Michael Gartenberg (@Gartenberg) | Twitter
Michael Gartenberg
analyst in residence @imore book reader, bagel eater, coffee drinker. Former Sr. Marketing Director @Apple, ex Jupiter Research, Gartner & other stuff

The swamps of Jersey
Joined December 2006
#mobile  #analyst  #SME  #Gartner 
10 hours ago
Polo Chau (@PoloChau) | Twitter
Polo Chau
Prof @GeorgiaTech @GTCSE. MS Analytics Assoc. Dir. ªªhttp://www.analytics.gatech.edu ºº Data mining, HCI hybrid. Covert designer. Rusty cellist, pianist.

Joined October 2011
#GaTech  #academic  #datascience  #expert  #HCI 
12 Voice Use Cases For Health Systems Mobiquity 20180314
12 Voice Use Cases For Health Systems
Steve LoSardo / Thought Leadership / March 14, 2018

Hospitals are no longer giving voice the silent treatment! As consumers continue to adopt voice assistants in their everyday lives, health systems are increasingly thinking about delivering voice solutions for patients and providers alike.

We’ve seen early adopters like Beth Israel Deaconess Medical Center launch Alexa skills that allow inpatients to call a nurse or ask about their prescribed diets. Meanwhile, Boston Children’s, which happens to be one of the busiest pediatric transplant-surgery hospitals in the nation, piloted a voice-prompted checklist for pre-operative organ validation. And we can’t forget about organizations like Inglis that are leveraging Alexa to empower adults with disabilities to live more independently.

With Amazon demonstrating Alexa at last week’s HIMSS18 Annual Conference and recently announcing its plans to hire a HIPAA compliance lead, it’s only a matter of time until voice truly transforms the patient, caregiver, and provider experience. In anticipation, we’ve created the below infographic detailing 12 use cases for health systems to consider as they explore their voice strategies.
#voice  #application  #healthcare  #patient  #engagement 
CSE Ph.D. Students Claim Three Prestigious Fellowships from , , and .

Congratulations Shang,…
from twitter_favs
2 days ago
Is AI already good enough to transform healthcare Interview with Daniel Nathrath, Founder and CEO at Ada Health 201804
Is AI already good enough to transform healthcare? – Interview with Daniel Nathrath, Founder and CEO at Ada Health
According to the mHealth App Economics 2017 study, 61% of decision makers and experts of digital health see Artificial Intelligence as the most disruptive technology shaping the digital health sector. And although AI is still in infancy its capability to offer significant digital health personalized value with the right actionable insights by empowering a new generation of personal health companions and medical chatbots, telemedicine and the prominent IBM Watson for Oncology notably improves the quality of people’s lives and transforms the healthcare sphere.


Digital solutions powered by Artificial Intelligence’s data driven nature and its ability to process unthinkable amount of data, identify the relevant insights to be matched with specific patient case and records, leads to unique user experience. Taking prompt actions to feel better and manage more effectively one’s everyday condition gives a sense of responsibility for one’s own health. In some rural areas around the world with no easy physical access to a doctor, AI based mHealth solutions could be a game changer for people with health conditions that are not-life threatening. AI and machine learning, chatbots, predictive diagnostics and telemedicine provide the support doctors need in the patient-centric journey.

At present, some medical chatbots that utilize advanced Artificial intelligence algorithm / self-learning AI technology can be used as a personal health assistant to: check symptoms and get a diagnosis, advise how to treat the sickness and whether one should see personally a doctor, book a consultation with a medical specialist, and allow for remote monitoring of a health status. What makes one medical chatbot stand out from the rest? The quality of the medical and scientific data that is behind the AI technology used, the ability to process more cases and insights, as well as the propensity to learn from real time smart conversations with the user and to build a personalized profile with every interaction make one chatbot a trustworthy partner in managing one’s health.
#mhealth  #app  #EU  #consumer 
4 days ago
Hard Questions: What Data Does Facebook Collect When I’m Not Using Facebook, and Why? 20180416
Hard Questions: What Data Does Facebook Collect When I’m Not Using Facebook, and Why?

Hard Questions is a series from Facebook that addresses the impact of our products on society.

By David Baser, Product Management Director

Last week, Mark Zuckerberg testified in front of the US Congress. He answered more than 500 questions and promised that we would get back on the 40 or so questions he couldn’t answer at the time. We’re following up with Congress on these directly but we also wanted to take the opportunity to explain more about the information we get from other websites and apps, how we use the data they send to us, and the controls you have. I lead a team focused on privacy and data use, including GDPR compliance and the tools people can use to control and download their information.
#datasharing  #privacy  #FB 
4 days ago
Scott Zoldi (@ScottZoldi) | Twitter
Scott Zoldi
@ScottZoldi Follows you
Driving #analytics #innovation as Chief Analytics Officer at @FICO®, tweeting on #AI #IoT #cybersecurity #regtech. 87 authored patents: 43 granted, 44 pending

San Diego, CA
Joined January 2016
#analytics  #CAO 
4 days ago
“People Believe Are Becoming More ... users feel bombarded by too many
ads  Intrusive  from twitter
5 days ago
Jeremy Howard (@jeremyphoward) | Twitter
Jeremy Howard
Deep learning researcher & educator. Founder: fast.ai; Faculty: USF & Singularity University; // Previously - CEO: Enlitic; President: Kaggle; CEO Fastmail

San Francisco
Joined August 2010
#dl  #sme  #expert  #startup  #healthcare  #founder  +SF 
5 days ago
Quid, Inc. (@Quid) | Twitter
Quid, Inc.Verified account
We power human intuition with machine intelligence, enabling organizations to make decisions that matter. For inquires please contact Hi@quid.com

San Francisco, CA
Joined February 2011
#trends  #analytics  #ET  #platform  #A+  #research  #tool  >100 
5 days ago
The power of three: AI, IoT and blockchain 20180330
The power of three: AI, IoT and blockchain
Adoption of the technologies in corporates across the world has increased in a bid to increase efficiency and make businesses more customer-friendly
Last Published: Fri, Mar 30 2018. 08 32 AM IST
#ai  #IoT  #blockchain  #et  #nwm  #outlook  #potential  AI  IoT  blockchain 
5 days ago
If Your Data Is Bad, Your Machine Learning Tools Are Useless 20180402
If Your Data Is Bad, Your Machine Learning Tools Are Useless
Thomas C. Redman
APRIL 02, 2018


Chase Sapphire: Creating a Millennial Cult Brand

How to Date Your Clients in the 21st Century: Challenges in...

Transformation at Eli Lilly & Co. (B)

Poor data quality is enemy number one to the widespread, profitable use of machine learning. While the caustic observation, “garbage-in, garbage-out” has plagued analytics and decision-making for generations, it carries a special warning for machine learning. The quality demands of machine learning are steep, and bad data can rear its ugly head twice — first in the historical data used to train the predictive model and second in the new data used by that model to make future decisions.

To properly train a predictive model, historical data must meet exceptionally broad and high quality standards. First, the data must be right: It must be correct, properly labeled, de-deduped, and so forth. But you must also have the right data — lots of unbiased data, over the entire range of inputs for which one aims to develop the predictive model. Most data quality work focuses on one criterion or the other, but for machine learning, you must work on both simultaneously.
#data  #analytics  #challenges 
5 days ago
The Enterprise Data Debt Crisis 20180221
The Enterprise Data Debt Crisis
Feb 21, 2018
Eliot Knudsen


Large enterprises are facing a debt crisis. Not financial debt, but “data debt.” It’s a form of technical debt, and it can hamstring an organization’s capacity to tackle new challenges and stifle its ability to innovate. The problem is pervasive.

A recent article in Harvard Business Review showed that only a shocking 3% of companies’ data met basic quality standards. For years, software development teams have understood and reckoned with the future work created by making short-term tradeoffs to ship their code faster, and now IT organizations are realizing they have created massive amounts of remediation work for themselves due to decades of deprioritizing data management.

For most large enterprises, the root of this problem lies in years of treating the data generated by their operational systems as a form of exhaust rather than as a fuel to deliver great services, build better products, and create competitive advantage. Every new enterprise application deployed is essentially a data creation engine. Unless companies have a method of easily integrating each new data source to capture and leverage the new data, the debt will grow daily—and exponentially—with the number of data sources in a company. For many companies, this problem is compounded by a history of M&A, reorganizations, “data hoarding,” politics, and rogue shadow IT activity.
#data  #quality  #dataops  #enterprise 
5 days ago
With GDPR looming, DSPs are under pressure to adapt 20180119
With GDPR looming, DSPs are under pressure to adapt
JANUARY 19, 2018 by Ross Benes
With the General Data Protection Regulation being enforced in May, demand-side platforms need to figure out how to target users without relying on personal data. DSPs that are unable to adapt to the new rules are likely to lose market share and suffer a similar fate as the programmatic platforms that were late to adopt header bidding.

The GDPR demands that personal data only be used with explicit permission from individuals. This could become problematic for DSPs because they rely on audience data to target ads, and 50 percent of European internet users said that if given the option, they would opt out of seeing retargeted ads, according to a December survey by HubSpot.

Johnny Ryan, head of ecosystem at anti-ad blocking firm PageFair, said that when users opt out of having their data used for ad-targeting purposes, DSPs will have to scrupulously avoid using any information that ties back to an individual user. Data like IP addresses and cookies, which are the backbone of real-time bidding, will be off the table in these scenarios. These data restrictions will burden many vendors, and the GDPR will revolutionize ad tech akin to how the auto industry is being pushed to switch to electric vehicles, he said.

To obtain consent from users, DSPs have to rely on other companies along the ad supply chain since DSPs don’t have direct relationships with the end human being receiving an ad. It is the consumer-facing websites of publishers that ad tech companies will rely on to obtain consent, said Ratko Vidakovic, founder of ad tech consultancy AdProfs.
#advertising  #DSPs  #consent  #GDPR  #challenges 
5 days ago
Blockchain for programmatic? You must be kidding 20180410
Blockchain for programmatic? You must be kidding
Trying to use blockchain to solve programmatic media is excessive use of technology, argues the chief executive and founder of BrainLabs.
#advertising  #programmatic  #blockchain 
5 days ago
DataOps: A Unique Moment in Time for Next Generation Data Engineering 20180220
DataOps: A Unique Moment in Time for Next Generation Data Engineering
Published on February 20, 2018

Andy Palmer
Following Unfollow
Like 241

Write an article
Judging from the engagement on my latest post from across the spectrum of business leaders, data engineers, data scientists and thought leaders, DataOps is clearly picking up steam. There were too many comments for me to respond to them all on LinkedIn, so I decided to post this follow up.

My overall takeaway? The sense of optimism that people are feeling about next-generation data engineering in the enterprise. It finally feels like large organizations have embraced their “data debt” and are figuring out how to monetize their data. It helps when they realize that great analytics depend on great data.

We’re at a unique point in time when fundamental changes in data management in the enterprise, the low barrier to cloud migration and the volume and value of enterprise data combine into a massive opportunity to create next generation data engineering pathways.
#dataengineering  #dataops 
5 days ago
Ad retargeters scramble to get consumer consent 20180110
Ad retargeters scramble to get consumer consent
JANUARY 10, 2018 by Ross Benes
Desperate times call for desperate in-browser messages.

With Apple already making moves against ad tracking in its Safari browser and the General Data Protection Regulation being enforced in May, ad retargeters are desperately trying to get consent from users to track their digital browsing behavior. Companies such as Criteo and AdRoll are trying to get people’s consent by serving in-browser messages that opt users into ad tracking once they close the messages.
#advertising  #retargeting  #consent  #GDPR 
5 days ago
DataOps Building A Next Generation Data Engineering Organization 20180208
DataOps: Building A Next Generation Data Engineering Organization
Published on February 8, 2018

Andy Palmer
Follow Follow
Like 1,452

Write an article
Large enterprises are experiencing a foundational shift in how they view their data and structure their data engineering teams. As organizations capture more data than ever before, and store it in an ever-increasing variety of data stores, the prospect of competing on analytics becomes more tantalizing than ever. The challenges of using data at scale, however, is rooted in the “data debt” accumulated over time by enterprises struggling to manage the extreme volume and variety of their data. Paying down this data debt is the proverbial long pole in the tent for competing on analytics.  

If you ask most employees, they likely believe their company’s data is neatly organized and easily accessible. As enterprise data professionals know, the reality is that a typical data environment resembles a “random data salad.” For decades, companies have been idiosyncratically deploying systems for business process automation, with the data generated from these deployments treated mainly as “exhaust” to the business processes. The resulting data environment is deeply fragmented and virtually impossible to integrate at scale — crushing the hopes of companies that want to develop an analytical advantage.
5 days ago
Terry T. (@TerryTaouss) | Twitter
Terry T.
Principal @AdProfs. Formerly MD @SiteScout & exec @Centro. Fully-recovered lawyer.

Toronto, most of the time.
Joined March 2012
#advertising  #SME  >tw 
5 days ago
AdProfs (@adprofs) | Twitter
Research firm and consultancy focused on programmatic advertising technology. Get insights and learn from expert industry insiders.

Joined February 2016
#advertising  #source  >tw 
5 days ago
Ratko Vidakovic (@ratko) | Twitter
Ratko Vidakovic
Founder @AdProfs. Author of ‘This Week In Ad Tech’ newsletter.

Joined March 2010
#advertising  #SME  >tw 
5 days ago
What Will Be The Fate Of Third-Party Data After GDPR? 20180412
What Will Be The Fate Of Third-Party Data After GDPR?
by Allison Schiff // Thursday, April 12th, 2018 – 2:00 pm
Europe’s General Data Protection Regulation (GDPR) will kill the third-party data ecosystem. Or third-party data isn’t going anywhere.
The truth sits somewhere in the middle, said Alice Lincoln, MediaMath’s VP of data policy and governance, at AdExchanger’s Programmatic I/O in San Francisco on Wednesday.

“Third-party data is here to stay – if it’s high-quality,” said Lincoln, who’s both a man and a woman – if you go by the data floating around about her in the third-party ecosystem. She’s been targeted as both.

Patrick Salyer, CEO of SAP-owned Gigya, is slim and around six feet tall, but when he looked up what data the brokers have on him, “weight-loss products” was listed as an interest.

“I question the validity of third-party data moving forward,” Salyer said. “The brands we’re working with, including large CPGs, are realizing that a direct digital connection with consumers is extremely important – in fact, it’s a differentiator.”
#advertising  #digital  #third-party  #data  #tpd  #GDPR  #impact 
5 days ago
People Believe Ads Are Becoming More Intrusive 20180410
People Believe Ads Are Becoming More Intrusive
Users feel bombarded by too many ads

2 min read
If you believe ads are becoming more invasive, you're not alone.

In a survey of US internet users by Kantar Millward Brown, 71% of respondents said that ads are more intrusive now than they were three years ago. A similar number indicated they’re seeing more ads overall, and even more agreed that ads are now appearing in more places.
#ads  #critique  #consumer  #privacy  #intrusiveness 
5 days ago
Getting Data Right eBook O'Reilly
Getting Data Right

Featuring Michael Stonebraker, Tom Davenport, James Markarian, and others
In “Getting Data Right“, some of the industry’s most respected minds explain how data variety can be transformed from a roadblock into ROI. Throughout this ebook, you’ll learn how to question conventional assumptions, and explore alternative approaches to managing big data in enterprise environments.
#data  #dataengineering  #TomDavenport  >cd 
5 days ago
How AT&T's Smart Watering is Making Waves 20180313
How AT&T's Smart Watering is Making Waves

Learn how AT&T is helping several companies connect irrigation systems that regulate water on farms and public spaces by using AT&T Internet of Things (IoT) technology to detect moisture levels using AT&T Smart Irrigation.

By Chris Morgan, staff writer, AT&T Insider

Have you ever noticed a sprinkler system in full gear, persistently watering a lush, green lawn as the rain pours down?

That is not a smart watering system.
#IoT  #application  #casestudy  +ATT 
5 days ago
AT&T Shape (@ATTShape) | Twitter
AT&T ShapeVerified account
Encouraging revolutionary technology and thinking that transforms the way you live. Championing connectivity for everyone, everywhere.

Joined August 2012
+ATT  >Twitter  #mobile  #operator  #US 
5 days ago
Julie Woods-Moss (@juliewoodsmoss) | Twitter
Julie Woods-Moss
@juliewoodsmoss Follows you
#Strategist, #Change Expert, Market Maker. Chief #Marketing & #Innovation Officer @tata_comm. Forbes Technology Council Contributor. Views expressed personal

Joined June 2009
#cmo  #tl  #marketing  #innovation 
5 days ago
After the Facebook scandal: The grand plan to hold AI to account | New Scientist 201804
After the Facebook scandal: The grand plan to hold AI to account
From next month, EU citizens will have sweeping rights to know what computers are thinking about them –  but can that work, and if so how?

Bruno Mangyoku
By Timothy Revell

IT SHOULD not have taken Cambridge Analytica to remind us that algorithms can have an insidious influence. Arguments rumble on about what privacy rules were broken, if any, and whether the company’s mass profiling of Facebook users swung the 2016 US Presidential Election and the UK’s Brexit vote. What we are clear on is something we had been warned about: give an algorithm a load of data about ourselves, and in return it assumes power over our lives.

Facebook and Google’s artificial-intelligence algorithms, learning from the data we feed them, already control what we read on the web. Similar machine-learning algorithms determine the interest we pay on a loan and, in some places, the chances the police will stop and search us on our way home. Soon they could be driving cars, helping to make life-or-death decisions in the operating theatre and deciding fates on the battlefield.

Sometimes these algorithms blunder, discriminate, or overstep the line – so we need to be able to hold them to account. The European Union has fired the first salvo, giving its citizens the right to an explanation for why an algorithm did something that affects their lives. The trouble is, the techniques behind the AI boom are by their very nature a black box. Even the people who create these machine minds don’t understand their reasoning.

That’s alarming enough given their current reach. But if AI is going to fulfil its promise and take an ever-more important role in society, we need to find a way to trust it. The question now is: how?
#ai  #accountability 
5 days ago
A Closer Look at Data: Algorithms, Analytics, and Accuracy 20180318
A Closer Look at Data: Algorithms, Analytics, and
Mar 13, 2018
Jeffrey Feinstein 

Using Big Data for Good Requires Testing, Transparency, Precision, and Due Diligence

Big data can help drive decisions in almost every aspect of our lives—from the way financial products are underwritten, learning programs are designed, energy is used, healthcare diagnoses are made, insurance rates are assessed, commerce is conducted, and fraud is prevented—the list is infinite. As these decisions can affect individuals and society as a whole, it is compulsory that data experts apply integrity, transparency, and due diligence into the analytics that mine information and the algorithms that inform our decision making and problem solving.

The first step in an analytic development is linking information together from a variety of different sources. This is one of the core challenges of a big data program because different sources can describe the same people in very different ways. It is important for these linking algorithms to be precise in order to make sense of the data. If linking algorithms are not precise, the information provided can lead to ill-informed decisions. For instance, consider the billions of records that exist about all facets of our lives—birth records, drivers’ licenses, vehicle registrations, student records, Social Security numbers, liens and judgments, and property addresses. The information in these records is often used to validate that “you are who you say you are” and to enable decisions such as mortgage and car loan approvals and much more. If inaccurate information is associated with an individual’s file because of imprecise linking algorithms, he or she could be unfairly declined for credit products, and financial institutions could miss an opportunity to develop a relationship with a potentially good customer.
#data  #analytics  #algorithms  #quality  #impact  #explainability 
5 days ago
Seizing Opportunity in Data Quality 20171127
Seizing Opportunity in Data Quality
FrontiersBlog November 27, 2017 Reading Time: 8 min 
Thomas C. Redman
Data & Analytics, Organizational Behavior, Leading Change, Analytics & Performance, Quality & Service
Share on Twitter Share on Facebook Share on LinkedIn Share through Email
The cost of bad data is an astonishing 15% to 25% of revenue for most companies.


Getting in front on data quality presents a terrific opportunity to improve business performance. Better data means fewer mistakes, lower costs, better decisions, and better products. Further, I predict that many companies that don’t give data quality its due will struggle to survive in the business environment of the future.

Bad data is the norm. Every day, businesses send packages to customers, managers decide which candidate to hire, and executives make long-term plans based on data provided by others. When that data is incomplete, poorly defined, or wrong, there are immediate consequences: angry customers, wasted time, and added difficulties in the execution of strategy. You know the sound bites — “decisions are no better than the data on which they’re based” and “garbage in, garbage out.” But do you know the price tag to your organization?

Based on recent research by Experian plc, as well as by consultants James Price of Experience Matters and Martin Spratt of Clear Strategic IT Partners Pty. Ltd., we estimate the cost of bad data to be 15% to 25% of revenue for most companies (more on this research later). These costs come as people accommodate bad data by correcting errors, seeking confirmation in other sources, and dealing with the inevitable mistakes that follow.
#data  #quality  #analytics  #impact  #baddata 
5 days ago
Blockchain Is Changing Our World Here Are The Best Practical Examples Of How It Is Used In 2018 20180101
Blockchain Is Changing Our World: Here Are The Best Practical Examples Of How It Is Used In 2018

Bernard Marr , CONTRIBUTOR

Opinions expressed by Forbes Contributors are their own.
The potential of blockchain technology to disrupt nearly every industry in some way cannot be dismissed even though there are still several hurdles to overcome before we see its full transformative impact.


Leaders of major financial institutions where security is paramount and change is often resisted see enough upside in blockchain technology that they have been willing to invest millions in resources to learn how to best implement it. And, they are not alone. Any business with valuable digital assets from contacts to contracts they need to protect can find a legitimate use case for blockchain technology.
5 days ago
Blockchain’s applications reach further than you think 20180212
By Rebecca Linke  |  February 12, 2018

Blockchain technology is evolving rapidly, and so are its potential uses. Here’s where disruption could be coming.

Have a question or comment for Michael Casey and Paul Vigna? Join them for a Twitter chat on Feb. 28 at 1 p.m. EST using #MITSloanExperts.

Many people are familiar with bitcoin, the cryptocurrency that doubled its price four times in 2017 before falling again in the new year. Fewer people are familiar with blockchain, bitcoin’s underlying technology that has the potential to affect every industry.

MIT Sloan senior lecturer Michael Casey realized that blockchain’s disruptive potential shouldn’t be underestimated when he was writing his 2015 book " The Age of Cryptocurrency." That book explored how digital money could upend the financial system, but while writing it Casey and his coauthor, Wall Street Journal reporter Paul Vigna, realized that blockchain and its broader applications was going to be as big a story.
#blockchain  #impact  #trust  #SME  #book  #author  #A+ 
5 days ago
The Truth Machine The Blockchain and the Future of Everything Paul Vigna Michael J. Casey 201802
The Truth Machine: The Blockchain and the Future of Everything Kindle Edition
by Paul Vigna (Author), Michael J. Casey (Author)

"Views differ on bitcoin, but few doubt the transformative potential of Blockchain technology. The Truth Machine is the best book so far on what has happened and what may come along. It demands the attention of anyone concerned with our economic future." —Lawrence H. Summers, Charles W. Eliot University Professor and President Emeritus at Harvard, Former Treasury Secretary

From Michael J. Casey and Paul Vigna, the authors of The Age of Cryptocurrency, comes the definitive work on the Internet’s Next Big Thing: The Blockchain.

Big banks have grown bigger and more entrenched. Privacy exists only until the next hack. Credit card fraud is a fact of life. Many of the “legacy systems” once designed to make our lives easier and our economy more efficient are no longer up to the task. Yet there is a way past all this—a new kind of operating system with the potential to revolutionize vast swaths of our economy: the blockchain.

In The Truth Machine, Michael J. Casey and Paul Vigna demystify the blockchain and explain why it can restore personal control over our data, assets, and identities; grant billions of excluded people access to the global economy; and shift the balance of power to revive society’s faith in itself. They reveal the disruption it promises for industries including finance, tech, legal, and shipping.

Casey and Vigna expose the challenge of replacing trusted (and not-so-trusted) institutions on which we’ve relied for centuries with a radical model that bypasses them. The Truth Machine reveals the empowerment possible when self-interested middlemen give way to the transparency of the blockchain, while highlighting the job losses, assertion of special interests, and threat to social cohesion that will accompany this shift. With the same balanced perspective they brought to The Age of Cryptocurrency, Casey and Vigna show why we all must care about the path that blockchain technology takes—moving humanity forward, not backward.
#blockchain  #book  #MIT  #A+  >acq 
5 days ago
Matchmakers The New Economics of Multisided Platforms Book David S. Evans Richard Schmalensee 2018
Matchmakers: The New Economics of Multisided Platforms Kindle Edition
by David S. Evans (Author), Richard Schmalensee (Author)
4.4 out of 5 stars 55 customer reviews
See all 4 formats and editions
Read with Our Free App

24 Used from $15.48
32 New from $15.48

$11.95 or 1 credit
or 1 credit

5 Used from $6.43
10 New from $6.71
#platform  #digital  #strategy  #A+  +DavidEvans  >acq 
5 days ago
The Sharing Economy The End of Employment and the Rise of Crowd-Based Capitalism Book Arun Sundararajan 2016
The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism (MIT Press) Reprint Edition, Kindle Edition
by Arun Sundararajan (Author)
Sharing isn't new. Giving someone a ride, having a guest in your spare room, running errands for someone, participating in a supper club -- these are not revolutionary concepts. What is new, in the "sharing economy," is that you are not helping a friend for free; you are providing these services to a stranger for money. In this book, Arun Sundararajan, an expert on the sharing economy, explains the transition to what he describes as "crowd-based capitalism" -- a new way of organizing economic activity that may supplant the traditional corporate-centered model. As peer-to-peer commercial exchange blurs the lines between the personal and the professional, how will the economy, government regulation, what it means to have a job, and our social fabric be affected?

Drawing on extensive research and numerous real-world examples -- including Airbnb, Lyft, Uber, Etsy, TaskRabbit, France's BlaBlaCar, China's Didi Kuaidi, and India's Ola, Sundararajan explains the basics of crowd-based capitalism. He describes the intriguing mix of "gift" and "market" in its transactions, demystifies emerging blockchain technologies, and clarifies the dizzying array of emerging on-demand platforms. He considers how this new paradigm changes economic growth and the future of work. Will we live in a world of empowered entrepreneurs who enjoy professional flexibility and independence? Or will we become disenfranchised digital laborers scurrying between platforms in search of the next wedge of piecework? Sundararajan highlights the important policy choices and suggests possible new directions for self-regulatory organizations, labor law, and funding our social safety net.
#tech  #sharingeconomy  #shec  #MIT  #trust  #A+  #rt  >acq 
5 days ago
The Sharing Economy The End of Employment and the Rise of Crowd-Based Capitalism Book Arun Sundararajan 2016
The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism (MIT Press) Reprint Edition, Kindle Edition
by Arun Sundararajan (Author)
#tech  #sharingeconomy  #shec  #MIT  #trust  #A+  #rt  >acq 
5 days ago
Zacharia Crockett Writer, Journalist
I’m a writer based in San Francisco and Washington, DC.

My work—a mix of multimedia-driven original reporting and data analysis—has appeared in The Atlantic, Time Magazine, Longreads, Gizmodo, Priceonomics, Vox, and elsewhere. I’ve also done radio for Marketplace and NPR, video for The Discovery Channel, and design work for Google.

Much of my storytelling lies at the intersection of tech and business, but I’ve also extensively covered adventure and the outdoors, Internet culture, gun violence, and the 2016 presidential election. I’m interested in mysteries, obsessions, and underworlds.
#tech  #impact  #trust  #digital  +Vox  #journalist  #A+  #tl 
5 days ago
"Tech has changed our mechanisms for trust. Companies now gain through like ranking…
trust  technologies  digital  from twitter
5 days ago
How the sharing economy makes us trust complete strangers 20180414
How the sharing economy makes us trust complete strangers
The sharing economy relies on the moral righteousness of strangers. And we deeply trust it — even when everything goes to hell.
APRIL 14, 2018


ast July, an idealistic young entrepreneur by the name of Zhao Shuping had an epiphany: “Everything on the street,” he proclaimed, “can now be shared.”

Capitalizing on China’s sharing economy fetish, Shuping raised 10m yuan (~$1.6m USD) from a cadre of drooling investors, purchased 300k umbrellas, and rented them out at train stations across 11 Chinese cities for a fee of $0.80 per half-hour.

Within 2 weeks, all 300k umbrellas had been stolen.

The sharing economy is poised to grow to $335B worldwide by 2025 — and, as these platforms become more common, so too do the tales of their utter failure. Yet, our trust in collaborative consumption remains astronomically high.


The deprogramming of ‘stranger danger’
In its purest form, the “sharing economy” leverages technology to facilitate transactions between people with idle goods and resources, and people willing to pay for them.

This system is highly dependent on us trusting complete strangers: we get into their cars, sleep in their beds, invite them into our homes to assemble IKEA furniture, and message them to watch our pets.
#trust  #privacy  #survey  #stats  #sharingeconomy  #technology  #impact 
5 days ago
“The most radical technological advances aren’t coming from linear improvements within a single subject or expertis…
from twitter
6 days ago
"Using & smart product technologies – from mobile devices and sensors to real-time cloud applications –…
IoT  from twitter
6 days ago
"Brands lost sight of the importance of empathetic connections with people... paradoxically, at the time when…
from twitter
6 days ago
"The in which we interact with each other and the world around us has become increasingly and pervasively…
context  from twitter
6 days ago
Andy Hobsbawm (@AndyHobs) | Twitter
Andy Hobsbawm
Digital things, Green things, Internet of things, Guitar things. Co-founder & CMO @Evrythng.

Joined March 2009
#IoT  #exec  #EVRYTHNG  #startup  #tl  #digital  #engagement 
6 days ago
Digital Emotional Intelligence (DEQ0 Report EVRYTHNG 2018
A Customer Experience Framework to Understand and Anticipate Human Emotions Across Physical and Digital Channels

Download this report to discover:

A new form of brand intelligence that integrates technology with humanity
How smart, digital technologies can augment human emotions
How to harness contextual, real-time data to drive sales and loyalty
The brands that use digital technology to connect more emotionally, personally and contextually will win.
#EVRYTHNG  #digital  #engagement  #cx  #context  #real-time  #DEQ  #report 
6 days ago
Turning Bottles into Owned Digital Media Assets Diageo EVRYTHNG Case Study

Diageo & EVRYTHNG’s IoT Smart Products Platform
How to drive sales when consumers use smartphones to make buying decisions just moments before purchase.
Digitally connecting physical products to the Web to drive a new era in consumer engagement.
The Father’s Day pilot in Brazil where consumers attached a personalized film tribute to their dad to the bottle of whisky they were giving as a gift.
Using APIs and web services to integrate with internal global ERP and CRM systems, and external agencies, developers, and social networks.
“EVRYTHNG’s technology is game-changing. We now have a profound strategic opportunity to transform our physical products into owned digital media, which can communicate personalized information and experiences to consumers, exactly when and where they want it.”
#IoT  +EVRYTHNG  #casestudy  #smartproducts 
6 days ago
Consumer Engagement | EVRYTHNG IoT Smart Products Platform

Your products already touch consumers millions of times a day. EVRYTHNG activates these ubiquitous and under-used assets with a combination of smartphones, smart packaging and our smart software in the cloud.

Deliver ‘in-the-moment’ content, loyalty rewards or offers, based on contextual triggers like time, place, product, past interaction and purchase history, or lifestyle data pulled in real-time from social networks.

Now consumers can digitally interact with products to unlock personalized content and rewarding brand experiences at point of sale, or post-purchase. And manufacturers can operate every product as data-driven interactive media to drive brand attraction, differentiation, and 1:2:1 consumer connections.
#brand  #cx  #engagement  #IoT  #vendor  #A+  #nwm  #sponsor 
6 days ago
EVRYTHNG IoT Smart Products Platform |
We’re called EVRYTHNG because we believe that every physical thing around us is coming to life digitally in some shape or form.

From the cars we drive and the clothes we wear, to the beers we drink and the homes we live in.

We started the company to connect all of these products to the Web, each with its own unique, real-time digital identity, to make them smarter.

And we built the industry’s leading IoT Smart Products Platform in the cloud to do it.
#iot  #platform  #vendor  #A+  #nwm  #sponsor 
6 days ago
The 3 Technological Forces Your Strategy Can't Ignore Martin Hirt McKinsey 20180405
The 3 Technological Forces Your Strategy Can't Ignore
Published on April 5, 2018

Martin Hirt
Following Unfollow
Senior Partner (Director) McKinsey & Company · Leader of McKinsey's Global Strategy Practice · Author
7 articles
Like 187

What do ingestible sensors, blockchains and driverless cars have in common? They were all in the realm of science fiction only a few years ago, for one. But they share something else: Each of these potentially revolutionary technologies marries breakthroughs in multiple fields to create an unexpectedly powerful whole.

Digitization, machine learning, and the life sciences are increasingly combining with one another to create an accelerating technological explosion. In the process, they’re redefining what companies do and where industry boundaries lie. While that degree of change can be uncomfortable or even destructive, it can also contain the seeds of great opportunity.
#tech  #convergence  #strategy  +McKinsey  +MartinHirt  #A+  #quotes 
6 days ago
A business leader’s guide to agile McKinsey 201707
A business leader’s guide to agile
By Santiago Comella-Dorda, Krish Krishnakanthan, Jeff Maurone, and Gayatri Shenai
Article Actions
Agile promises rapidly evolving software and substantial business benefits, but it requires new habits from everyone: from IT and from business partners.

Agile development has largely become synonymous with digitization: senior business leaders have realized that their companies cannot take full advantage of digital tools and technologies without having new, amped-up processes for managing them. The value of these processes is immense.

Senior executives need only look at two recent examples in the banking industry to understand what’s at stake: ING and South Africa’s Standard Bank have both incorporated digital technologies and agile ways of working into their operations, and both are achieving positive results. ING is releasing software features to its web and mobile sites every two or three weeks rather than five or six times a year. As a result, the company’s customer-satisfaction scores are up by multiple points. Standard Bank has improved the quality of its new mobile applications by finding and fixing potential bugs earlier in the software-development process—building more trust with employees and customers in the process.

What may be less clear to senior executives is the role they can play in jolting their own business units and IT organizations to break from the status quo and realize similar advantages. “This was one of the toughest challenges,” says Mike Murphy, CTO at Standard Bank. “A lot of staffers at the bank were comfortable with the ways things were. They didn’t want to change their daily routines. They were focused on simply getting the job done.”

Stay current on your favorite topics
Senior executives often tend to assume that after they set overarching digital goals, it’s up to IT to deliver on them quickly through a range of initiatives. In their view, agility is something for R&D engineers and software developers only. The business units hold fast to tried-and-true methods for communicating with IT—throwing their requirements “over the wall” and waiting for IT to build and deliver finished products. The IT organization ends up operating with limited information from the business, the business units lose their opportunity to steer technology development toward desired goals, and agility stalls.
#agile  #guide  #strategy  #bestpractices  +McKinsey 
6 days ago
The five trademarks of agile organizations McKinsey 201801
The five trademarks of agile organizations
By Wouter Aghina, Aaron De Smet, Gerald Lackey, Michael Lurie, and Monica Murarka
Article Actions
Agile organizations—of any size and across industries—have five key elements in common.

This article was written collaboratively by the McKinsey Agile Tribe, a group of over 50 global colleagues bringing expertise from the digital, operations, marketing, and organization disciplines. They integrate their deep experience and thought leadership to extract the best from McKinsey’s global experience as it helps organizations transform themselves into agile organizations.

Our experience and research demonstrate that successful agile organizations consistently exhibit the five trademarks described in this article. The trademarks include a network of teams within a people-centered culture that operates in rapid learning and fast decision cycles which are enabled by technology, and a common purpose that co-creates value for all stakeholders. These trademarks complement the findings from “How to create an agile organization.”
#agile  #strategy  #bestpractices  #advice  +McKinsey  #A+ 
6 days ago
John Straw (@johnstraw) | Twitter
John Straw

iPhone: 37.787037,-122.412270
Joined May 2009
#disruption  #tl 
6 days ago
The Autonomous Vehicle 50 Disruption Hub Report
The Autonomous Vehicle 50
Find out what Companies Racing to Put Driverless Cars on the Road by 2020
This year’s Consumer Electronics Show could be summed up in one word: Cars. However, the vehicles on show at CES 2017 weren’t just flashy supercars with futuristic bodywork. Automakers and software developers alike used the event to demonstrate their latest developments in autonomous (and electric) technology.

The end of car ownership as we know it has been talked about for some time, ever since the first driverless car prototypes hit the roads almost a decade ago. Now, the market is swarming with major manufacturers and ambitious start-ups looking towards 2020 as the year of mass autonomy.

In the first of our special report series we look at 50 companies shaping the future of autonomous vehicles. Who’s in the race to build the first, and the best, driverless vehicles?

The report includes insights on leading Automative Manufactures:
Audi, BMW, Faraday Future, Fiat Chrysler, Ford, General Motors, Honda, Hyundai, Jaguar Landrover, John Deere, Lucid Motors, Mazda, Mercedes Benz, Mitsubishi, Nissan, Porsche, Peugeot Citreon, Subaru, Tesla, Toyota, Volvo, Volkswagen

And Software and Hardware Providers:
Didi Chuxing, Drive.a, Fisker, Five.ai, Google, Hitachi, Intel, Microsoft, Mitsubishi Electric, Mobileye, Nauto, NextEv, NuTonomy, Nvidia, Oxbotica, QNX, Qualcomm, Seegrid, Uber, Udacity, Valeo, Wheego, Zoox.
#av  #report  #dhub  #2017  >cd 
6 days ago
Rob Crasco #VR #AR #AI (@RoblemVR) | Twitter
Rob Crasco #VR #AR #AI
@RoblemVR Follows you
Influencer, Thought Leader & Futurist. Focus on VR AR & AI #IndieDev #VRforGood #360Video #VRVideo #VirtualWorlds #WomeninTech #WomeninVR #Ally #Resist

Boston, MA
Joined April 2009
Born on August 03
#vr  #ar  #SME 
6 days ago
10 Uses of Facial Recognition Technology Disruption Hub 20170913
10 Uses of Facial Recognition Technology
FaceTech is making an important impact
From security, identification, payments, healthcare, and marketing. For most of us at the moment our only contact with FaceTech is likely to be at electronic passport gates or finding novelty filters on Snapchat. However, like it or not, our faces seem to be becoming an increasingly important tool for accessing possessions and information, as well as enabling different sectors to learn more about consumer markets. Wild wide ranging implications on ethics and business, in future, how might industries – not to mention everyday people – use FaceTech to their advantage?
#image  #recognition  #facial  #applications  +dhub  #2017 
6 days ago
18 Disruptive Technology Trends For 2018 Disruption Hub 20180111
8 Disruptive Technology Trends For 2018
Over the coming year, what will be the most important developments in disruptive technology?
When we think about technology, we often think about physical devices that are electrical or digital. In fact technology encompasses far more than that.  The dictionary definition refers to Technology as, “methods, systems, and devices which are the result of scientific knowledge being used for practical purposes.” As we look to the year ahead  tech disruption will be driven as much by the methods and systems as it is by the devices we associate with tech disruption.

It’s impossible to predict exactly which trends will become the most disruptive over the course of 2018. That being said, there are a number of developments that have and will continue to shape business strategies. From automation to sustainability, organisations are adapting to a whole new wave of consumer preferences. So, this year, which themes can we expect to see influencing businesses and consumers alike?
#tech  #trends  #disruptive  #mobile  #ai  #nwm  #2018 
6 days ago
RT : Artificial Intelligence First - How corporates must now craft their own by Tariq Khatri of…
AI  strategy  from twitter_favs
6 days ago
Machinable (@machinableML) | Twitter
machinable helps organisations shape and deliver practical machine learning solutions that yield real business and social benefit.

London, England
Joined February 2018
#ml  #tl 
6 days ago
Braze Mobile Marketing Platform (formerly Appboy)
Braze moves across channels to bring messaging experiences to life.
Braze is a customer engagement platform built for today’s mobile-first world. We help leading brands create live views of their customers that stream and process historical, in-the-moment, and predictive data in an interactive feedback loop, so immediate action on insights can be taken with relevant messaging across mobile and web. Your customers' behaviors should guide your interactions with them. Braze delivers live customer views that collect and present you with historical, in-the-moment, and predictive data. Use that information to create smarter messaging triggered by the real world.
#CRM  #cx  #engagement  #omnichannel  #analytics  #nwm 
6 days ago
The Artificial Intelligence Talent War Disruption Hub 20180329
The Artificial Intelligence Talent War
AI – the most disruptive technology so far?
Unless you’ve been living under a rock, you’ll be well aware of the importance of Artificial Intelligence for businesses across the board. In a society run on mass data, artificially intelligent platforms are the most effective way to collect and analyse enormous quantities of information. After the Internet, AI could well be the most disruptive technology we are yet to experience. It’s not surprising, then, that companies are vying to get their hands on experts in the field. In fact, the demand for personnel is so high that there aren’t enough specialists to go around. In the words of KPMG, talent is the new arms race. As tech giants gradually accumulate more and more AI expertise, how will this disrupt the use of AI within other businesses?

The scramble for talent
Although AI is clearly the technology of the hour, the demand for talent is not matched by supply. The autonomous car space has been particularly impacted by the need for programming teams and it shows. Automakers are willing to part with serious cash to acquire even modest companies. Last year, for example, General Motors bought 40 person startup, Cruise Automation, for almost $1 billion. As well as competing for programmers, automotive businesses are jealously guarding their intellectual property. In one ongoing lawsuit, Uber has been accused of stealing IP from Alphabet’s Waymo. As all of the promising startups are gobbled up by tech giants, companies have looked to academia as an alternative talent pool. In 2015, Uber shamelessly poached over 40 staff members from Carnegie Melon University’s robotics department, and there’s no doubt that other companies will seek out AI experts too. In fact, 54% of all deep learning specialists are employed by just six companies, and it’s a somewhat predictable list – Google, Microsoft, NVIDIA, IBM, Intel and Samsung.
#ai  #talent  #shortage  #jobs  #datascientists 
6 days ago
Artificial Intelligence First 20180301
Artificial Intelligence First
AI is now a proven technology in discrete applications. How can it be used in more all-encompassing roles?
Although materially beneficial corporate deployments of AI are beginning to proliferate, the AI activities of the majority still amount to a few isolated pilot projects conceived in an ad-hoc basis. Organisations without a clear AI strategy – and that’s most – run the risk of falling behind as other better organised industry players move forward.

That said, while individual AI solutions can be transformative within the scope of their application, that’s not as clear-cut an argument for front-to-back change as, say, the digital transformation of a high street retailer. Developing an AI strategy requires an exercise of careful discrimination – acknowledging the present limitations of AI as well as its strengths in order to identify where one can, cannot, or even should not exploit it.

This article is about the ‘what’ of an AI strategy rather than the equally important ‘how’. We will look at business areas where AI solutions are already having an impact, we’ll try to characterise the boundary line of its applicability and we’ll also hear from some of the areas of research that may eventually bring more business and operations areas within the scope of AI solutions.

Some terminology first though. We prefer ‘machine learning’ over ‘AI’ for being less loaded with singularity overtones. Better still would be the simple term ‘machine prediction’ since, in truth, what the machine learning community anthropomorphically calls ‘learning’ generally means not much more than fitting a model to data.
#ai  #applications  #deployment  #impact  #strategy  A+  #rt 
6 days ago
David Raab (@draab) | Twitter
David Raab
author Guide to Demand Generation Systems ªªhttp://www.raabguide.com ºº; marketing technology and analysis consultant

New York
Joined January 2009
#cdp  #data  #martech  #expert  #SME  #tl  $rr 
6 days ago
Blockchain explained in simple way! 20171028
New trending innovation: Blockchain explained in simple way!

The blockchain is a technology reverberating around the world in the recent times. And it’s been the complex subject as well as complexity solving subject. So, all eyes are looking at this gripping technology that might solve most of the demerits. Let us understand, what exactly it is?

There was a person named ABC and he wants to transact money online to person XYZ. To do this transaction, ABC should use a third-party application that will transact money to XYZ. This process clearly shows a vulnerability, that ABC and XYZ should depend on third-party. So, your security is obviously in the hands of another person.

In such Scenario, we – the users need an efficient, effective, secure, independent, and smart system that can solve complex problems. And most importantly it should be trustworthy and honest.
#blockchain  #explainer 
6 days ago
"The government won't solve the problem for ... they'll need to find their own solutions. What’s n…
trust  marketers  from twitter
7 days ago
"GDPR, and calls for similar regulation in the U.S. may lead to end of what has long been the internet’s grand barg…
from twitter
7 days ago
Beware of A.I. in Social Media Advertising 20180326
Beware of A.I. in Social Media Advertising
CreditYuichiro Chino/Getty Images
By Dipayan Ghosh

March 26, 2018
Nine days ago, we learned that Cambridge Analytica, the firm engaged by the Trump campaign to lead its digital strategy leading up to the 2016 United States presidential elections, illegitimately gained access to the Facebook data of more than 50 million users, many of them American voters. This revelation came on the heels of the announcement made last month by the Justice Department special counsel Robert Mueller of the indictment of 13 Russians who worked for the Internet Research Agency, a “troll farm” tied to the Kremlin, charging that they wielded fake social media accounts to influence the 2016 presidential elections.

But as Facebook, Google, Twitter and like companies now contritely cover their tracks and comply with the government’s requests, they simultaneously remain quiet about a critical trend that promises to subvert the nation’s political integrity yet again if left unaddressed: the systemic integration of artificial intelligence into the same digital marketing technologies that were exploited by both Cambridge Analytica and the Internet Research Agency.
#ai  #advertising  #risks  #critique  #privacy  #socialmedia  #policy 
7 days ago
Dipayan Ghosh (@ghoshd7) | Twitter
Dipayan Ghosh
AI, algorithms & privacy @NewAmerica & @ShorensteinCtr. Former U.S. privacy & public policy advisor @Facebook; tech policy advisor @ObamaWhiteHouse / @WHOSTP44.

Washington, DC
Joined November 2010
#ai  #algorithms  #privacy  #tech  #policy  #SME 
7 days ago
Facebook Is Changing How Marketers Can Target Ads. What Does That Mean for Data Brokers? 20180409
Facebook Is Changing How Marketers Can Target Ads. What Does That Mean for Data Brokers?
Dipayan Ghosh
APRIL 09, 2018


MasterCard: Driving Financial Inclusion

The Power of Consumer Stories in Digital Marketing

Marketing Transformation Using Social Network on...

Last month, Facebook announced in a brief statement that it will be shutting down Partner Categories, a feature that allows marketers to target ads on the company’s universe of platforms by using third-party data provided by data brokers. The move, which comes during a period of intense scrutiny over the social media giant’s privacy and security practices following the Cambridge Analytica revelations, marks a first-of-its-kind pivot among internet companies. This development could have major repercussions for internet companies and the broader digital advertising ecosystem if the firms at the center of this industry follow suit, collectively distancing themselves from data brokers and increasing transparency into their practices with personal data.

Traditionally, marketers on Facebook — and on most major platforms that allow targeted ads — have had three types of data streams they could leverage for targeting. First, they could use data they have collected themselves, like the names and email addresses of the customers who visit their brick-and-mortar or online stores. Second, they could use data gathered by Facebook, which maintains a rich data profile on users based on their use of the platform, web browsing history, and cellular location, among other sources. And third, they could use data provided by third parties — which typically are the companies we know as data brokers. Among these are well-known names in the industry, including Acxiom, Oracle, Epsilon, and Experian.
#ad  #targeting  #data  #brokers  #FB  #personalization  #privacy 
7 days ago
What's The Right Path For Deploying 5G Infrastructure? 20180307
What's The Right Path For Deploying 5G Infrastructure?

Roslyn Layton , CONTRIBUTOR
Evidence-based tech policy
Opinions expressed by Forbes Contributors are their own.
5G, the fifth generation in mobile wireless networks, promises an innovation revolution by bringing digital intelligence to previously analog technologies. 5G speeds will be ten times faster than the wireless speeds we know today and will eliminate latency (or lag time), enabling technologies that need instant, seamless connectivity. 5G will foster technologies like autonomous vehicles, virtual reality, and remote surgery and will herald a new era of smart bodies, homes, cities, farms, and cars.

The comparatively easy part of 5G is retrofitting old devices with artificial intelligence (AI) to make them smart. Consider AutoPi, which turns ordinary cars into something like KITT, the talking car from Knight Rider, or Ikea’s smart lightbulbs that connect to the internet to make power consumption more efficient.
#5G  #deployment  #status 
7 days ago
Robert M. McDowell (@McDowellTweet) | Twitter
Robert M. McDowell
Random thoughts (personal only) of @DukeU & @WilliamandMary alum, former @fcc Commish, @cooleyllp partner & @hudsoninstitute Sr. Fellow. RT not endorsement etc.

Joined November 2013
#tech  #wireless  #mobile  #regulation  #FCC  #5G 
7 days ago
michael petricone (@mpetricone) | Twitter
michael petricone
A hodgepodge of tech policy, music, food & Boston sports. Head of Gov Affairs at CTA. All opinions are my own. RT ≠ agreement, RT = interesting thought

Washington DC
Joined December 2007
#CE  #tech  #exec  #SME  +CTA 
7 days ago
Martin Cooper (@MartyMobile) | Twitter
Martin Cooper
The best prize that life offers is the chance to work hard at something worth doing.—Theodore Roosevelt ªªhttp://bit.ly/1LxW7LU ºº; ªªhttp://bit.ly/1VU7II6 ºº

Del Mar, California
Joined August 2009
#mobile  #wireless  #SME  #history  #innovation  +MartyCooper 
7 days ago
Local Laws Imperil 5G Innovation 20180402
Local Laws Imperil 5G Innovation
Misapplied zoning rules and huge fees block antennas the size of pizza boxes.
Marty Cooper stepped out of his office and onto a New York street corner, pulled out his phone, and made a call. It happens millions of times a day—but it didn’t then. It was April 3, 1973, and Mr. Cooper, now 89, was making the first call ever from a hand-held cellphone.

Forty-five years later, governmental obstacles threaten to block a new wave of wireless innovation, known as fifth generation or “5G.” It will multiply download speeds by at least 10 times, allowing wireless carriers to compete with cable companies for high-speed internet access. With superfast speeds and low lag times, 5G will enable advances in everything from driverless cars to the “tactile internet,” in which surgeons can perform operations and builders operate construction equipment remotely, and entertainment can include sensations beyond the audiovisual.

A 5G-enabled Internet of Things will connect people, data and new devices, creating a surge of economic growth. IHS Markit estimates that in the U.S. alone 5G will yield $719 billion in growth and 3.4 million new jobs by 2035. The world-wide figures could be as high as $3.5 trillion and 22 million jobs.

But to prepare for 5G, wireless carriers need to deploy thousands of “small cell” antennas, the size of pizza boxes. Even though small cells can fit invisibly on rooftops and lampposts, some state and local governments are acting as if they’re 100-foot towers.
#mobile  #5G  #deployment  #challenges 
7 days ago
Larry Downes (@larrydownes) | Twitter
Larry Downes
NYT best-selling author. Technology, strategy and the law. Project Director, Georgetown Center for Business and Public Policy.

Berkeley, CA
Joined November 2008
#strategy  #innovation  #SME  #tl  +LarryDownes 
7 days ago
« earlier      
#2016 #2017 #2018 #a+ #academic #advertising #advice #ai #amazon #analyst #analytics #application #applications #atl #b2b #bain #behavioraleconomics #bestpractices #bigdata #book #cao #case #cases #casestudy #cdp #challenges #cmo #cognitivecomputing #competition #conference #consumer #course #critique #cx #data #datascience #davidraab #deeplearning #deloitte #deployment #design #digital #disruption #disruptive #dl #engagement #enterprise #execution #expert #explainer #firm #gartner #gatech #gdpr #gobackto #google #hbr #hc #healthcare #impact #incubator #india #innovation #iot #leadership #location #m&a #marketing #martech #mckinsey #mit #ml #mobile #news #nlp #nwm #optum #order #organization #outlook #patientengagement #payers #peh #personalization #platform #priorauth #privacy #providers #report #research #retail #role #rpa #rr #rt #sme #software #source #startup #startups #stats #status #strategy #survey #tech #technology #thoughtleader #thoughtleaders #tl #tomdavenport #tools #trends #ux #vc #vendor #vendors #video ad ads advertising advice agile agree ai analytics anticipatory app apps atl beacon beacons big bigdata brands connected consumers content context customer cx data datascience design devices digital digitalsignals disruptive dooh eddystone engagement enterprise fail growth health healthcare ibeacon in-store indoor innovation innovative iot lbs learning local location loyalty m-commerce marketing mcommerce media mhealth ml mobile mpayment mpayments mustread news nfc ooh payments peer personalization privacy proximity research retail retailers security sensors shoppers shopping smartphones social startup startups strategy tablets tech technology ui ux value vc

Copy this bookmark: