Tag Archives: Amazon

Cloud Serverless Computing: Why? and With Whom?

What is Cloud Serverless Computing?

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.

Microsoft Flow

 

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.

Microsoft Flow Pricing
Microsoft Flow Pricing

Microsoft Azure Functions

Process events with a serverless code architecture.  An event-based serverless compute experience to accelerate development. Scale based on demand and pay only for the resources you consume.

Google Cloud  Serverless

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.

Google Serverless Application Development
Google Serverless Application Development

 

Google Serverless Analytics and Machine Learning
Google Serverless Analytics and Machine Learning

 

Google Serverless Use Cases
Google Serverless Use Cases

 

Amazon AWS  Lambda

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.

IBM Bluemix OpenWhisk

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.

What’s Next?

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.

There’s an excellent article, recently published July 16th, 2017 by  Moshe Kranc called, “Serverless Computing: Ready for Prime Time” which at a high level can help you determine if your application is a candidate for Serverless Computing.


See Also:
  1. “Serverless computing architecture, microservices boost cloud outlook” by Mike Pfeiffer
  2. “What is serverless computing? A primer from the DevOps point of view” by J Steven Perry

Amazon X-Ray Studios for Indie Movie Producers

I remember building a companion app for the Windows desktop that pulled music data from iTunes and Gracenote.   Gracenote boasts:

“Gracenote technology is at the heart of every great entertainment experience, and is supported by the largest source of music metadata on the planet..”

Gracenote, in conjunction with the iTunes API / data allowed me to personalize the user experience beyond what iTunes provided out of the box.   X-Ray IMDb on Amazon Video also enriches the experience of watching movies and television hosted on Amazon Video .

While watching a movie using Amazon Video, you can tap the screen, and get details about the specific scene, shown in the foreground as the media continues to play.

“Go behind the scenes of your favorite movies and TV shows with X-Ray, powered by IMDb.  Get instant access to cast photos, bios, and filmographies, soundtrack info, and trivia.  “

IMDb is an Amazon company, which in his infinite foresight, in 1998, Jeff Bezos, founder, owner and CEO of Amazon.com, struck a deal to buy IMDb outright for approximately $55 million and attach it to Amazon as a subsidiary, private company.

The Internet Movie Database (abbreviated IMDb) is an online database of information related to films, television programs and video games, including cast, production crew, fictional characters, biographies, plot summaries, trivia and reviews, operated by IMDb.com, Inc., a subsidiary of Amazon. As of June 2017, IMDb has approximately 4.4 million titles (including episodes), 8 million personalities in its database,[2] as well as 75 million registered users.


In Amazon’s infinite wisdom again, they are looking to stretch both X-Ray and the IMDb property to budding film artists looking to cultivate and mature their following.

Approach to Adoption of X-Ray IMDb  / Amazon Video

Amazon must empower artists and their representatives to update IMDb.  IMDBPro seems to enable just such capabilities such as:

Showcase yourself on IMDb & Amazon

Manage your photos and the credits you are Known For on IMDbPro, IMDb, and Amazon Video”
  1. How then is new media content, such as Actor’s photos, and Filmography [approved] and updated by IMDb.
  2. Furthermore, what is the selection process to get indie content [approved] and posted to Amazon video.  Is there a curation process whereby not every indie artist is hosted, e.g. creative selection process is driven by Amazon Video business.
  3. To expand the use of X-Ray powered by IMDb, what are the  options for alternate Media Players and Streamers?  e.g. is YouTube a possibility, hosting and streaming content embedded with X-Ray capabilities?  Does Amazon X-Ray enabled capabilities require the Amazon Video player?
X-Ray Current Support: Amazon Hosted and Streaming

X-Ray is available on the Amazon Video app in the US, UK, Germany, and Austria for thousands of titles on compatible devices including Amazon Fire Tablets and TV/Stick, iOS and Android mobile devices, and the web.    To access X-Ray, tap the screen or click on the Fire TV remote while the video is playing.”

Amazon X-Ray Studios, Video Editing/Integration Desktop Application

Indie producers may leverage X-Ray Studios to integrate IMDb overlay content to enhance their audience’s experience.   Timecodes are leveraged to sync up X-Ray content with the video content.

“In video production and filmmakingSMPTE timecode is used extensively for synchronization, and for logging and identifying material in recorded media. During filmmaking or video production shoot, the camera assistant will typically log the start and end timecodes of shots, and the data generated will be sent on to the editorial department for use in referencing those shots.”

All metadata regarding an Indie Video may be integrated into the video source / target file, and transcoding may be required to output the Amazon required media standard.

Amazon has slightly complicated the situation by creating an Amazon Web Service (AWS) called X-Ray which has completely no relation to the X-Ray service powered by IMDb.

Amazon could not be reached for comment.

Uncommon Opportunity? R&D Conversational AI Engineer

I had to share this opportunity.  The Conversational AI Engineer role will continue to be in demand for some time.


Title: R&D Conversational AI Engineer
Location: Englewood Cliffs, NJ
Duration: 6+ months Contract(with Possible extension)

Responsibilities:

  • Create Alexa Skills, Google Home Actions, and chatbots for various direct Client’s brands and initiatives.
  • Work with the Digital Enterprises group to create production-ready conversational agents to help Client emerge in the connected life space.
  • Create additional add-ons to the conversational agents
  • Work with new technologies not be fully documented yet
  • Work with startups and their technology emerging in the connected life space.

Quals–
Client is looking for a developer in conversational AI and bot development.

What is Media Labs?   Media Labs is dedicated to driving a collaborative culture of innovation across all of Clients . We serve as an internal incubator and accelerator for emerging technology and are leading the way with fresh ideas to ignite the future of media and storytelling. We are committed to partnering with another telecom giant, startups, research and academic groups, content creators and brands to further innovation at client. One of our main themes is connected life and we are looking for an engineer to lead this development.

Requirements for R&D Engineer: –

  • Bachelor in Computer Science, Engineering, or other related field
  • Experience working with new technologies that may not be fully documented yet
  • Experience communicating technology to non-technical people
  • Experience with AWS (Lambda, CloudWatch, S3, API Gateway, etc)
  • Experience with JavaScript, Node.js
  • Some experience creating Alexa Skills, Google Home Actions, or chatbots

Optional Requirements:

  • Experience creating iOS or Android applications (native or non-native)
  •  Experience with API.AI or another NLP engine (Lex, Watson Conversation)

Amazon’s Alexa vs. Google’s Assistant: Same Questions, Different Answers

Excellent article by  .

Amazon’s Echo and Google’s Home are the two most compelling products in the new smart-speaker market. It’s a fascinating space to watch, for it is of substantial strategic importance to both companies as well as several more that will enter the fray soon. Why is this? Whatever device you outfit your home with will influence many downstream purchasing decisions, from automation hardware to digital media and even to where you order dog food. Because of this strategic importance, the leading players are investing vast amounts of money to make their product the market leader.

These devices have a broad range of functionality, most of which is not discussed in this article. As such, it is a review not of the devices overall, but rather simply their function as answer engines. You can, on a whim, ask them almost any question and they will try to answer it. I have both devices on my desk, and almost immediately I noticed something very puzzling: They often give different answers to the same questions. Not opinion questions, you understand, but factual questions, the kinds of things you would expect them to be in full agreement on, such as the number of seconds in a year.

How can this be? Assuming they correctly understand the words in the question, how can they give different answers to the same straightforward questions? Upon inspection, it turns out there are ten reasons, each of which reveals an inherent limitation of artificial intelligence as we currently know it…


Addendum to the Article:

As someone who has worked with Artificial Intelligence in some shape or form for the last 20 years, I’d like to throw in my commentary on the article.

  1. Human Utterances and their Correlation to Goal / Intent Recognition.  There are innumerable ways to ask for something you want.  The ‘ask’ is a ‘human utterance’ which should trigger the ‘goal / intent’ of what knowledge the person is requesting.  AI Chat Bots, digital agents, have a table of these utterances which all roll up to a single goal.  Hundreds of utterances may be supplied per goal.  In fact, Amazon has a service, Mechanical Turk, the Artificial Artificial Intelligence, which you may “Ask workers to complete HITs – Human Intelligence Tasks – and get results using Mechanical Turk”.   They boast access to a global, on-demand, 24 x 7 workforce to get thousands of HITs completed in minutes.  There are also ways in which the AI Digital Agent may ‘rephrase’ what the AI considers utterances that are closely related.  Companies like IBM look toward human recognition, accuracy of comprehension as 95% of the words in a given conversation.  On March 7, IBM announced it had become the first to hone in on that benchmark, having achieved a 5.5% error rate.
  2. Algorithmic ‘weighted’ Selection verses Curated Content.   It makes sense based on how these two companies ‘grew up’, that Amazon relies on their curated content acquisitions such as Evi,  a technology company which specialises in knowledge base and semantic search engine software. Its first product was an answer engine that aimed to directly answer questions on any subject posed in plain English text, which is accomplished using a database of discrete facts.   “Google, on the other hand, pulls many of its answers straight from the web. In fact, you know how sometimes you do a search in Google and the answer comes up in snippet form at the top of the results? Well, often Google Assistant simply reads those answers.”  Truncated answers equate to incorrect answers.
  3. Instead of a direct Q&A style approach, where a human utterance, question, triggers an intent/goal , a process by which ‘clarifying questions‘ maybe asked by the AI digital agent.  A dialog workflow may disambiguate the goal by narrowing down what the user is looking for.  This disambiguation process is a part of common technique in human interaction, and is represented in a workflow diagram with logic decision paths. It seems this technique may require human guidance, and prone to bias, error and additional overhead for content curation.
  4. Who are the content curators for knowledge, providing ‘factual’ answers, and/or opinions?  Are curators ‘self proclaimed’ Subject Matter Experts (SMEs), people entitled with degrees in History?  or IT / business analysts making the content decisions?
  5. Questions requesting opinionated information may vary greatly between AI platform, and between questions within the same AI knowledge base.  Opinions may offend, be intentionally biased, sour the AI / human experience.

Evaluating Amazon Lex – AI Digital Agent / Assistant Implementation

Evaluating AI chatbot solutions for:

  • Simple to Configure – e.g. Wizard Walkthrough
  • Flexible, and Mature Platform e.g. Executing backend processes
  • Cost Effective and Competitive Solutions
  • Rapid Deployment to XYZ platforms

The idea is almost anyone can build and deploy a chat bot for your business, small to midsize organizations.

Amazon Lex

Going through the Amazon Lex build chat process, and configuration of the Digital Assistant was a breeze.  AWS employs a ‘wizard’ style interface to help the user build the Chatbot / Digital Agent.  The wizard guides you through defining Intents, Utterances, Slots, and Fulfillment.

  • Intents – A particular goal that the user wants to achieve (e.g. book an airline reservation)
  •  Utterances – Spoken or typed phrases that invoke your intent
  • Slots – Data the user must provide to fulfill the intent
  • Prompts – Questions that ask the user to input data
  • Fulfillment – The business logic required to fulfill the user’s intent (i.e. backend call to another system, e.g. SAP)
Amazon Lex Chabot
Amazon Lex Chabot

The Amazon Lex Chatbot editor is also extremely easy to use, and to update / republish any changes.

Amazon Chat Bot Editor
Amazon Chat Bot Editor

The challenge with Amazon Lex appears to be a very limiting ability for chatbot distribution / deployment.  Your Amazon Lex Chatbot is required to use one of three methods to deploy: Facebook, Slack, or Twilio SMS.  Facebook is limiting in a sense if you do not want to engage your customers on this platform.   Slack is a ‘closed’ framework, whereby the user of the chat bot must belong to a Slack team in order to communicate.  Finally, Twilio SMS implies use of your chat bot though a mobile phone SMS.

Amazon Chatbot Channels
Amazon Chatbot Channels

 

I’ve reached out to AWS Support regarding any other options for Amazon Lex chatbot deployment.  Just in case I missed something.

Amazon Chatbot Support
Amazon Chatbot Support

There is a “Test Bot” in the lower right corner of the Amazon Lex, Intents menu.  The author of the business process can, in real-time, make changes to the bot, and test them all on the same page.

Amazon Chatbot, Test Bot
Amazon Chatbot, Test Bot

 

Key Followups

  • Is there a way to leverage the “Test Bot” as a “no frills” Chatbot UI,  and embed it in an existing web page?  Question to AWS Support.
  • One concern is for large volumes of utterances / Intents and slots. An ideal suggestion would allow the user a bulk upload through an Excel spreadsheet, for example.
  • I’ve not been able to utilize the Amazon Lambda to trigger server side processing.
  • Note: there seem to be several ‘quirky’ bugs in the Amazon Lex UI, so it may take one or two tries to workaround the UI issue.

IBM Watson Conversation also contends for this Digital Agent / Assistant space, and have a very interesting offering including dialog / workflow definition.

Both Amazon Lex and IBM Watson Conversation are FREE to try, and in minutes, you could have your bots created and deployed. Please see sites for pricing details.

Hey Siri, Ready for an Antitrust Lawsuit Against Apple? Guess Who’s Suing.

The AI personal assistant with the “most usage” spanning  connectivity across all smart devices, will be the anchor upon which users will gravitate to control their ‘automated’ lives.  An Amazon commercial just aired which depicted  a dad with his daughter, and the daughter was crying about her boyfriend who happened to be in the front yard yelling for her.  The dad says to Amazon’s Alexa, sprinklers on, and yes, the boyfriend got soaked.

What is so special about top spot for the AI Personal Assistant? Controlling the ‘funnel’ upon which all information is accessed, and actions are taken means the intelligent ability to:

  • Serve up content / information, which could then be mixed in with advertisements, or ‘intelligent suggestions’ based on historical data, i.e. machine learning.
  • Proactive, suggestive actions  may lead to sales of goods and services. e.g. AI Personal Assistant flags potential ‘buys’ from eBay based on user profiles.

Three main sources of AI Personal Assistant value add:

  • A portal to the “outside” world; E.g. If I need information, I wouldn’t “surf the web” I would ask Cortana to go “Research” XYZ;   in the Business Intelligence / data warehousing space, a business analyst may need to run a few queries in order to get the information they wanted.  In the same token, Microsoft Cortana may come back to you several times to ask “for your guidance”
  • An abstraction layer between the user and their apps;  The user need not ‘lift a finger’ to any app outside the Personal Assistant with noted exceptions like playing a game for you.
  • User Profiles derived from the first two points; I.e. data collection on everything from spending habits, or other day to day  rituals.

Proactive and chatty assistants may win the “Assistant of Choice” on all platforms.  Being proactive means collecting data more often then when it’s just you asking questions ADHOC.  Proactive AI Personal Assistants that are Geo Aware may may make “timely appropriate interruptions”(notifications) that may be based on time and location.  E.g. “Don’t forget milk” says Siri,  as your passing the grocery store.  Around the time I leave work Google maps tells me if I have traffic and my ETA.

It’s possible for the [non-native] AI Personal Assistant to become the ‘abstract’ layer on top of ANY mobile OS (iOS, Android), and is the funnel by which all actions / requests are triggered.

Microsoft Corona has an iOS app and widget, which is wrapped around the OS.  Tighter integration may be possible but not allowed by the iOS, the iPhone, and the Apple Co. Note: Google’s Allo does not provide an iOS widget at the time of this writing.

Antitrust violation by mobile smartphone maker Apple:  iOS must allow for the ‘substitution’ of a competitive AI Personal Assistant to be triggered in the same manner as the native Siri,  “press and hold home button” capability that launches the default packaged iOS assistant Siri.
Reminiscent of the Microsoft IE Browser / OS antitrust violations in the past.

Holding the iPhone Home button brings up Siri. There should be an OS setting to swap out which Assistant is to be used with the mobile OS as the default.  Today, the iPhone / iPad iOS only supports “Siri” under the Settings menu.

ANY AI Personal assistant should be allowed to replace the default OS Personal assistant from Amazon’s Alexa, Microsoft’s Cortana to any startup company with expertise and resources needed to build, and deploy a Personal Assistant solution.  Has Apple has taken steps to tightly couple Siri with it’s iOS?

AI Personal Assistant ‘Wish” list:

  • Interactive, Voice Menu Driven Dialog; The AI Personal Assistant should know what installed [mobile] apps exist, as well as their actionable, hierarchical taxonomy of feature / functions.   The Assistant should, for example, ask which application the user wants to use, and if not known by the user, the assistant should verbally / visually list the apps.  After the user selects the app, the Assistant should then provide a list of function choices for that application; e.g. “Press 1 for “Play Song”
    • The interactive voice menu should also provide a level of abstraction when available, e.g. User need not select the app, and just say “Create Reminder”.  There may be several applications on the Smartphone that do the same thing, such as Note Taking and Reminders.  In the OS Settings, under the soon to be NEW menu ‘ AI Personal Assistant’, a list of installed system applications compatible with this “AI Personal Assistant” service layer should be listed, and should be grouped by sets of categories defined by the Mobile OS.
  • Capability to interact with IoT using user defined workflows.  Hardware and software may exist in the Cloud.
  • Ever tighter integration with native as well as 3rd party apps, e.g. Google Allo and Google Keep.

Apple could already be making the changes as a natural course of their product evolution.  Even if the ‘big boys’ don’t want to stir up a hornet’s nest, all you need is VC and a few good programmers to pick a fight with Apple.

The Race Is On to Control Artificial Intelligence, and Tech’s Future

Amazon, Google, IBM and Microsoft are using high salaries and games pitting humans against computers to try to claim the standard on which all companies will build their A.I. technology.

In this fight — no doubt in its early stages — the big tech companies are engaged in tit-for-tat publicity stunts, circling the same start-ups that could provide the technology pieces they are missing and, perhaps most important, trying to hire the same brains.

For years, tech companies have used man-versus-machine competitions to show they are making progress on A.I. In 1997, an IBM computer beat the chess champion Garry Kasparov. Five years ago, IBM went even further when its Watson system won a three-day match on the television trivia show “Jeopardy!” Today, Watson is the centerpiece of IBM’s A.I. efforts.

Today, only about 1 percent of all software apps have A.I. features, IDC estimates. By 2018, IDC predicts, at least 50 percent of developers will include A.I. features in what they create.

Source: The Race Is On to Control Artificial Intelligence, and Tech’s Future – The New York Times

The next “tit-for-tat” publicity stunt should most definitely be a battle with robots, exactly like BattleBots, except…

  1. Use A.I. to consume vast amounts of video footage from previous bot battles, while identifying key elements of bot design that gave a bot the ‘upper hand’.  From a human cognition perspective, this exercise may be subjective. The BattleBot scoring process can play a factor in 1) conceiving designs, and 2) defining ‘rules’ of engagement.
  2. Use A.I. to produce BattleBot designs for humans to assemble.
  3. Autonomous battles, bot on bot, based on Artificial Intelligence battle ‘rules’ acquired from the input and analysis of video footage.

Streaming Companies Provide the Power of their Platform to Any Content Provider

Streaming companies enable any digital entertainment producer to use branded, customized “copy” of the streaming platform to reach their audience, and potentially growth, exposure into new markets.

  • Direct competition with Google’s YouTube.
  • Microsoft to stretch SharePoint’s abilities re: video streaming, Video on Demand, and Broadcast Live, as well as it’s user licensing model, it could be another tool for entrepreneurs to offer any content creator a “Digital Entertainment Portal”.

Any content provider of digital media entertainment:

  • Broadcast Television Channels – e.g. CBS, NBC, SyFy
  • Independent digital media producers, e.g. currently using channels to reach a large audience, e.g. YouTube

The streaming company can create a portal wizard to buildcopy a streaming portal template.  The digital media producer uses web app widgets, similar to Microsoft SharePoint sites, to customize their portal to their digital media video / assets.  The Streaming “Portal” provider, as part of their service, handles the monetary transactions for customer subscriptions, or other business models supported.  In addition, the bandwidth load from streaming would be handled by the Streaming “Portal Provider”, a major benefit, leveraging the companies’ Content Delivery Network (CDN).

Anyone could apply for a partnership with the streaming company, and once approved, may use the tools provided by the streaming partner to spawn a new platform site around the customer  / producer’s content.

This new revenue stream of streaming companies platforms, such as Netflix and Amazon Instant, may be vastly multiplied using a “Partner Portal” model.

 

G.E. Plans Big Entry into IoT, Providing Analytics and Predictive Rules

G.E. Plans App Store for Gears of Industry

The investment of $500 million annually signals the importance of the so-called Internet of Things to the future of manufacturing.

G.E. expects revenue of $6 billion from software in 2015, a 50 percent increase in one year. Much of this is from a pattern-finding system called Predix.  G.E. calls its new service the Predix Cloud, and hopes it will be used by both customers and competitors, along with independent software developers. “We can take sensor data from anybody, though it’s optimized for our own products,” Mr. Ruh said.

[Competitive solutions from IBM, Microsoft, and Google] raises the stakes for G.E. “It’s a whole new competition for them,” said Yefim Natis, a senior analyst with Gartner. “To run businesses in a modern way you have to be analytic and predictive.”

G.E. is running the Predix Cloud on a combination of G.E. computers, the vast computing resources of Amazon Web Services, and a few [local] providers, like China Telecom.

China, along with countries like Germany, [are] sensitive about moving its data offshore, or even holding information on computers in the United States.  
The practice of “Ring fencing”  data exists in dozens of jurisdictions globally.  Ring fencing of data may be a legal and/or regulatory issue, that may inhibit the global growth of cloud services moving forward.

Source: G.E. Plans App Store for Gears of Industry

Abundant Content: Selecting Your Movie / TV Show is Burdensome

Although content is still ‘King’, the side effect of Streaming Services aggressively rolling out content makes the connection between the ‘ideal’ content and consumer burdensome to initiate.

Streaming Services create a ‘funnel’ to get ‘ideal’ content to the consumer through the use of custom carousels and search.

5 minutes max, I stroll around the Streamers’ carousels for random movies or TV shows that catch my interest.  If I don’t find anything worthy to commit my time, I bounce to another streaming service, and repeat the process.

The problem is compounded when you add broadcast Content Channels: ABC, CBS, Comedy Central, HBO, SyFy,  USA, etc, in addition to Streamers like Amazon Instant and Netflix.

The cost of making a decision of which Movie/TV episode to watch comes down to a basic Microeconomic theory.

In order for the consumer to make an accurate assessment of Opportunity Cost, one has to consider ~ALL available options.

Therefore, the cost of making a decision is inefficient, and most importantly inaccurate due to the amount of Video On Demand, (VOD) repositories available to the consumer.

Opportunities to Curtail Consumer Search Time:

  • On demand chat with a Genre Aficionado, video or text chat, 24/7, an employee of the Streaming Service, or central service contracted to the Service.
  • More robust search that has the capacity to drill down on metadata.  E.g. Filter: N stars rating; Sort: ‘added’ date,
  • Add Closed Captioning  to Search metadata
  • Add object and facial recognition index of objects to Search; Open and Play media at time code. E.g. Nike Sneakers
  • ‘Mad Libs’ style secondary search; fill in fields such as leading actor or actress, director of photography, etc.
  • Inbox – recommendations ‘people’ have sent you, manual and automated messages.  Queue up Search results to notify you once per week.  User may send a message with a link to a movie.
  • Cross Video On Demand (VOD) libraries Searching.  Industry Standards derived and implemented.