WhatsTheBigData

The Machine Learning Landscape

Posted on January 9, 2016 by GilPress

MachineIntelligenceLandscape

Most of these machine intelligence startups take well-worn machine intelligence techniques, some more than a decade old, and apply them to new data sets and workflows. It’s still true that big companies, with their massive data sets and contact with their customers, have inherent advantages—though startups are finding a way to enter.

Achieving autonomy

In last year’s roundup, the focus was almost exclusively on machine intelligence in the virtual world. This time we’re seeing it in the physical world, in the many flavors of autonomous systems: self-driving cars, autopilot drones, robots that can perform dynamic tasks without every action being hard coded. It’s still very early days—most of these systems are just barely useful, though we expect that to change quickly.

These physical systems are emerging because they meld many now-maturing research avenues in machine intelligence. Computer vision, the combination of deep learning and reinforcement learning, natural language interfaces, and question-answering systems are all building blocks to make a physical system autonomous and interactive. Building these autonomous systems today is as much about integrating these methods as inventing new ones.

The new (in)human touch

The virtual world is becoming more autonomous, too. Virtual agents, sometimes called bots, use conversational interfaces (think of Her, without the charm). Some of these virtual agents are entirely automated, others are a “human-in-the-loop” system, where algorithms take “machine-like” subtasks and a human adds creativity or execution. (In some, the human is training the bot while she or he works.) The user interacts with the system by either typing in natural language or speaking, and the agent responds in kind.

These services sometimes give customers confusing experiences, like mine the other day when I needed to contact customer service about my cell phone. I didn’t want to talk to anyone, so I opted for online chat. It was the most “human” customer service experience of my life, so weirdly perfect I found myself wondering whether I was chatting with a person, a bot, or some hybrid. Then I wondered if it even mattered. I had a fantastic experience and my issue was resolved. I felt gratitude to whatever it was on the other end, even if it was a bot.

On one hand, these agents can act utterly professional, helping us with customer support, research, project management, scheduling, and e-commerce transactions. On the other hand, they can be quite personal and maybe we are getting closer to Her — with Microsoft’s romantic chatbot Xiaoice, automated emotional support is already here.

As these technologies warm up, they could transform new areas like education, psychiatry, and elder care, working alongside human beings to close the gap in care for students, patients, and the elderly.

Posted in Artificial Intelligence, Machine Learning, Misc | Leave a comment

Remembrance of Technology Past in 2030

Posted on January 8, 2016 by GilPress

Tech_in2030

Source: @ValaAfshar

Posted in Misc | Tagged skype, YouTube | Leave a comment

Music streaming grew 93% in 2015

Posted on January 7, 2016 by GilPress

music_streaming_2015

Nielsen:

…on-demand audio and video streaming continued to gain in popularity in 2015, posting growth rates of 83% and 102%, respectively. In fact, Justin Bieber’s album Purpose set an all-time record for total audio on-demand streams when it was streamed more than 100 million times the week of its release.

In the physical realm, vinyl stayed strong, as sales of LPs hit a new record in 2015—nearly 12 million units. This marks the 10^th straight year of vinyl sales growth. The big winners in this realm were independent record stores, which drove 45% of all vinyl sales. The biggest genre for vinyl? Rock, with 68% of LP sales.

Tech Crunch:

…despite the rise of streaming, these services have not yet overtaken radio as the number one way people are discovering new music. Instead, 61 percent report hearing songs first on AM, FM or satellite radio; 45 percent say it’s word-of-mouth that leads to discovery; 31 percent hear songs in movies or in soundtracks; and then streaming clocks in at fourth place, with 27 percent saying they learned of new songs from streaming websites or apps…

In the U.S., consumers spend 24 hours per week on average listening to music. And of the 91 percent of Americans who listen to music, 75 percent report listening to music online every week, while 44 percent listen on smartphones…

Meanwhile, when it comes to spending on music, live music like concerts (32%) and music festivals (10%) still eat up nearly the majority of spend. Satellite radio accounts for another 11 percent of spending, while paid streaming registers at only 7 percent – behind physical sales (13%) and digital downloads (11%).

Posted in Misc | Tagged music streaming, Nielsen, video streaming | Leave a comment

Mobile App Usage Rose 58% in 2015

Posted on January 6, 2016 by GilPress

Mobile_growth

Flurry Insights:

In 2015 overall app usage grew by 58%. In this context, we define app usage as a user opening an app and recording what we call a “session.” With the exception of Games, every app category posted year-over-year growth with Personalization, News & Magazines and Productivity leading the way with triple-digit growth…. What was even more impressive is the majority of that growth rate came from existing users versus new users. In fact, in 2015, we estimate that 40% of the 58% total growth in sessions came from existing users, compared to 20% in 2014 and 10% in 2013…

Personalization apps saw their sessions balloon more than 332% in 2015. These apps range from Android lock-screens to Emoji keyboards. When we looked deeper into the category, we noticed that the majority of the growth is coming from Emoji apps (mainly keyboards) giving consumers the ability to share customized correspondence in their favorite messaging apps, such as Facebook Messenger, Whatsapp, Line and Snapchat. It is not a surprise then to see Kim Kardashian’s app “Kimoji”skyrocket to the number 1 spot on the Apple AppStore, on its launch day.

News and Magazine apps grew a whopping 135% in 2015. This growth validates the trend in media consumption we reported on last summer, signaling a shift in media consumption from television and PCs to smartphones in general, and phablets in particular, as we will discuss later.

Productivity apps continued the trend that started in 2014, with 125% sessions grow in 2015. In fact, more and more consumers, especially teens and college students are using their smartphones, phablets and tablets as their primary computing device and their sole device to access email and other productivity apps, like Google Docs, Quip, Slack and the Microsoft productivity suite.

Lastly, Lifestyle and Shopping apps grew 81% in 2015, following a 174% growth in 2014. This growth rate validates reports in early 2015 that mobile commerce is “growing like a weed” and already accounts for 33% of online commerce in the US and 40% of online commerce on a worldwide basis.

Inch by Inch, Mobile and its Apps Absorb the Media Industry.

Mobile_timeSpent

Time spent on phablets grew 334% year-over-year (2.9 times more than the average), compared to 117% for all form factors. With time spent on mobile surpassing that on television, and phablets posting astonishing growth in media consumption, it appears that the cable industry will find in the phablet and its apps its long-awaited digital nemesis.

The Phablet: The Unstoppable Media Consumption Device.

…In 2015, Flurry tracked a mind boggling 3.2 trillion sessions. When we started 8 years ago, we never thought that our counters could reach these numbers. But, we have been fortunate enough to have a front row seat watching the mobile revolution unfold and absorb (and in some case demolish) industry after industry.

Posted in Misc | Tagged Flurry | Leave a comment

History of Databases (Infographic)

Posted on January 4, 2016 by GilPress

Source: Cazena

Posted in Databases, Misc | Tagged cazena | Leave a comment

Technologies Shaping the Future: #cloud, #mobile, #IoT, #cognitive

Posted on December 29, 2015 by GilPress

technologies-of-the-future-cloud-mobile-tech

Source: World Economic Forum

Posted in Internet of Things, Misc, Predictions | Tagged technologies shaping the future | Leave a comment

Gartner, IDC and Forrester on the Future of Digital Transformation

Posted on December 27, 2015 by GilPress

digital transformation wordl

Gazing intensely into their respective crystal balls, Gartner, IDC, and Forrester have come up with predictions for 2016 and beyond, highlighting digital transformation and its impact on businesses and consumers worldwide.

According to Forrester, only 27% of today’s businesses have a coherent digital strategy that sets out how the firm will create customer value as a digital business. Gartner says, however, that 125,000 large organizations are launching digital business initiatives now and that CEOs expect their digital revenue to increase by more than 80% by 2020. IDC expects that the percentage of enterprises creating advanced digital transformation initiatives will more than double by 2020, from today’s 22% to almost 50%.

IDC predicts the emergence of the “DX (digital transformation) economy,” Gartner talks about the rise of the “algorithmic business” and the “programmable economy,” and Forrester charts a roadmap for companies responding to digitally savvy customers and consumers. Based on their predictions, here are 3 strategic trends and 3 sets of technologies – big data analytics, Internet of Things (IoT) and Artificial Intelligence (AI) – that will drive digital transformation for the balance of this decade.

Digital transformation will become the key strategic thrust for most CEOs

In 2016, CEOs will make a concerted effort to integrate the various digital initiatives across the business and create a clear digital vision that shows how the business will deliver revenue-generating digital experiences. B2B industries will start to close the digital gap with their B2C peers as they too are confronting rapidly rising customer expectations. By 2018, 67% of the CEOs of Global 2000 enterprises will have digital transformation at the center of their corporate strategy.

Digital transformation initiatives will be consolidated into one vision and function

In 2016, CEOs will make a concerted effort to integrate various digital initiatives across the business and create a clear digital vision that shows how the business will deliver revenue generating digital experiences. By 2017, 60% of enterprises with a digital transformation strategy will deem it too critical for any one functional area and create an independent corporate executive to oversee the implementation.

Digital transformation will require new skills and a shift in IT investments

By 2018, 35% of IT resources will be spent to support the creation of new digital revenue streams and by 2020 almost 50% of IT budgets will be tied to digital transformation initiatives.

Access to talent and the ability to hire the right people at the right time and place will become a big competitive differentiator. Enterprises pursuing digital transformation initiatives will more than double the size of their software development teams by 2018, focusing new hires almost entirely on digital initiatives. Digital skills like mobile app development, analytics, and design thinking will become the new normal for software development.

A greater reliance on digital will bring new challenges: The typical IT organization will spend up to 30% of its budget on risk, security and compliance by 2017, and will allocate 10% of IT staff to these functions.

Big data analytics will serve as the foundation of digital transformation

Embedded data analytics will provide U.S. enterprises $60+ billion in annual savings by 2020. While some enterprises will continue to drown in big data, others will use it to deliver personalized services, and will use emerging classification and analysis tools to find new insights in the data deluge.

Successful digital transformation will be based on establishing data streams in and out of the enterprise and finding new ways to monetize them. Data analytics will be embedded in all new apps, with a specific focus on automating actions based on real-time data analysis.

The Internet of Things (IoT) will be a catalyst for the expansion of digital transformation to all corners of the economy

Greatly expanding the range of digital interactions between consumers and enterprises and the scope and range of data creation, the Internet of Things (IoT) will serve as the growth engine of digital transformation.

By 2018, there will be 22 billion IoT devices installed, driving the development of over 200,000 new IoT apps and services. Also in 2018, six billion connected things will be requesting support and responding to service requests from things, creating new service businesses. In five years, 1 million new devices will come online every hour. IoT devices and solutions have the potential to redefine competitive advantage in every type of economic activity and fundamentally alter how consumers interact with enterprises and how enterprises interact with their supply chain and distribution partners.

Artificial Intelligence (AI) will drive new digital transformation revenue streams

Over the next few years, we will see a shift in focus for digital transformation initiatives from gathering and mining data to creating new models and algorithms that augment work activities and support consumers when they shop, trade, and make decisions.

By 2018, at least 20% of all workers will use automated assistance technologies to make decisions and more than 3 million workers worldwide will be supervised by a “robo-boss.” By 2020, autonomous software agents outside of human control will participate in 5% of all economic transactions.

Sources

Gartner

Gartner Says the Economics of Connections in Digital Business are Accelerating by the Use of Algorithms

Gartner Reveals Top Predictions for IT Organizations and Users for 2016 and Beyond

Gartner Says It’s Not Just About Big Data; It’s What You Do With It: Welcome to the Algorithmic Economy

Gartner Identifies the Top 10 Strategic Technology Trends for 2016

Forrester

Companies Will Thrive And Fail In The Age Of The Customer In 2016

Predictions 2016: The Trust Imperative For Customer Insights Pros

Predictions 2016: The New Breed Of CIO

IDC

IDC Predicts the Emergence of “the DX Economy” in a Critical Period of Widespread Digital Transformation and Massive Scale Up of 3rd Platform Technologies in Every Industry

IDC Reveals Worldwide Digital Transformation Predictions; Kicks Off IDC FutureScape Web Conference Series

IDC On-Demand Webcasts: IT Industry 2016 Predictions; Digital Transformation 2016 Predictions; CIO Agenda 2016 Predictions

Originally published on Forbes.com

Posted in digital transformation, Misc | Tagged Forrester, Gartner, IDC | Leave a comment

Digital Marketing Trends (Infographic)

Posted on December 25, 2015 by GilPress

Source: DazeInfo

Posted in digital transformation, Misc | Tagged Facebook, Google, twitter, YouTube | Leave a comment

Organizing the world’s information, one reference at a time

Posted on December 21, 2015 by GilPress

Desk Set, 1957

In his book Weaving the Web, Tim Berners-Lee writes:

I was excited about escaping from the straightjacket of hierarchical documentation systems…. By being able to reference everything with equal ease, the web could also represent associations between things that might seem unrelated but for some reason did actually share a relationship. This is something the brain can do easily, spontaneously. … The research community has used links between paper documents for ages: Tables of content, indexes, bibliographies and reference sections… On the Web… scientists could escape from the sequential organization of each paper and bibliography, to pick and choose a path of references that served their own interest.

With this one imaginative leap, Berners-Lee moved beyond a major stumbling block for all previous information retrieval systems: The pre-defined classification system at their core. This insight was so counter-intuitive that even during the early years of the Web, attempts were made to do just that: To classify (and organize in pre-defined taxonomies) all the information on the Web.

Google’s founders were the first to seize on Berners-Lee’s insight and build their information retrieval business on tracking closely cross-references (i.e., links between pages) as they were happening and correlate relevance with quantity of cross-references (i.e., popularity of pages as judged by how many other pages linked to them). This was what set Google apart from its competitors (Yahoo had a Chief Ontologist on staff).

Berners-Lee’s insight is frequently linked to Vannevar Bush who wrote in 1945, “Our ineptitude at getting at the record is largely caused by the artificiality of systems of indexing… Selection [i.e., information retrieval] by association, rather than by indexing may yet be mechanized.” But I prefer to start the history of the Web (and organizing information) with what was, to my knowledge, the earliest use of cross-references.

This was Ephraim Chambers’ Cyclopaedia, published in London in 1728. While lacking the worldwide platform for “crowd-sourcing” references that Berners-Lee invented, Chambers shared with him (and Bush) a dislike for hierarchical, alphabetical, indexing systems. Here’s how Chambers explained in the Preface his innovative system of cross-references:

Former lexicographers have not attempted anything like Structure in their Works; nor seem to have been aware that a dictionary was in some measure capable of the Advantages of a continued Discourse. Accordingly, we see nothing like a Whole in what they have done…. This we endeavoured to attain, by considering the several Matters [i.e., topics] not only absolutely and independently, as to what they are in themselves; but also relatively, or as they respect each other. They are both treated as so many Wholes, and so many Parts of some greater Whole; their Connexion with which is pointed out by a Reference. So that by a Course of References, from Generals to Particulars; from Premises to Conclusions; from a Cause to Effect; and vice versa, i.e., in one word, from more to less complex, and from less to more: A Communication is opened between the several parts of the Work; and the several Articles are in some measure replaced in their natural Order of Science, out of which the Technical or Alphabetical one had remov’d them.

Chambers’ Cyclopaedia was the earliest attempt to link by association all the articles in an Encyclopedia or, in more general terms, of everything we know at a given point in time. And like the World Wide Web, it moved some people to voice their concern about what Google is doing to our brains. The supplement to the 1758 edition of the Cyclopaedia says:

Some few however condemn the use of all such dictionaries, on the first pretence, that, by lessening the difficulties of attaining knowledge, they abate our diligence in the pursuit of it; and by dazzling our eyes with superficial shew, seduce us from digging solid riches in the mine itself.

The fear of what tools for organizing information could do to our thinking (and livelihood) was renewed many-fold with the advent of modern computers. “They can’t build a machine to do our job; there are too many cross-references in this place,” says the head librarian (Katharine Hepburn) to her anxious colleagues in the research department when a “methods engineer” (Spencer Tracy) is hired to “improve workman-hour relationship” in a large corporation. By the end of the film, Desk Set (released in 1957), she proves her point by winning, not only the engineer’s heart, but also a contest with the ominous looking “Electronic Brain” (aka Computer).

Posted in Misc | Tagged Efraim Chambers, Gogole, Tim Berners-Lee, Vannevar Bush | Leave a comment

Andrew Ng, Chief Scientist at Baidu, on Deep Learning (Video)