The Apple Watch, Uber, and Robotic Car Service

apple-watch-uberTech Crunch: “When you open the Uber app on your Apple Watch, it goes straight to a screen showing how long it’ll be until a car can come get you — no pulling out your phone to drop pins or choose between Uber X, Uber Pool, or black car service.”

The efficiencies of ride sharing will get another boost, on the supply side, when Uber and Google will substitute robots for drivers. Here’s the forecast from ABI:

Car and ride sharing is just one example of the new on-demand economy allowing real-time matching of supply and demand through connected smartphone applications. According to ABI Research, successive forms of vehicle sharing approaches represent paradigm shifts in uptake and popularity; each new generation seeing adoption rates at least an order of magnitude larger than the previous:

  • Car Sharing 1.0 – Street Rental Service: Cars parked on the street can be located, unlocked, used, and left behind. Examples: Zipcar, car2go, DriveNow.
  • Car Sharing 2.0 – Ride Sharing Taxi Service and Carpooling: Private drivers picking up customers using their privately owned vehicles. Examples: Uber, Lyft, Sidecar, Carpooling.com, BlaBlaCar.
  • Car Sharing 3.0 – Robotic Car Service: Driverless cars which can be called remotely and used without a driver on board.

ABI-RideSharing-Forecast

Posted in Robotics | Leave a comment

The Hadoop Bubble Quivers As Hortonworks Misses

Hadoop BubbleLast month, Hortonworks announced quarterly results for the first time as a public company and they came below expectations. It had revenues of $12.7 million (up 55% year-over-year), but average Wall Street estimates were $13.42 million. Similarly, Wall Street expected a loss of $2.04 per share and Hortonworks reported a loss of $2.19 per share.

The results could be attributed to a company new to the game of providing guidance to Wall Street. But the company’s management had substantial experience in that department throughout their impressive careers so we must look somewhere else for an explanation. What if November 10, 2014, the day Hortonworks filed the paperwork for its IPO was the beginning of the end of the Hadoop bubble, to quote your humble correspondent? What if December 12, 2014, the day Hortonworks went public, surprising many by its swift action, the bubble “began to quiver and shake preparatory to its bursting”? What if Hortonworks had decided to rush to the exit while expectations were high?

People who had over-inflated expectations—and may have grumbled yesterday “what were we thinking”—should have listened to Mike Stonebraker last August. Here’s what this foremost authority on databases (and serial entrepreneur) said about the new generation of Hadoop from Hortonworks competitor Cloudera:

Impala is architected exactly like all of the shared-nothing parallel SQL DBMSs, serving the data warehouse market. Specifically, notice clearly that the MapReduce layer has been removed, and for good reason. As some of us have been pointing out for years, MapReduce is not a useful internal interface inside a SQL (or Hive) DBMS. Impala was architected by savvy DBMS developers, who know the above pragma. In fact, development activity similar to Impala is being done by both HortonWorks and FaceBook. This, of course, presents the Hadoop vendors with a dilemma. Historically, “Hadoop” referred to the open source version of MapReduce written by Yahoo. However, Impala has thrown this layer out of the stack. How can one be a Hadoop vendor, when Hadoop is no longer in the mainstream stack? The answer is simple: redefine “Hadoop”, and that is exactly what the Hadoop vendors have done. The word “Hadoop” is now used to mean the entire stack.

In my post, I suggested “a few things to ponder when considering the potential success of the current leading Hadoop vendors and whether Hadoop in general is in the first stage of a rapid market expansion or the last stage of a bubble inflating.” One of them was the incorporation of Hadoop and similar tools by established software vendors into their traditional database and information management offerings.  Stonebraker is highlighting the opposite, the recasting of Hadoop into what looks like a traditional database technology. He says: “Meanwhile most of the data warehouse vendors support HDFS, and many offer features to support semi-structured data. Hence, the data warehouse market and the Hadoop market will quickly converge.”

Another argument I made was “Hadoop is so 2004 (at least at Google).” Here’s Stonebraker on the subject:

Google must be “laughing in their beer” about now. They invented MapReduce to support the web crawl for their search engine in 2004. A few years ago they replaced MapReduce in this application with BigTable, because they wanted an interactive storage system and MapReduce was batch-only. Hence, the driving application behind MapReduce moved to a better platform a while ago. Now Google is reporting that they see little-to-no future need for MapReduce. It is indeed ironic that Hadoop is picking up support in the general community about five years after Google moved on to better things. Hence, the rest of the world followed Google into Hadoop with a delay of most of a decade. Google has long since abandoned it. I wonder how long it will take the rest of the world to follow Google’s direction and do likewise…

No matter. Here’s what Matthew Hedberg, an analyst for RBC Capital Markets, wrote (according to Investor’s Business Daily) just before the Hortonworks quarterly earnings announcement:  “We remain bullish on Hortonworks’ opportunity as a pure play on Hadoop and believe it to be one of the better-positioned disruptive vendors in what could be a once-in-a-decade data replatforming opportunity.” An analyst with Cowen and Co, Jesse Hulsing, expressed a similar bullish sentiment: “The Hadoop market is in early stages of adoption. Our view is that most large enterprises (5,000-plus employees) will have adopted or piloted the technology by fiscal year 2020. The underlying driver of this adoption is the growth in analytic applications, which is driven by rapid growth in new data types and new user types. Hortonworks should benefit from this.”

Maybe the market is indeed going gangbusters and Hortonworks is simply losing to better-equipped competitors, primarily Cloudera?

Apparently anticipating this question, Cloudera issued last week a “momentum press release,” announcing that its 2014 revenues “surpassed $100 million,” calling the results “an indicator of Hadoop’s strong momentum.” Derrick Harris at GigaOm had this to say about the news: “That the company, which is still privately held, would choose to disclose even that much information about its finances speaks to the fast maturation, growing competition and big egos in the Hadoop space.”  Similarly, Arik Hesseldahl at Re/Code noted that a “likely motivation for the press release is a battle of optics between Cloudera and its primary rival, Hortonworks… Cloudera may simply be seeking to remind the marketplace which Hadoop company is bigger.”

It is also reminding the marketplace that it’s not going to be subject to the scrutiny accorded public companies anytime soon. Cloudera co-founder and chief strategy officer Mike Olson told Re/Code: “We have no timeline for an IPO, period.” CEO Reilly told Fortune “We’re of the size and scale that we could be a successful public company right now. But we’re so well backed that we don’t need to go public to have access to financing.” Indeed, after riding a bubble and raising a cool $1 billion, who needs Wall Street?

But they need Main Street. Regardless of the close to $1.5 billion in venture capital the key Hadoop competitors left standing—Cloudera, Hortonworks and MapR—have raised, to survive and succeed they need enterprise customers to buy the current (and future) Hadoop incarnations they offer.

In my previous post on the Hadoop Bubble, I quoted a 2014 survey conducted by Wikibon which found that only 36% of the respondents were using Hadoop and the majority of those (64%) were using it in proof-of-concept environments.  Even more important to the financial future of Hadoop vendors, Wikibon found that “only 25% of Hadoop practitioners are paying customers of one or another Hadoop vendor. 24% use a free distribution provided by a vendor, but the majority, 51%, roll their own Hadoop downloaded from the Apache Software Foundation.” Don’t you think this has something to do with Hortonworks’ quarterly results?

The author of the excellent Wikibon report, Jeff Kelly, gave a presentation last week, titled The Big Data Money Trail. About 23 minutes into the presentation, Kelly gets to a slide titled (surprise!) “Is this the beginning of the end of the bubble, or is there something next that matters?”

Kelly definitely thinks (or at least thought last week) that Hadoop still matters. He thinks Cloudera and Hortonworks will survive and doesn’t back down from his previous estimates of how big the big data market will get. He predicts three future developments, all helping accelerate big data adoption, but not necessarily (in my opinion) promising for Hadoop vendors: enterprises will overcome their process and culture obstacles for adopting big data technologies; innovation will continue to drive the market because it is based on open source software; and while Hadoop was the “low-hanging fruit,” offering cost saving opportunities, now enterprises will start building “data-driven applications.”

To illustrate the last point, specifically the value that can be created by all these new applications of big data, Kelly reproduced on the slide the results of previous work done by Wikibon which estimated the “spend and value delivered by industrial internet” to reach $1.2 trillion in 2020. Bert Latamore, his colleague at Silicon Angle, wrote in his summary of Kelly’s talk that “Vendors will do well in the Big Data market over the next decade, Kelly predicts, but the real winners will be the companies that harness the technology creatively. He estimates that practitioners will create $1.2 trillion in new value from Big Data over the coming decade.” (Italics mine)

So a 2013 report on the Industrial Internet has metamorphosed into current (and misattributed) estimates of how many dollars are swimming in the big data lake. This is how bubbles rise, and eventually, burst.

Or maybe not, maybe I’m wrong and what we have is the beginning of a solid market for products from disruptive vendors going after “once-in-a-decade data replatforming opportunity.”  After all, Hortonworks provided above-consensus guidance for the current quarter and they are much closer than I to what is really happening in the marketplace.

In an interview with Derrick Harris conducted last week, Hortonworks CEO Rob Bearden said that he is not backing off his 2014 prediction that Hadoop will soon become a multi-billion-dollar market and Hortonworks will be a billion-dollar company in terms of revenue. Hadoop is actually just a part — albeit a big one — of a major evolution in the data-infrastructure space, he explained to Harris. As companies start replacing the pieces of their data environments, they’ll do so with the open source options that now dominate new technologies. These include Hadoop, NoSQL databases, Storm, Kafka, Spark and the like. “Open source companies can be very successful in terms of revenue growth and in terms of profitability faster than the old proprietary platforms got there,” Bearden said.

 Originally posted on Forbes.com

 

Posted in Big Data | Leave a comment

Big Data and Healthcare (Infographic)

Health_BigData_Infographic

From Steve Lohr’s @SteveLohr profile of Jeff Hammerbacher  in the New York Times

On the Case at Mount Sinai, It’s Dr. Data

Jeffrey Hammerbacher is a number cruncher — a Harvard math major who went from a job as a Wall Street quant to a key role at Facebook to a founder of a successful data start-up.

But five years ago, he was given a diagnosis of bipolar disorder, a crisis that fueled in him a fierce curiosity in medicine — about how the body and brain work and why they sometimes fail. The more he read and talked to experts, the more he became convinced that medicine needed people like him: skilled practitioners of data science who could guide scientific discovery and decision-making.

Now Mr. Hammerbacher, 32, is on the faculty of the Icahn School of Medicine at Mount Sinai, despite the fact that he has no academic training in medicine or biology. He is there because the school has begun an ambitious, well-funded initiative to apply data science to medicine.  …

Jeffrey Hammerbacher now leads a team that uses quantitative skills to improve medical treatments. His move from the start-up world was inspired by his own health crisis.

“We’re pursuing problems that are computationally and intellectually exciting, and where there is the potential to change how doctors treat patients in two or three years,” Mr. Hammerbacher said.

Eric Schadt, the computational biologist who recruited Mr. Hammerbacher to Mount Sinai, says the goal is to transform medicine into an information science, where data and computing are marshaled to deliver breakthroughs in the treatment of cancer, Alzheimer’s, diabetes and other chronic diseases. Mount Sinai is only one of several major medical schools turning to data science as a big part of the future of medicine and health care.

They are reaching out to people like Mr. Hammerbacher, whose career arc traces the evolution of data science as it has spread across the economy. After a job designing trading models at Bear Stearns, he worked for a few important years at Facebook, where he started the social network’s data team and made his reputation and a tidy sum. Next, he was one of four founders of Cloudera, a fast-growing company that makes software tools for data science. And now he is immersed in medicine.  …

Dr. Schadt had concluded that medicine was ripe for a data-driven revolution. Chronic diseases, Dr. Schadt explained, are not caused by single genes, but are “complex networked disorders” involving genetics, but also patient characteristics such as weight, age, gender, vital signs, tobacco use, toxic exposure and exercise routines — all of which can be captured as data and modeled.

“We are trying to move medicine in the direction of climatology and physics; disciplines that are far more advanced and mature quantitatively,” he said.

That message resonated with Mr. Hammerbacher. By 2013 he was spending most of his time in New York rather than on the West Coast, assembling a research team that now numbers 10 people. Their expertise spans the breadth of data science: machine learning, data visualization, statistics and programming.

His group’s objective is to alter how doctors treat patients someday. For example, Mount Sinai medical researchers have done promising work on personalized cancer treatments. It involves the genetic sequencing of a patient’s healthy cells and cancer tumor. Once the misbehaving gene cluster is identified and analyzed, it is targeted with tailored therapies, drugs or vaccines that stimulate the body’s defenses.

Mr. Hammerbacher’s team does not do the basic science. Other researchers do that. His group works on the “computational pipeline,” he said, with the goal of making personalized cancer treatments more automated and thus more affordable and practical. “It’s ultimately what cancer cures are going to look like,” he said.

The road to technology revolutions is paved with failure, halting progress and hard work. Mr. Hammerbacher and his colleagues are engaged in pathbreaking yet often frustrating data science work.

He is optimistic about his initiative’s prospects, but has come to appreciate that the mysteries of the human body may be more resistant to math than finance or social networks are. Today he speaks less about quants taking over than about their lending a hand. “We’re not the most important people,” he said, “but we can help.”

Posted in Misc | Leave a comment

The Age of Context Quantified

AmbientIntelligence

 

Ambient intelligence is a relatively new term in the technology lexicon, yet ABI Research forecasts that it will become the major evolution in technology-based consumer services and quality of life applications over the next 10 years. Essentially, ambient intelligence is the ability of a system to appreciate its environment, be aware of the user (and other people / objects) within that environment and most importantly, interpret and respond to their needs, unprompted.

Senior Analyst Patrick Connolly comments, “In technology terms ambient intelligence is the unification of hot new areas such as neural networks, big data, IoT, connected home, wearables, device user interfaces, and health / fitness, into services that can automate processes and make recommendations to improve the users quality of life. A major aspect in enabling this is the arrival of new location technologies such as BLE beacons, LED / VLC, sensor / data fusion, LTE-direct, Wi-Fi 2.0, etc.”

“The applications of ambient intelligence are multitude, but on the consumer side, the big drive is the battle for next generation search and evolved personal assistant applications that can predict the needs of their users and make changes / recommendations to facilitate these needs. From an application point of view, ABI Research forecasts over 8 billion ambient intelligence related application downloads in 2020, primarily focused on personal assistant, social, health / fitness, augmented reality, and local search / discovery applications.”

These findings are part of ABI Research’s Location Based Services Market Research.

Ambient Intelligence or what Robert Scoble and Shel Israel call The Age of Context:

[slideshare id=39285195&doc=samsungscoble-140919063950-phpapp01]

 

 

 

Posted in Misc | Leave a comment

Growing the digital business (infographic)

14-6325 - Mobility Research Infographic_v10

 

Source: Accenture Mobility Research 2015

Posted in Digitization | Leave a comment

Net Neutrality Means Different Things to Different People (Infographic)

net-neutrality-definedSource: Defining Net Neutrality Without the Politics and Net Neutrality’s Technical Troubles

 

Posted in Misc | Leave a comment

3 Database Admins Walked into a NoSQL Bar…

NoSQL bar Joke

Posted in Misc | Leave a comment

15 Most-Funded Crowdfunding Projects On Kickstarter And Indiegogo

Coolest 3-4 Prototype 11_15_142014 was a great year for crowdfunding. Kickstarter had 22,252 projects raising a total of $529 million, up from $480 million raised in 2013. Indiegogo had 1,000% increase in funds raised over the past two years and both Indiegogo and Kickstarter had their most-funded projects ever in 2014.

This year is already shaping up as the greatest ever for the young industry, with three 2015 projects already making it to the list of 15 most-funded crowdfunding projects on Kicstarter and Indeigogo:

1.            $13,285,226  from 62,642 funders August 2014 (Kickstarter)

Coolest Cooler: 21st Century cooler that’s actually cooler, complete with built-in ice crushing blender, a waterproof bluetooth speaker and a USB charger.

2.            $10,266,845 from 68,929 funders May 2012 (Kickstarter)

Pebble: E-paper watch for iPhone and Android, customizable watch with downloadable watchfaces, sports and fitness apps, notifications from mobile phone.

3.            $8,782,571 from 219,382 funders February 2015 (Kickstarter)

Exploding Kittens: A card game for people who are into kittens and explosions and laser beams and sometimes goats.

4.            $8,596,474 from 63,416 funders August 2012 (Kickstarter)

OUYA: A new kind of video game console, cracking open the last closed platform, the TV; a beautiful, affordable console, built on Android.

5.            $6,225,354 from 18,220 funders April 2014 (Kickstarter)

Pono Music: Where your soul rediscovers music, providing the best possible listening experience of your favorite digital music. With the PonoPlayer, you can finally feel the master in all its glory, in its native resolution, CD quality or higher, the way the artist made it, exactly.

6.            $5,702,153 from 91,585 funders April 2013 (Kickstarter)

The Veronica Mars Movie Project, a feature film version of the defunct television series.

7.            $5,408,916 from 105,857 funders July 2014 (Kickstarter)

Bring Reading Rainbow Back for Every Child, Everywhere! Bring Reading Rainbow’s library of interactive books & video field trips to more platforms & provide free access to classrooms in need.

8.            $5,022,041 (including $2.5 million matched contributions) from 2,801 funders December 2014 (indiegogo)

Code.org, introducing coding to 100 million students.

9.            $4,188,927 from 74,405 funders April 2013 (Kickstarter)

Torment: Tides of Numenera, a story-driven Computer Role-Playing Game (CRPG) set in the world of Monte Cook’s Numenera.

10.          $3,986,929 from 73,986 funders October 2012 (Kickstarter)

Project Eternity, an isometric, party-based computer RPG set in a new fantasy world.

11.          $3,845,170 from 67,226 funders October 2013 (Kickstarter)

Mighty No. 9, a video game

12.          $3,602,037 from 12,075 funders January 2015 (Kickstarter)

ZANO, the world’s most sophisticated nano drone.

Sondors_Bike13.          $3,576,151+ from 6,548 funders ends March 3, 2015 (Indiegogo)

Sondors Electric Bike, the world’s most affordable, versatile electric bike.

14.          $3,429,235 from 17,744 funders August 2012 (Kickstarter)

Reaper Miniatures Bone: Gaming miniatures.

15.          $3,401,361 from 11,855 funders May 2014 (Kickstarter)

The Micro: The first truly consumer 3D printer.

[Originally published on Forbes.com]

Posted in Misc | Tagged | Leave a comment

History of Data Science (Infographic)

DataScience_History

 

Source: Capgemini

Posted in Data Science | Leave a comment

4 billion people buying phones every 2 years instead of 1.6 billion buying PCs every 5 years

MobilePCs

Source: Benedict Evans

Posted in Misc | Leave a comment