Category Archives: Technology

People Turn Toward “Data Banks” to Commoditize on their Purchase and User Behavior Profiles

Anyone who is anti “Big Brother”, this may not be the article for you, in fact, skip it. ūüôā

 

The Pendulum Swings Away from GDPR

In the not so distant future, “Data Bank” companies consisting of¬†Subject Matter Experts¬†(SME) across all verticals, ¬†may process¬†your data¬†feeds collected from your purchase and user behavior profiles.¬† Consumers will be encouraged to submit their data profiles into a Data Bank who will offer incentives such as a reduction of¬†insurance premiums to cash back rewards.

 

Everything from activity trackers, home¬†automation, to¬†vehicular automation¬†data may be captured and aggregated. ¬† ¬†The data collected can then be sliced and diced to provide macro and¬†micro views of the information. ¬† ¬†On the abstract, macro level the¬†information¬†may allow for demographic, statistical correlations, which may¬†contribute to corporate strategy. On a¬†granular¬†view, the data¬†will provide “data banks” the opportunity to sift through data to perform analysis and correlations that lead to actionable information.

 

Is it secure?  Do you care if a hacker steals your weight loss information? May not be an issue if collected Purchase and Use Behavior Profiles aggregate into a Blockchain general ledger.  Data Curators and Aggregators work with SMEs to correlate the data into:

  • Canned, ‘intelligent’ reports targeted for a specific subject matter, or across silos of¬†data types
  • ‘Universes’ (i.e. ¬†Business Objects) of data that may be ‘mined’ by consumer approved, ‘trusted’ third party companies, e.g. your insurance companies.
  • Actionable information based on AI subject matter rules engines and consumer rule transparency may be provided.

 

¬†“Data Banks” may be required to report to their customers who agreed to sell their data examples of specific rows of the data, which was sold on a “Data Market”.

Consumers may have¬†the option of sharing their personal¬†data with specific companies by proxy, through a ‘data bank’¬†granular to the data point¬†collected.¬† Sharing of Purchase and User Behavior Profiles:

  1. may lower [or raise] your insurance premiums
  2. provide discounts on preventive health care products and services, e.g. vitamins to yoga classes
  3. Targeted, affordable,  medicine that may redirect the choice of the doctor to an alternate.  The MD would be contacted to validate the alternate.

 

The curriated data collected may be harnessed by thousands of affinity groups to offer very discrete products and services.  Purchase and User Behavior Profiles,  correlated information stretches beyond any consumer relationship experienced today.

 

At some point, health insurance companies may require you to wear a tracker to increase or slash premiums.  Auto Insurance companies may offer discounts for access to car smart data to make sure suggested maintenance guidelines for service are met.

 

You may approve your “data bank”¬†to give access¬†to specific soliciting government agencies or private firms looking to analyze data for their studies. You may qualify based on the demographic, abstracted data points collected for incentives provided may be tax credits, or paying studies.

Purchase and User Behavior Profiles:  Adoption and Affordability

If ‘Data Banks’ are allowed to collect Internet of Things (IoT)¬†device profile and the devices themselves are cost prohibitive. ¬†here are a few¬†ways to increase their adoption:

  1.  [US] tax coupons to enable the buyer, at the time of purchase, to save money.  For example, a 100 USD discount applied at the time of purchase of an Activity Tracker, with the stipulation that you may agree,  at some point, to participate in a study.
  2. Government subsidies: the cost of aggregating and archiving Purchase and Behavioral profiles through annual tax deductions.  Today, tax incentives may allow you to purchase an IoT device if the cost is an itemized medical tax deduction, such as an Activity Tracker that monitors your heart rate, if your medical condition requires it.
  3. Auto, Life, Homeowners, and Health policyholders may qualify for additional insurance deductions
  4. Affinity branded IoT devices, such as American Lung Association may sell a logo branded Activity Tracker.  People may sponsor the owner of the tracking pedometer to raise funds for the cause.

The World Bank has a repository of data, World DataBank, which seems to store a large depth of information:

World Bank Open Data: free and open access to data about development in countries around the globe.”

Here is the article that inspired me to write this article:

http://www.marketwatch.com/story/you-might-be-wearing-a-health-tracker-at-work-one-day-2015-03-11

 

Privacy and Data Protection Creates Data Markets

Initiatives such as¬†General Data Protection Regulation (GDPR) and other privacy initiatives which seek to constrict access to your data to you as the “owner”, as a byproduct, create opportunities for you to¬†sell your data.¬†¬†

 

Blockchain: Purchase, and User Behavior Profiles

As your “vault”, “Data Banks” will collect and maintain your two primary datasets:

  1. As a consumer of goods and services, a Purchase Profile is established and evolves over time.¬† Online purchases are automatically collected, curated, appended with metadata, and stored in a data vault [Blockchain].¬† “Offline” purchases at some point, may become a hybrid [on/off] line purchase, with advances in traditional monetary exchanges, and would follow the online transaction model.
  2. User Behavior (UB)¬† profiles, both on and offline will be collected and stored for analytical purposes.¬† A user behavior “session” is a use case of activity where YOU are the prime actor.¬† Each session would create a single UB transaction and are also stored in a “Data Vault”.¬† ¬†UB use cases may not lead to any purchases.

Not all Purchase and User Behavior profiles are created equal.¬† Eg. One person’s profile may show a monthly spend higher than another.¬† The consumer who purchases more may be entitled to more benefits.

These datasets wholly owned by the consumer, are safely stored, propagated, and immutable with a solution such as with a Blockchain general ledger.

Man Trains Dog. Dog Trains AI Model. Cats Rule the World.

Researchers Teach AI to Think like a Dog

Source:¬†Researchers teach AI to think like a dog and find out what they know about the world ‚Äď The Verge

Animals could provide a new source of training data for AI systems.

To train AI to think like a dog, the researchers first needed data. They collected this in the form of videos and motion information captured from a single dog, a Malamute named Kelp. A total of 380 short videos were taken from a GoPro camera mounted to the dog’s head, along with movement data from sensors on its legs and body.

They captured a dog going about its daily life ‚ÄĒ walking, playing fetch, and going to the park.

Researchers analyzed Kelp’s behavior using deep learning, an AI technique that can be used to sift patterns from data, matching the motion data of Kelp’s limbs and the visual data from the GoPro with various doggy activities.

The resulting neural network trained on this information could predict what a dog would do in certain situations. If it saw someone throwing a ball, for example, it would know that the reaction of a dog would be to turn and chase it.

The predictive capacity of their AI system was very accurate, but only in short bursts. In other words, if the video shows a set of stairs, then you can guess the dog is going to climb them. But beyond that, life is simply too varied to predict. 

 

Dogs ‚Äúclearly demonstrate visual intelligence, recognizing food, obstacles, other humans, and animals,‚ÄĚ so does a neural network trained to¬†act¬†like a dog show the same cleverness?

It turns out yes.

Researchers applied two tests to the neural network, asking it to identify different scenes (e.g., indoors, outdoors, on stairs, on a balcony) and ‚Äúwalkable surfaces‚ÄĚ (which are exactly what they sound like: places can walk). In both cases, the¬†neural network was able to complete these tasks with decent accuracy using just the basic data it had of a dog‚Äôs movements and whereabouts.

Dog AI Model Training
Dog AI Model Training

 

Blended Data Warehouse SW/HW Solutions Phased Into the Cloud

Relational Database Solutions “In a Box”

Several of the relational database software vendors, such as IBM, Oracle, and Teradata have developed proprietary data warehouse software to be tightly coupled with server hardware to maximize performance.¬† These solutions have been developed and refined as “on-prem” solutions for many years.

We’ve¬†seen the rise of “Database (DW)¬† as a Service” from companies like Amazon, who sell Redshift services.

Amazon Redshift is a fast, fully managed data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools.  It allows you to run complex analytic queries against petabytes of structured data, using sophisticated query optimization, columnar storage on high-performance local disks, and massively parallel query execution. Most results come back in seconds.

RDB Complex Software/Hardware Maintenance

In recent times, the traditional relational database software vendors shifted gears to become service providers offering maximum performance from a solution hosted by them, the vendor, in the Cloud.¬† ¬† On the positive side, the added complexity of configuring and tuning a blended software/hardware data warehouse has been shifted from the client’s team resources¬†such as Database Administrators (DBAs), Network Administrators,¬† Unix/Windows Server Admins,… to the database software service provider.¬† The complexity of tuning for scalability, and other maintenance challenges shifts to the software vendor’s expertise, if that’s the abstraction you select.¬† There is some ambiguity in the delineation¬†of responsibilities with the RDBMS vendor’s cloud offerings.

Total Cost of Ownership

Quantifying the total cost of ownership of a solution may be a bit tricky, especially if you’re trying to quantify the RDBMS hybrid software/hardware “on-prem” solution¬†versus the same or similar capabilities brought to the client via “Database (DW) as a Service”.

“On-Prem”, RDB Client Hosted Solution

Several factors need to be considered when selecting ANY software and/or Hardware to be hosted at the client site.

  • Infrastructure “when in Rome”
    • Organizations have a quantifiable cost related to hosting physical or virtual servers in the client’s data center and may be boiled down to a number that may include things like HVAC, or new rack space.
    • Resources used to maintain/monitor DC usage, there may be an abstracted/blended figure.
  • Database Administrators maintain and monitor RDB solutions.
    • Activities may range from RDB patches/upgrades to resizing/scaling the DB storage “containers”.
    • Application Database Admins/Developers may be required to maintain the data warehouse architecture, such as new requirements, e.g. creating aggregate tables for BI analysis.
  • Network Administrators
    • Firewalls, VPN
    • Port Scanning
  • Windows/Unix Server Administrators
    • Antivirus
    • OS Patches

Trying to correlate these costs in some type of “Apples to Apples” comparison to the “Data Warehouse as a Service” may require accountants and technical folks to do extensive financial modeling to make the comparison.¬† ¬†Vendors, such as Oracle, offer fully managed services to the opposite end of the spectrum, the “Bare Metal”, essentially the “Infra as a Service.”¬† The Oracle Exadata solution can be a significant investment depending on the investment in redundancy and scalability leveraging Oracle Real Application Clusters (RAC).¬†

Support and Staffing Models for DW Cloud Vendors

In order for the traditional RDB software vendors to accommodate a “Data Warehouse as a Service” model, they may need to significantly increase staff for a variety of technical disciplines, as outlined above with the Client “On-Prem” model.¬† A significant ramp-up of staff and the organizational challenges of developing and implementing a support model based on a variety of factors may have relational database vendors ask: Should they leverage a top tier consulting agency such as¬†Accenture, or¬†Deloitte to define, implement, and refine a managed service?¬† It’s certainly a tall order to go from a software vendor to offering large scale services.¬† With corporate footprints globally and positive track records implementing managed services of all types, it’s an attractive proposition for both the RDB vendor and the consulting agency who wins the bid.¬† Looking at the DW Service billing¬†models don’t seem sensical on some level.¬† Any consulting agency who implements a DW managed service would be responsible to ensure ROI both for the RDS vendor and their clients.¬† It may be opaque to the end client leveraging the Data Warehouse as a Service, but certainly, the quality of service provided should be nothing less than if implemented by the RDB vendor itself.¬† If the end game for the RDB vendor is for the consulting agency to implement, and mature the service then at some point bring the service in-house, it could help to keep costs down while maturing the managed service.

Oracle Exadata

Here are URLs for reference to understand the capabilities that are realized through Oracle’s managed services.

https://cloud.oracle.com/en_US/database

https://cloud.oracle.com/en_US/database/exadata/features

https://www.oracle.com/engineered-systems/exadata/index.html

Teradata

https://www.teradata.com/products-and-services/intellicloud

https://www.teradata.com/products-and-services/cloud-overview

Teradata
Teradata

DB2

https://www.ibm.com/cloud/db2-warehouse-on-cloud

IBM Mainframe
IBM Mainframe

Note: The opinions shared here are my own.

Bose AR, Audio Augmented Reality – Use Cases

I’ve been enamored with Bose products for well over a decade. However,¬† we’ve seen quality¬†brands enter the hi-fidelity¬†audio market over that time.¬† Beyond quality design in their classic audio products, can Bose Augmented Reality (Bose AR) be the market differentiator?

Bose: Using a Bose-AR-equipped wearable, a smartphone, and an app-enabled with Bose AR, the new platform lets you hear what you see.

It sounds like Bose may come up with an initial design, sunglasses, but turn to 3rd party hardware manufacturers of all sorts to integrate Bose AR into other wearable products.

Bose Augmented Reality isn’t just about audio. The devices will use sensors to track head motions for gesture controls and work with GPS from a paired smartphone to track location.  The company also aspires to combine visual information with the Bose AR platform.

Bose AR Use Cases

  • Bose Augmented Reality device reenact historical events or speeches from landmarks and statues as you visit them.
  • The Bose and NFL partnership could be leveraged to get these AR units into the football player’s helmets.¬† Audio queues from the on-field lead, quarterback, and dynamically replayed/relayed at the appropriate time of required action by the receiver.
  • Audio directions to your gate when your GPS detects that you‚Äôve arrived at the airport, or any other destination from your calendar.¬† Audio queues would be richer the more inclusive you are to the access to Calendars, To Do lists, etc.
  • Combine visual information with the Bose AR platform, too, so you could hear a translation of a sign you‚Äôre looking at.
  • Hear the history of a painting in a museum.

Time until it’s in consumer’s hands?¬† TBD.¬† Bose objective is to¬†have the developer kit, including a pair of glasses, available later this year.

When I was on vacation in Athens, Greece, I created a post which had Greek actors running tours in their ancient, native garb.  The Bose AR could be a complementary offering to the tour, which includes live, greek local actors portraying out scenes in ancient ruins.  Record the scenes, and interact with them while walking through the Greek ruins in your Bose AR (Augmented Reality) glasses.

Greece, Prosperity, and Taxes: The World Will Come See You in AR

Please take a moment to prioritize the use cases, or add your own.

Takeaway

I’m a cheerleader for Bose, among several others in this space, but I question a Bose AR headset that produces a high fidelity sound. Most of the¬†use cases listed should be able to “get along OK” with an average quality sound.¬† Maybe high definition AR games with a high level of realism might benefit from the high-quality sound. However, their site reads like Bose is positioning themselves as a component to be integrated into other AR headsets, i.e. “Bose-AR-equipped wearable

Information Architecture: An Afterthought for Content Creation Solutions

Maximizing Digital Asset Reuse

Many applications that enable users to create their own content from word processing to graphics/image creation have typically relied¬†upon 3rd party Content Management Solutions (CMS) / Digital Asset Management (DAM) platforms to collect metadata describing the assets upon ingestion into their platforms.¬† Many of these platforms have been “stood up” to support projects/teams either for collaboration on an existing project, or reuse of assets for “other” projects.¬† As a person constantly creating content, where do you “park” your digital resources for archiving and reuse?¬† Your local drive, cloud storage, or not archived?

Average “Jane” / “Joe” Digital Authors

If I were asked for all the content I’ve created around a particular topic or group of topics from all my¬†collected/ingested digital assets, it may be a herculean¬†search effort spanning multiple platforms.¬† As an independent creator of content, I may have digital assets ranging from Microsoft Word¬†documents, Google Sheets spreadsheets, Twitter tweets,¬† Paint.Net (.pdn) Graphics, Blog Posts, etc.

Capturing Content from Microsoft Office Suite Products

Many of the MS Office content creation products such as Microsoft Word have minimal capacity to capture metadata, and if the ability exists, it’s subdued in the application.¬† MS Word, for example, if a user selects “Save As”, they will be able to add/insert “Authors”, and Tags.¬† In Microsoft Excel, latest version,¬† the author of the Workbook has the ability to add Properties, such as Tags, and Categories.¬† It’s not clear how this data is utilized outside the application, such as the tag data being searchable after uploaded/ingested by OneDrive?

Blog Posts: High Visibility into Categorization and Tagging

A “blogging platform”, such as WordPress, places the Category and Tagging selection fields right justified to the content being posted.¬† In this UI/UX, it forces a specific mentality to the creation, categorization, and tagging of content.¬† This blogging structure constantly reminds the author to identify the content so others may identify and consume the content.¬† Blog post content is created to be consumed by a wide audience of interested viewers based on those tags and categories selected.

Proactive Categorization and Tagging

Perpetuate¬†content classification through drill-down navigation of a derived Information Architecture Taxonomy.¬† As a “light weight” example, in WordPress, the Tags field when editing a Post, a user starts typing in a few characters, an auto-complete dropdown list appears to the user to select one or more of these previously used tags.¬† Excellent starting point for other Content Creation Apps.

Users creating Blog Posts can define a Parent/Child hierarchy of categories, and the author may select one or more of relevant categories to be associated with the Post.

Artificial Intelligence (AI) Derived Tags

It wouldn’t be a post without mentioning AI.¬† Integrated into applications that enable user content creation could be a tool, at a minimum, automatically derives an “Index” of words, or tags.¬† The way in which this “intelligent index” is derived may be based upon:

  • # of times word occurrence
  • mention of words in a particular context
  • reference of the same word(s) or phrases in other content
    • defined by the same author, and/or across the platform.

This intelligently derived index of data should be made available to any platforms that ingest content from OneDrive, SharePoint, Google Docs, etc.  These DAMs ( or Intelligent Cloud Storage) can leverage this information for any searches across the platforms.

Easy to Retrieve the Desired Content, and Repurpose It

Many Content Creation applications heavily rely on “Recent Accessed Files” within the app.¬† If the Information Architecture/Taxonomy hierarchy were presented in the “File Open” section, and a user can drill down on select Categories/Subcategories (and/or tags), it might be easier to find the most desired content.

All Eyes on Content Curation: Creation to Archive
  • Content creation products should all focus on the collection of metadata at the time of their creation.
  • Using the Blog Posting methodology, the creation of content should be alongside the metadata tagging
  • Taxonomy (categories, and tags with hierarchy) searches from within the Content Creation applications, and from the Operating System level, the “Original” Digital Asset Management solution (DAM), e.g. MS Windows, Mac

 

Popular Tweets from January and February 2018

Tweet Activity Analytics

Leveraging Twitter’s Analytics, I’ve extracted the Top Tweets from the last¬†57 day period (Jan 1 until today).¬† ¬†During that period, there were 46.8K impressions earned.

Summary:

  • 61 Link Clicks
  • 27 Retweets
  • 86 Likes
  • 34 Replies
Top Tweets for January and February 2018
Top Tweets for January and February 2018

Microsoft Productivity Suite – Content Creation, Ingestion, Curation, Search, and Repurpose

Auto Curation: AI Rules Engine Processing

There are, of course, 3rd party platforms that perform very well, are feature rich, and agnostic to all file types.  For example, within a very short period of time, low cost, and possibly a few plugins, a WordPress site can be configured and deployed to suit your needs of Digital Asset Managment (DAM).  The long-term goal is to incorporate techniques such as Auto Curation to any/all files, leveraging an ever-growing intelligent taxonomy, a taxonomy built on user-defined labels/tags, as well an AI rules engine with ML techniques.   OneDrive, as a cloud storage platform, may bridge the gap between JUST cloud storage and a DAM.

Ingestion and Curation Workflow

Content Creation Apps and Auto Curation

  • The ability for Content Creation applications, such as Microsoft Word, to capture not only the user-defined tags but also the context of the tags relating to the content.
    • When ingesting a Microsoft PowerPoint presentation, after consuming the file, and Auto Curation process can extract “reusable components” of the file, such as¬†slide¬†header/name, and the correlated content such as a table, chart, or graphics.
    • Ingesting Microsoft Excel and Auto Curation of Workbooks may yield “reusable components” stored as metadata tags, and their correlated content, such as chart and table names.
    • Ingesting and Auto Curation of Microsoft Word documents may build a classic Index for all the most frequently occurring words, and augment the manually user-defined tags in the file.
    • Ingestion of Photos [and Videos] into and Intelligent Cloud Storage Platform, during the Auto Curation process, may identify commonly identifiable objects, such as trees or people.¬† These objects would be automatically tagged through the Auto Curation process after Ingestion.
  • Ability to extract the content file metadata, objects and text tags, to be stored in a standard format to be extracted by DAMs, or Intelligent Cloud Storage Platforms with file and metadata search capabilities.¬† Could OneDrive be that intelligent platform?
  • A user can search for a¬†file title or throughout the Manual and Auto Curated, defined metadata¬†associated with the file.¬† The¬†DAM or Intelligent Cloud Storage Platform provides both search results.¬† ¬†“Reusable components” of files are also searchable.¬†
    • For “Reusable Components” to be parsed out of the files to be separate entities, a process needs to occur after Ingestion Auto Curration.
  • Content Creation application, user-entry tag/text fields should have “drop-down” access to the search index populated with auto/manual created tags.

Auto Curation and Intelligent Cloud Storage

  • The intelligence of Auto Curation should be built into the Cloud Storage Platform, e.g. potentially OneDrive.
  • At a minimum, auto curation should update the cloud storage platform indexing engine to correlate files and metadata.
  • Auto Curation is the ‘secret sauce’ that “digests” the content to build the search engine index, which contains identified objects (e.g. tag and text or¬†coordinates)¬† automatically
    • Auto Curation may leverage a rules engine (AI) and apply user configurable rules such as “keyword density” thresholds
    • Artificial Intelligence, Machine Learning rules may be applied to the content to derive additional¬†labels/tags.
  • If leveraging version control of the intelligent cloud storage platform, each iteration should “re-index” the content, and update the Auto Curation metadata tags.¬† User-created tags are untouched.
  • If no user-defined labels/tags exist, upon ingestion, the user may be prompted for tags

Auto Curation and “3rd Party” Sources

In the context of sources such as a Twitter feed, there exists no incorporation of feeds into an Intelligent Cloud Storage.  OneDrive, Cloud Intelligent Storage may import feeds from 3rd party sources, and each Tweet would be defined as an object which is searchable along with its metadata (e.g. likes; tags).

Operating System, Intelligent Cloud Storage/DAM

The Intelligent Cloud Storage and DAM solutions should have integrated search capabilities, so on the OS (mobile or desktop) level, the discovery of content through the OS search of tagged metadata is possible.

Current State

  1. OneDrive has no ability to search Microsoft Word tags
  2. The UI for all Productivity Tools must have a comprehensive and simple design for leveraging an existing taxonomy for manual tagging, and the ability to add hints for auto curation
    1. Currently, Microsoft Word has two fields to collect metadata about the file.¬† It’s obscurely found at the “Save As” dialog.
      1. The “Save As”¬†dialogue box allows a user to add tags and authors but only when using the MS Word desktop version.¬† The Online (Cloud) version of Word has no such option when saving to Microsoft OneDrive Cloud Storage
  3. Auto Curation (Artificial Intelligence, AI) must inspect the MS Productivity suite tools, and extract tags automatically which does not exist today.
  4. No manual taging or Auto Curation/Facial Recognition exists.

Politics around Privacy: Implementing Facial and Object Recognition

This Article is Not…

about deconstructing existing functionality of entire Photo Archive and Sharing platforms.

It is…

to bring an awareness to the masses about corporate decisions to omit the advanced capabilities of cataloguing photos, object recognition, and advanced metadata tagging.

Backstory: The Asks / Needs

Every day my family takes tons of pictures, and the pictures are bulk loaded up to The Cloud using Cloud Storage Services, such as DropBox, OneDrive,  Google Photos,  or iCloud.  A selected set of photos are uploaded to our favourite Social Networking platform (e.g. Facebook, Instagram, Snapchat,  and/or Twitter).

Every so often, I will take pause, and create either a Photobook or print out pictures from the last several months.  The kids may have a project for school to print out e.g. Family Portrait or just a picture of Mom and the kids.  In order to find these photos, I have to manually go through our collection of photographs from our Cloud Storage Services, or identify the photos from our Social Network libraries.

Social Networking Platform Facebook

As far as I can remember the Social Networking platform¬†Facebook has¬†had the¬†ability to¬†tag¬†faces¬†in¬†photos¬†uploaded to the¬†platform.¬† There are restrictions, such as whom¬†you can¬†tag from the privacy side, but¬†the¬†capability¬†still exists. The¬†Facebook¬†platform¬†also¬†automatically identifies¬†faces within photos, i.e. places a box¬†around¬†faces¬†in¬†a photo to¬†make the¬†person¬†tagging¬†capability¬†easier.¬† So, in essence, there¬†is an¬†“intelligent¬†capability” to¬†identify¬†faces in a photo.¬† It seems¬†like the¬†Facebook¬†platform¬†allows¬†you¬†to see¬†“Photos of¬†You”,¬† but¬†what seems to be¬†missing¬†is¬†to¬†search for¬†all¬†photos¬†of¬†Fred¬†Smith, a friend of yours, even if all his photos are public.¬† ¬† By design, it sounds¬†fit for the¬†purpose of the¬†networking platform.

Auto Curation

  1. Automatically upload new images in bulk or one at a time to a Cloud Storage Service ( with or without Online Printing Capabilities, e.g. Photobooks) and an automated curation process begins.
  2. The Auto Curation process scans photos for:
    1. “Commonly Identifiable Objects”, such as #Car, #Clock,¬† #Fireworks, and¬†#People
    2. Auto Curation of new photos, based on previously tagged objects and faces in newly uploaded photos will be automatically tagged.
    3. Once auto curation runs several times, and people are manually #taged, the auto curation process will “Learn”¬† faces. Any new auto curation process executed should be able to recognize tagged people in new pictures.
  3. Auto Curation process emails / notifies the library owners of the ingestion process results, e.g. Jane Doe and John Smith photographed at Disney World on Date / Time stamp. i.e. Report of executed ingestion, and auto curation process.

Manual Curation

After¬†upload,¬† and auto curation process, optionally, it’s time to manually tag people’s faces, and any ‘objects’ which you would like to track, e.g. Car aficionado, #tag vehicle make/model with additional descriptive tags.¬†¬†Using the photo curator function on the Cloud Storage Service can¬†tag¬†any¬†“objects” in the¬†photo¬†using Rectangle or¬†Lasso¬†Select.

Curation to Take Action

Once photo libraries are curated, the library owner(s) can:

  • Automatically build albums based one or more #tags
  • Smart Albums automatically update, e.g.¬† after ingestion and Auto Curation.¬† Albums are tag sensitive and update with new pics that contain certain people or objects.¬† The user/ librarian may dictate logic for tags.

Where is this Functionality??

Why are may major companies not implementing facial (and object) recognition?  Google and Microsoft seem to have the capability/size of the company to be able to produce the technology.

Is it possible Google and Microsoft are subject to more scrutiny than a Shutterfly?  Do privacy concerns at the moment, leave others to become trailblazers in this area?

Akamai Cuts 5 Percent of Workforce as Q4 tops expectations | ZDNet

The company is cutting workers primarily in its media division as it aims to improve margins.

The media division, Akamai’s unit that speeds up Web pages (including Video streaming), saw fourth quarter revenue fall 3 percent.

Source: Akamai cuts 5 percent of workforce as Q4 tops expectations | ZDNet

Suprised?

Based on the conditions of the markets, i.e. the dissolution of Net Neutrality, companies like Akamai are primed to present attractive solutions to a bandwidth constrained market.¬† Akamai historically has been a market leader in this space, along with Amazon’s CloudFront solution.¬† So, I take pause by these actions, although on the surface Akamai has market dominance in this growth area, are there other potential impeding factors:

  • Akamai’s business operating plan needs to be retooled to compete with ever-increasing competitors into space once dominated.
  • Projected (i.e. inside information) regarding FCC regulations that will put Akamai at a market disadvantage.¬† Lobbyists!

KODAKOne platform and KODAKCoin cryptocurrency | An Innovative Path Forward

The KODAKOne image rights management platform will create an encrypted, digital ledger of rights ownership for photographers to register both new and archive work that they can then license within the platform. KODAKCoin allows participating photographers to take part in a new economy for photography, receive payment for licensing their work immediately upon sale, and sell their work confidently on a secure blockchain [cryptocurrency] platform.

Source: KODAKOne platform and KODAKCoin  | Kodak Graphic Communications Group

I’m really excited about these two technologies coming to fruition.¬† I believe there are several companies already in the digital asset enforcement and management space, such as embedded digital watermarks, so I’m curious how Kodak and¬†WENN Digital will:

  • Crawl the digital landscape we call the Internet and identify potential infringements of licensing for specific digital photos.
  • The ability to “automatically” notify the person(s) or legal business entity who have been flagged for the infringement.
  • Enforcement of licensing or the removal of images.

I’m more skeptical re: Cryptocurrencies, such as Bitcoin.¬† However, with KODAKCoin, it gives me more to reflect upon.

Based on the minimum information currently released:

Government-backed regulation
This community [KODAKCoin] will be supported with a set of unique benefits only available by the issuance of KODAKCoin cryptocurrency via an SEC Regulated Initial Coin Offering (ICO).

Branded cryptocurrency could have some legitimate legs which are “relatable” to a wider audience of people who “don’t get it.”¬† Kodak still has a solid brand, and a business model to integrate the coin.