blogs - Mantra AI

Top 6 technology disruptors for 2018

An industrial revolution (it is official to call it Industry 4.0) is on our way. This time it will be technology that will drive this revolution. AI and IOT will be central to almost every application. This revolution will completely transform the way economy is generated. Most of the contemporary technologies will be replaced by the technologies that were envisioned a decade ago and have matured to the level that they can be adopted by this year of 2018.

The six trends in technology that have entered into the innovative products after a volume of skepticism in 2015 – 2017, and providing a strong competitive advantage to those who are using it, are introduced and summarized. The use of these technologies today will have a huge impact by 2020-2021.

1. Digital twins:  

According to a report by Gartner, 50% of large companies will use digital twins by 2021 and this will lead to acquiring 10% more efficiency in their operations. It’s not that it. There is huge IOT, and AI driven process modeling application in making a digital twin. It Will let us store our physical assets in a digital world. The real objects will have a ‘data-alternative’. The physical asset is represented by the huge amount of data it generates. With this, the real physical asset and the digitally stored asset, they both supplement each other.

2. Edge computing:  

Will free the congestion in data networks. This is one of the top priorities for the digital transformations in 2018. More awesome things are getting connected every hour, crowding up the place where data lives and moves, and the data they generate are causing congestion in their connectivity graph. Edge computing uses IOT to connects the physical world with the cloud. The data is processed close to the component instead of travelling all the way up to the cloud. The components can include DSL boxes, Wifi routers, base stations, field devices etc.

3. Immersive experience:

Takes AR and VR to a matured evolution where the experience is extended to immersion. Creating experiences where the audience is truly immersed is now focus of the music, education, gaming, restaurants, events, aerospace, education, risk control and fitness industries in 2018. Immersive experience changes the way we interact with everything by converting the AR / VR space into a 3D space. Gartner predicts that by 2019, 20% of big corporates will adopt immersive experience for their customers and also to improve business efficiency inside teams. By 2020, the quality devices, tools and, systems will be very easily available, making space for massive penetration of immersive experience.

4. Blockchain IOT(BioT):

Will provide a secure mesh network and make provisions for the threat-free creation of reliably interconnected IoT networks. The Blockchain is a security method that lets the distribution of data on the internet but does not allow a copy of the same. In fact, the distribution of blockchain is a type of internet that cannot be corrupted. The agriculture and manufacturing industries, which have remote centers have already started using blockchain to secure their IoT infrastructure. Blockchain in IoT eliminates the need of a central server. 
According to IDC, by 2019, 20% of all IoT networks will have a deployment for the blockchain. The convergence of blockchain and IoT have created markets for using blockchain outside cryptocurrencies. This convergence is the solution to IoT challenges. Platforms to build blockchain IOT applications are IBM Watson IoT, Flowchain and, NetObjex.

5. Prescriptive analytics:

Comes as a final stage in understanding a business. In past, predictive analytics was used by many organizations to improve their processes and customer experiences. Organizations are spending on creating prescriptive analytics teams in 2018. Most handy application in which prescriptive analytics is used is deciding to price. Some of the platforms for prescriptive analytics are IBM Prescriptive analytics, NGData, LIONoso. However, independent AI teams are also working to create algorithms for a better prescriptive analytics.

6. FinTech:

Will become biometric. By 2016 – 2017, the mobile transactions grew rapidly. The payments were open to the blockchain. This year, the fintech industries are looking to make shopping biometric-enabled. The facial recognition, voice ID and fingerprints will eliminate the need to swipe cards and will make payments quick. In retinal payment, the payment can be made by scanning retina in a phone. After retinal payment, the payment can be done by cryptocurrency that makes transaction settled in no time.


All of these trends for this year within Industry 4.0 open for large potentials when deployed perfectly. However, there are possible problems like government regulations, distribution of internet and customer’s habits. The solution to these problems will be open for innovation.


Benefits of AI in Insurance

Insurance sectors are increasingly investing in latest technologies in order to improve their customer experience. According to the new report by tractica the investment in AI applications has increased from $3.2 billion in 2016 to $89.8 billion by 2025.

            “Artificial Intelligence Software  Market to Reach $89.8 Billion in Annual Worldwide Revenue by 2025”

Applications of Artificial Intelligence in the insurance industry will change the way companies carry their business. AI applications such as Machine Learning, Robotic Process Automation (RPA) Text Analytics and Natural Language Processing (NLP) has an impact in the insurance field.

Machine Learning:

Machine learning algorithms play a key role in all business areas from product design, sales to services and settling claims. Machine learning in the insurance industry is also useful in fraud detection, risk evaluation and identifying cross-selling opportunities. Some use cases are telematics, Customer engagement, claim management.

Text Analytics and Natural Language Processing (NLP):

Customer experience and customer engagement have been the key business trends in insurance companies. Digital technologies have offered a variety of options to improve the customer engagement and experience.
Text analytics and Natural Language Processing (NLP) have redefined self-service capabilities and are taking customer engagement to the next level.
Customer apps are now equipped with AI-powered chatbots that can hold meaningful conversations with consumers to understand their needs and address them. Mobile Apps, Chatbots are some key elements to improving the customer focus issues highlighted earlier and these can be assisted by AI to provide customized experience to individuals.

Robotic Process Automation(RPA)

Many insurance companies are adopting automation technologies to help them streamline their business processes and to get more clients on-board. If we talk about great automation properties then what else could be better than robotic process automation(RPA). RPA can provide added support to help insurance companies automate entire workflows and to reduce the work pressure of an Insurer. It provides an end-to-end automated solution for business problems. Automated underwriting and customer experience are some of the examples of RPA.

Insurance expert’s view on how AI will impact the insurance industry by 2025

Jack M Cordes, Principal Agent @BridgeFirstInsurance says-
“AI can help with tedious data collection to generate quotes as well. This will free time up for agents to handle more complex questions and focus on their true value-added benefits like strengthening client relationships, understanding their clients’ needs and proposing solutions”

What is your take on AI will either significantly alter or completely transform the overall insurance industry by 2025? We would love to know your views, write us at or you can write us in the comments below.


AI predictions: How AI is expected to evolve in 2018

The major changes coming in Artificial Intelligence in 2018 will be results of the continued expansion of artificial intelligence into realms of human cognitive work.

One of the most exciting tech developments of 2018 is the new breed of commercial AI that is emerging to meet the more complex demands of modern human-machine interactions. Most of the current AI offerings on the market have substantial limits. Even when models can accurately predict outcomes, they are still far away from providing any actionable suggestions for alternate outcomes.

The first step is to enhance the big data and machine learning with another layer of AI functionality – that of cognitive intelligence. The aim of cognitive intelligence AI platforms isn’t to supplant big data or machine learning. Rather, it’s there as a supervisor of sorts, monitoring how traditional AI process data, filling in gaps and identifying misinterpretations. Ultimately, the goal of a cognitive AI platform is to be able to complete tasks without the need for human supervision, to be able to quickly process unexpected or unfamiliar external input and adjust its response accordingly. Wherever it is used, cognitive intelligence will be the true watershed AI.

1. Smart IoT – Connecting and optimizing devices, data and the IoT.

2. AI-Enabled Cybersecurity – Data security encryption and enhanced situational awareness. Provides document, data, and network locking using smart distributed data secured by an AI key.

3. Next Generation Search – Intent and reasoning based search that produces the highest accuracy and relevancy results.

4. Content AI – Personalized media delivery & content monetization.

5. Intelligent Assistants – The solution continuously learns and reasons, becomes smarter and can simultaneously integrate location, time of day, user habits, semantic intensity, intent, sentiment, social media, contextual awareness and other personal attributes.

6. Cognitive Analytics – Advanced and deep analytics and insights.

7. Intent-Based Natural Language Processing – Moving beyond word template matching to user intent.


AI can bring a high quality of change to our lives. We’ve already seen how robotics can replace the physical work done by human beings – consider driverless cars, automated checkout lines, predictive healthcare. Hopefully We’ll get to see more from this year.

Thank you AJ Abdallat, CEO of for providing your inputs on this.


Image detection and Augmented Reality tools

The ongoing hype regarding Augmented Reality has sparked an interesting conversation about the possibilities of Image detection. After Facebook F8 conference and Google I/O 2017 it becomes inevitable among tech giants to get in the game.

Though the VR has been available to everyone (Thanks to Google’s Cardbox), the concept of AR isn’t yet prominent among the public usage. When you think of Augmented Reality, one of the key elements to consider is object or image recognition technology, also known as Image detection.

Recently Microsoft with its Holo lens and Apple with it’s AR Kit spiked interest among everyone by instating it’s the future of the current technology.


Let’s have look at a couple of Augmented Reality frameworks for better understanding.



Kudan is a framework which works on marker less version of AR. With Kudan, whether it’s a Video, 3D Render or a Transparent Video, all you have to do is set it up with the related image as a trigger. You won’t need to go through the hassle of learning of another framework or programs such as Unity. Have a look at this example, the link of the video.

It also includes KudanAR toolkit for converting 3D object formats to ARModel format for the use. This tool kit supports 3D object formats such as FBX, OBJ, DAE which are pretty much easy to render in most of the tools available nowadays.

One good part about this framework is the media which is viewable from different angles and auto resumes when displaced and replaced on the trigger.


Vuforia has one of the best trackings and augmented solution out there. Vuforia we can use when we have to detect an image and have to show some 3D object and after that to play with that 3D object. For example, To build an app in which you have to detect an image and in that position, you want to show a lamp with on off feature and color change of lamp feature. Link to video.

From my experience, Vuforia is easy to make a marker, add a target with the marker on the scene and make whatever AR object(3D object should be in OBJ or FBX format.) you want to associate with the target as a child of the image target object.

Unity is a cross-platform game engine is used to develop games and Augmented reality apps. We can develop high-quality 3D and 2D games using unity.

One downside of the Vuforia is the lack of marker less AR support.

Both of these frameworks come with free developer license and have extensive usages and flexibility for the development. In the end, the selection of the framework to use depends on the flexibility, comfort and the requirements of the developer and the application.

Do you have any suggestions about what AR might be useful for? Please leave a comment!


The Five Myths of AI


Debunking AI Myths – AI is lot more than Algorithms and Robots

AI the complicated yet lucrative technology, the need for many and known to few. While AI is everything from machine intelligence to technology, it also has some common misconceptions like AI is the only solution that your industry needs or AI can think and reason by itself or how about AI is the next generation of the human machine? Which one do you believe?

Let’s dive in to clear off the dust from the myths that prevail about AI. Are you ready?

Myth One – AI is synonym to Algorithms

AI cannot work unless the data provided to them is structured, parsed and accurate. For example, a hypothesis that existed quite earlier that if we allow two different language dictionaries to talk we may create a translator. However, the execution only could happen when the two dictionaries were termed as big data, structure it and mash them to provide accurate results. So now if we have the algorithm to convert from Spanish to English but the data inputted is German and English it is bound to go wrong.

Myth Two – AI is to replace humans

Be it your marketing strategy or your virtual assistant, all solutions in the modern world could be AI enabled, but it never means they would lack the human touch. While automation and AI could replace human for less skilled jobs like folding papers or cleaning bin, a place for qualified and experienced professional still exists.

Myth Three – Moving things like Robots are AI

Do you think Drones or HDFC bank IRA is an AI solution? Well, these are a just machine that could move and work as expected from their design like Robotic assistance for Ira and travel for drones.

Myth Four – An AI solution could solve all your business problems

AI is not a magic wand that could eradicate all your problems from the design process to its delivery and maintenance. Well, AI could help at each stage but what is necessary to look for the quantity and quality of data at these steps, feed it to the algorithm apply some human intelligence and then get your problem solved.

Myth Five – AI solutions produces results instantly

How much time do you think you would take to learn two languages? Or how about a calculation of –

Courtesy – Softpedia

We are sure unless you are a great mathematician or a person with superb IQ you would need to work on it step by step. Similarly, AI tries to match human cognition that means training about data, building models and finally optimizing the algorithm. So, do not expect results to be quick.

However, the question yet remains what type of future do we need to build with AI? Self-destructive weapons or Self Treating Clinics? Super humans or Job Automation? Will the intelligent machines supersede us or coexists in harmony? Only time can tell

Reference Links:


Why use Python? : Advantages and features of Python

Python is a general-purpose language, which means you can build anything with the right tools and libraries. It is a dynamic, object oriented and multipurpose programming language which is designed to be easily learn, use, and to enforce a clean and uniform syntax.

Professionally, Python is great for backend web development, data analysis, artificial intelligence, and scientific computing. Many developers have also used Python to build productivity tools, games, and desktop apps.

Some of the biggest advantages are

  • Easy to Read & Easy to Learn
  • Very productive or small as well as big projects
  • Big libraries for many things

Some Key Features

1. Dynamically typed:

No need to ‘type declaration’ of a variable. Instead, you have variable names, and you bind them to entities whose type stays with the entity itself. a=5 makes the variable name ‘a’ to refer to the integer 5. Later, a= ‘hello’ makes the variable name ‘a’ to refer to a string containing “hello”. Statically typed languages would have you declare ‘int a’ and then a= 5 but assigning a= ‘hello’ would have been a compile time error.

2. Strongly typed:

It means that if a = “5”(the string whose value is ‘5’) will remain a string, and never coerced to a number if the context requires so. Every type conversion is explicitly done in Python.

3. Object Oriented with class-based inheritance:

Everything is an object (including classes, functions, modules, etc), in the sense that they can be passed around as arguments, have methods and attributes, and so on.

4. Multipurpose:

it is not specialized to a specific target of users (like PHP for web programming). It has extensible modules and libraries, that hook very easily into the C programming language.

5. Indentation:

There are no control braces in Python. Level of indentation identifies the Blocks of code. Although a big turn off for many programmers not used to this, it is precious as it gives a very uniform style and results in code that is visually pleasant to read.


 Precompiled code is portable between platforms. The code is compiled into byte code and then executed in a virtual machine.

What is Python Programming Language used for?

Users can easily use Python for small, large, online and offline projects. The best options for utilizing Python are web development, simple scripting, and data analysis.

Below are a few examples of what Python will let you do:

Web Development:

You can use Python to create web applications on many levels of complexity. There are many excellent Python web frameworks including, Pyramid, Django, and Flask, to name a few.

Data Analysis:

Python is the leading language of choice for many data scientists. Python has grown in popularity, within this field, due to its excellent libraries including; NumPy and Pandas and its superb libraries for data visualization like Matplotlib and Seaborn.

Machine Learning:

What if you could predict customer satisfaction or analyze what factors will affect household pricing or to predict stocks over the next few days, based on previous years data? There are many wonderful libraries implementing machine learning algorithms such as Scikit-Learn, NLTK, and TensorFlow.

Computer Vision:

You can do many interesting things such as Face Detection, Color detection while using Opencv and Python.

Internet Of Things With Raspberry Pi:

Raspberry Pi is a very tiny and affordable computer for education. It has gained enormous popularity among hobbyists with do-it-yourself hardware and automation. You can even build a robot and automate your entire home. Raspberry Pi can be used as the brain for your robot in order to perform various actions and/or react to the environment. The Possibilities are endless!

Game Development:

Create a video game using module Pygame. Basically, you use Python to write the logic of the game. PyGame applications can run on Android devices.

Web Scraping:

If you need to grab data from a website but the site does not have an API to expose data, use Python to scraping data.

Writing Scripts:

If you’re doing something manually and want to automate repetitive stuff, such as emails, it’s not difficult to automate once you know the basics of this language.

Browser Automation:

Perform some neat things such as opening a browser and posting a Facebook status, you can do it with Selenium with Python.

GUI Development:

Build a GUI application (desktop app) using Python modules Tkinter, PyQt to support it.

Rapid Prototyping:

Python has libraries for just about everything. Use it to quickly built a (lower-performance, often less powerful) prototype. It is also great for validating ideas or products for established companies and start-ups alike.

If you are new to programming, Python is the perfect choice for learning quickly and easily because the community provides many introductory resources.

You can get the detail list of organisations using Python is here


Amazon Cognitive Services

Amazon has launched three new cognitive services

  1. Rekognition – Object and facial analysis
  2.  Polly – Text into Speech
  3. Amazon Lex – Chatbot for voice and text


Amazon Rekognition is a service that makes it easy to add image analysis to your applications. 

 Four functions are provided in this API:

  • Object and Scene detection: Rekognition identifies various interesting objects such as vehicles, pets, or furniture, and provides a confidence score.
  • Image Moderation: It detects adult content in the image and provides suitable labels for the adult content detected.

          Cons : Does not classify images with violence/bloodshed as adult content.

  • Facial Analysis: You can locate faces within images and analyze face attributes, such as whether or not the face is smiling or the eyes are open with certain confidence scores.



  • Face Comparison: Rekognition lets you measure the likelihood that faces in two images are of the same person. Cons: The similarity measure of two faces of the same person depends on the age. Also localised increase in the illumination of face alters the results of face comparison.


Amazon Polly is a service that turns text into lifelike speech. Polly lets you create applications that talk, enabling you to build entirely new categories of speech-enabled products. 

  • 47 voices and 24 languages can be used and Indian English option is provided.
  • Tones whispering, anger, etc can be added to particular part of the speech using “amazon effects”.
  •  We can also instruct the system how to pronounce a particular phrase or word in a different way. Ex : W3C pronounced as World Wide Web Consortium. We can also give the input text in SSML format.

Amazon Lex is a service for building conversational interfaces into any application using voice and text.

Cons: There is no synonym option and there is not so proper entity extraction and intent classification. 

 Note: Amazon has not launched speech to text conversion API so far.


6 biggest keynotes from Apple’s WWDC 2017


Keynote event of Apple’s Worldwide Developer’s Conference (WWDC2017) where announces happened about iPhones, MacBooks, Apple TV, and more. News about what Apple’s doing with macOS, its hardware, iOS 11 and big features like augmented reality or launching a smart speaker.

Here are some highlights:

Apple Watch – OS 4 has Siri

An update for the Apple Watch is coming which introduces new faces that display different types of informations, such as

  • Automatically displays information based on routines and apps that you use. uses machine learning to display relevant alerts on the watch
  • Personalised activity notifications based on your exercise patterns.
  • Creates personalised goals and challenges for somethings you could not do earlier or came close to finishing

MacOS High Sierra

The latest version of macOS will be called High Sierra, and it comes with updates such as

  • Safari browser- help block site trackers
  • Control over autoplaying videos and  ads
  • Cookies to avoid being tracked.
  • Better search
  • Photos – added new photo-editing tools like curves, it has better filtering tools to sort images by keywords or faces.
  • Advance neural networks used for facial recognition.
  • Supports VR content creation libraries, SDK and engines.


  • Messages are on cloud and allows p2p payment integrated.
  • Siri  has deep learning with multiple ways to speech capabilities.
  • Allows translation of language.
  • Allows security while driving with drive mode using the  doppler bluetooth and wifi readings, intelligently identifying when you are driving to stop notification alerts.
  • Camera is improved with capability of having AR. able to identify surfaces and add objects to it. the objects interaction is taken care of like shadows based on added lights


It has predictive area that identifies what application you may want to use next. This is based on machine learning about your usage of apps searchable handwritten notes. The OS recognises what is written and allows searching wishing handwritten notes.


It has spatial recognition to allow the music quality to be updated based on the room it is being used in . Support of Siri and base home kit allows you to control home kit devices remotely.


iOS 11

You’ll be looking forward to in iOS 11

  • Now you can type to Siri in latest version
  • Create and capture GIFs now
  • Redesigned podcast app
  • QR code support

Stay tuned for more updates.


Difference between Face Detection, Face Recognition and Facial Analysis

Artificial Intelligence(AI) attempts to create a machine that simulate human intelligence to identify and use the right pieces of knowledge at the time of decision-making and solving problems. It deals with computational models that can think and behave like the way humans do.

Computer Vision is a super exciting part of Artificial Intelligence where we attempt to get intelligence out of visual data. Intelligence can be scene/object detection, face detection, face recognition, facial analysis.

Common misconception regarding face detection is to be highlighted. To be exact, let us try to understand the computer vision terms nicely.


1. Face Detection : Finding the faces (any) in an image/frame. It does not care about “whose face “. It just counts number of persons in the given image/frame. To know the number of persons in a conference/store, it can be used.

2. Face Recognition: Recognizing the face in an image/frame. It identifies/recognizes the face that face belong to X person. When you upload a picture on Facebook, you get recommendation regarding tagging your friends or yourself. That is the face recognition capability of Facebook.

3. Facial Analysis: Analysis of face in terms of age-group, sex, expression etc. It can help you know detailed information about your customers in a store if you use this capability.

Amazon (AWS) has launched Amazon Rekognition API to perform the above activities. IBM Watson offers visual recogntion API to perform the similar activities whereas Microsoft Azure has Face API to do it. There are other companies (service providers) that can offer the similar services in customized manner. Please explore and get the best out of the latest technologies.

Please feel free to share your comments.



7 best reasons to adopt Blockchain in your business

Blockchain has been in news for more than a couple of years. Many companies have gone ahead with the idea of implementing blockchain. Recently, Finance and supply chain companies have shown special interest in understanding and implementing blockchain. Other sectors including government bodies have shown interest in adopting blockchain. Even Dubai has shown keen interest in implementing Blockchain for all government activities.

Blockchain is the public ledger (and distributed database) that keeps records of transactions(between two parties transparently), called blocks, chronologically and publicly that is why it is transparent and immutable. Due to the peer-to-peer network and the distributed timestamping server, the public ledger (database) is managed autonomously. Smart contracts, automatic transactions etc can be easily programmed for fast actions.

Blockchain can be used for creating and maintaining these


A. Digital currency to be used in e-commerce, remittance, micro-finance and other similar contexts.


B. Smart contracts to be used in online shops, government and non-government deals


C. Securities to be used for debt,equity , crowd-funding


D. Record keeping to be used for hospitals, government bodies, voting, real estate and intellectual properties


You may be curious to know why you should implement Blockchain. Here are the reasons.


Reason 1 : Decentralized : It offers decentralization ( peer to peer networks). So, it is a good idea to go beyond paradigm of central system for anything and everything.


Reason 2 : Simplified Ledger : As all the transactions are added to a single ledger (blockchain), it avoids complications of multiple ledgers.


Reason3 : Less prone to viral attacks : Due to the decentralized networks, blockchain can easily withstand malicious attacks due to lack of dependency on the central system


Reason 4 : Fast : As the blockchain is programmatic, it takes a few moments to execute the transactions.


Reason 5 : Transparent and Immutable : Any change in public blockchain can be easily viewed by miners. so any transaction can not be altered or deleted.


Reason 6 : Automated : Since the details of contracts, deals, currency are well defined in programmatic eco-system, transactions are automated.


Reason 7 : Affordable : Unlike costly transactional costs offered by any central system such as banks, it can provide an eco-system of quite low transactional costs.

Ethereum is an open source, blockchain that anyone can use it as decentralized ledger. Corporates support for the Enterprise Ethereum Alliance (EEA).


Hope you have got some take-away points. I wish you the best for continuous learning.

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