“A lot of manufacturers think that it means they are going to sell more chips. … The real value comes from establishment of services on top of the connectivity.”
The Internet of Things is a fast-growing phenomenon in which formerly dumb devices get chips and sensors to become smart gadgets, connected to a network as part of various cyber-physical systems. Sokwoo Rhee, associate director of the Cyber-Physical Systems Program at the National Institute of Standards and Technology, is one of the government’s chief overseers of this rising trend.
Rhee spoke at a recent Wharton conference titled “Strategies for Success in the New Era of Connected Ecosystems,” sponsored by the Mack Institute for Innovation Management. Separately, he spoke with Knowledge@Wharton about some of the less obvious trends in the Internet of Things, how companies are adapting their business models, the government’s role in this cyber world, and how we should secure new smart devices coming online from potential hackers and cybercriminals.
To continue reading the full article on knowledge.Wharton.upenn, click here.
“The requests coming from the end users are not exactly aligned with the problems that these companies are solving today.”
“If your PC gets hacked, you’re going to lose your credit card number. OK, that’s not good. But in CPS and IoT, if something gets hacked, somebody may die because of it.”
If you’re not turning your company into a “math house” you’re headed for serious trouble. Every industry will soon be driven by digitization and every winning company will be using algorithms, or mathematical rules for processing information, to shape the end-to-end customer experience. Any advantages you have now will pale in comparison with a great set of algorithms that differentiates the customer experience. It is the algorithms that will create value for the business.
This is not guesswork. Sensors, the cloud, mobile and broadband wireless, and other such technologies are increasing the flow of digitized information exponentially. Algorithms, run on ever faster computers, can do amazing things with that information, from detecting patterns and making predictions to solving complex problems. They can even modify themselves as new information comes to light. In the hands of a “catalyst,” such as the late Steve Jobs, Jeff Bezos, Larry Page, Sergey Brin, Mark Zuckerberg, or Mark Andreessen, algorithms can radically alter the consumer experience.
More such catalysts are entering the fray every day. Venture capitalists have their radar out for and provide ample resources for the catalysts to scale up very quickly. The result is the reconstitution or destruction of industries, creation of new market spaces, and reshaping of old industry ecosystems.
The global digital transformation has only just begun. McKinsey’s Paul Willmott and Jay Scanlan discuss how senior executives can raise the Digital Quotient of their companies.
Just about every industry is undergoing some level of digital disruption, and the transformation is only in its infancy, according to McKinsey Digital global leader Paul Willmott, and Jay Scanlan, leader of McKinsey’s Digital Strategy Practice. In this episode of the McKinsey Podcast, they speak with McKinsey Quarterly executive editor Lang Davison about the simple metric McKinsey has developed—Digital Quotient—to measure the digital maturity of companies, and how learning from the best digital performers can help companies find their own ways to excel. An edited transcript of their conversation follows.
To continue reading the full article on McKinsey, click here. The article was written by: Jay Scanlan & Lang Davison
The prospective scale of the Internet of Things (IoT) has the potential to fill anyone looking from the outside with the technical equivalent of agoraphobia. However, from the inside, the view is very different. Looked at in detail, it is a series of intricate threads being aligned by a complex array of organizations.
As with any new technological epoch, questions around shape, ownership and regulation are starting to rise. Imagine trying to build the Internet again. It’s like that, but at a bigger scale.
The first hurdle is that of technological standards. We are at a pivotal moment in the development of the IoT. As the diversity of connected things grows, so does the potential risk from not allowing each “thing” to talk to one another.
This begins with networking standards. From ZigBee to Z-Wave, EnOcean, Bluetooth LE or SigFox and LoRa, there are simply too many competing and incompatible networking standards from which to choose. Luckily enough, things seem to be converging and consolidating.
Empathy is a tricky business. The range and complexity of human emotion makes it difficult, if not impossible, to ever really understand how someone else is feeling. Nevertheless, empathy is considered to be a crucial aspect of what makes us human—indeed, our brains appear to be hardwired for it. So perhaps it won’t come as much of a surprise that as machine learning becomes ever more sophisticated and capable of mimicking some of the most complex functions of the human brain, figuring out a way to teach a computer empathy is quickly becoming a business in itself.
Known as artificial empathy, the idea here is to train machines to recognize social signals from humans, aka ‘visual data,’ and then produce an appropriate response. The emergence of social signal processing as a branch of computer science and robotics is a relatively new phenomenon, but it has already attracted a significant amount of attention from another field of research that is also profoundly interested in understanding the way humans communicate: marketing.
At the moment, the Internet of Things has some communications issues.
Unless you shop carefully, you might end up with a smart garage door opener that can’t converse with your security camera, or a smart door lock that won’t talk to your alarm system. The set of connected light bulbs in your hallway might not be on speaking terms with the ones in the living room, and your basement flood detector probably couldn’t get a message through to your smart TV.
Ideally, these devices would simply have a standard way to communicate, so users wouldn’t have to worry about making sure every product works together. Some companies, such as Microsoft, Qualcomm, Samsung, and Intel, are now trying to figure out how to make that happen.
Even so, the ambitious goal of a common Internet of Things language is starting to seem like a Tower of Babel. Over the last year, tech titans like Apple, Google, and Amazon have built up their own ways of connecting to vast numbers of smart home products, and these companies have shown little interest in standardization. As these platforms gain traction, is it too late for a unified language to take hold?
“Technology goes beyond mere tool making; it is a process of creating ever more powerful technology using the tools from the previous round of innovation.” –Ray Kurzweil
A decade ago, smartphones (as we know them by today’s standards) didn’t exist. Three decades earlier, no one even owned a computer. Think about that—the first personal computers arrived about 40 years ago. Today, it seems nearly everyone is gazing at a glowing, handheld computer. (In fact, two-thirds of Americans own one, according to a Pew Report.)
Intuitively, it feels like technology is progressing faster than ever. But is it really? According to Ray Kurzweil—yes, it absolutely is. In his book The Singularity Is Near, Kurzweil shows technology’s quickening pace and explains the force behind it all.
This article will explore Kurzweil’s explanation of this driving force, which he dubbed the law of accelerating returns, and the surprising implications of technology’s acceleration.
The Internet of Things (IoT) is changing business models, increasing output, and automating processes across a number of industries. But no other sector has been more impacted by this technological revolution than manufacturing.
Manufacturers across all areas —automotive, chemical, durable goods, electronics, etc. — have invested heavily in IoT devices, and they’re already reaping the benefits. Manufacturers utilizing IoT solutions in 2014 saw an average 28.5% increase in revenues between 2013 and 2014, according to a TATA Consultancy Survey.
In this report, we examine the ways the IoT will impact the manufacturing sector. We include forecasts on device shipments, the investments made by manufacturers on IoT solutions, and we examine the return on investment that manufacturers are witnessing from their IoT solutions. Further, we look at the common IoT use cases in manufacturing, including asset tracking, control room consolidation, predictive maintenance, autonomous robots, augmented reality, and additive manufacturing.
Tata finds 26 companies set to spend $1 billion on the Internet of things this year
Twenty-six companies (including 14 in the U.S.) plan to spend $1 billion or more each on Internet of things initiatives this year according to research out from Tata Consultancy Services. That billion-dollar group comes from seven industries: six from banking and financial services; five from automotive; four from travel, hospitality, and transportation; four from high tech; three from insurance; two telecommunications firms; one retailer; and one from healthcare and life sciences.
Those companies are outliers, but a broad swath of businesses intend to invest $86 million this year–or 0.4% of their revenue—on Internet of things projects according to Tata Consultancy. And while surveys about the purported value of the Internet of things are a dime a dozen, this one also offers excellent points about the cultural changes that would need to accompany the technical implementations if businesses really wanted to take advantage of the promise of the Internet of…
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