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!
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.
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.
Coupling Content Distribution (i.e. ISPs) with Content Producers
Verizon FiOS offers Netflix as another channel in their already expansive lineup of content. Is this a deal of convenience for the consumer, keeping consumers going through one medium, or is it something more? Amazon Video iOS application offers HBO, STARZ, and others as long as Amazon Prime customers have a subscription to the Content Producers. Convenience or more? The Netflix Content and Distribution via Set-top box (STB) channel should be mimicked by Google YouTube and Amazon Video despite their competing hardware offerings. Consumers should be empowered to decide how they want to consume Amazon Video; e.g. through their Set-top box (STB). However, there may be more than just a convenience benefit.
As Net Neutrality fades into the sunset of congressional debates and lobbyists, the new FCC ruling indicates the prevailing winds of change. We question how content providers, large and small, navigate the path to survival/sustainability. Some business models from content distribution invoke Bandwidth Throttling, which may inhibit the consumers of some content, either by content types (e.g. Video formats) or content providers (e.g. Verizon FiOS providing priority bandwidth to Netflix).
Content Creators / Producers, without a deal with ISPs for “priority bandwidth” may find their customers flock to ‘larger content creators’ who may be able to get better deals for content throughput.
Akamai and Amazon CloudFront – Content Delivery Networks (CDNs)
Amazon CloudFront a global content delivery network (CDN) service that securely delivers data, videos, applications, and APIs to viewers with low latency and high transfer speeds. CloudFront, like Akamai, may significantly benefit from the decision by the FCC to repeal Net Neutrality.
Akamai’s industry-leading scale and resiliency mean delivering critical content with consistency, quality, and security across every device, every time. Great web and mobile experiences are key to engaging users, yet difficult to achieve. To drive engagement and online revenue, it’s critical to optimize performance for consumer audiences and employees alike to meet or exceed their expectations for consistent, fast, secure experiences.
Integrating into Content/Internet Service Provider’s Bundle of Channels
By elevating Content Producers into the ISP (distribution channel) Set-top box (STB), does this ‘packaging’ go beyond bundling of content for convenience? For example, when Netflix uses Verizon FiOS’ CDN for content delivery to their clients, will the consumer benefit from this bundled partnership beyond convenience (i.e. performance)? When Netflix is invoked by a Verizon FiOS customer from their laptop (direct from Netflix), is there a performance improvement if Netflix is invoked from the Verizon FiOS Set-top Box (STB) instead? Would these two separate use cases for invoking Netflix movies utilize two alternate Content delivery network (CDN) paths, one more optimized than the other?
As of this post update (12/26), there has been no comment from Verizon.
Advice is integrated within the application, proactive and reactive: When searching in Microsoft Edge, a blinking circle representing Cortana is illuminated. Cortana says “I’ve collected similar articles on this topic.” If selected, presents 10 similar results in a right panel to help you find what you need.
Personal Data Access and Management
The user can vocally access their personal data, and make modifications to that data; E.g. Add entries to their Calendar, and retrieve the current day’s agenda.
Platform Capabilities: Mobile Phone Advantage
Strengthen core telephonic capabilities where competition, Amazon and Microsoft, are relatively week.
Ability to record conversations, and push/store content in Cloud, e.g. iCloud. Cloud Serverless recording mechanism dynamically tags a conversations with “Keywords” creating an Index to the conversation. Users may search recording, and playback audio clips +/- 10 seconds before and after tagged occurrence.
Calls into the User’s Smartphones May Interact Directly with the Digital Assistant
Call Screening – The digital assistant asks for the name of the caller, purpose of the call, and if the matter is “Urgent”
A generic “purpose” response, or a list of caller purpose items can be supplied to the caller, e.g. 1) Schedule an Appointment
The smartphone’s user would receive the caller’s name, and the purpose as a message back to the UI from the call, currently in a ‘hold’ state,
The smartphone user may decide to accept the call, or reject the call and send the caller to voice mail.
A caller may ask to schedule a meeting with the user, and the digital assistant may access the user’s calendar to determine availability. The digital assistant may schedule a ‘tentative’ appointment within the user’s calendar.
If calendar indicates availability, a ‘tentative’ meeting will be entered. The smartphone user would have a list of tasks from the assistant, and one of the tasks is to ‘affirm’ availability of the meetings scheduled.
If a caller would like to know the address of the smartphone user’s office, the Digital Assistant may access a database of “generally available” information, and provide it. The Smartphone user may use applications like Google Keep, and any note tagged with a label “Open Access” may be accessible to any caller.
Custom business workflows may be triggered through the smartphone, such as “Pay by Phone”. When a caller is calling a business user’s smartphone, the call goes to “voice mail” or “digital assistant” based on smartphone user’s configuration. If the user reaches the “Digital Assistant”, there may be a list of options the user may perform, such as “Request for Service” appointment. The caller would navigate through a voice recognition, one of many defined by the smartphone users’ workflows.
Platform Capabilities: Mobile Multimedia
Either through your mobile Smartphone, or through a portable speaker with voice recognition (VR).
Streaming media / music to portable device based on interactions with Digital Assistant.
Menu to navigate relevant (to you) news, and Digital Assistant to read articles through your portable media device (without UI)
Third Party Partnerships: Adding User Base, and Expanding Capabilities
In the form of platform apps (abstraction), or 3rd party APIs which integrate into the Digital Assistant, allowing users to directly execute application commands, e.g. Play Spotify song, My Way by Frank Sinatra.
Any “Skill Set” with specialized knowledge: direct Q&A or instructional guidance – e.g Home Improvement, Cooking
eCommerce Personalized Experience – Amazon
Home Automation – doors, thermostats
Music – Spotify
Navigate Set Top Box (STB) – e.g. find a program to watch
Video on Demand (VOD) – e.g. set to record entertainment
Excellent presentations from the Hortonworks team for “NiFi on HDF” solutions architecture and best practices. Powerful solution to process and distribute data in real-time, any data, and in large quantities with resiliency. It’s no wonder why the US NSA originally developed the ability to consume data in real-time, manipulate it, and then send it on it’s way. However, recognizing the commercial applications (benevolent wisdom?), the NSA released the product as open-source software, via its technology transfer program.
As a tangent, among other things, I’m currently exploring the capabilities of “Microsoft Flow“, which has recently been promoted to GA from their ‘Preview Release’. One resonating question came to mind during the presentations last night:
At it’s peak maturity (not yet), can Microsoft Flow successfully compete with Apache NiFi on Hortonworks HDF?
The NiFi / HDF solution manages data flows in real-time. The Microsoft Flow architecture seems to fall short in this capacity. Is it on the product road map for Flow? Is it a capability Microsoft wants to have?
There a bit of architecture / infrastructure on the Hortonworks HDF side, which enables the solution as a whole to be able to ingest, process, and push the data in real-time. Not sure Microsoft Flow is currently engineered on the back end to handle the throughput.
The current Microsoft Flow UI may need to be updated to handle this ‘slightly altered’ paradigm of real-time content consumption and distribution.
The comparison between Microsoft Flow and NiFi on HDF may be a huge stretch for comparison.
Serverless computing is a cloud computing code execution model in which the cloud provider fully manages starting and stopping virtual machines as necessary to serve requests, and requests are billed by an abstract measure of the resources required to satisfy the request, rather than per virtual machine, per hour. Despite the name, it does not actually involve running code without servers. Serverless computing is so named because the business or person that owns the system does not have to purchase, rent or provision servers or virtual machines for the back-end code to run .
Based on your application Use Case(s), Cloud Serverless Computing architecture may reduce ongoing costs for application usage, and provide scalability on demand without the Cloud Server Instance management overhead, i.e. costs and effort.
Note: Cloud Serverless Computing is used interchangeability with Functions as a service (FaaS) which makes sense from a developer’s standpoint as they are coding Functions (or Methods), and that’s the level of abstraction.
Create automated workflows between apps and services to get notifications, synchronize files, collect data, and more. Although not the traditional Serverless Computing implementation, it’s the quickest way to perform application services without having to procure the application servers. Depending on your microservices (connectors + templates) definitions, you may not need to write a single line of code, and could all be done through the Flow console.
Connectors are “enablers” to connect to [data] sources in order to extract or insert data, typically one Connector per service, such as Twitter.
Templates utilize Connectors, and enable workflow designers to build business process workflows. Execution of the manufactured workflows performs the activities either Event trigger driven, or ADHOC / manual execution through the portal or through the Microsoft Flow mobile apps.
154 Service Connectors Exist. Several “Premium” connectors require monthly nominal fee (5 USD). For example, using the Oracle Database Connecter empowers the workflow designer insert, update, select, and delete rows in a table.
Automating business processes by designing workflows to turn repetitive tasks into multi-step workflows
Microsoft Flow Pricing
As listed below, there are three tiers, which includes a free tier for personal use or exploring the platform for your business. The pay Flow plans seem ridiculously inexpensive based on what business workflow designers receive for the 5 USD or 15 USD per month. Microsoft Flow has abstracted building workflows so almost anyone can build application workflows or automate business manual workflows leveraging almost any of the popular applications on the market.
It doesn’t seem like 3rd party [data] Connectors and Template creators receive any direct monetary value from the Microsoft Flow platform. Although workflow designers and business owners may be swayed to purchase 3rd party product licenses for the use of their core technology.
Properly designed microservices have a single responsibility and can independently scale. With traditional applications being broken up into 100s of microservices, traditional platform technologies can lead to significant increase in management and infrastructure costs. Google Cloud Platform’s serverless products mitigates these challenges and help you create cost-effective microservices.
AWS provides a set of fully managed services that you can use to build and run serverless applications. You use these services to build serverless applications that don’t require provisioning, maintaining, and administering servers for backend components such as compute, databases, storage, stream processing, message queueing, and more. You also no longer need to worry about ensuring application fault tolerance and availability. Instead, AWS handles all of these capabilities for you, allowing you to focus on product innovation and get faster time-to-market. It’s important to note that Amazon was the first contender in this space with a 2014 product launch.
Execute code on demand in a highly scalable serverless environment. Create and run event-driven apps that scale on demand.
Focus on essential event-driven logic, not on maintaining servers
Integrate with a catalog of services
Pay for actual usage rather than projected peaks
The OpenWhisk serverless architecture accelerates development as a set of small, distinct, and independent actions. By abstracting away infrastructure, OpenWhisk frees members of small teams to rapidly work on different pieces of code simultaneously, keeping the overall focus on creating user experiences customers want.
Serverless Computing is a decision that needs to be made based on the usage profile of your application. For the right use case, serverless computing is an excellent choice that is ready for prime time and can provide significant cost savings.
Protecting the Data Warehouse with Artificial Intelligence
Teleran is a middleware company who’s software monitors and governs OLAP activity between the Data Warehouse and Business Intelligence tools, like Business Objects and Cognos. Teleran’s suite of tools encompass a comprehensive analytical and monitoring solution called iSight. In addition, Teleran has a product that leverages artificial intelligence and machine learning to impose real-time query and data access controls. Architecture also allows for Teleran’s agent not to be on the same host as the database, for additional security and prevention of utilizing resources from the database host.
Key Features of iGuard:
Policy engine prevents “bad” queries before reaching database
Patented rule engine resides in-memory to evaluate queries at database protocol layer on TCP/IP network
Patented rule engine prevents inappropriate or long-running queries from reaching the data
70 Customizable Policy Templates
SQL Query Policies
Create policies using policy templates based on SQL Syntax:
Require JOIN to Security Table
Column Combination Restriction – Ex. Prevents combining customer name and social security #
Table JOIN restriction – Ex. Prevents joining two different tables in same query
Equi-literal Compare requirement – Tightly Constrains Query Ex. Prevents hunting for sensitive data by requiring ‘=‘ condition
By user or user groups and time of day (shift) (e.g. ETL)
Blocks connections to the database
White list or black list by
DB User Logins
OS User Logins
Applications (BI, Query Apps)
Rule Templates Contain Customizable Messages
Each of the “Policy Templates” has the ability to send the user querying the database a customized message based on the defined policy. The message back to the user from Teleran should be seamless to the application user’s experience.
Machine Learning: Curbing Inappropriate, or Long Running Queries
iGuard has the ability to analyze all of the historical SQL passed through to the Data Warehouse, and suggest new, customized policies to cancel queries with certain SQL characteristics. The Teleran administrator sets parameters such as rows or bytes returned, and then runs the induction process. New rules will be suggested which exceed these defined parameters. The induction engine is “smart” enough to look at the repository of queries holistically and not make determinations based on a single query.
The ultimate goal, in my mind, is to have the capability within a Search Engine to be able to upload an image, then the search engine analyzes the image, and finds comparable images within some degree of variation, as dictated in the search properties. The search engine may also derive metadata from the uploaded image such as attributes specific to the image object(s) types. For example, determine if a person [object] is “Joyful” or “Angry”.
As of the writing of this article, search engines Yahoo and Microsoft Bing do not have the capability to upload an image and perform image/pattern recognition, and return results. Behold, Google’s search engine has the ability to use some type of pattern matching, and find instances of your image across the world wide web. From the Google Search “home page”, select “Images”, or after a text search, select the “Images” menu item. From there, an additional icon appears, a camera with the hint text “Search by Image”. Select the Camera icon, and you are presented with options on how Google can acquire your image, e.g. upload, or an image URL.
Select the “Upload an Image” tab, choose a file, and upload. I used a fictional character, Max Headroom. The search results were very good (see below). I also attempted an uncommon shape, and it did not meet my expectations. The poor performance of matching this possibly “unique” shape is mostly likely due to how the Google Image Classifier Model was defined, and correlating training data that tested the classifier model. If the shape is “Unique” the Google Search Image Engine did it’s job.
Google Image Search Results – Max Headroom
Google Image Search Results – Odd Shaped Metal Object
The Google Search Image Engine was able to “Classify” the image as “metal”, so that’s good. However I would have liked to see better matches under the “Visually Similar Image” section. Again, this is probably due to the image classification process, and potentially the diversity of image samples.
A Few Questions for Google
How often is the Classifier Modeling process executed (i.e. training the classifier), and the model tested? How are new images incorporated into the Classifier model? Are the user uploaded images now included in the Model (after model training is run again)? Is Google Search Image incorporating ALL Internet images into Classifier Model(s)? Is an alternate AI Image Recognition process used beyond Classifier Models?
I’m not sure if the Cloud Vision API uses the same technology as Google’s Search Image Engine, but it’s worth noting. After reaching the Cloud Vision API starting page, go to the “Try the API” section, and upload your image. I tried a number of samples, including my odd shaped metal, and I uploaded the image. I think it performed fairly well on the “labels” (i.e. image attributes)
Using the Google Cloud Vision API, to determine if there were any WEB matches with my odd shaped metal object, the search came up with no results. In contrast, using Google’s Search Image Engine produced some “similar” web results.
Finally, I tested the Google Cloud Vision API with a self portrait image. THIS was so cool.
The API brought back several image attributes specific to “Faces”. It attempts to identify certain complex facial attributes, things like emotions, e.g. Joy, and Sorrow.
The API brought back the “Standard” set of Labels which show how the Classifier identified this image as a “Person”, such as Forehead and Chin.
Finally, the Google Cloud Vision API brought back the Web references, things like it identified me as a Project Manager, and an obscure reference to Zurg in my Twitter Bio.
The Google Cloud Vision API, and their own baked in Google Search Image Engine are extremely enticing, but yet have a ways to go in terms of accuracy %. Of course, I tried using my face in the Google Search Image Engine, and looking at the “Visually Similar Images” didn’t retrieve any images of me, or even a distant cousin (maybe?)
Businesses already exist which have developed and sell Virtual Receptionist, that handle many caller needs (e.g. call routing).
However, AI Digital Assistants such as Alexa, Cortana, Google Now, and Siri have an opportunity to stretch their capabilities even further. Leveraging technologies such as Natural language processing (NLP) and Speech recognition (SR), as well as APIs into the Smartphone’s OS answer/calling capabilities, functionality can be expanded to include:
Call Screening – The digital executive assistant asks for the name of the caller, purpose of the call, and if the matter is “Urgent”
A generic “purpose” response or a list of caller purpose items can be supplied to the caller, e.g. 1) Schedule an Appointment
The smartphone’s user would receive the caller’s name, and the purpose as a message back to the UI from the call, currently in a ‘hold’ state,
The smartphone user may decide to accept the call, or reject the call and send the caller to voicemail.
Call / Digital Assistant Capabilities
The digital executive assistant may schedule a ‘tentative’ appointment within the user’s calendar. The caller may ask to schedule a meeting, the digital executive assistant would access the user’s calendar to determine availability. If calendar indicates availability, a ‘tentative’ meeting will be entered. The smartphone user would have a list of tasks from the assistant, and one of the tasks is to ‘affirm’ availability of the meetings scheduled.
Allow recall of ‘generally available’ information. If a caller would like to know the address of the smartphone user’s office, the Digital Assistant may access a database of generally available information, and provide it. The Smartphone user may use applications like Google Keep, and any notes tagged with a label “Open Access” may be accessible to any caller.
Join the smartphone user’s social network, such as LinkedIn. If the caller knows the phone number of the person but is unable to find the user through the social network directory, an invite may be requested by the caller.
Custom business workflows may also be triggered by the smartphone, such as “Pay by Phone”.
The Digital Executive Assistant capabilities:
Able to gain control of your Smartphone’s incoming phone calls
Able to interact with the 3rd party, dial in caller, on a set of business dialog workflows defined by you, the executive.
Are you ready for a challenge, and 150,000 USD to begin to pursue your challenge?
That’s just SBIR Phase I, Concept Development (~6 months). The second phase, Prototype Development, may be funded up to 1 MM USD, and last 24 months.
The Small Business Innovation Research (SBIR) program is a highly competitive program that encourages domestic small businesses to engage in Federal Research/Research and Development (R/R&D) that has the potential for commercialization. Through a competitive awards-based program, SBIR enables small businesses to explore their technological potential and provides the incentive to profit from its commercialization. By including qualified small businesses in the nation’s R&D arena, high-tech innovation is stimulated and the United States gains entrepreneurial spirit as it meets its specific research and development needs.
The program’s goals are four-fold:
Stimulate technological innovation.
Meet Federal research and development needs.
Foster and encourage participation in innovation and entrepreneurship by socially and economically disadvantaged persons.
Increase private-sector commercialization of innovations derived from Federal research and development funding.