I Can See for Miles: Using Augmented Reality to Analyze Business Data Sets

matrix-1013612__340, Image from Pixabay

While one of The Who’s first hit singles, I Can See for Miles, was most certainly not about data visualization, it still might – – on a bit of a stretch – – find a fitting a new context in describing one of the latest dazzling new technologies in the opening stanza’s declaration “there’s magic in my eye”.  In determining Who’s who and what’s what about all this, let’s have a look at report on a new tool enabling data scientists to indeed “see for miles and miles” in an exciting new manner.

This innovative approach was recently the subject of a fascinating article by an augmented reality (AR) designer named Benjamin Resnick about his team’s work at IBM on a project called Immersive Insights, entitled Visualizing High Dimensional Data In Augmented Reality, posted on July 3, 2017 on Medium.com. (Also embedded is a very cool video of a demo of this system.) They are applying AR’s rapidly advancing technology1 to display, interpret and leverage insights gained from business data. I highly recommend reading this in its entirety. I will summarize and annotate it here and then pose a few real-world questions of my own.

Immersive Insights into Where the Data-Points Point

As Resnick foresees such a system in several years, a user will start his or her workday by donning their AR glasses and viewing a “sea of gently glowing, colored orbs”, each of which visually displays their business’s big data sets2. The user will be able to “reach out select that data” which, in turn, will generate additional details on a nearby monitor. Thus, the user can efficiently track their data in an “aesthetically pleasing” and practical display.

The project team’s key objective is to provide a means to visualize and sum up the key “relationships in the data”. In the short-term, the team is aiming Immersive Insights towards data scientists who are facile coders, enabling them to visualize, using AR’s capabilities upon time series, geographical and networked data. For their long-term goals, they are planning to expand the range of Immersive Insight’s applicability to the work of business analysts.

For example, Instacart, a same-day food delivery service, maintains an open source data set on food purchases (accessible here). Every consumer represents a data-point wherein they can be expressed as a “list of purchased products” from among 50,000 possible items.

How can this sizable pool of data be better understood and the deeper relationships within it be extracted and understood? Traditionally, data scientists create a “matrix of 2D scatter plots” in their efforts to intuit connections in the information’s attributes. However, for those sets with many attributes, this methodology does not scale well.

Consequently, Resnick’s team has been using their own new approach to:

  • Lower complex data to just three dimensions in order to sum up key relationships
  • Visualize the data by applying their Immersive Insights application, and
  • Iteratively label and color-code the data” in conjunction with an “evolving understanding” of its inner workings

Their results have enable them to “validate hypotheses more quickly” and establish a sense about the relationships within the data sets. As well, their system was built to permit users to employ a number of versatile data analysis programming languages.

The types of data sets being used here are likewise deployed in training machine learning systems3. As a result, the potential exists for these three technologies to become complementary and mutually supportive in identifying and understanding relationships within the data as well as deriving any “black box predictive models”.

Analyzing the Instacart Data Set: Food for Thought

Passing over the more technical details provided on the creation of team’s demo in the video (linked above), and next turning to the results of the visualizations, their findings included:

  • A great deal of the variance in Instacart’s customers’ “purchasing patterns” was between those who bought “premium items” and those who chose less expensive “versions of similar items”. In turn, this difference has “meaningful implications” in the company’s “marketing, promotion and recommendation strategies”.
  • Among all food categories, produce was clearly the leader. Nearly all customers buy it.
  • When the users were categorized by the “most common department” they patronized, they were “not linearly separable”. This is, in terms of purchasing patterns, this “categorization” missed most of the variance in the system’s three main components (described above).

Resnick concludes that the three cornerstone technologies of Immersive Insights – – big data, augmented reality and machine learning – – are individually and in complementary combinations “disruptive” and, as such, will affect the “future of business and society”.

Questions

  • Can this system be used on a real-time basis? Can it be configured to handle changing data sets in volatile business markets where there are significant changes within short time periods that may affect time-sensitive decisions?
  • Would web metrics be a worthwhile application, perhaps as an add-on module to a service such as Google Analytics?
  • Is Immersive Insights limited only to business data or can it be adapted to less commercial or non-profit ventures to gain insights into processes that might affect high-level decision-making?
  • Is this system extensible enough so that it will likely end up finding unintended and productive uses that its designers and engineers never could have anticipated? For example, might it be helpful to juries in cases involving technically or financially complex matters such as intellectual property or antitrust?

 


1.  See the Subway Fold category Virtual and Augmented Reality for other posts on emerging AR and VR applications.

2.  See the Subway Fold category of Big Data and Analytics for other posts covering a range of applications in this field.

3.  See the Subway Fold category of Smart Systems for other posts on developments in artificial intelligence, machine learning and expert systems.

4.  For a highly informative and insightful examination of this phenomenon where data scientists on occasion are not exactly sure about how AI and machine learning systems produce their results, I suggest a click-through and reading of The Dark Secret at the Heart of AI,  by Will Knight, which was published in the May/June 2017 issue of MIT Technology Review.

Applying Origami Folding Techniques to Strands of DNA to Produce Faster and Cheaper Computer Chips

"Origami", Image by David Wicks

“Origami”, Image by David Wicks

We all learned about the periodic table of elements in high school chemistry class. This involved becoming familiar with the names, symbols and atomic weights of all of the chemical occupants of this display. Today, the only thing I still recall from this academic experience was when the teacher told us on the first day of class that we would soon learn to laugh at the following:

Two hydrogen atoms walk into a bar and the first one says to the other “I’ve lost my electron”. The other one answers “Are you sure?”. The first one says “I’m positive.”

I still find this hilarious but whatever I recall today about learning chemistry would likely get lost at the bottom of a thimble. I know, you are probably thinking “Sew what”.

Facing the Elements

Besides everyone’s all-time favorites like oxygen and hydrogen that love to get mixed up with each other and most of the other 116 elements, another one stands alone as the foundation upon which the modern information age was born and continues to thrive today. Silicon has been used to create integrated circuits, much more commonly known as computer chips.

This has been the case since they were first fabricated in the late 1950’s. It has remained the material of choice including nearly all the chips running every imaginable one of our modern computing and communication devices. Through major advances in design, engineering and fabrication during the last five decades, chip manufacturers have been able to vastly shrink this circuitry and pack millions of components into smaller squares of this remarkable material.

A fundamental principle that has held up and guided the semiconductor industry, under relentlessly rigorous testing during silicon’s enduring run, is Moore’s Law. In its simplest terms, it states that the number of transistors that can be written onto a chip doubles nearly every two years. There have been numerous predictions for many years that the end of Moore’s Law is approaching and that another substrate, other than silicon, will be found in order to continue making chips smaller, faster and cheaper. This has not yet come to pass and may not do so for years to come.

Nonetheless, scientists and developers from a diversity of fields, industries and academia have remained in pursuit of alternative computing materials. This includes elements and compounds to improve or replace silicon’s extensible properties, and other efforts to research and fabricate entirely new computing architectures. One involves exploiting the spin states of electrons in a rapidly growing field called quantum computing (this Wikipedia link provides a detailed and accessible survey of its fundamentals and operations), and another involves using, of all things, DNA as a medium.

The field of DNA computing has actually been around in scientific labs and journals for several decades but has not gained much real traction as a viable alternative ready to produce computing chips for the modern marketplace. Recently though, a new advance was reported in a fascinating article posted on Phys.org on March 13, 2016, entitled DNA ‘origami’ Could Help Build Faster, Cheaper Computer Chips, provided by the American Chemical Society (no author is credited). I will summarize and annotate it in order to add some more context, and then pose several of my own molecular questions.

Know When to Fold ‘Em

A team of researchers reported that fabricating such chips is possible when DNA is folded and “formed into specific shapes” using a process much like origami, the Japanese art of folding paper into sculptures. They presented their findings at the 251st American Chemical Society Meeting & Exposition held in San Diego, CA during March 13 through 17, 2016. Their paper entitled 3D DNA Origami Templated Nanoscale Device Fabrication, appears listed as number 305 on Page 202 of the linked document.  Their presentation on March 14, 2016, was captured on this 16-minute YouTube video, with Adam T. Woolley, Ph.D. of Brigham Young University as the presenter for the researchers.

According to Dr. Woolley, researchers want to use DNA’s “small size, base-pairing capabilities and ability to self-assemble” in order to produce “nanoscale electronics”. By comparison, silicon chips currently in production contain features 14 nanometers wide, which turn out to be 10 times “the diameter of single-stranded DNA”. Thus, DNA could be used to build chips on a much smaller and efficient scale.

However, the problem with using DNA as a chip-building material is that it is not a good conductor of electrical current. To circumvent this, Dr. Woolley and his team is using “DNA as a scaffold” and then adding other materials to the assembly to create electronics. He is working on this with his colleagues, Robert C. Davis, Ph.D. and John N. Harb, Ph.D, at Brigham Young University. They are drawing upon their prior work on “DNA origami and DNA nanofabrication”.

Know When to Hold ‘Em

To create this new configuration of origami-ed DNA, they begin with a single long strand of it, which is comparable to a “shoelace” insofar as it is “flexible and floppy”. Then they mix this with shorter stand of DNA called “staples” which, in turn, “use base pairing” to gather and cross-link numerous other “specific segments of the long strand” to build an intended shape.

Dr. Woolley’s team is not satisfied with just replicating “two-dimensional circuits”, but rather, 3D circuitry because it can hold many more electronic components. An undergraduate who works with Dr. Woolley named Kenneth Lee, has already build such a “3-D, tube-shaped DNA origami structure”. He has been further experimenting with adding more components including “nano-sized gold particles”. He is planning to add still more nano-items to his creations with the objective of “forming a semiconductor”.

The entire team’s lead objective is to “place such tubes, and other DNA origami structures, at particular sites on the substrate”. As well, they are seeking us use gold nanoparticles to create circuits. The DNA is thus being used as “girders” to create integrated circuits.

Dr. Woolley also pointed to the advantageous cost differential between the two methods of fabrication. While traditional silicon chip fabrication facilities can cost more than $1 billion, exploiting DNA’s self-assembling capabilities “would likely entail much lower startup funding” and yield potentially “huge cost savings”.

My Questions

  • What is the optimal range and variety in design, processing power and software that can elevate DNA chips to their highest uses? Are there only very specific applications or can they be more broadly used in commercial computing, telecom, science, and other fields?
  • Can any of the advances currently being made and widely followed in the media using the CRISPR gene editing technology somehow be applied here to make more economical, extensible and/or specialized DNA chips?
  • Does DNA computing represent enough of a potential market to attract additional researchers, startups, venture capital and academic training to be considered a sustainable technology growth sector?
  • Because of the potentially lower startup and investment costs, does DNA chip development lend itself to smaller scale crowd-funded support such Kickstarter campaigns? Might this field also benefit if it was treated more as an open source movement?

February 19, 2017 Update:  On February 15, 2017, on the NOVA science show on PBS in the US, there was an absolutely fascinating documentary shown entitled The Origami Revolution. (The link is to the full 53-minute broadcast.) It covered many of the today’s revolutionary applications of origami in science, mathematics, design, architecture and biology. It was both highly informative and visually stunning. I highly recommend clicking through to learn about how some very smart people are doing incredibly imaginative and practical work in modern applications of this ancient art.

Does 3D Printing Pose a Challenge to the Patent System?

"Quadrifolium 3D Print", Image by fdecomite

“Quadrifolium 3D Print”, Image by fdecomite

Whenever Captain Picard ordered up some of his favorite brew, “Earl Grey tea, hot”, from the Enterprise’s replicator, it materialized right there within seconds. What seemed like pure science fiction back when Star Trek: The Next Generation was first on the air (1987 – 1994), we know today to be a very real, innovative and thriving technology called 3D printing. So it seems that Jean-Luc literally and figuratively excelled at reading the tea leaves.

These five Subway Fold posts have recently covered just a small sampling of the multitude of applications this technology has found in both the arts and sciences. (See also #3dprinting for the very latest trends and developments.)

Let us then, well, “Engage!” a related legal issue about 3D printing: Does it violate US federal copyright law in certain circumstances? A fascinating analysis of this appeared in an article on posted January 6, 2016 on ScientificAmerican.com entitled How 3-D Printing Threatens Our Patent System by Timothy Holbrook. I highly recommend reading this in its entirety. I will summarize and annotate it, and then pose some of my own non-3D questions.

Easily Downloadable and Sharable Objects

Today, anyone using a range of relatively inexpensive consumer 3D printers and a Web connection can essentially “download a physical object”. All they need to do is access a computer-aided design (CAD) file online and run it on their computer connected to their 3D printer. The CAD file provides the highly detailed and technical instructions needed for the 3D printer to fabricate the item. As seen in the photo above, this technology has the versatility to produce some very complex and intricate designs, dimensions and textures.

Since the CAD files are digital, just like music and movie files, they can be freely shared online. This makes it likely that just as music and entertainment companies were threatened by file-sharing networks, so too is it possible that 3D printing will result in directly challenging the patent system. However, this current legal framework “is even more ill-equipped” to manage this threat. Consequently, 3D printing technology may well conflict with “a key component of our innovation system”.*

The US federal government (through the US Patent and Trademark office – USPTO), issues patents for inventions they determine are “nontrivial advances in state of the art”. These documents award their holders the exclusive right to commercialize, manufacture, use, sell or import the invention, while preventing other from doing so.

Infringements, Infringers and Economic Values

Nonetheless, if 3D printing enables parties other than the patent holder to “evade the patent”, its value and incentives are diminished. Once someone else employs a 3D printer to produce an object covered by a particular patent, they have infringed on the holder’s legal rights to their invention.

In order for the patent holder to bring a case against a possible infringer, they would need to have knowledge that someone else is actually doing this. Today this would be quite difficult because 3D printers are so readily available to consumers and businesses. Alternatively, the patent laws allow the patent holder to pursue an action against anyone facilitating the means to commit the infringement. This means that manufacturers, vendors and other suppliers of CAD and 3D technologies could be potential defendants.

US copyright laws likewise prohibit the “inducement of infringement”. For example, while Grokster did not actually produce the music on its file-sharing network, it did facilitate the easy exchange of pirated music files. The music industry sued them for this activity and their operations were eventually shut down. (See also this August 31, 2015 Subway Fold post entitled Book Review of “How Music Got Free” about a recent book covering the history and consequences of music file sharing.)

This approach could also possibly be applied to 3D printing but based instead upon the patent laws. However, a significant impediment of this requires “actual knowledge of the relevant patent”. While nearly everyone knows that music is copyrighted, everyone is not nearly as aware that devices are covered by patents. 3D printers alone are covered by numerous patents that infringers are highly unlikely to know about much less abide. Moreover, how could a potentially aggrieved patent holder know about all of the infringers and infringements, especially since files can be so easily distributed online?

The author of this piece, Timothy Holbrook, a law professor at Emory University School of Law, and Professor Lucas Osborn from Campbell University School of Law, believe that the courts should focus on the CAD files to stem this problem. They frame the issue such that if the infringing object can so easily be produced with 3D printing then “should the CAD files themselves be viewed as digital patent infringement, similar to copyright law?” Furthermore, the CAD files have their own value and, when they are sold and used to 3D print an item, then such seller is benefiting from the “economic value of the invention”. The professors also believe there is no infringement if a party merely possesses a CAD file and is not selling it.

Neither Congress nor the courts have indicated whether and how they might deal with these issues.

My Questions

  • Would blockchain technology’s online ledger system provide patent holders with adequate protection against infringement? Because of the economic value of CAD files, perhaps under such an arrangement could they be written to the blockchain and then have Bitcoin transferred to the patent holder every time the file is downloaded.  (See the August 21, 2015 Subway Fold post entitled Two Startups’ Note-Worthy Efforts to Adapt Blockchain Technology for the Music Industry which covered an innovative approach now being explored for copyrights and royalties in the music industry)
  • Would the digital watermarking of CAD files be a sufficient deterrent to protect against file-sharing and potentially infringing 3D printing?
  • What new opportunities might exist for entrepreneurs, developers and consultants to help inventors protect and monitor their patents with regard to 3D printing?
  • Might some inventors be willing to share the CAD files of their inventions on an open source basis online as an alternative that may improve their work while possibly avoiding any costly litigation?

 


These seven Subway Fold posts cover a series of other recent systems, developments and issues in intellectual property.


If this ends up in litigation, the lawyers will add an entirely new meaning to their object-ions.

New IBM Watson and Medtronic App Anticipates Low Blood Glucose Levels for People with Diabetes

"Glucose: Ball-and-Stick Model", Image by Siyavula Education

“Glucose: Ball-and-Stick Model”, Image by Siyavula Education

Can a new app jointly developed by IBM with its Watson AI technology in partnership with the medical device maker Medtronic provide a new form of  support for people with diabetes by safely avoiding low blood glucose (BG) levels (called hypoglycemia), in advance? If so, and assuming regulatory approval, this technology could potentially be a very significant boon to the care of this disease.

Basics of Managing Blood Glucose Levels

The daily management of diabetes involves a diverse mix of factors including, but not limited to, regulating insulin dosages, checking BG readings, measuring carbohydrate intakes at meals, gauging activity and exercise levels, and controlling stress levels. There is no perfect algorithm to do this as everyone with this medical condition is different from one another and their bodies react in individual ways in trying to balance all of this while striving to maintain healthy short and long-term control of BG levels.

Diabetes care today operates in a very data-driven environment. BG levels, expressed numerically, can be checked on hand-held meter and test strips using a single drop of blood or a continuous glucose monitoring system (CGM). The latter consists of a thumb drive-size sensor attached with temporary adhesive to the skin and a needle attached to this unit inserted just below the skin. This system provides patients with frequent real-time readings of their BG levels, and whether they are trending up or down, so they can adjust their medication accordingly. That is, for A grams of carbs and B amounts of physical activity and other contributing factors, C amount of insulin can be calculated and dispensed.

Insulin itself can be administered either manually by injection or by an insulin pump (also with a subcutaneously inserted needle). The later of these consists of two devices: The pump itself, a small enclosed device (about the size of a pager), with an infusion needle placed under the patient’s skin and a Bluetooth-enabled handheld device (that looks just like a smartphone), used to adjust the pump’s dosage and timing of insulin released. Some pump manufacturers are also bringing to market their latest generation of CGMs that integrate their data and command functions with their users’ smartphones.

(The links in the previous two paragraphs are to Wikipedia pages with detailed pages and photos on CGMs and insulin pumps. See also, this June 27, 2015 Subway Fold post entitled Medical Researchers are Developing a “Smart Insulin Patch” for another glucose sensing and insulin dispensing system under development.)

The trickiest part of all of these systems is maintaining levels of BG throughout each day that are within an acceptable range of values. High levels can result in a host of difficult symptoms. Hypoglycemic low levels, can quickly become serious, manifesting as dizziness, confusion and other symptoms, and can ultimately lead to unconsciousness in extreme cases if not treated immediately.

New App for Predicting and Preventing Low Blood Glucose Levels

Taking this challenge to an entirely new level, at last week’s annual Consumer Electronics Show (CES) held in Las Vegas, IBM and Medtronic jointly announced their new app to predict hypoglycemic events in advance. The app is built upon Watson’s significant strengths in artificial intelligence (AI) and machine learning to sift through and intuit patterns in large volumes of data, in this case generated from Medtronic’s user base for their CGMs and insulin pumps. This story was covered in a most interesting article posted in The Washington Post on January 6, 2016 entitled IBM Extends Health Care Bet With Under Armour, Medtronic by Jing Cao and Michelle Fay Cortez. I will summarize and annotate this report and then pose some of my own questions.

The announcement and demo of this new app on January 6, 2016 at CES showed the process by which a patient’s data can be collected from their Medtronic devices and then combined with additional information from their wearable activity trackers and food intake. Next, all of this information is processed through Watson in order to “provide feedback” for the patient to “manage their diabetes”.

Present and Future Plans for The App and This Approach

Making the announcement were Virginia Rometty, Chairman, President and CEO of IBM, and Omar Ishrak, Chairman and CEO of Medtronic. The introduction of this technology is expected in the summer of 2016. It still needs to be submitted to the US government’s regulatory review process.

Ms. Rometty said that the capability to predict low BG events, in some cases up to three hours before they occur, is a “breakthrough”. She described Watson as “cognitive computing”, using algorithms to generate “prescriptive and predictive analysis”. The company is currently making a major strategic move into finding and facilitating applications and partners for Watson in the health care industry. (The eight Subway Fold posts cover other various systems and developments using Watson.)

Hooman Hakami, Executive VP and President, of the Diabetes Group at Medtronic, described how his company is working to “anticipate” how the behavior of each person with Diabetes affects their blood glucose levels. With this information they can then “make choices to improve their health”. Here is the page from the company’s website about their partnership with IBM to work together on treating diabetes.

In the future, both companies are aiming to “give patients real-time information” on how their individual data is influencing their BG levels and “provide coaching” to assist them in making adjustments to keep their readings in a “healthy range”. In one scenario, patients might receive a text message that “they have an 85% chance of developing low blood sugar within an hour”. This will also include a recommendation to watch their readings and eat something to raise their BG back up to a safer level.

My Questions

  • Will this make patients more or less diligent in their daily care? Is there potential for patients to possibly assume less responsibility for their care if they sense that the management of their diabetes is running on a form of remote control? Alternatively, might this result in too much information for patients to manage?
  • What would be the possible results if this app is ever engineered to work in conjunction with the artificial pancreas project being led in by Ed Damiano and his group of developers in Boston?
  • If this app receives regulatory approval and gains wide acceptance among people with diabetes, what does this medical ecosystem look like in the future for patients, doctors, medical insurance providers, regulatory agencies, and medical system entrepreneurs? How might it positively or negatively affect the market for insulin pumps and CGMs?
  • Should IBM and Medtronic consider making their app available on and open-source basis to enable other individuals and groups of developers to improve it as well as develop additional new apps?
  • Whether and how will insurance policies for both patients and manufacturers, deal with any potential liability that may arise if the app causes some unforeseen adverse effects? Will medical insurance even cover, encourage or discourage the use of such an app?
  • Will the data generated by the app ever be used in any unforeseen ways that could affect patients’ privacy? Would patients using the new app have to relinquish all rights and interests to their own BG data?
  • What other medical conditions might benefit from a similar type of real-time data, feedback and recommendation system?

Google is Giving Away Certain Patents to 50 Startups In Their Latest Effort to Thwart Patent Trolls

"She Runs Neon Fraction of a Second", Image by Wonderlane

“She Runs Neon Fraction of a Second”, Image by Wonderlane

In the highly competitive world of creating, monetizing, defending and challenging tech-based intellectual property, “free” is neither a word often heard nor an offer frequently made.

However, Google has just begun a new program, for a limited time, to give away a certain types of patents they own to an initial group of 50 startups.  This is principally being done in an effort to resist time and resources devouring litigation with “patent trolls“, companies that purchase patents for no other purpose than to litigate infringement claims in their attempts to win monetary judgments. (We first visited this issue in an April 21, 2015 Subway Fold post entitled New Analytics Process Uses Patent Data to Predict Advancements in Specific Technologies.)

The details of this initiative were carried in a most interesting new article on TechCrunch.com posted on July 23, 2015 entitled Google Offers To Give Away Patents To Startups In Its Push Against Patent Trolls by Ingrid Lunden. I will summarize, annotate, and pose some free questions of my own.

In April 2015, Google successfully started a temporary program for companies to offer to sell them (Google) their patents. Then on July 23, 2015, they launched a reciprocal program to give away, at no cost, “non-organic” patents (that is, those purchased by Google from third parties), to startups.

The recipients of these giveaways are required to abide by two primary conditions:

  • They must join the LOT Network for two years.  This is a tech industry association of patent owners dedicated to reducing the volume of patent troll-driven litigation.
  • The patents can only be used defensively to “protect a company against another patent suit”. Thus, the patents cannot be used to bring a case “against another company” or else its ownership “reverts back to Google”.

Kurt Brasch, one of Google’s senior patent licensing managers who was interviewed for the TechCrunch story, expects other members of the LOT Network to start their own similar programs.

For any of the 50 startups to be eligible for Google’s program, another key requirement is that their 2014 revenues must fall between $500,000 and $20 million. Next, if eligibility is determined, within 30 days they will receive “a list of three to five families of patents”, from which they can make their selection. Still, Google “will retain a broad, nonexclusive license to all divested assets”, as these patents might still be important to the company.

For those startups that apply and are determined to be ineligible, Google will nonetheless provide them with access “to its own database of patents”. These are presumed to alas be categorized as “non-organic”. The unselected startups will be able to ask Google to consider “the potential purchase of any such assets”.

Back in April, when Google began their acquisitions of patents, they were approached by many operating companies and patent brokers. Both types of entities told Mr. Brasch about a “problem in the secondary market“. These businesses were looking for an alternative means to sell their patents to Google and Mr. Brasch was seeking a means to assist interested buyers and sellers.

Google eventually purchased 28% of the patents they were offered that the company felt could potentially be used in their own operations. As these patents were added to Google’s patent portfolio, a portion of them were categorized as “non-organic” and, as such, the company is now seeking to give them away.

Both sides of Google’s latest patent initiative demonstrate two important strategic points as the company is now:

  • Taking more action in enabling other tech firms to provide assistance against litigation brought by troll-driven lawsuits.
  • Presenting the company as a comprehensive “broker and portal” for patents matters.

Last week, as another part of this process, Google substantially upgraded the features on its Google Patents Search. This included the addition of search results from both Google Scholar and Google Prior Art Finder.  (For the full details and insights on the changes to these services see Google’s New, Simplified Patent Search Now Integrates Prior Art And Google Scholar, also by Ingrid Lunden, posted on TechCrunch.com on July 16, 2015.)

While both the purchasing and selling operations of Google’s effort to test new approaches to the dynamics of the patent marketplace appear to be limited, they might become more permanent later on depending on the  results achieved. Mr. Brasch also anticipates continuing development of this patent market going forward either from his company or a larger “group of organizations”.  Just as Google has moved into other commercial sector including, among others, “shopping, travel and media”, so too does he expect the appearance of more new and comparable marketplaces.

My own questions are as follows:

  • In addition to opposing patent troll litigation, what other policy, public relations, technical and economic benefits does Google get from their new testbed of marketplace services?
  • What other industries would benefit from Google’s new marketplace? What about pharmaceuticals and medical devices, materials science (see these four recent Subway Fold posts in this category),  and/or automotive and aerospace?
  • Should Google limit this project only to startups? Would they consider a more expansive multi-tiered approach to include different ranges of yearly revenue? If so, how might the selection of patents to be offered and other eligibility requirements be decided?
  • Might there be some instances where Google and perhaps other companies would consider giving away non-organic patents to the public domain and allowing further implementation and development of them to operate on an open source basis? (These 10 Subway Fold posts have variously touched upon open source projects and methods.)

Book Review of “More Awesome Than Money”

The rapid rise and ubiquity of Facebook during the last ten years has been a remarkable phenomenon. The figure currently used to express the company’s breadth is that they have more than 1.3 billion user accounts. They have successfully monetized their social platform using a variety of means including, among others, advertizing, networking, communications, and harvesting vast amounts of user data, on their site and elsewhere online, to make the users’ experience more “personal”.

Nonetheless, while most users have become highly dependent on their regular use of Facebook, there are many others who still feel somewhat uncomfortable with its privacy policies and intensive data gathering and analytics.

In 2010, four NYU students heard a presentation by Eben Moglen, a law professor at Columbia University, about the lack of online privacy and overall invasiveness of all of the data relentlessly vacuumed up across the web and used for a multitude of largely invisible purposes. This was the inspiration point for them to join together and try to create a privacy aware and fully decentralized social networked called Diaspora. Most importantly, users would own their individual data and be able to take it with them if they chose to leave. They established it as a non-profit entity that operated on an open source basis for its dedicated global corps of  developers.

The compelling story of the founders and Diaspora has been now been deeply and dramatically told by author Jim Dwyer (the About New York columnist for The New York Times and the author five other books), in his latest book entitled More Awesome Than Money (Viking, October 2014). With their full access and cooperation, he followed these four young men during every phase of Diaspora’s founding, funding and construction and implementation. They were driven by their desire to make a difference to like-minded social network users who wanted true ownership of their own data, rather than many of today’s other typical startups who are looking to strike it rich.

Their noble quest, with its many high and low points, has been very poignantly captured and told here. This not just another geeked out tome about a tech startup that struggles and then hits the jackpot. Rather, this text operates on multiple levels to very skillfully present and weave together, with much pathos and insight, the lives and motivations of the founding four, their rapid relocation and education in the startup culture of Silicon Valley*, and the complexity of achieving their objectives.

Despite their goal to assemble a true technological and philosophical alternative to Facebook and the support they received in their Kickstarter funding campaign, open source coding support, and the goodwill of many potential users seeking something utterly new like Diaspora, there were many obstacles along the way. These included differences that emerged among the core four, overly ambitious release dates and correspondingly high user expectations, funding challenges, and a tragic personal issue of one founder.

Dwyer recounts, with great internal consistency and engaging prose throughout the text, the complex trajectory of Diaspora. Readers will very quickly be drawn into the narrative and the multiple challenges encountered by the young company. As well, for anyone currently involved in a startup or considering taking the leap to launch one, More Awesome Than Money should be considered required reading. Its cover price alone, consider it a form of nominal seed capital if you will, is certain to yield valuable insights into the unique world of the startup.

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*  For another very high quality piece of journalism about a completely different startup in Silicon Valley, see  One Startup’s Struggle to Survive the Silicon Valley Gold Rush, by Gideon Lewis-Kraus in the April 2014 issue of WIRED.