AI-ML Algorithm


  1. Choosing the right estimator (scikit-learn) : http://scikit-learn.org/stable/tutorial/machine_learning_map/
  2. How to choose algorithms for Azure Machine Learning Studio : https://docs.microsoft.com/en-us/azure/machine-learning/studio/algorithm-choice
  3. A Tour of Machine Learning Algorithms : https://machinelearningmastery.com/a-tour-of-machine-learning-algorithms/
  4. Guidelines to Select Machine Learning Scheme for Classification of Biomedical Datasets http://nexginrc.org/Publications/pub_files/evobio09-ajay.pdf
  5. A Tour of The Top 10 Algorithms for Machine Learning Newbies : https://towardsdatascience.com/a-tour-of-the-top-10-algorithms-for-machine-learning-newbies-dde4edffae11
  6. Machine Learning Algorithms: Which One to Choose for Your Problem : https://blog.statsbot.co/machine-learning-algorithms-183cc73197c

Yantra


Yantra (यन्त्र) (Sanskrit) (literally "machine, contraption" is a mystical diagram, mainly from the Tantric traditions of the Indian religions



They are used for the worship of deities in temples or at home; as an aid in meditation; used for the benefits given by their supposed occult powers based on Hindu astrology and tantric texts. They are also used for adornment of temple floors, due mainly to their aesthetic and symmetric qualities. Specific yantras are traditionally associated with specific deities.



Yantras are usually associated with a particular deity and are used for specific benefits, such as: for meditation; protection from harmful influences; development of particular powers; attraction of wealth or success, etc.They are often used in daily ritual worship at home or in temples, and sometimes worn as a talisman.

As an aid to meditation, yantras represent the deity that is the object of meditation. These yantras emanate from the central point, the bindu. The yantra typically has several geometric shapes radiating concentrically from the center, including triangles, circles, hexagons, octagons, and symbolic lotus petals. The outside often includes a square representing the four cardinal directions, with doors to each of them

Yantras can be on a flat surface or three dimensional. Yantras can be drawn or painted on paper, engraved on metal, or any flat surface. They tend to be smaller in size than the similar mandala, and traditionally use less color than mandalas.

Occult yantras are used as good luck charms, to ward off evil, as preventative medicine, in exorcism, etc., by using their magical power. When used as a talisman, the yantra is seen to represent a deity who can be called on at will by the user. They are traditionally consecrated and energized by a priest, including the use of mantras which are closely associated to the specific deity and yantra. Practitioners believe that a yantra that is not energized with mantra is lifeless

A yantra comprises geometric shapes, images, and written mantra. Triangles and hexagrams are common, as are circles and lotuses of 4 to 1,000 petals.


Image Courtesy : Desktop calendar of year 2017 by Ganesha Housing Corporation Limited






AI/ML for SMB


1. Salesforce Einstein AI Intelligent CRM

2. MailChimp : Email marketing

3. Clare.AIClare.AI is an example of a plug and play app for (1) online banking services, and (2) to handle a larger volume of customer inquiries without hiring more staff.

4. Malaysian company, Supahands for upwork like service to select crowd sourcing v/s freelancer 

5. smart speaker or home robot can be used at retail outlet

6. Digital Genius : Intelligent customer service query. The AI platform for customer service

7. Acquisio : online ads on Facebook, Bing, Adwords

8. Darktrace : Data security. 
Enterprise Immune System technology for cyber security.

9. Crayon : Competitor analysis

10. Aivo : chat bot

11. ThoughtSpot business-intelligence analytics search software 

12. Datoramaend to end marketing integration platform 

13. VoxPro multilingual customer experience and technical support solutions 

14. bold360 Better customer engagement


16. SAP CoPilot: Digital Assistant in the Enterprise

17. Deloitte: Machine-Learning Contract Reviews

18. AISense: Call, Meeting Transcriptions


19. WalkMe: AI for Software Training. Integrated with Athenahealth, Salesforce, Workday etc.


20. Workday: Finance and HR

21. Athenahealth uses WalkMe to train doctor, nurse about how to use system

22. ServiceChannel for restaurants

23. Niles for conversation

24. MESHNot Rocket Science: Branded Bots


25. Acculation Social Media content decision.

Node.js


What is Node.js?

Node.js is JavaScript runtime built on Chrome’s V8 JavaScript engine.

- Event Driven
- Non-Blocking
- Single thread

For Details
Read: https://nodesource.com/blog/understanding-the-nodejs-event-loop/
Watch: https://www.youtube.com/watch?v=8aGhZQkoFbQ

Its package eco system is npm : https://www.npmjs.com/ It contains over 400k public library. 

How to install Node.js Refer : https://github.com/creationix/nvm

Why one should user Node.js ? https://blog.hellotangible.com/10-reasons-to-use-node-js-b74ed06bb366

Node.js core API : https://nodejs.org/api/

Hapi HTTP server https://hapijs.com/

Getting Started with NPM https://docs.npmjs.com/getting-started/what-is-npm

Ref: https://blog.hellotangible.com/an-absolute-beginners-guide-to-node-js-c27e6d108b5c


Managing Storage with Containers


https://www.meetup.com/Docker-Bangalore/events/253542738/

Flex Volume Drivers in Kubernetes and CSI, Peeyush Gupta, IBM
=============================================================

Storage in container

- stateless / stateful
- volumes
- dynamic provisioning
- PVC, PV and Storage Class

* Storage Class refers to dynamic provisioning
* PVC refers to Storage Class
* POD refers to PVC for volume. 

Kubelets running on host, request Flex Driver. Flex Driver implements vendor specific APIs for storage/volume : 1. Mount 2. Unmount 3. attach 4. detach. 

This binary need to be placed(copied) at specific path for each POD. 
For CNI also cadico driver need to be placed(copied) at specific path for each POD. The better alternative is CSI = Container Storage Interface. 

CO = Container Orachstrator. Example: Kubernetes (K8S), MESOS, Cloud Foundray, OpenShift (by RedHat). 
CO has 1. node 2. controller 3. identity

There is a single binary for node and controller. Based on Identity either node or controller role can be played. 

1. Indemotent APIs
2. Sidecar container
2.1 Driver register (Identity Service)
2.2 Extended  Provisoner (watch create volume)
2.3 Extended Attacher (watch attach)
2.4 Liveness Probe
2.5 Extended snapshotter (started in mid July 2018)

Containerized Gluster Storage in Kubernetes - Saravanakumar, Red Hat
====================================================================

GlusterFS was born by oil industry. Oil industry need to process data from different hosts to detect presence of oil.  Now it is more than 10 years old. 

Steps (all steps as sudo)

1. install and start glusterd service on all host. 
2. gluster peer status
3. gluster volume create
4. gluster volume start
This will start gluster on all host. 
5. gluster volume status
6. mount -t glusterfs

PVC access mode
1. ROX: Read only by many nodes
2. RWO: Read/Write by single node
3. RWX: Read/Write by many nodes

Heketi provides a RESTful management interface which can be used to manage the life cycle of GlusterFS volumes

Storage requirements for running Spark workloads on Kubernetes, Rachit Arora
============================================================================

Spark core engine runs over 1. Yarn, 2. MESOS, 3. Standalone Schedular, 4. K8S
1. Spark SQL 2. Spark Streaming 3. Spark Machine Learning Lib 4. GraphX runs over Spark Core Engine

* Data engineer 1. Ingest and store data from multiple source 2. Prepare Data. 
* Data Scientis 2. Prepare Data 3. Analysze Data build model 
* Application Developer 4. Visulize Data

Now new trend is serverless analytics. 

'Spark over K8S' provides Jupyter-Kernel gateway for data scientist to analyze data

Distributed FS
1. NFS and BigNFS
2. HDFS
3. DBFS (Data Briks FS)
4. S3 / Object Storage
5. Portworx
6. GlusterFS

URLs: 

datascience.ibm.com 
www.ibm.com/analytics/us/en/watson-data-platform/tutorial

Tweeter Handle : @k8sBLR

MLCC


Let me share key take away points from meetup event "Google Machine Learning Study Jam

In Feb/March 2018, Google announced MLCC Machine Learning crash course In July 2018, MLCC Study Jam series comes to India. Click here and click here to know more. I attended one such event with my friend, by Industry 5.0 meetup.

Here are few useful links

TensorFlow Content Bundle, Spring 2018

Gradients and Partial Derivatives : YouTube Video 
Later on, I found the Maths play list is good. All videos  by  Eugene Khutoryansky are excellent

Another YouTube video by  Christopher Gondek. Here also, the playlist about 'Machine Learning Visualization' is good. 

Microsoft announced about FPGA based Edge Computing : Brainwave project

AutoML and transfer learning. At present, they are at nascent stage. Once let it fully evolved then we may not need people who know AI/ML. The machine themselves will learn. I did little Googling and found few links : http://www.ml4aad.org/automl/ and https://automl.info/

As per my knowledge, after completing any Machine Learning course till one completely switch his/her career path, Kaggle is the only platform to get hands-on experience. I came to know one more such platform Seedbank  I found one seed about 'Piano Transcription' quite interesting. We discussed with Sanjay Chitnis about creating similar seed to recognize Indian Raga

There is an interesting book 'Pattern Recognition and Machine Learning (Information Science and Statistics)' by Chrisopher M. Bishop

http://playground.tensorflow.org is an excellent, browser based Neural network tool. It is also used as part of MLCC We discussed about L1 regularization, L2 regularization, confusion matrix, precision, accuracy, recall, F1 score, Receiver operating characteristic etc. Precision is all about how many positive case, the algorithm could able to detect out of all positive cases. Recall is about how good is the diagnostic test? 

CNN is combination of filter and dimension reduction. RNN is a special case of LSTM. GAN is widely used to creation. The GAN Zoo has list of all variations of GAN

We also discussed about Semi-Supervised Learning , Topic Learning OR Keyword Learning, that is beyond supervised learning, Gold standard etc. 

At the end, Sanjay drew out attention to an interesting trend that now, product cost is keep reducing. Features in products are keep increasing. Service cost is keep increasing ! India has lots of data available. There is good scope of data analytics and machine learning for General Election 2019 at India. 

DevOps & Digital Transformation


DevOn (Prowernesss) conducted its first meetup with core theme of "DevOps and Digital Transformation". We noticed many buzzwords in Software Quality. It started with CMMI, then P-CMMI, then Agile, Scrum and now DevOps. The most important is, how any orgnisation tunes the latest trend with (like DevOps) with its business strategy, culture and customer expectation. Uber became successful with this approach. 

Hariharan Ganesan broke myths that Rolls-Royce is no longer making cars ! He himself does not posses any car by Rolls-Royce and neither he is getting any discount to buy one. :-) He talked more about Rolls-Royce, its business, product, strategy, market, people etc. In spite of being company based on metal, nut and bolts, DevOps is relevant for Rolls-Royce. 

We were amazed by less-known facts about aviation industry. The first IoT enable business was aircraft. Its engine is not sold, but offered on rental per hour basis. It is an intelligent engine and having engine to engine communication capability. Rolls Royce outsources 10mm size small robot (size of a bug) which goes inside of aircraft and takes inside engine photos. R2 (R square) Data Labs is sister concern of Rolls Royce. Key criteria are (1) availability : avoid flight delay and flight cancellation (2) safety and (3) fuel efficiency. At R2 lab, there is a 'digital twin' of each engine. Digital Twin is much more than Aut-CAD or CAM. It is mathematical model (relatively simple) and/or physical model based on CAD/CAM running on HPC. When aircraft is flying over Atlantic ocean, its engine talked with other engine about yesterday's weather condition over Atlantic ocean to compare. At R2 Labs, weather data is fedded to digital twin of the engine for to fine tune and make better engine performance 

Prashant Kumar talked about Docker and Kubernetes. As per definition : docker is combination of code, runtime, system tools, system libs etc. It is most popular container. Docker image is immutable. DockerHub is docker registry - something like git, github, big-bucket. Docker is popular container. Docker improves DevOps workflow by (1) environment consistency (2) Isolation (3) organizing applications and (4) portability. One must mention/use correction version of docker engine for portability. Prashant gave tips about 'dangling API' to clean manually all the unused objects, else the file system will be out of space. Kubernetes maintains containers at scale. A pod can have one or more than one containers. Sometimes, for state-full services we need to attached volume like EBS. 

Vinay Krishna talked about ' DevOps Success Recipe: One Team One Goal ' The process and tools are just means. They may not solve actual problem. Vinay explained few real life scenarios, without mentioning any organisation name. 

1. Developers re-designed a web page that was used by customer support team, without informing them. The team faced lots of issue while answering the customer call and at mid night the software needed to be rollback to previous version. 

2. The end-users were involved from beginning. Developers completed many modules, and then started GUI. The end-users raise concern about GUI and finally GUI was re-designed after many e-mail exchanges (to blame) . Involving the end-user may not help, if they attend the meeting just for shake of attending. 

3. All stack holders were involved. Code coverage was 80 percentage and above. CI/CD pipeline was green. All test cases passed. There was 100 % automation. No severity three bugs, yet customer was not happy. All bugs were moved as severity.  Many test cases for code coverage was not up to the mark and few does not have even needed assert statement. 

Yes all three amigos (as per agile) business, developers and testers must be involved as one team. Once someone commented that this task belongs to new DevOps team. There were already three teams, (1) Developers, (2) QA (3) Operation. DevOps team members were same people from operation team and after Docker + cloud training the team was re-branded as DevOps team! Operation people does not like development work. Developers does not like to do work , that is done by operation team. All needs to work as one team. 

4. Prashant also shared a positive example about valuable suggestions from operation team like : (1) Add human readable logs (2) add feature switch turn on/off etc. 

Prashant also talked about NetFlix tools like Chaos Monkey, Simian Army, Chaos Gorilla etc. They are resiliency tools that helps applications tolerate random instance failures on cloud. He suggested to read "Value Stream Mapping" and "Software Horror Stories"

Now let me share my views. This talk remind me about similar practical facts that I learnt during MBA. When SPC (statistical process control) introduced, the shop-floor people does not understand about 2 lines in chart recorder. They drew manually to keep chart withing two lines !! It reminded me the famous business novel 'The Goal' about ToC (theory of constraints). In the novel the people strongly rejected reporting so many numbers/statistics. Later on, new system of using green tag and rad tag itself caused another issue.  Now time changed. I also remember a famous joke when a US firm ordered something from Japan with 97% quality, the Japan team prepared 3% pieces separately with poor quality. 

In IT industry also, I observed that (1) sometimes, all the review process does not apply to 'system engineers team' even the clarity in requirement is the most crucial part. (2) Sometimes, quality people have un-realistic matrices about number comments within kLOC, to meet them, manager add dummy comments or remove genuine comments from the record. It defeats its purpose. 

So in summary, the human tendency, the culture, power politics cannot be ignored to bring the change. Quality must be everyone's responsibility. 

Shynish Meladath talked about Industrial IOT and DevOps. The key take away points were 

1. 'Particle Photon' It is an IoT kit 
2. Eclipse 4diac  provides an open source infrastructure for distributed industrial process measurement and control systems based on the IEC 61499 standard.
3. resion.io that brings Linux containers to IoT. 
4. Kaa is an open source IoT platform
5. Spanner CI is continuous integration for IoT
6. macchina is a versatile platform for car. 

I missed the last session "Data-Driven DevOps" by Ashwin Shankarananda, due to other priority. 

Disclaimer: I did my best to capture notes and key take away points from the event. However the content is as per my understanding and it may or may not reflect the original content/intention by the speaker. Any corrections are welcome. 

Reference https://www.meetup.com/Digital-DevOps-Bangalore/events/252154106/


OpenStack meetup


16th June 2018, I attended OpenStack Meetup at Ericsson office. Let me share my notes for readers of this blog : Express YourSelf !

Shashi Singh from Altiostar Networks discussed about EPA (Enhanced Platform Awareness). 

EPA is about about making aware NFVO, VNFM and VIM, that specialized hardware is available below virtualization layer. E.g. High I/O throughput, high performance CPU, GPU, crupto accelerators and many more as below slides:







Shashi explained nicely NFV MANO architecture to build the context and introducing the acronmys. Telco NFVI providers are: RedHat, WindRiver, VMWare, Mirantis etc. VNFM is categorized as specific VNFM and Generic VNFM. It supports three interfaces: Ve-Vnfm-vnf, Vi-Vnfm and Or-Vnfm.

He explained how EPA can eliminate the need of passing through virtualization layer for data packet, if the required VNFs are running at same CPU socket. I confirmed my understanding that, one example of EPA is let all VNFs for user-plane data having single CPU afinity. We also discussed about SR-IOV single root input/output virtualization, cpu pinning, threading policy etc. Sometimes within storage node, one can leaverage use of SR-IOV, DPDK etc to support more I/O. TOSCA standard defines combination of NS-D (Network Service Descriptor) and VNFD (VNF Descriptor). Shashi also mentioend about Queens Release, Cyborg framework, nova, ironic etc. 

Here is list of Intel technologies for EPA

1. Intel Advance Encryption Standard - New Instructions (Intel AES-NI)
2. Intel Advance Vector Extensions (AVE) and AVE2
3. Intel Quick Sync Video Technology
4. Intel QuickAssist Technology for encryption / decryption and  compression / decompression
5. Intel Trusted Execution Technology (TXT)
6. Intel Node Manager : Server Mangement at Data Center
7. Data Plane Development Kit (DPDK) at Xenon processor
8. SR-IOV
9. Intel Xeon Phi Co-processor: for PCI

I came to know about this website https://www.telecomtv.com/ During tea-break, someone commented, that Kubernetes is now open source, but it is very old. Google is working on new technology / product named by Omega that is yet to be open sourced. 

Palaniswamy from Tech M, explains about ManageIQ (with demostration) as Multi Cloud Management Platform. ManageIQ supports public clouds like : Amazon Web Services, Microsoft Azure, Google Cloud Platform; OpenStack based private clouds; containers like Kubernetes, OpenShift Origin etc. ManageIQ internally uses PostgreSQL DB. Ansible Tower is used for configuration and automation. 




Sukant J R and Manoranjan Sahoo from Ericsson presented about CI/CD for containerized openstack development based on Helm. 




We also discussed about 4 types of people in IT industry always remains. (1) Developers (2) Support engineers (3) Integrators and (4) Testers. The new technology comes and goes. One needs to work, as per his/her core strength. 

Apart from that, Uday T.Kumar from Ericsson shared some insights about OpenStack Summit and how to contribute to OpenStack community. He also acknowledged that Bangalore OpenStack community is very active and sharing the latest updates. Later on those updates are known to entire world at OpenStack summit. 

Disclaimer: I captured this notes, as per my understanding on best effor basis. So it may not accurately refelct the spearker's view. Any corrections are welcome.  

Reference: 
https://www.meetup.com/Indian-OpenStack-User-Group/events/249891291/
https://01.org/sites/default/files/page/openstack-epa_wp_fin.pdf
https://networkbuilders.intel.com/network-technologies/enhancedplatformawareness

My Holiday Destination



HDH Mahant Swami Maharaj @ Bangalore


Jai SwamiNarayan

Recently, HDH Mahant Swami Maharaj visited Bangalore. All followers of BAPS SwamiNarayan religion were super excited with full of devotion. If one remains in the presence of such divine Saint, even for short time, he/she get huge benefits in all fronts. I was lucky enough to get His blessings and listen to His speeches. He emphasize on importance of unity among all followers/volunteers for great success. 

One of BAPS followers planned to sing Kirtan/Bhajan/rhyme in different languages : Hindi, Panjabi, Gujarati and Sanskrit. I just contributed by translating one such Gujarati hymn

ગુરુદેવના ચરણમાં કરીયે કરોડો વંદન 

into Sanskrit. Here it goes for the benefits of all readers of this blog "Express YourSelf !





गुरुदेवनाम् पादयोः।           कुर्महे कोटि प्रणामान्
परब्रह्मन: पादयोः           कुर्महे कोटि प्रणामान्

भवसागरम् तारयन्त:           न: नाविका: भवन्त:
दीनबंधव: भो: रसवन्त:           कुर्महे कोटि प्रणामान्

वयम् दीन हीना: आगता:           न किमपि नीता:
भवद्भि:  ह्रदा  स्विकृता:            कुर्महे कोटि प्रणामान्


भो: श्री हरिसखीन:           श्रीजी सदृशा: प्रतापिन:
अन्तरे वसन्त: शाक्षिन :            कुर्महे कोटि प्रणामान्

भवन्त: अमृतम्  वर्षन्त:           तथापि वयम् पिपीषन्त:
परम् ह्रदया: रमन्त:            कुर्महे कोटि प्रणामान्

सदा नेत्रेषु वसन्तु              शरणे न: स्थापयन्तु 
वयम् पादयोः वसेम            कुर्महे कोटि प्रणामान्

Translation: 

we all are bowing down at lotus feets of the master for crores of times. 
he is like supreme Bhraman. We all are bowing down at lotus feet of supreme Bhraman for crores of times

oh master, you are making us to cross this worldly ocean (Bhava-saagar). you are like Helmsman /sailor /caption of our boats. 
you are very interesting and relative of all poor people. we all are bowing down for crores of times. 

we are poor and with less reources. We did not bring anything. 
(in spite of that) you accepted us with full heart. we all are bowing down for crores of times. 

you are close friend of God. You are as powerful as God.
you are like witness staying in our hearts. we all are bowing down for crores of times. 

you did rain of nector. in spite of that we are thirsty. 
but our hearts are feeling pleasant. we all are bowing down for crores of times. 

please stay always in our eyes (we always want to see you everywhere). we all surrender you, please accept us. 
we all wish to stay at your lotus feet. we all are bowing down for crores of times.

Alexa


I attended few sessions by Amazon about its Alexa devices, during last few months. Voice represents next major disruption in computing. These devices provides VUI (Voice User Interface). We had hands-on sessions and interactive QAs. Let me cover some of the relevant URLs and overview in this blog post for readers of "Express YourSelf !"

Comparison 


Here is a quick comparison of all major devices:



Echo Dot Echo Dot
Kids Edition
Echo Echo Plus Echo Spot Echo Show
Price Rs. 4000 N/A Rs. 10,000 Rs. 15000 Rs. 13000 N/A
$50 $80 $100 $150 $130 $230
Rs. 3341 Rs. 5346 Rs 6682 Rs. 10023 Rs.8687 Rs. 15369
Microphones 7 7 7 7 4 8
Misc. Smart hub 2.5" screen 7" screen

Apart from the regular devices from Amazon, few smart cars and smart TVs also have built-in Alexa support. Amazon also launched "Alexa 7-Mic Far-Field Dev Kit" that hardware can be part of any product. One can add display support also like Echo Spot and Echo Show, however it needs to go through rigorous certification process from Amazon.

Comparison of Mobile App with Alexa Skill

Mobile App ~ Alexa Skill
Mobile App icon ~ Invocation Name
GUI ~ VUI

Many mobile apps have Alexa skill e.g ola, goibibo, crickinfo, zomato etc. have alexa skill


How it works

Alexa software has mainly two major components

1. ASK (Alexa skills kit) to build new skill

2. AVS (Alexa voice service) to integrate with RPi kind of device. 

The hardware is quite simple with microphone array and speaker. The microphone array used for noise cancellation. The spoken sentence is divided into :

1. Wakeup word
2. launch
3. Invocation name. It should be two words. 
3. Utterance

Steps

step 1. Wake up word can be = Alexa / Computer / Echo / Amazon

This will wakeup the device. It triggered beam forming to listen. 

step 2. The utterance (captured audio) goes to cloud

step 3. At cloud real magic happens with

3.1 speech processing 
3.2 NLP


step 4. The invocation name  is detected. With invocation name, the execution flow goes to specific skill. Now skill has all the logic, algorithm to further understand the utterance, to access cloud service, database etc and finally for the response

Here the front-end is developed and tested with simulator using developer.amazon.com

step 5. As per training model, Alexa translate the utterance to Intent. The developer need to create custom intent, that mapped to function implementation to provide response. Alexa also provide standard built-in Intent, that developer can implement
https://developer.amazon.com/docs/custom-skills/standard-built-in-intents.html
There is a set of built-in intent libraries for various use cases
https://developer.amazon.com/docs/custom-skills/built-in-intent-library.html


In Alexa terms "slot" is like argument to function. Alexa has built-in slot types : https://developer.amazon.com/docs/custom-skills/slot-type-reference.html

There is many to one mapping between utterances and intent. There is one to one mapping between intent and function

There is many to one mapping between utterances and custom slot. There is one to one mapping between custom slot value and argument value to function. 
So one can pronounce "A.C" or "Air Conditioner" still it maps to same enumarated value as argument to function. Such synonymous are detected using "Entity Resolution" 

The back-end function can be implemented at any HTTPS terminated end-point or AWS lambda service. The AWS Lambda service, at present, is available only for regions: 
1. US east North vergina
2. EU (Ireland)

The professional skill can use session attribute for better user experience and also for data analytics. 

step 6. The response can be 
6.1 Speech : SSML, Local lingo, TTS, audio stream, small mp3 files
6.2 Cards = title, subtitle (skill name), text (content), image. 
Cards are optional. We can use rich text with different font including Unicode at card. It is built using various BodyTemplate and ListTemplate. 

The speech output goes to speaker. The card output goes to 
1. Alexa Companion App
2. Echo Spot and
3. Echo Show

One can check device capability for including card/video in response. 

The Alexa skill can be built using pre-built models

1. Custom: For unique need
2. Flash briefing : For RSS feed
3. Smart Home : For home automation
4. Video : For video application

Questions - Answers

Let me highlights few leanings about Alexa Echo eco-system and the devices

* The Alexa companion app can be connected to only one device. So it is not possible to push same image/content/card to all companion app running on mobile using single Alexa device
* Amazon allows to use same invocation word for multiple skill developed by same/different people. All such skill can be configured for given device. However the skill that is configured last, it will be invoked for the duplicate invocation word. 
* It is possible to enable/disable specific app on the device using mobile app
* It may possible to develop smart home device using Raspberry Pi for single user, with skill that is not published. One can use Smart Home pre-built model. Let the Intent invoke code running at Raspberry Pi, that turn on/off home appliances using GPIO pin and relay. 
* None of the Alexa devices has built-in battery. 
* "Alexa for Business" can have features like allowing access to very specific limited set of skills only. 
* Alexa does not have any adult content, so parental control is not needed. 
* One can change wakup word and replace "alexa". However still it will be female voice only. The Alexa devices do not support response in male voice. 
* Alexa device cannot be used for dictation or speech to text conversion. One can use AWS transcribe service https://aws.amazon.com/transcribe/ for the same.  
* One can develop (1) one shot dialogue (2) multi-turn dialogue skills
* To design multi-turn dialogue skills, one can use (1) graph UI or (2) frame UI. 
* Alexa can prompt for missing slot
* Amazon is coming up with Notification, that will be triggered by skill to Alexa device. However until the end-user ask to get notifications, the Alexa device will not start talking by itself to inform about notification. 

URLs

Now, let's have a look to important URLs

alexa.design/guide : Design of Voice Experience 

alexa.design/indiacheckin :Join the Amazon developer community & check in for the event in India. 

alexa.design/india : It has details about all meetup, hackathon, webinar, slack channel etc.

alexa.design/codecademy  and alexa.design/training : Online learning resources

alexa.design/factskill and bit.ly/2JWxlY9: Getting started with skill development

https://github.com/alexa : Alexa public sample code repository

https://developer.amazon.com/en-in/alexa-skills-kit Getting Started in India

Alexa response can be further enhanced at skill using

1. SSML. SSML is Speech Synthesis Markup Language. More details:

https://en.wikipedia.org/wiki/Speech_Synthesis_Markup_Language
https://www.w3.org/TR/speech-synthesis11/

Alexa specific SSML : https://developer.amazon.com/docs/custom-skills/speech-synthesis-markup-language-ssml-reference.html

2. Speechcon https://developer.amazon.com/docs/custom-skills/speechcon-reference-interjections-english-india.html

Reference

Sohan Maheshwar
@soganmageshwar

sohanm@amazon.com

https://www.slideshare.net/AmazonWebServices/alx326applying-alexas-natural-language-to-your-challenges
https://developer.amazon.com/blogs/alexa/post/5b0efd02-0ed0-42d5-b922-5ee594d30a38/new-alexa-skills-kit-template-build-an-alexa-decision-tree-skill

https://www.slideshare.net/AmazonWebServices/alexa-bootcamp-skill-building-101
https://www.slideshare.net/RickWargo/how-to-build-an-alexa-skill
https://www.slideshare.net/AmazonWebServices/wks403-build-an-alexa-skill-using-aws-lambda-78928075
https://medium.com/tribalscale/getting-started-with-voice-faqs-from-our-partnersby-tribalscales-voice-experts-fd5edec6f042
http://www.smith.co/blog/2017/CAFFEINATED-COMMERCE---EPISODE-3-TESTING-CONVERSATIONAL-USER-INTERFACES