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When I ask people what they think the Internet of Things (IoT) is all about, the vast majority will say “smart homes,” probably based on personal experience. If I say that it is also about industries making using of data from sensors, then most people’s immediate reaction is to think of manufacturing. Sensors have been used for a long time in manufacturing, and the concept of using data generated at the edge to monitor and run automated processes is well understood.

This perception, however, is underselling the IoT. In practice, it can be applied anywhere.

Monitoring ‘things’

The use cases for industries with “things” to monitor are easy to identify.

Manufacturing is one of the most obvious. Connected sensors can be used to monitor and manage the health of manufacturing equipment, identify root causes of defects and improve quality.

Health care has equipment that generates digital information about how patients’ bodies are working (e.g., blood pressure) and what they look like (e.g., scans). There are numerous opportunities to monitor people’s health more closely and accurately and catch signs of disease early, or even avoid it altogether.

The insurance industry is using telematics to monitor driving behaviour and assess the risk posed by individual drivers. Telematics also helps with the claims process because information from before a crash can indicate who is at fault, and images of a damaged vehicle can be used to assess whether the car should be written off or repaired.

The IoT also, however, has potential in industries that, on the face of it, do not really have “things,” such as financial services. Banks and other financial providers are extremely interested in the IoT, focusing on “things” which do not belong to the banks themselves, but to customers: mobile phones and payment cards, for example. Banks can improve fraud detection by notifying customers each time their cards are used – in real time – and also checking that the customer is with the card at the time. That, clearly, is a huge service for customers: no more cloning and no more fraudulent transactions.

A change in business model

A fundamental shift in business model is being enabled by IoT analytics: a move from products to services. For example, Rolls-Royce is traditionally considered an engine manufacturer. The company made and sold engines, then sold services to maintain those engines. Now, however, rather than pay for maintenance, airlines can choose to pay an hourly rate for the time that the engine is propelling the aircraft. In other words, it can pay for what it actually wants: the plane in flight at particular times. Increasingly individuals, too, are choosing to pay for a service, rather than goods, such as access to a car-sharing service, rather than owning a car.

This shift, however, has challenges for the service providers. If you are providing a service that includes a physical asset, you do not want to have to spend time and resources inspecting that asset. Instead, you want it to run itself as much as possible. The IoT allows providers to remotely monitor and collect data on all the important aspects of each asset – how it is performing, how it is being used and environmental factors, for example – and therefore automate much of its management.

The data collected from the IoT is only really useful when you can derive useful intelligence from it, and preferably in an automated way. This automation, however, requires intelligence, and that means artificial intelligence (AI).

The importance of AI – and the problem

This is one of the biggest reasons why the IoT is really taking off now: AI algorithms are becoming more usable. There is, however, still a problem. Most AI algorithms need huge amounts of data and computing power. They therefore rely on powerful servers and central data storage.

In computing terms, we humans perform most of our computation and decision making at the edge (in our brain) and in the (pre-)moment, referring to other sources (internet, library, other people) where our own processing power and memory will not suffice. This is more or less the complete opposite of the current AI algorithms, which tend to perform most of their calculations far from the data source, in servers, drawing on stored data.

To enable timely decision making in the world of IoT, you need to be able to deploy some of the cleverness (predictive models and decisioning rules) at the edge, closer to the “things” that you are managing. Some businesses are already doing this, whilst many others are still trying to figure out how to organise and make sense of the deluge of data available to them. Those at the forefront of combining AI and IoT have a huge opportunity to steal a march on their competition.

In my personal view, this is the biggest change in business models since the dot-com boom. And, as in the 1990s, there will be some big winners, and there will also be those who don’t quite get it right, and fall by the wayside.

by Jennifer Major, Head of IoT, SAS

This blog originally appeared as a SAS "Higgen Insights" Blog

Photo by Franki Chamaki on Unsplash

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Until recently, we knew unicorns were mythical creatures which made an appearance only in Greek literature, the Bible, and Marco Polo’s travels. While not a single unicorn was ever discovered in the real world, these days, we seem to be dealing with a whole bunch of them, especially when it comes to business.

Technology has played a crucial role in small and medium businesses, made startups fashionable. Today we have many unicorns trotting about the business landscape.

The unicorns are celebrated for their successes and business acumen. Essentially, a unicorn is a start-up that is valued over $1 billion. When you think of them, think about, AirBnB, Uber, Xiaomi or even Flipkart. These are the new set of businesses that have disrupted the market in their respected sphere. But companies rise and fall all the time, so one may be tempted to ask what is so magical about these creatures?

The term Unicorn was coined in a TechCrunch article by Aileen Lee of Cowboy Ventures.

Part of the charm lies in reinventing the business model. They find a better way to do business. It may be a new idea or an improvement over the existing one. They offer a vision; a glimpse of what the future may hold and have an intense desire to grow.

Fuelling these dreams through constant innovation and the ability to adapt quickly. Precisely where some of the giant falter. Large businesses are bogged by internal processes and complexities resulting in delayed decision-making, allowing a start-up to swoop in.

 According to a study by CB Insights, there are around 175 unicorn companies globally.

The Unicorns and the Internet of Things

Many entrepreneurs have realized that IoT/IIOT technologies can level the playing field if they intend to dislodge industry giants. IoT Start-ups are looking to attract consumers or SMBs or large enterprises by increasingly relying on innovation on cloud and edge computing, IoT platforms, Artificial intelligence, IoT networks, IoT security or IoT devices.  Advanced technology is a key differentiator but not the only one- A new business model to attract customers could also become the initiator of a new unicorn.

After five years of exploring the fragmented but rich universe of IoT startups, no new unicorn has yet appeared. The most promising startups have seen their light turned off behind the Tech and Industry Giants check books. Those who are still pursuing their dreams of being unicorns see that the market does not accompany and no longer rely on analysts' predictions.

With all this, we may not see any unicorn of IoT. However, if I had to bet on some startups then these are my suggestions. 

The IoT Application Unicorn

My vote for the startup to become a unicorn in IoT Application category goes to: Uptake

Founded in 2014 by the CEO, Brad Keywell, that was also Co-Founder of Groupon, the company counts with a good number of investors. The company is stealing execs away from GE. (Uptake hiring several General Electric top digital executives) and have raised around $260 million since launching in 2014. Uptake was last valued at more than $2 billion, in fact, this startup is probably the first IoT unicorn. Uptake's revenue run-rate exceeds more than $100 million a year and future rounds of financing are expected.

LinkedIn profile: “Uptake helps industrial companies digitally transform with open, purpose-built software that delivers outcomes that matter. Built on a foundation of data science and machine learning, our vision is to create a world that always works — one where the machines and equipment we depend on daily don’t break, and industrial companies are once again the creators of economic growth and opportunity.”

WHY MY VOTE: Predictive analytics software is hot. The company sells to the mining, rail, energy, aviation, retail and construction industries and hopes to leverage data to improve safety, efficiency and productivity for their clients' operations. In spite his CEO has not accepted my LinkedIn invitation, no surprise to be honest, only 54% approve of CEO in glassdoor, the aggressive campaign against GE could launch the company this year. I like that his employees are sent directly to the field to observe fast hand the needs of its client base so they can really build software that solve real business problems.

ALSO FOLLOWING: FogHorn Systems a developer of “edge intelligence” software for industrial and commercial IoT applications..

The Hardware and Sensor Data platform Unicorn

My vote for the startup to become a unicorn in IoT hardware category goes to: Samsara

Samsara sells hardware and end-to-end solutions for fleet and industrial applications.

Samsara was founded in 2015 by CEO Sanjit Biswas and CTO John Bicket, who previously founded and led Meraki – a successful cloud networking company that was acquired by Cisco in 2012 for $1.2 billion. Samsara is based in San Francisco and was funded by Andreessen Horowitz (Raising $25M in funding). In May 2017, the startup announced that it had secured $40 million in a Series C funding round.

Sanjit Biswas, recognized that “They were definitely not the first to notice the technology trend behind the Internet of Things movement, but they realized no one was building products the way we did at Meraki, by combining hardware, software and cloud into an easy-to-use system”.

LinkedIn profile: “Samsara’s mission is to bring the benefits of sensor data to the organizations that drive our economy—from transportation and logistics to construction, food production, energy, and manufacturing—and to improve the safety, efficiency, and quality of their operations.”

WHY MY VOTE: Although not on this occasion his CEO accepted my invitation to LinkedIn, I like that Samsara disrupts the traditional sensor model with an integrated, software-centric solution. The products combine plug-and-play sensors, wireless connectivity, and rich cloud-hosted software, all tightly-integrated for simple deployment. Samsara is used by customers in a wide variety of industries, from transportation and logistics to energy and manufacturing. The company offers various solutions including fleet, ELD compliance, trailer, industrial, temperature, and power.

By focusing Samsara system for ease of use and streamlining deployments in the field, the teams were able to make several design choices that help them deliver a 10 times overall improvement over traditional solution. Samsara was in the list of “The 20 Fastest Growing IoT Companies” and is demonstrating is able to capture customers  in the fleet management and logistics industry against Verizon. The challenge is growth globally not only in US.

ALSO FOLLOWINGGeotab

The IoT Connectivity Unicorn

My vote for the startup to become unicorn in IoT connectivity category goes to: SigFox

LinkedIn profile: Founded in 2010 by Ludovic Le Moan and Christophe Fourtet, the company is headquartered in Labège near Toulouse, France’s “IoT Valley”. Sigfox provides connectivity for the Internet of Things (IoT). The company has built a global network to connect billions of devices to the Internet while consuming as little energy as possible, as simply as possible.

WHY MY VOTE: There are drastic limitations in the Sigfox global network. I could say that this will be the network of the stupid devices, but if they improve the network, ensure scalability, quality and security and allow interoperability with their competitors that will connect the most intelligent devices, then this startup will continue empowering companies to create new innovations on the IoT.

Sources announced that Sigfox is in peril as Senior Execs exit. The company has reacted but the pressure to growth in revenues and network deployment is high. Compete with the Telco Incumbents and the mighty powerful GSMA is a Hercules' own task. Some help from the French government and the EU will be appreciated, so the company can not be acquired. The Board and investors should guarantee the money the company need to comply with the high expectations of the market. In my opinion the window of opportunity is 2020. They have 2 years to demonstrate they can become the IoT-Connectivity unicorn.

ALSO FOLLOWINGActility, Link Labs, and of course the LORA alliance and M2M Service Providers.

The IoT -AI Platform Unicorn

My vote for the startup to become a unicorn in IoT/AI platform category goes to: C3IoT

I have written a lot about IoT platforms and I think that most startups will disappear in 3-5 years or they will never become a digi-unicorn. But there is a special case that can reach the end of the road. Mainly for who is behind, my old CEO Thomas Siebel.

LinkedIn profile: C3 IoT is an AI and IoT software platform provider for digital transformation. C3 IoT delivers a comprehensive and proven platform as a service (PaaS) for rapidly developing, deploying, and operating large-scale AI, predictive analytics, and IoT applications at scale for any enterprise value chain in any industry. At the core of the C3 IoT offering is the revolutionary C3 Type System—an extensible, model-driven AI architecture that dramatically enhances data scientist and application developer productivity. C3 IoT also offers configurable, high-value SaaS products for predictive maintenance, fraud detection, sensor network health, supply chain optimization, energy management, and customer engagement.

WHY MY VOTE: In January 17, 2018, the company announced a new round ($100 Million) of financing by existing investors TPG Growth, Breyer Capital, Sutter Hill, Pat House, and Thomas M. Siebel.

After the sale to Oracle of its CRM business, Tom, could with this new adventure, return to be relevant in the industry and I think he will not allow his new baby to be acquired. Not at least until he makes C3 IOT a unicorn.

ALSO FOLLOWING: The competition in the AI-powered industrial IoT sector is brutal, but the opportunity is big enough that the 10 startups highlighted here still have room to maneuver and time to scale up. I also keep an eye on them because one or more could well be the next unicorn in this hot market.

Key Takeaway:

Not being a IoT unicorn is not a tragedy. Many companies that started in the M2M business or that have been born in the heat of the IoT are doing well. Their employees are happy and satisfied customers guarantee a long life.

In my post “Is it possible to democratize the Internet of Things? How to avoid that a handful of companies can dominate the IoT”, I pointed out the opinion of Ryan Lester (Director of IoT Strategy, Xively by LogMeIn company acquired by Google). Ryan alerted that IoT feels only achievable to those companies with unlimited resources to make it happen. Looks like, the facts have given him the reason.

Yes, I admit, I would like to see unicorns in IoT. I would also like startups not to be obsessed with this issue and not throw in the towel too soon. If they are acquired, their legacy is very likely to be lost soon and in exchange for money they will have lost the opportunity to contribute to changing the world with their unique innovation in IoT.

Thanks in advance for your Likes and your Shares.

References:

http://www.moneycontrol.com/india-business-live-ibl/growth-for-sme/article/unicorns-in-our-midst-7501221.html

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The dream of making money with IoT, AI and Blockchain

Have you ever think about how could you make money with the Internet of Things (IoT) or Artificial Intelligence (AI) and of course with Blockchain?  What would happen if you could use the three of them in a new business model?.  Apparently, Success, Success and Success.

In the next sections I provide information of some business models implemented with these three technologies.

IoT Business Models

As IoT moves past its infancy, certain trends and economic realities are becoming clear. Perhaps the most significant of those is the realisation that traditional hardware business models just don’t work in IoT. Take a look at “The top 5 most successful IoT business models” that have emerged as particularly effective applications for IoT.

If any of you is building an IoT product, this article ” IoT Business Models For Monetizing Your IoT Product”  show how to make money with IoT.

Zack Supalla, the founder and CEO of Particle, an Internet of Things (IoT) startup, suggest “6 ways to make money in IoT”.

Finally, in “How IoT is Spawning Better Business Models” we can read three ways companies like Rolls Royce, Peloton, MTailor or STYR Lab  was rethinking their business model and have created revolution in the marketplace. 

Blockchain Business Models 

It sounds repetitive, but yes "Blockchain technology may disrupt the existing business models”. The authors´ s findings concerning the implications of blockchain technology for business models are summarised in the following picture.

 

Do you think that blockchain will likely to cut into big-players’ revenues? Then, this article: “New Blockchain-Based Business Models Set to Disrupt Facebook and Others”, is for you.

If you are ambitious and you are planning to build a viable business on blockchain, then read “Building an International Business Model on Blockchain”.

I am also an advocate of the coming era of decentralization (at least in my most optimistic version) and Blockchain is a step more to create value when the End of All Corporate Business Models will arrive.

AI Business Models 

Companies from all industries, of all shapes and sizes are thus faced with an important set of questions: Which AI business models and applications can I use ? And what technologies and infrastructures are required?.

It seems that we all are convinced that artificial intelligence is now the most important general-purpose technology in the world that can drive changes at existing business models. Not surprised then, that  AI is Revolutionizing Business Models.  The “data trap” strategy, that in venture capitalist Matt Turck’s words consists of offering (often for free) products that can initialize a data network effect. In addition, the user experience and the design are becoming tangibly relevant for AI, and this creates friction in early stage companies with limited resources to be allocated between engineers, business, and design.

This article introduces  some good examples of AI business models :

New Business models with the intersection of IoT, AI and Blockchain

With IoT we are connecting the Digital to the Physical world. Connected objects offers a host of new opportunities for companies, especially in terms of creating new services. The amount of data generated by the billions of connected objects will be the perfect complementary feed to many AI applications. Finally, blockchain technology could be used to secure the ‘internet of things’ and create smart contracts in a decentralized infrastructure that boost the democratization of technology and creation of sustainable communities.

You must remember that new business models that include IoT, AI and blockchain need among other characteristics: Volume and Scalability. Volume of devices, Volume of data, Volume of customers, volume of developers and powerful ecosystems to escalate. 

Good luck in your search and implementation of your new business model.

Thanks for your Likes, Comments and Shares

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We are in the dawn of a new cyber society. A society where organizations shall design plans to utilize the unique skillsets of both AI Systems and humans. A society where Humans and AI systems shall work and live together and without fear. A society where humans shall use newfound time and freedom to advance strategic skills and individual talents.
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As mobile devices become smaller and smarter, artificial intelligence (AI) is steadily gaining significant popularity among users and developers alike. Every now and then mobile developers around the world are working assiduously to develop and employ the emerging technology in mobile app development which is aimed at improving the way users interact with apps. Already, there are several signs, indications, and signals revealing that the AI will dominate the future of mobile apps.

In the tech world, AI is believed to hold immense potential and Indian app developers are gradually embracing and integrating this relatively new technology into their mobile app development seeing that it presents the best bet for the future. Already, the current mobile app market is consequently being flooded with new mobile applications and models leading to the creation of new and improved mobile app development services.

Even if you don’t notice it, AI is already around you and it has come to stay. In the past, this technology was only regarded as a futuristic concept for movies but today it has become a reality. And there is no better time to get involved with the trend than now. Interestingly, many Indian app developers are beginning to discover that mobile development and AI share common features and can make a perfect match. Obviously, there are lots of possibilities that can be accrued from the advancement of AI.

Combining artificial intelligence (AI) with mobile development will result in the creation of intelligent apps. Basically, this is concerned with the design and development of mobile apps that have the ability to learn, think logically, and solve problems. In a bid to effectively engage users, transform customer experience, and ultimately retain them, many app developers and top app development companies in India alike are already working to integrate the technology into their mobile applications.

The impact of AI on mobile development

Many tech and industry experts are suggesting that AI will be a major trend in various sectors, particularly in the mobile application development. To this end, everyone in the industry including, startups, growing businesses, and top app development companies are investing in artificial intelligence (AI) with the aim of providing efficient customer services and bring about a positive change. While some are incorporating the technology in the form of chatbots, others are looking to embed it into the infrastructure of their mobile app development as assistants to create smart apps.

Already, some tech giants like Uber, Amazon, eBay and the rest are making use of AI and judging from the look of things, it is a meaningful realization. With this new technology, Indian app developers are helping businesses support their customers with relevant, seamless, and personalized services. With time AI in mobile apps will understand customer behavior, thanks to its ability to effectively gather massive amounts of data from previous customer interactions and learn them. Apart from helping to bring customers closer to the business, AI-enabled apps are also helping to enhance customer interaction thereby boosting customer retention rate.

Basically, Indian app developers are finding ways to make use of the data that businesses are getting via mobile devices, online traffic, and point-of-sale machines to impact both business and consumer experience with AI’s influence. As more artificial and machine learning-driven apps make their way into app stores, things will change in the way and manner people communicate and interact. In a bid to create more insightful, context-rich experiences, the algorithms will be able to sift through the obtained data, find correlations and trends and get the apps adjusted to suit the personal needs of the user.

Obviously, there is much to achieve with these artificial intelligence algorithms in mobile app development. There is a wide range of AI-based mobile app development projects undertaken by Indian app developers. With the development of personal assistants, chatbots, and other artificial intelligence features, many big companies are already reinventing their user experience (UX) strategies. And in order to remain ahead of the competition, other businesses are following suit.

The future of AI-driven apps

Now that the entire ecosystem has been enhanced with regular and active access of data management and delivery, many Indian app developers will be employing AI which will become an essential necessity for robust mobile app development in the near future. Basically, there is every need for systems featuring data governance, data security, and metadata management to be fast and robust in indexing and cataloging.

Here are other ways through which AI development will impact the industry

Cloud services

It’s no longer news that businesses are adopting cloud computing technology to improve their services. It may interest you to know that Indian app developers will not only be adopting this technology to enhance development but will also be using it to troubleshoot errors in AI-driven apps.

Business apps

As already mentioned, many businesses are already seeking to enhance customer interaction by investing mobile app development. However, integrating AI will help to boost convenience for customers and also help businesses reach a wider target audience. Businesses will not only be using AI-driven apps to observe internal communications, but these will help to simplify business activities in several ways.

Location-based applications

Today, people are using location-based apps to search and find virtually anything they need in any location. AI-enabled apps will be synchronizing users’ interest, as well as their frequent searches to create results. Basically, these apps will be using obtained data to provide more desirable suggestions. Already, Google users can easily search for promotion offers, nearby restaurants and department stores with their smartphone via Google Assistant or Siri.

Internet of Things (IoT)

In recent times, there has been an increase in a range of new technologies due to the desire to further increase the mobility of users. IoT is one of such recent developments making waves in the industry. No doubt, AI will be enhancing the development of IoT helping smartphone users manage real-life events in the near future.

AR and VR

Together with AI, Augmented Reality (AR) and Virtual Reality (VR) is taking both the gaming and entertainment industry by storm. The release of Oculus Rift, Google Cardboard, Samsung Gear VR and other numerous models of VR devices are already influencing the industry.

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Artificial intelligence is one field of science and technology that is wildly becoming popular. Artificial intelligence involves the introduction of human level precision and accuracy to bots. Artificial intelligence has found application by top app development companies in every field of life; from medicine to tourism, from engineering to production. Artificial intelligence has helped to automate our work and has made life easier. Below are 10 most popular artificial intelligence apps for iPhone/iOS;

  1. Google Allo:

Google Allo is one of the best artificial intelligence apps for messaging available for iOS users which can be used in iPhone app development. It allows users to take action on their smartphones using their voice; such as voice to text input. The app comes with emojis and stickers that allows users to easily express their emotions and feelings. It also has a smart reply feature. The app also provides an incognito mode option that allows users to hide their search history from their smartphone.

  1. ESLA Speak:

Perhaps you want to learn how to speak and write English and don't have an English teacher close by. No need to worry, ELSA Speak is one of the best and most popular iOS apps for iPhone app development that helps users to learn English Language in less than 4 weeks. With this app, English speaking users can also improve their pronunciation of English words and phrases. The app comes with English test designed by experts, which allows users to test and estimate their progress. The app also comes with day by day full progress report.

  1. Cortana:

Perhaps what you need is a personal assistant that can help to arrange and keep track of your documents, images and act as reminder for your scheduled event, then Cortana is one of the your best iOS artificial intelligence app that is of importance in iPhone app development that can perform this function. This artificial intelligence app can easily sync between your mobile phone and laptop, so regardless where your files are kept or where your schedule is listed, Cortana can perform its function perfectly well. Cortana can provide its users with their favorite TV shows, series, sports, artists etc.

  1. Robin:

Robin is an iOS artificial intelligence app that combines the function of a personal assistant and a voice-to-text app. Users can use this app to write text without having to touch their mobile phone, only by the use of voice. It allows users to set reminders for important events or work that needs to be done. It also allows users to get GPS navigation, hence locating places more easily.

  1. Socratic:

Math is one of the biggest challenges for students all around the world. Finding a quality math tutor to help out with homework is equally as difficult as the math problems given. But Socratic is here to help. Socratic is one of the most popular and smartest math homework helper available on iOS that is very important in iPhone app development. Socratic will help users with their math homework in good time and with expert technique. It artificial intelligence feature is one of the smartest. All that is needed is for users to take a picture of their homework using the camera app and instantly the AI provides you with concepts that can assist in solving the problem.

  1. Edison Assistant:

Also known as easilyDo Smart assistant app, Edison Assistant is an artificial intelligence app that works as a personal assistant and informs users about traffic conditions between where they are and their destination. It informs on better, shorter routes devoid of traffic that users can take to get their destination or when the best time is to leave their present location to their destination. As a personal assistant, it helps to delete multiple contacts from users smartphone and also help to book ticket to hotels, events, movies, restaurant and so on.

  1. Siftr Magic:

Siftr Magic is a very effective artificial intelligence iOS app that is of importance in iPhone app development, which helps users free up space on their smartphone by helping to clean up junk photos and videos. Photos typically taken by smartphone tend to be large in size and they easily fill up space. Finding the images to delete to free up space may be quite difficult. Siftr Magic uses artificial intelligence to sift through thousands of images in seconds and identify duplicate images or images that are not relevant and needs to be deleted. The app does not delete images on its own, it only makes recommendation based on the content of the images and the number of times it has been viewed.

It also helps to identify and remove battery draining apps or problems, so as to improve battery life.

  1. SwiftKey Keyboard:

This is the most popular artificial intelligence iOS keyboard app that helps to automatically correct wrong words or sentences. Aside from its auto-correct feature, the app comes with the ability to change font style, color, size, theme, and design. It comes with emojis that can help users express feelings.

  1. Replika:

Replika is one of the most advanced iOS artificial intelligence app that is of importance in iPhone app development. It is known as the good friend app as users can have an endless conversation with the app. The app is so advanced that having a conversation with it appears like having a conversation with a real friend. What's more, Replika has the ability to, over time, learn the preferences of the user, therefore its conversation changes from being generic to become more specific and personalized. Replika is your best friend on mobile, and it is available anytime you need it 24/7.

The app also comes with a notepad, allowing users to save notes and memories, which will be easily available at any time.

  1. Seeing AI:

Seeing AI is one of the most effective and advance artificial intelligence iOS app that is built for visually impaired users. This app is giving hope to visually impaired individuals, allowing them to interact better with their surroundings. Using the phone camera, Seeing AI has the ability to read signs, letters, identify people and relay it back to users. Visually impaired people can understand text, recognize setting, and even know what the weather looks like. One of the most impressive features of the app is its ability to recognize people's emotions, therefore users can know how people around him/her feels.

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Be careful of the Walking Dead of IoT

Those who follow my articles know that I like to make comparisons between the IoT and TV shows and movies. For this article, I have selected the famous show "The Walking Dead" (TWD).

When preparing this article, I read this piece “The Real Walking Dead: Surviving the Software-Defined Zombie Apocalypse” by Scott Noteboom and I thought, well, I am not alone. As Scott, I see a lot of similarities between IoT technology and biology.

Many companies are thinking about their survival after the apocalypse that will be produced by the mix of IoT, AI and Blockchain. CEOs, must make decisions that prevent their companies from disappearing or worse becoming walking dead. And one of the most important will be choose their travel companions well, in order to build a strong ecosystem capable of resist the most adverse scenarios one might think.

IoT solutions that companies need to implement to survive the apocalypse are composed of many apparently simple blocks (devices, protocols, edge computing, fog computing, communication networks, platforms, cloud, analytics, AI, Machine Learning, blockchain, security, applications). But the selection of the vendors and the integration of all of them in the business processes, systems and organizations of companies is complex and there are few companies who can boast of having achieved it.

You probably are tired of hearing that the IoT is very complicated and the ecosystem is very fragmented. You feel that many will become walking dead. But, no one has the crystal ball to know who will be the IoT companies are going to continue within 10 years, not even within 1, 2 or 3 years. Some of them are perhaps in the phase of becoming, when just a couple of years ago they were in good health and of they enjoyed the sympathy of the analysts.

If you have been living in a sanctuary, isolated, it will not last for a long time. You will receive soon the visit of survivors and walking dead. You have to decide to accept or fight the survivors and you must protect your community against the zombies.

The good news is that you are not alone. During the last 5 years I have lived 24x7 by and for the IoT. I have been monitoring and analyzing the IoT landscape. I have seen many IoT start-ups appear and some disappear. We have seen large companies make absurd purchases, or sell IoT businesses when they have not been able to obtain the expected return.

That´s why I am able to provide wise advice and recommendation to avoid from being trapped by partnerships with potentials Walking Dead of the IoT and help you build robust and scalable IoT solutions.

Do not walk blind alone among The Walking Dead of IoT

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The past decade witnessed the emergence of two of the most significant technologies- virtual reality and Internet of Things.

Virtual reality refers to the use of technology to counterfeit an environment where the digital world seems real. It aims to place the user inside an experience, consequently enabling them to interact with the 3D worlds. On the other hand, Internet of Things is all about making real-world objects connect and manipulate in the digital world.

While both these technologies work to bring augmented ease to our lives, it's the convergence of the two that offer the most promising opportunities. Becoming quickly enmeshed in the prevailing times, the two disruptive technologies have largely revolutionized the industrial platform.

The meeting point of the two technologies boasts of immense potential. Let’s understand this with some examples.

1) Telepresence

The encroachment of telepresence depicts the colossal potential of the confluence of IoT and VR. If we talk about a typical video conference, the system includes a monitor screen, sound system, and codec. You can add additional speakers or a projector screen to improve the video conference experience. However, with telepresence, it is not the same.

With an aim to extend near lifelike audio and video quality, telepresence leverages compound multi-codec, multi-monitor, and multi-speakers. It has successfully transformed the way we can communicate with others over long distances. It offers the ability to look and move freely within a real-world environment, giving the illusion of actually being present there.

Telepresence has efficaciously eliminated the time and financial constraints related to travel. Offering all the benefits of a face-to-face interaction, it has made long-distance meetings exceedingly convenient.

2) Virtual Smart Cities

An increasing number of cities around the world are looking to become “smart” in order to improve comfort, reduce costs and consumption of resources and augment the quality of life of its citizens. Consequently, for the concept to materialize, it is significant that Internet of Things along with its accessibility to public grows. This will enable adequate accurate data to be amassed in cities for analysis and forecasting.

Moving ahead, these cities need to be integrated into a well-controlled virtual environment. This will allow an accurate analysis of the prevailing city conditions as well as help in making predictions of the impending future scenario. Thus, any kind of risk or disaster can be effectively monitored to simulate its effects.

3) Healthcare

The union of VR and IoT technologies has greatly assisted the healthcare field by bringing improved ease to patients as well as doctors. A competent example of this is robotic-assisted surgery, which has been in use for quite some time now. Also known as da Vinci Surgical System, it allows the surgeons to perform a least invasive surgery. A camera along with a few tools is inserted into the body through a relatively small opening that allows the surgeon to get a full view of the operating area without exposing the patient to the ordeal of a large incision.

The system includes a 3D HD vision system and small wristed devices that revolve and bend much better than the human hand, thus enabling improved vision, control, and accuracy.

But, this is just the beginning. It is anticipated that VR surgeries will soon control real da Vinci systems, permitting surgeons to operate on patients while sitting in their offices.

Final Thoughts

Considering the potential of the two technologies, more and more companies are investing into the development of new applications of both virtual reality and internet of things and because of that, in past several years so many IoT App development companies has been evolved in the market. In the following year, it is predicted to see a growing number of integration of smart objects within virtual simulations, for purposes such as leisure, training, or damage prevention.

 

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Believe it or not, but the possibilities that the Internet of Things, IoT brings to the table are countless. The internet of things, IoT continues to be the next big thing in technology, and now the new phase of the internet of things is pushing everyone hard to ask questions about the data collected by sensors and devices of IoT.  

Undoubtedly, the internet of things, IoT will generate a tsunami of data, with the swift expansion of sensors and devices connected to the IoT. The sheer volume of data being produced by the internet of things will rise exponentially in the upcoming years. This generated data can provide extremely valuable insight to figure out what’s working well and what’s not. Moreover, the internet of things, IoT, will point out the issues that often arise and provide meaningful and actionable insight into new business opportunities and potential risks as correlations and associations are made. 

Examples of IoT Data:  

  • Data that improves productivity of industries through predictive maintenance of equipment and machinery 
  • Data that assists smart cities in predicting crime rates and accidents   
  • Data that creates truly smart living homes with connected devices    
  • Data that provides doctors real-time insight into information from biochips to pacemakers 
  • Data that gives critical communication between self-driven automobiles          

That’s great news, but it’s not possible for humans to monitor, analyze and understand all of this data using traditional methods. Even if they reduce the sample size, it will simply consume too much of their time.  Undoubtedly, finding actionable insights in terabytes of machine data is not a cakewalk, just ask a data scientist. The biggest challenge is to find ways to analyze the deluge of performance data and information that the internet of things, IoT devices creates. The only possible way to keep up with the terabytes of data generated by IoT devices and sensors and gain the hidden insights that it holds is using Artificial Intelligence, commonly known as AI.  

Artificial Intelligence (AI) and IoT    

Artificial intelligence, also known as machine intelligence (MI) is the intelligence that is exhibited by machines or software. John McCarthy, the person who coined this terminology back in 1955, describes it as "the science and engineering of making intelligent machines". In a nutshell, AI is a branch of computer science that emphasizes the creation of an intelligent machine that thinks intelligently, the way intelligent humans think and works and reacts like humans.   

In an IoT environment, Artificial Intelligence (AI) can aid business enterprises take the billions of data points they have and prune them down to what’s really helpful and actionable. The general principle is akin to that in retail applications i.e. review and analyze the data you have collected from different sources to find out similarities or patterns, so that better business decisions can be made.  

To be able to figure out the potential risks or problems, the collected data has to be analyzed in terms of what’s normal and what’s not. Abnormalities, correlations, and similarities need to be identified based on the real-time streams of data generated. The collected data combined with Artificial Intelligence makes life easier with predictive analytics, intelligent automation, and proactive intervention. 

Artificial Intelligence in IoT Applications  

  • New sensors will enable computers and smart devices to “hear,” gather sonic information about the user’s ambience   
  • Visual big data will allow computers and smart devices to gain a deeper insight of images on the screen, with the new AI app that understands the context of images

These are some of the promising applications of Artificial Intelligence in the internet of things, IoT ecosystem. The potential for highly personalized services are countless and will dramatically change the way people live. For example, Amazon.com can suggest what other books and movies you may like, helping Saavn and Gaana to determine what other songs you may love listening, and your family doctor would receive notification if you’re not feeling comfortable.  

Here Are Some Challenges Facing AI in IoT

  • Artificial Stupidity
  • Complexity
  • Safety
  • Ethical and legal Issues
  • Compatibility
  • Privacy/Security 

What’s Next? 

Gartner has predicted that by the end of next year, 6 billion connected devices will be requesting support, which means that processes, technologies, and strategies will have to be in place to respond to them. It is important to think of connected devices less as ‘things’, but more as customers or consumers of services in themselves. The need for Artificial intelligence, AI will become more prominent at the stage when the number of connected devices and sensors increase manifold.

Hope you find this post helpful. If you did, share it with your friends and colleagues. For AI and IoT Courses Online, you can do some research on Google to find the best institute that suits your needs and budget.

For any query related to this post, you can comment down below. Thanks for your time. 

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How Customer Analytics has evolved...

Customer analytics has been one of hottest buzzwords for years. Few years back it was only  marketing department’s monopoly carried out with limited volumes of customer data, which was stored in relational databases like Oracle or appliances like Teradata and Netezza.
SAS & SPSS were the leaders in providing customer analytics but it was restricted to conducting segmentation of customers who are likely to buy your products or services.
In the 90’s came web analytics, it was more popular for page hits, time on sessions, use of cookies for visitors and then using that for customer analytics.
By the late 2000s, Facebook, Twitter and all the other  socialchannels changed the way people interacted with brands and each other. Businesses needed to have a presence on the major social sites to stay relevant.
With the  digital age things have changed drastically. Customer is superman now. Their mobile interactions have increased substantially and they leave digital footprint everywhere they go. They are more informed, more connected, always on and looking for exceptionally simple and easy experience.
This tsunami of data has changed the customer analytics forever.
Today customer analytics is not only restricted to marketing for churn and retention but more focus is going on how to improve the customer experience and is done by every department of the organization.
A lot of companies had problems integrating large bulk of customer data between various databases and warehouse systems. They are not completely sure of which key metrics to use for profiling customers. Hence creating  customer 360 degree view became the foundation for customer analytics. It can capture all customer interactions which can be used for further analytics.
From the technology perspective, the biggest change is the introduction of  big data platforms which can do the analytics very fast on all the data organization has, instead of sampling and segmentation.
Then came  Cloud based platforms, which can scale up and down as per the need of analysis, so companies didn’t have to invest upfront on infrastructure.
Predictive models of customer churn, Retention,  Cross-Sell do exist today as well, but they run against more data than ever before.
Even analytics has further evolved from descriptive to predictive to prescriptive. Only showing what will happen next is not helping anymore but what actions you need to take is becoming more critical.
There are various ways customer analytics is carried out:
·       Acquiring all the customer data
·       Understanding the customer journey
·       Applying big data concepts to customer relationships
·       Finding high propensity prospects
·       Upselling by identifying related products and interests
·       Generating customer loyalty by discovering response patterns
·       Predicting customer lifetime value (CLV)
·       Identifying dissatisfied customers & churn patterns
·       Applying predictive analytics
·       Implementing continuous improvement
Hyper-personalization is the center stage now which gives your customer the right message, on the right platform, using the right channel, at the right time
Now via  Cognitive computing and  Artificial Intelligence using IBM Watson, Microsoft and Google cognitive services, customer analytics will become sharper as their  deep learning neural network algorithms provide a game changing aspect.
Tomorrow there may not be just plain simple customer  sentiment analyticsbased on feedbacks or surveys or social media, but with help of cognitive it may be what customer’s facial expressions show in real time.
There’s no doubt that customer analytics is absolutely essential for brand  survival.
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In the age of  Digital Transformation, Artificial Intelligence has come a long way from Siri to driverless cars.
If you have used a GPS on Google Maps to navigate in your car, purchased a book recommended to you by  Amazon or watched a movie suggested to you by Netflix, then you have interacted with  artificial intelligence.
Artificial Intelligence is the capability of a machine to imitate intelligent human behavior which relies on the processing and comparison of vast amounts of data in volumes with help of  big data  analytics, no human being could ever absorb.
Stephen Hawking, Elon Musk, Bill Gates have recently expressed concern in the media about the risks posed by AI.
According to them, AI will soon replace all kinds of manual tasks and make humans redundant. This could be true in some sense but still this is a far cry from the current maturity levels of AI, which is still at the stage of figuring out real-world use cases.
Today machines can carry out complex actions but without a mind or thinking for themselves. Smartphones are smart because they are responding to your specific inputs.
The world’s top tech companies are in a race to build the best AI and capture that massive market, which means the technology will get better fast, and come at us at faster speed. IBM is investing billions in its Watson, Apple improving Siri, Amazon is banking on Alexa;  Google, Facebook and Microsoft are devoting their research labs to AI and robotics.
Together, they will swirl into that roaring  twister, blowing down the industries and businesses in its path.
Within maybe few years, AI will be better than humans at diagnosing medical images and converting speech to emotions. But it can also be stealing millions of records from a government agency to identify targets vulnerable to extortion.
Soon you’ll be able to contact an AI doctor on your smartphone, talk to it about your symptoms, use your camera to show it anything it wants to see and get a diagnosis that tells you to either take a couple of Tylenols or see a specialist.
In all the fairy tales we have seen so far, good almost always wins over evil.
This is what we have seen in the movies like I, Robot or Avengers: Age of Ultron.  But Will Smith or team of avengers does not know that till end of the story. That’s where we are now: face to face with the demon for the first time, doing everything we can to get through the scary plot alive.
Today many companies are using AI for improving their business:
·         Geico is using Watson based  cognitive computing to learn the underwriting guidelines, read the risk submissions, and effectively help underwrite
·         Google Translate applies AI in not only translating words, but in understanding the meaning of sentences to provide a true translation.
·         IBM Watson is the most prominent example of AI based question answering via petabytes of data retrieval that helps in various areas like finance, healthcare & insurance.
As Humans we are programmed from childhood either by nurture or nature to do things the way we do. All the nine emotions we have learned since then are the inseparable part of our lives.
Currently we are in the control of the planet because we are smartest species compared to all the animals.
But when, and if machines learns to love or hate, work in peace or retaliate in anger, then it’s not too far that, with the ability to consume & digest the vast amount of data, they will become more smarter & start taking control of the planet.

Only then we will be able to know that AI is helping us like Iron Man's Jarvis or planning to eradicate us like Terminator!!
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We are living in a century where technology dominates lifestyle;Digital Transformation with Big Data, IoT, Artificial Intelligence(AI) are such examples.
Over the past six months, Chatbots have dominated much of the tech conversation, the next big gold rush in the field of online marketing.
Chatbots are built to mimic human interaction, making them seem like an actual individual existing digitally. It could live in any major chat product (Facebook Messenger, Slack, Telegram, Text Messages, etc.), powered by basic rules engine or NLP and AI.
Chatbots have helped in conversation commerce in real time such as booking a cab or ordering a bouquet of flowers or pizza. Consumers will benefit from chatbots through personalization, and this is where social media plays a big part.

Here are a couple of other examples:
·       Weather bot: Get the weather whenever you ask like Poncho
·       Grocery bot:  Help me pick out and order groceries for the week like Yana, MagicX
·       News bot:  Ask it to tell you whenever something interesting happens like TechCrunch, CNN
·       Personal finance bot: It helps me manage my money better like Abe
A chatbot for an airline will function fundamentally differently from a banking bot.
People are now spending more time in messaging apps than in  social media and that is a huge turning point. Messaging apps are the platforms of the future and bots as over 90% of our time on mobile is spent on messaging platforms like Facebook messenger, Whatsapp, Wechat, Viber etc.
Typically business need to answer following questions to create a bot:
·       Do you need a constant communication back and forth with the consumer?
·       What are customers’ expectations for the interaction?
·       How will the bot act?
·       What happens when the bot fails?
Chat bots have to be great at answering questions, this is usually how they are challenged, and IBM’s Watson is probably the best question and answer system.
There are several advantage of Chatbots:
·       24×7 availability – A bot exists digitally unlike a human being, and can thus be pressed into service continuously without any interference
·       Faster response time than humans, coupled with an AI, chatbot’s machine learning and multi-tasking abilities make it a highly efficient virtual assistant
·       Bots allow for a two-way, personalized interaction between the consumer and a brand
·       Saves Resources – Employing a chatbot to handle basic customer interactions can free up valuable human resources without a decline in productivity
Tacobot Allows to order Taco Bell even more quickly.

KLM has a customer service bot that's able to check your flight status and let you know if it's been delayed.

Interacting with software at a human level is becoming more mainstream from digital assistants  like Google Home, Google Now, Apple Siri. 

Going forward people will not be able to tell the difference between human and machine.
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Today, with  Digitization of everything, 80 percent the data being created is unstructured. 
Audio, Video, our social footprints, the data generated from conversations between customer service reps, tons of legal document’s texts processed in financial sectors are examples of unstructured data stored in  Big Data.
Organizations are turning to natural language processing (NLP) technology to derive understanding from the myriad of these unstructured data available online and in call-logs.
Natural language processing (NLP) is the ability of computers to understand human speech as it is spoken. NLP is a branch of  artificial intelligence that has many important implications on the ways that computers and humans interact.  Machine Learning has helped computers parse the ambiguity of human language.
Apache OpenNLP, Natural Language Toolkit(NLTK), Stanford NLP are various open source NLP libraries used in real world application below.
Here are multiple ways NLP is used today:
The most basic and well known application of NLP is Microsoft Word spell checking.
Text analysis, also known as  sentiment analytics is a key use of NLP. Businesses are most concerned with comprehending how their customers feel emotionally adn use that data for betterment of their service.
Email filters are another important application of NLP. By analyzing the emails that flow through the servers, email providers can calculate the likelihood that an email is spam based its content by using Bayesian or Naive based spam filtering.
Call centers representatives engage with customers to hear list of specific complaints and problems. Mining this data for sentiment can lead to incredibly actionable intelligence that can be applied to product placement, messaging, design, or a range of other use cases.
Google and Bing and other search systems use NLP to extract terms from text to populate their indexes and to parse search queries.
Google Translate applies machine translation technologies in not only translating words, but in understanding the meaning of sentences to provide a true translation.
Many important decisions in financial markets use NLP by taking plain text announcements, and extracting the relevant info in a format that can be factored into algorithmic trading decisions. E.g. news of a merger between companies can have a big impact on trading decisions, and the speed at which the particulars of the merger, players, prices, who acquires who, can be incorporated into a trading algorithm can have profit implications in the millions of dollars.
Since the invention of the typewriter, the keyboard has been the king of human-computer interface. But today with voice recognition via  virtual assistants, like Amazon’s Alexa, Google’s Now, Apple’s Siri and Microsoft’s Cortana respond to vocal prompts and do everything from finding a coffee shop to getting directions to our office and also tasks like turning on the lights in home, switching the heat on etc. depending on how digitized and wired-up our life is.
Question Answering - IBM Watson is the most prominent example of question answering via information retrieval that helps guide in various areas like healthcare, weather, insurance etc.
Therefore it is clear that Natural Language Processing takes a very important role in new machine human interfaces. It’s an essential tool for leading-edge analytics & is the near future.
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