Tag Archives: Amazon AWS

Technology

Evaluating Amazon Lex – AI Digital Agent / Assistant Implementation

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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.

Business, Entertainment, Media, Technology

As a Data Deluge Grows, Companies Rethink Storage

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At Pure Storage, a device introduced on Monday holds five times as much data as a conventional unit.

  • IBM estimates that by 2020 we will have 44 zettabytes — the thousandfold number next up from exabytes — generated by all those devices. It is so much information that Big Blue is staking its future on so-called machine learning and artificial intelligence, two kinds of pattern-finding software built to cope with all that information.
  • Pure Storage chief executive, Scott Dietzen, “No one can look at all their data anymore; they need algorithms just to decide what to look at,”

Source: As a Data Deluge Grows, Companies Rethink Storage – The New York Times

Additional Editorial:

Pure Storage is looking to “compress” the amount of data that can be stored in a Storage Array using Flash Memory, “Flashblade”.   They are also tuning the capabilities of the solution for higher I/O throughput, and optimized, addressable storage.

Several companies with large and growing storage footprints have already begin to customize their storage solutions to accommodate the void in this space.

Building more storage arrays is a temporary measure while the masses of people, or fleets of cars turn on their IoT enabled devices.

Data is flooding the Internet, and innumerable, duplicate ‘objects’  of information, requiring redundant storage, are prevalent conditions. A registry, or public ‘records’ may be maintained.   Based on security measures, and the public’s appetite determine what “information objects” may be centrally located.  As intermediaries, registrars may build open source repositories, as an example, using Google Drive, or Microsoft Azure based on the data types of ‘Information Objects”

  • Information object registrars may contain all different types of objects, which indicate where data resides on the Internet.
    • vaguely similar to Domain name registrar hierarchy
    • another example, Domain Name System (DNS) is the best example of the registration process I am suggesting to clone and leverage for all types of data ranging from entertainment to medical records.
  • Medical “Records”, or Medical “Information Objects”
    • X-ray images, everything from dental to medical, and correlating to other medical information object(s),
  • Official ‘Education’ records from K-12 and beyond, e.g. degrees and certifications achieved;
  • Secure, easy access to ‘public’ ‘information objects’ by the owner, and creator.  Central portal(s) driving user traffic.  Enables ‘owner’ of records to take ‘ownership’ of their health, for example

Note: there are already ‘open’ platforms being developed and used for several industries including medical; with limed access.  However, the changes I’m proposing imposes a ‘registrar’ process whereby portals of information are registered, and are interwoven, linking to one another.

It’s an issue of excess weight upon the “Internet”, and not just the ‘weight’ of unnecessary storage, the throughput within a weaved set of networks as well.

Think of it in terms of opportunity cost.  First quantify what an ‘information object’, or ‘block of data’ equates to in cost.  It seems there must already be a measurement in existence, a medium amount to charge / cost per “information object”.  Finally, for each information object type, e.g. song, movie, news story, technical specifications, etc. identify how many times this exact object is perpetuated in the Internet.

Steps on reducing  data waste:

  • Without exception, each ‘information object’ contains an (XML) meta data file.
  • Each of the attributes describing information objects are built out as these assets are being used; e.g. proactive autopopulate search, and using an AI Induction engine
  • X out of Y metadata type and values are equivalent
    • the more attributes correlate to one or more objects, the more likely these objects are
      • related on some level, e.g. sibling, cousin
      • or identical objects, and may need meta relationship update
    • the metadata encapsulates the ‘information object’

Another opportunity to organize “Information Asset Objects” would be to leverage the existing DNS platform for managing “Information Asset Repositories”.   This additional Internet DNS structure would enable queries across information asset repositories.   Please see “So Much Streaming Music, Just Not in One Place”  for more details.

Business, Economy, Finance, Law, Legal, Technology, Work

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

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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

Entertainment, Fun, Media, Technology

Google Introduces their Cloud, Digital Asset Management (DAM) solution

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Although this is a saturated space, with many products, some highly recommended, I thought this idea might interest those involved in the Digital Asset Management space.  Based on the maturity of existing products, and cost, it’s up to you, build or buy.  The following may provide an opportunity for augmenting existing Google products, and overlaying a custom solution.

Google products can be integrated across their suite of solutions and may produce a cloud based, secure, Digital Asset Management, DAM solution.   In this use case, the digital assets are Media (e.g. videos, still images)

A Google DAM may be created by leveraging existing features of Google Plus, Google Drive, YouTube, and other Google products, as well as building / extending additional functionality, e.g. Google Plus API, to create a DAM solution.   An over arching custom framework weaves these products together to act as the DAM.

Google Digital Asset Management (New)

  1. A dashboard for Digital Asset Management should be created, which articulates, at a glance, where project media assets are in their life cycle, e.g. ingestion, transcoding, editing media, adding meta data, inclusion / editing of closed captions, workflow approvals, etc.
  2. Creation and maintenance of project asset folder structure within storage such as Google Drive for active projects as well as Google Cloud Storage for archived content.  Ingested content to arrive in the project folders.
  3. Ability to use [Google YouTube] default encoding / transcoding functionality, or optionally leverage alternate cloud accessible transcoding solutions.
  4. A basic DAM UI may provide user interaction with the project and asset meta data.
  5. Components of the DAM should allow plug in integration with other components on the  market today, such as an ingestion solution.

Google Drive and Google Cloud Storage.  Cloud storage offers large quantities of storage e.g. for Media (video, audio), economically.

  1. Google Drive ingestion of assets may occur through an automated process, such as a drop folder within an FTP site.  The folder may be polled every N seconds by the Google DAM orchestration, or other 3rd party orchestration product, and ingested into Google Drive.  The ingested files are placed into a project folder designated by the accompanying XML meta file.
  2. The version control of assets, implemented by Google Drive and the DAM to facilitate collaboration and approval.
  3. Distribution and publishing media to designated people and locations, such as to social media channels, may be automatically triggered by DAM orchestration polling Google Drive custom meta data changes.   On demand publishing is also achievable through the DAM.
  4. Archiving project assets to custom locations, such as Google Cloud solution, may be triggered by a project meta data status modification, or on demand through the DAM.
  5. Assets may be spawned into other assets, such as clips.  Derived child assets are correlated with the master, or parent asset within the DAM asset meta data to trace back to origin.  Eliminates redundancy of asset, enabling users to easily find related files and reuse all or a portion of the asset.

Google Docs

  1. Documents required to accompany each media project, such as production guidelines, may go through several iterations before they are complete.  Many of the components of a document may be static.  Google Docs may incorporate ‘Document Assembly’ technology for automation of document construction.

Google’s YouTube

  1. Editing media either using default YouTube functionality, or using third party software, e.g. Adobe suite
  2. Enable caption creation and editing  may use YouTube or third party software.
  3. The addition & modification of meta data according to the corporate taxonomy may be added or modified through [custom] YouTube fields, or directly through the Google DAM Db where the project data resides.

Google’s Google Plus +

  1. G+ project page may be used for project and asset collaboration
  2. Project team members may subscribe to the project page to receive notifications on changes, such as new sub clips
  3. Asset workflow notifications,  human and automated:
    1. Asset modification approvals (i.e. G+ API <- -> DAM Db) through custom fields in G + page
    2. Changes to assets (i.e. collaboration) notifications,
    3. [Automated] e.g. ingestion in progress, or completed updates.
    4. [Automated] Process notifications: e.g. ‘distribution to XYZ’ and ‘transcoding N workflow’.  G + may include links to assets.
  4. Google Plus for in-house, and outside org. team(s) collaboration
  5. G + UI may trigger actions, such as ingestion e.g.  by specifying a specific Google Drive link, and a configured workflow.

Google Custom Search

  1. Allows for the search of assets within a project, within all projects within a silo of business, and across entire organization of assets.
  2. Ability to find and share DAM motion pictures, still images, and text assets with individuals, groups, project teams in or outside the organization.  Google Plus to facilitate sharing.
  3. Asset meta data will e.g. describe how the assets may be used for distribution, digital distribution rights.   Users and groups are implemented within G+, control of asset distribution may be implemented in Google Plus, and/or custom Google Search.

Here are a list of DAM vendors.