed nutritional content in the context of over 15 years of health data gathered on the man to inform him on the potential risk of his decision. The Internet of Things is bigger than money. It’s a new world where planes don’t crash and  smartphones can tell their users the location of the nearest empty parking spot to minimize travel time and ensure the city is maintaining optimum functionality. A pregnant wife is gently guided through a safe 9-month path to the newest addition to her family. The edges of the world are being smoothed out by data. The Internet of Things is leading the human race toward new levels of efficiency, productivity and effectiveness.

“Show me the money”

As a major technological evolution takes place, many businesses are looking to monetize it. Although the world has yet to see the full impact of the Internet of Things, it has already revolutionized process improvement for everything from manufacturing to health care, product enhancement, and safety. For the developer eager to enter a burgeoning field with infinite possibilities, here are some of the common techniques for monetizing IoT applications.

ONE-TIME PAY + FREE APP

The most basic monetization method entails creating a simple product with everyday applications, like Jawbone and the Phillips Hue Connected Bulb for example, and offering the equipment for purchase which works in conjunction with a connected app for iOS & Android. This method is most effective for products where the manufacturing cost to market ratio is kept low.

SUBSCRIPTION-BASED

One of the major issues with the IoT is the amount of data generated regularly by their devices. The amount of data and possibilities are so staggering, it’s vital to understand and decide upon relevant metrics and analysis tactics. For developers, it means that the cost of maintaining many IoT apps calls for a constant stream of revenue. Companies like Audi offer a hotspot subscription, ranging from 6 to 30 months, for Audi Connect, their hotspot navigation system utilizing Google Earth and Voice to offer real-time alerts, weather and traffic. In some applications, data plans will likely emerge as a another way of tiering subscription-based purchases.

WHITE LABEL SERVICES

Perhaps the most profitable and complex option, monetizing IoT applications through white label services entails having the foresight to identify the future of the technology and the necessary human & financial resources to act upon it effectively through the creation of a template offering which businesses can rebrand as their own. Jasper Technologies created the Connected Car Cloud as a cloud-based turnkey solution for developing smart-cars with real-time diagnostics, safety, security, and more.

Acquired by Cisco for about $1.4 billion in March, Jasper is one of the big success stories of IoT monetization and a model for future innovators looking to capitalize on the business opportunities brought about by the Internet of Things.

Learn more about IoT through this awesome article with advice from early adopters via Computer World.

Get Fluent in IoT: Top Programming Languages for the Internet of Things

As we explored in our previous blog, the Internet of Things is shaping our future. With Internet of Things development on the rise and potentially $11.1 trillion in economic value generated per year due to IoT, many companies are creating strategies to develop for the platform.

To all the decision-makers out there looking to develop for the loT platform, getting familiar with the programming languages and how they relate to the platform will have a major impact on the budget and quality of any given IoT project. IEEE, the largest technical professional organization dedicated to advancing technology for human benefit, recently ranked the top programming languages of 2015. Bearing in mind embedded devices present their own programming difficulties, here are the top programming languages for the IoT:

Java: James Gosling, Mike Sheridan, and Patrick Naughton began developing the Java language project in June 1991. Java has become the most popular programming language and many choose Java when developing for IoT. Java is an object-oriented language designed for portability. With few hardware dependencies, Java is a great choice from an economic standpoint. Java code can be transmitted to multiple platforms and hardware-support libraries give Java developers the ability to control specific pieces of hardware. Developing for Java can be deterred by the hardware-support libraries available for control functions.

Python: In December 1989, implementation of Python began. Designed by Guido van Rossum, Python is a multi-paradigm programming language which has become one of the go-to languages for web developers. Python’s flexibility and emphasis on readability have caused it to rise in the ranks of top languages used for embedded control and IoT. Readability increases workflow as programmers who have attempted to decipher other programmer’s optimized C code would know.

C: With development beginning in 1972 on the PDP-11 Unix system, C is one of the most popular programming languages. C has influenced many languages, including C++, Go, Java, JavaScript, & Python. Due to its long history, C functions as a common language for many software developers. C’s popularity and lack of built-in hardware bias toward a graphical interface make it a good choice for IoT development.

C++: Created in 1979 by Danish computer scientist Bjarne Stroustrup, C++ was designed as an object-oriented pre-processor for C, keeping the spare nature of the language but adding data abstraction, classes and objects. C++ is commonly used to write embedded and IoT code for Linux systems.

Assembler: Assembler is the simplest method intended to keep projects as compact as possible. Assembler is a low-level language which maintains a high correspondence between language and the hardware’s machine code instructions. Assembler minimizes overhead, making a popular choice despite how it doesn’t allow a safety net. Silly mistakes are easy to make and some hardcore programmers may be frustrated by its simplicity.

Go: Announced by Google in 2009, Go is an open-source, embedded-specific programming language gaining traction in the IoT world. Go supports concurrent input, output, and process different channels, an asset to gathering data from and sending data to separate sensors. Go was created in the tradition of C, but with specific changes to make it simpler, safer & more concise.

ParaSail: ParaSail was created in 2009 as an embedded-specific language. ParaSail stands for Parallel Specification and Implementation Language. ParaSail was created to support safe, secure, highly parallel applications which can be mapped to multicore, many core, heterogenous, or distributed architecture.

Choosing the right programming language will have a major impact on the budget and functionality of any IoT project. Doing the proper research on the subject will pay off in the long run. Stay tuned for more blogs on this subject and learn more about best IoT development practices via this awesome article by InformationWeek. 

Smartphones to Smartworlds: How the Internet of Things Is Shaping Our Future

Our five-part series on the top Mobile App Development Trends for 2016 has now reached part 4, where we’ll be discussing how the Internet of Things, IoT, is changing the world as we know it.

In November 2015, Gartner (a leading research and advisory firm) predicted 6.4 billion connected “Things” will be in use in 2016, up 30% from 2015. By 2020, they expect the number to reach 20.8 billion. McKinsey Global Institute recently reported that $4 trillion to $11 trillion of economic value could be generated by IoT by 2025. IoT has been consistently hailed as one of the biggest technology trends in the world, yet many people are confused about what the IoT really is.

Top put it simply, the Internet of Things is the network of physical objects embedded with electronics, software and sensors which enable them to collect large amounts of data and communicate with other smart objects. Jamboxes, smart cars, TVs, homes, gyms, bridges and more have been implanted with sensors that allows them to communicate with other devices and objects seamlessly.

Technically, the Internet of Things was created before the World Wide Web. In 1991, researchers at University of Cambridge used a camera, a frame-grabbing card, and a Motorola 68000 series-based computer to create a networked sensor to show the state of their communal coffee pot. Two major shifts have helped evolve the “IOT” into a billion dollar, world-changing industry:  shrinking prices and sizes of computer processors and sensors, and the evolution of the cloud. Cloud-based applications interpret and send data coming from sensors, enabling IoT to exist.

IoT is a major disruptor in virtually every industry: from agriculture to healthcare, car manufacturing, disaster management and more. Businesses are leveraging the IoT to save money and prevent potential threats from becoming catastrophes. The speed with which crucial data can be processed will give mankind incomparable control over asset, resource and disaster management. For example, smart cars will be equipped with unparalleled diagnostic systems capable of learning exactly what problems are happening and how to solve them in seconds. As Google has demonstrated, we’re headed toward a world of self-driving cars.

Self-driving cars only scratch the surface of what this type of object-to-object communication can achieve. Homes equipped with sensors which connect to the web can optimize energy efficiency based on temperature and the GPS location of the owner. Bridges will soon be built with smart cement equipped with censors which will evaluate stresses, cracks and warpages in a way which will allow them to communicate with authorities to fix problems before they cause disasters. IoT will create a smart world in which risk has been decreased significantly.

In order to leverage IoT, businesses need to not only invest money in technology, they must invest brainpower in innovation. As a burgeoning disruptor, the ramifications of the IoT haven’t quite processed in all industries. Management and business model innovation are required for the IoT to fulfill its potential across many industries. Those capable of capitalizing on the IoT will dictate the trends and sail to the top of their industries.

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