Juniper Research forecasts that the number of connected IoT (Internet of Things) devices, sensors and actuators will reach over 46 billion in 2021. This 200% increase, from 2016, will be driven in large part by a reduction in the unit costs of hardware. Juniper forecasts that it will average close to the ‘magic’ $1 throughout the period. It was found that industrial and public services will post the highest growth over the forecast period, averaging over 24% annually.
Ten years ago today, Apple announced the iPhone.
Demonstrating the new pocket communicating computer at Macworld in San Francisco, Steve Jobs said:
Every once in a while, a revolutionary product comes along that changes everything… today, we’re introducing three revolutionary products… The first one is a widescreen iPod with touch controls. The second is a revolutionary mobile phone. And the third is a breakthrough Internet communications device…. An iPod, a phone, and an Internet communicator…These are not three separate devices, this is one device, and we are calling it iPhone.
Walter Isaacson in Steve Jobs:
The iPhone was immediately dubbed the “Jesus Phone” by bloggers. But Apple’s competitors emphasized that, at $500, it cost too much to be successful. “It’s the most expensive phone in the world,” Microsoft’s Steve Ballmer said in a CNBC interview. “And it doesn’t appeal to business customers because it doesn’t have a keyboard.”… By the end of 2010, Apple has sold ninety million iPhones and it reaped more than half the total profits generated in the global cell phone market.
From designer Tony Fadell interview with the BBC:
The press mocked the cultish manner in which iPhone was unveiled. Steve Ballmer, at the time Microsoft’s chief executive, famously laughed at the device, calling it “not a very good email machine” that wouldn’t appeal to business users.
“We all laughed at him,” Fadell remembered.
“We also laughed at Blackberry. Whenever I create a new product?, and I learned this with Steve [Jobs], if the incumbents laugh at you and the press laugh at you, you go, ‘we’ve hit a nerve’.”
Since that day, more than a billion iPhones have been sold, helping make Apple the richest company in the world.
In 2017, 2.35 billion people, more than half of the world’s mobile phone users, will regularly use a smartphone, according to eMarketer. And by 2020, smartphones will account for more than 60.0% of mobile phone users worldwide.
In Pressed Data, my Forbes.com column, I try to chronicle the evolution of digital technologies, their business impact, and the people behind the innovations, business models, and new ideas. In 2016, I covered artificial intelligence—the 60-year-old new new thing, big data—the most recent hottest trend and a catalyst for the new-found popularity of the new one, the fading away of former tech leaders, a number of startups, and a number of influential business and tech innovators. These were the highlights:
When Artificial Intelligence Started To ‘Change The World’
A review of ENIAC in Action: Making and Remaking the Modern Computer, “a nuanced, engaging and thoroughly researched account of the early days of computers, the people who built and operated them, and their old and new applications,” contrasting it with “history as hype, offering a distorted view of the past, sometimes through the tinted lenses of contemporary fads and preoccupations.”
A New Documentary Reveals A One-Dimensional Face Of Big Data
Hype is on full display in “The Human Face of Big Data” of which I wrote: “…in our technology-obsessed world, new technologies and new technology applications tend sometimes to become buzzwords that are hyped, celebrated and often discussed irresponsibly by technology vendors and the media. Unfortunately, ‘The Human Face of Big Data’ by and large falls into this trap, the fascination (self-delusion?) with the idea of we are living a momentous time in history thanks to technology.”
Top 10 Hot Big Data Technologies
The hype—and an ambiguous and ill-defined term—does not mean that there is no value in adopting and applying the set of technologies that can be classified as big data technologies. In TechRadar: Big Data, Q1 2016, Forrester Research evaluated the maturity and trajectory of 22 technologies across the entire data life cycle.
Many of the Yahoo obituaries published in 2016 contrasted its demise with the flourishing of Google, another Web pioneer. Why was Google’s attempt to “organize all the world’s information” vastly more successful than Yahoo’s? The short answer: Because Google did not organize the world’s information. Google got the true spirit of the Web, as it was invented by Tim Berners-Lee. Following the latter’s disdain for pre-defined classification systems and taxonomies, Google’s founders built their information retrieval business on tracking closely cross-references (i.e., links between pages) as they were happening and correlating relevance with quantity of cross-references (i.e., popularity of pages as judged by how many other pages linked to them). In contrast, Yahoo had a “Chief Ontologist” on staff. As happens often in the cutting-edge technology business, new ideas are “revolutionary” only in the sense of revolving back to old ones: The concept of cross-references can be trace back to Ephraim Chambers’ Cyclopaedia, published in London in 1728.
The 3 Mindset Shifts You Need For A Successful Digital Transformation
Keri Gohman, Executive Vice President and Head of Small Business Banking at Capital One, on what businesses need to do to gain customer loyalty in the new digital environment.
AI And Machine Learning Take Center Stage At Intel Analytics Summit
From the most recent edition of the tech bible: Moore’s Law begat faster processing and cheap storage which begat machine learning and big data which begat deep learning and today’s AI Spring.
Future Business Leaders As Data Scientists: Reflections On The Career Of Intel Chief Data Scientist
A profile of Bob Rogers, Chief Data Scientist for Big Data Solutions at Intel, the entrepreneurial data scientist who has successfully applied artificial intelligence to healthcare.
A Very Short History Of Artificial Intelligence (AI)
Milestones in the evolution of “thinking machines.”
Artificial Intelligence Pioneers: Peter Norvig, Google
A profile of Peter Norvig, Director of Research at Google.
Deep Learning Is Still A No-Show In Gartner 2016 Hype Cycle For Emerging Technologies
In 2016, Gartner has moved machine learning back a few notches from where it placed it on the previous year’s “Hype Cycle,” putting it at the peak of inflated expectations, and still estimating 2 to 5 years until mainstream adoption. Is machine learning an “emerging technology” and is there a better term to describe what most of the hype is about nowadays in tech circles?
Internet Of Things By The Numbers: What New Surveys Found
Things are looking up for the Internet of Things. 80% of organizations have a more positive view of IoT today compared to a year ago, according to a survey of 512 IT and business executives by CompTIA.
A Very Short History Of EMC Corporation
Milestones in the remarkable 37-year history of EMC Corporation, 16 of which I had the pleasure to witness in person.
Only Humans Need Apply Is A Must-Read On AI For Facebook Executives
In Only Humans Need Apply: Winners and Losers in the Age of Smart Machines, knowledge work and analytics expert Tom Davenport and Julia Kirby, a contributing editor for the Harvard Business Review, re-introduce the concept of augmentation to our discussion of the impact of AI on jobs—humans and computers combing “their strengths to achieve more favorable outcomes than either could do alone.”
12 Observations About Artificial Intelligence From The O’Reilly AI Conference
At the inaugural O’Reilly AI conference, 66 artificial intelligence practitioners and researchers from 39 organizations presented the current state-of-AI: From chatbots and deep learning to self-driving cars and emotion recognition to automating jobs and obstacles to AI progress to saving lives and new business opportunities.
Artificial intelligence (AI) And The Future Of Marketing: 6 Observations From Inbound 2016
At Inbound 2016, HubSpot’s co-founders Brian Halligan and Dharmesh Shah entertained 19,000 attendees with their take on the past and future of marketing.
2017 Predictions For AI, Big Data, IoT, Cybersecurity, And Jobs From Senior Tech Executives
Artificial intelligence (and machine/deep learning) is the hottest trend, eclipsing, but building on, the accumulated hype for the previous “new big thing,” big data. The new catalyst for the data explosion is the Internet of Things, bringing with it new cybersecurity vulnerabilities. The rapid fluctuations in the relative temperature of these trends also create new dislocations and opportunities in the tech job market.
Here’s to a productive and enjoyable 2017!
Brian Halligan and Dharmesh Shah at Inbound 2016
At Inbound 2016, HubSpot’s co-founders Brian Halligan and Dharmesh Shah entertained 19,000 attendees with their take on the past and future of marketing. Here’s what I learned from their keynote presentation and a brief interview.
2017 will be the year of the bot. So predicts Halligan, adding “in five years, you will do a lot less navigating through apps and more just asking questions and chatting back and forth with bots… the next thing you know, we like it and it’s easier and more efficient than waiting for the sales rep to call you back.” Shah notes that businesses started building websites in the 1990s so they can answer customer questions 24/7. “Soon,” he says, “they will start building bots. They won’t replace the websites, but they will power them. The shortest time between a customer question and the answer will be a bot. It’s not human vs. bot, it’s human to the bot powered.” (HubSpot’s recent contribution to the bot power movement: Growthbot).
The “marketing conversation” will become a human-machine conversation. That the essence of marketing is a “conversation” between a business (or any “brand”) and its customers and potential customers has been a marketing tenet (and cliché) for a long time. While that conversation has been conducted over the last twenty years increasingly through a computer screen with the help of a keyboard, it is now transforming into human-machine conversation. “The conversational UI,” says Shah, “is going to be an even bigger leap in software than we had with the shift to Web-based software. We are all re-thinking now how to build products.” It’s the most natural way to engage, interact, market and sell: “We will have voice input because it’s much more efficient [than typing] and visual output because it’s more efficient than listening—we can see and read and scan much faster that we can listen. I don’t think screens are going away but the keyboard is likely going to be less and less prevalent.”
AI will accelerate marketing and sales. “In the next few years,” says Shah, we are going to have autonomous, self-driving, marketing automation.” Machine learning will improve sales and marketing software by giving it “the ability to do things without us explicitly telling it what to do.” As a result, tasks such as predictive lead scoring, content recommendations, and email acquisition will get a lot better. Another interesting example Shah pointed to is what he calls ”Match.com for leads”—Automatically routing leads to the right sales person based on analysis of the data about the lead and about the sales people.
Marketers will not be replaced by AI and will be able to skip the boring stuff. “Anything that seems rote or mechanical,” says Shah, “there is no reason for humans to do—it’s all going to go to AI.” Marketers will continue to be involved, however, with anything that has to do with creativity and they will focus on “understanding the customer, figuring out what the overall positioning is, having actual conversations with other humans. More interaction design is what marketers will do rather than the mechanics of marketing.” Bots working in the background as virtual assistants will help with the kind of work we (especially sales people) don’t like to do, such as updating the CRM.
Algorithm development will become a commodity and data will become the key differentiator. Now that you can buy algorithms off-the-shelf, “mere mortals like me don’t have to learn about machine learning per se,” says Shah. “More companies, including HubSpot, will start doing things that we thought required 100 PhDs. The winners will be the ones that have the data that can feed the machine learning algorithm.”
The Link Graph is going to be replaced by the Engagement Graph. Google has gained fame and fortune because it has built the best link graph, indexing and mapping the connections between all Web pages, determining content quality by popularity, i.e., inbound links. Amazon has built the Product Graph and today, more than 50% of people looking for a product, first turn to Amazon. Facebook has built the Social Graph linking 1.79 billion people, and they use its search box 2 billion times a day. But the future belongs to the Engagement Graph where the quality of content is determined by the number of people listening, interacting, getting engaged.
Ten years ago, Halligan and Shah took the idea of inbound links and applied it to sales and marketing. Giving birth to “inbound marketing” and to HubSpot, they understood that the Web changed how people buy. In this new customer landscape, blanketing the market with generic ads and messages and press releases was not going to work as it did before. Instead, businesses, especially small businesses, should get potential buyers to want to come to them, to find them just like they find a good and relevant Web page. With high quality, helpful, and engaging content, they can gain the buyer’s trust and loyalty.
In his keynote presentation, Halligan enumerated what has changed over the last ten years since the inception of inbound marketing and HubSpot:
| 2006 | 2016 |
| Fight for an inch on a 4-foot shelf | Battle for a millimeter on an infinite shelf |
| Buyers read all day | Buyers watch video all day |
| Google helps you find answers | Google gives you the answer |
| Pay per click | Pay per lead |
| The website augments the salesperson | The salesperson augments the website |
| Buyer expects to get value after purchase | Buyer expects to get value before purchase |
Ten years ago, Halligan and Shah imagined not only the soul of the new marketing—the new type of content you need to produce to get the buyers’ attention—but also the new food for the soul—data. To succeed with inbound marketing, you need to have all the data at your fingertips, the data about what people do on your website, and the data about these people and the needs and desires they represent. “We are a data play,” says Halligan. “The fun part of our job is to try and predict the future and build a platform that will match that future.”
Originally published on Forbes.com
Americans are incorporating a wide range of digital tools and platforms into their purchasing decisions and buying habits, according to a Pew Research Center survey of U.S. adults. The survey finds that roughly eight-in-ten Americans are now online shoppers: 79% have made an online purchase of any type, while 51% have bought something using a cellphone and 15% have made purchases by following a link from social media sites. When the Center first asked about online shopping in a June 2000 survey, just 22% of Americans had made a purchase online. In other words, today nearly as many Americans have made purchases directly through social media platforms as had engaged in any type of online purchasing behavior 16 years ago.
But even as a sizeable majority of Americans have joined the world of e-commerce, many still appreciate the benefits of brick-and-mortar stores. Overall, 64% of Americans indicate that, all things being equal, they prefer buying from physical stores to buying online. Of course, all things are often not equal – and a substantial share of the public says that price is often a far more important consideration than whether their purchases happen online or in physical stores. Fully 65% of Americans indicate that when they need to make purchases they typically compare the price they can get in stores with the price they can get online and choose whichever option is cheapest. Roughly one-in-five (21%) say they would buy from stores without checking prices online, while 14% would typically buy online without checking prices at physical locations first.
Startup Aperio Systems emerged from stealth mode in November, offering “a polygraph for process data, detecting when your system is lying to you,” says CEO Yevgeni Nogin. “We are not a typical cybersecurity company,” Nogin explained in a phone interview on November 13. “We have an unusual number of physicists on board, in addition to cybersecurity experts.”
One of the physicists is vice president of product Michael Shalyt who walked me through Aperio’s clever answer to the recent increase in attacks on critical infrastructure systems. In December 2015, a Ukrainian power grid was taken down, leaving more than 230,000 residents in the dark. A few months later, hackers managed to infiltrate a water treatment plant in the U.S. and change the levels of chemicals being used to treat tap water. But “the vast majority of attacks are not disclosed,” says Shalyt. “Hackers have realized recently that they can attack the physical world using digital code.”
The much talked-about Internet of Things (IoT) is the poster boy for both the accelerated merger of the physical and digital worlds and the inadequate security of physical objects. That became apparent last month with the temporary shutdown of the Internet in parts of the U.S. due to an attack orchestrated by taking control of insecure connected devices such as security cameras and baby monitors. Going beyond consumer devices, the same type of attacks now threaten the sensors and other physical objects in critical infrastructure installations such as power plants and other industrial control systems.
Aperio answers the challenge by non-intrusively plugging into an existing control system and unleashing its advanced machine learning algorithms to study and identify the system’s unique “fingerprints.” That serves as the baseline for determining the validity of the process data produced at any given moment and alerting operators when an anomaly—forged data—is detected. The attackers typically produce forged data because they need to mask their presence and gain the time required for them to inflict long-term damage to the equipment. “Our role is to understand the process well enough that whenever an attacker will send a signal that cannot be generated by this specific equipment or plant or mode of operation, we alert the operators that someone is fooling them,” says Shalyt.
Using a sophisticated combination of physics and state-of-the-art machine learning techniques, Aperio than reconstructs the real values of the forged operational data and reverts it to its original state in real time. Establishing the true state of the system is important because that could mean the difference between the necessity for an emergency shutdown of the system or a more controlled one which is less costly and disruptive. “The beauty of physical systems is that everything is connected to everything else and we use this complexity to our advantage,” says Shalyt.
It is also the beauty of having physicists who understand the laws of physics a system follows and can detect the normal rhythm of the system and its unusual and abnormal behavior. The same laws of physics operate across many specific domains—power plants, oil and gas facilities, water and waste control, pharma, manufacturing, and transportation—allowing Aperio to apply its artificial intelligence in multiple markets. In the future, Aperio would like to be able to provide a validation for any information communicated by any type of sensor, in both industrial and consumer environments.
Currently tested by four different power plants, Aperio has secured seed funding from a consortium of private investors, including prominent cybersecurity veterans Doron Bergerbest-Eilon, Liran Tancman, and Shlomi Boutnaru. Bergerbest-Eilon has played a major role in establishing the agency charged with protecting all critical infrastructure in the State of Israel and is the former director of the security and protection division of the Israel Security Agency (ISA). Tancman and Boutnaru, who played key roles in building Israel’s cybersecurity capabilities, founded predictive cybersecurity startup CyActive, which was acquired by PayPal in 2015.
Originally published on Forbes.com
“2017 will show us that limited deployments are technically, legally, and socially possible, even under today’s laws,” says Bryant Walker Smith, a professor at the University of South Carolina.
The cars themselves, with their distinctive sensor rigs mounted onto their rooftops, will be most visible as they putter down our roads. Behind the scenes, their makers are hurrying to iron out the technical, regulatory, and economic details needed so that one day somewhat soon, most of us will get to take our stupendously fallible meat gloves off the wheel.
BCG:
By 2035, 12 million fully autonomous units could be sold a year globally, and the market for partially and fully autonomous vehicles is expected to leap from about $42 billion in 2025 to nearly $77 billion in 2035. By 2035, autos with autonomous vehicle features are expected to capture 25% of the new car market.
After following the presidential election for 18 months and experiencing up close and personal the “best marketing case study ever,” marketing guru David Meerman Scott has concluded: “The best marketer has been elected president.” Here’s what I learned from his presentation at Inbound16, a day after Donald J. Trump became the 45th president of the United States.
Keep it simple: Trump relied on just two strategies, one online—real-time Twitter, the other offline—mega rallies. Both strategies aimed at getting free publicity, and with the aid of provocative sound bytes, Trump ended up generating $5 billion in free media. And the twin strategies were tightly integrated, with online and offline activities and events feeding each other (e.g., proper follow-up online after an event).
Keep it Inbound: Clinton (and Sanders and Bush) followed the old rules of marketing, relying on outbound marketing—spending heavily on advertising, acting like a large company pushing out messages, “targeting” what it thinks are the right “buyers.” The Trump campaign acted like today’s startups, relying on inbound marketing—“instead of the old outbound marketing methods of buying ads, buying email lists, and praying for leads, inbound marketing focuses on creating quality content that pulls people toward your company and product, where they naturally want to be.” Trump relied on “the proven methodology for the digital age.”
Keep it focused: Trump created (or vastly expanded) a powerful brand, using a memorable message (and a hashtag #MAGA) while many of her supporters could not recall Clinton’s slogan (“Stronger Together”).
Keep it energized: On Twitter, Trump reacted to news in real-time, generating reactions, conversations, free media, and more and more followers. Offline, Trump energized large audiences—“crowd size does matter,” to quote Kellyanne Conway—and showing off the size of the crowds on TV (for free) certainly mattered a lot.
Keep it up: Trump used every opportunity, including adversarial ones, to promote his message. When Gawker published Trump’s cell phone number (urging readers to call and ask him about his important ideas), anyone who called, as David Meerman Scott did, heard the following recorded message: “I’m Donald Trump and I’m running for the presidency of the United States of America. With your help and support, together we can make America truly great again. Visit me at Twitter @RealDonaldTrump and check out my campaign website at www.donaldtrump.com. Hope to see you on the campaign trail.”
David Meerman Scott called Trump “a marketing genius.” That may be true, but I think it’s more than just the mastery of the mechanics of digital marketing or intuitively understanding why inbound marketing may work better than outbound marketing. Trump understands the most fundamental underpinning of marketing, whether of the old or new variety: Know your customers, what they care about, what will make them act. And in 2016, the pundits suffering from Post-Trump-Matic-Stress-Syndrome notwithstanding, it was not “the economy, stupid.” It was not “jobs” or “globalization.”
It was the people revolting against political correctness, against arrogant and ossified political elites, and Trump’s sometimes revolting statements ensured them, even if they did not agree with some or all of these statements, that this time, they can really hope for a change. When asked in exit polls which candidate quality mattered most, only 35% of the respondents who answered “cares about me,” 26% that said “good judgment” and 8% of the respondents that opted for “right experience,” were Trump voters. But 83% of the respondents that answered “change” were Trump voters (as opposed to the 14% who voted for Clinton).
So I would venture to add another marketing lesson: Keep looking, keep asking what really motivates my customers.
Originally published on Forbes.com
IDC has released its 2017 predictions for digital transformation and for CIOs, in addition to its IT industry predictions. Digital transformation is a technology-centric transformation, says IDC, that is profoundly changing business and society. Here is what IDC expects to see in the coming years:
By 2021, one third of CEOs and COOs of Fortune 2000 companies will have spent at least 5 years of their career in a technology leadership role.
This will be a new career path for current CIOs who can forge digital-based alliances across the enterprise and lead digital transformation initiatives.
Only 40% of CIOs will lead the digital transformation of the enterprise by 2018.
CIOs leading digital transformation will build organizational linkages with line of business technology teams and across IT organizational silos, and will empower changes in thinking, culture, and practices.
By 2018, companies investing in IoT-based operational sensing and cognitive-based situational awareness will see 30% improvements in the cycle times.
IT will need human resources that have detailed process knowledge, as well as IT capabilities to implement IoT technologies.
By 2019, 40% of IT projects will create new digital services and revenue streams that monetize data.
IT will have to drive data and analytical strategies for companies. (See also Tom Davenport’s IT Organizations: The Shoemaker’s Analytical Children).
By 2019, 5% of revenue will come through interaction with a customer’s digital assistant.
Intelligent agents will create an array of conversational interaction points that need to be defined, maintained and managed. Organizations will need to develop a new set of skills in sales, marketing, and product organizations to serve a connected user.
By 2018, 45% of CIOs will shift primary focus from physical to digital and move away from BPM and optimization to deliver scale, predictability, and speed.
Leveraging digital technologies, new business models, and entrepreneurial cultures will be required for success.
By the end of 2017, revenue growth from information-based products will be double that of the rest of the product/service portfolio for one third of all Fortune 500 companies.
Analytics will become value-added services that will increase the revenue potential of information-based products. Organizations will need to develop new data mining skills that will be required to fully realize this potential.
By 2017, 80% of CIOs will help drive global risk portfolios that enable adaptive responses to security, compliance, business, or catastrophic threats.
This will be a significant expansion in the scope of responsibilities of the CIO and will lead the further integration of IT with the business and the opening of new career paths for CIOs.
The vast impact of the digital transformation of the enterprise will include the emergence of new funding models, acceleration in industry disruption and business innovation, data becoming the new capital and rapid increase in worldwide demand for digital workers. The end result will be the transformation of all enterprises into digital natives.
Originally published on Forbes.com
