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June 2020 - Page 3 of 5 - anteelo

Here’s how AI is transforming business processes

Business process are transformed through AI

The rise of artificial intelligence (AI) to drive business value has been truly incredible in recent years. Enterprises that recognize the power of AI and know how to effectively apply it to their business can reap significant rewards in a quickly evolving and hyper-competitive marketplace.

Just a few years ago, analytics was all about gaining insights from data to help make better business decisions. More recently, enterprises have been seeing massive benefits from adding AI to the analytics mix that is designed to transform and strategically influence business processes. The effective application of AI within business process transformation can produce many benefits including more efficient operations, faster delivery and reduced costs.

But how is AI actually helping companies transform business processes?

There are two primary ways AI is doing this today.  Some enterprises are actively implementing AI programs company-wide as part of their core functionality. And there are other companies that are building AI into their business in a sequential, controlled way via managed proof-of-concepts (POCs) to address particular aspects of their operations.

Artificial Intelligence Is Transforming Business

AI is specifically used as a tool to speed up the corporate buying process. It does this in two ways: by making recommendations of suitable suppliers who should be invited to a tendering process and by quickly sifting through dozens of supplier submissions and creating a ranking system to identify the best supplier agencies for bespoke projects. This type of accelerated procurement can shave weeks off the selection process and additionally save up to 20% on project budgets.

On the other side of the spectrum is a large UK retail chain with thousands of stores across the country. This company is implementing AI in a controlled way through their corporate transformation department and rolling it out to each store. The retailer is conducting live trials of the system and can conduct A/B testing for different approaches for 10% or 20% of their stores from the get-go, which did not happen before.

This retailer is seeing success by implementing AI to assist with critical business functions such as setting prices and managing stock. AI is taking on the work previously performed by humans, including analyzing pertinent purchasing data to set prices intended to keep products flying off the shelves and boost profit margins.

From the two cases above, we’ve seen that currently the best performance in AI applications is achieved when AI is combined with humans; where AI does the core number crunching and recommendations and humans oversee the process. This helps humans concentrate on fine-tuning and making improvements on those initial recommendations.

Time and budget savings are achieved during the corporate buying process due to the presence of AI. And for the retailer, cost savings are clearly achieved as AI does the routine processing work that was previously performed manually by humans.

These uses of AI yield fewer mistakes and demonstrate how AI can support efforts to optimize spend, ultimately impacting the bottom line. For both companies, AI is the go-to solution for solving business problems.

Humans will always have a place in transforming business processes, that goes without saying. But AI is quickly becoming an invaluable automation tool to drive efficiencies and reduce costs.

Still No viable method of transporting data from autonomous cars tests

Driverless Cars

Behind the scenes at locations around the world the auto makers are running tests on autonomous cars for literally thousands of hours. The industry has poured more than $80 billion into R&D on autonomous cars over the last four years, so they are serious about making this happen.

Those of us working on these tests have one overwhelming challenge: how to manage all the data that gets generated during the tests. One eight-hour shift can create more than 100 terabytes of data. In a week of testing multiple cars, we’re talking about petabytes of data. And often — at rural testing centers, for example — Internet bandwidth speeds are simply insufficient to ensure that the data reaches our data centers in North America, Europe and Asia at the end of the test day.

Autonomous car

Right now, we have two main ways to transport data back to a data center. They are both cumbersome, but have different plusses and minuses. Until advances in technology make these challenges easier to manage, here’s what we do today:

  • Connect the car to the data center. Test cars generate about 28 terabytes of data in an hour and it takes 30 to 60 minutes to offload that data by sending it to the data center over a fiber optic connection. While this is a time-consuming option, it remains viable in cases where the data gets processed in somewhat smaller increments.
  • Take/ship the media to a special station. In many situations the data loads are too large and the fiber connections unavailable (e.g., at geographically remote test locations such as deserts, ice lakes and rural areas) to upload data directly from the car to the data center. In these cases we remove a plug-in-disk from the car and take it or ship it to a “Smart Ingest Station” where the data is uploaded to a central data lake. Because it only takes a couple of minutes to swap out the disks, the car stays available for testing. The downside of this option is we need to have several sets of disks, so compared to Option 1 we are buying time by spending money.

In three to five years we may get to the point where both options are outmoded by advances in technology that make it possible for the computers in the car to run analysis and select the needed data. If the test car could isolate the test-car video on, for example, right-hand turns at a stop light, the need to send terabytes of data back to the main data center would be alleviated and the testers could send these smaller data sets over the Internet.

Of course, we’re several years away from having such a capability. In the past year, IBM and Sony have been working on a 330 terabyte tape drive that promises faster and more resilient data storage in a form factor that can fit in the palm of your hand. Once such products are commercialized, it should make our lives a bit easier.

Ultimately, we’d like the ability to move our various equipment easily in and out of hotel rooms and carry it on plane trips in our pockets or briefcases. Today, the equipment is often clunky and hard to move around. While technology can help, we have to be realistic and understand the data challenges surrounding autonomous cars are likely to increase exponentially.  The challenges may grow, but at least sometime soon the gear we use won’t be so cumbersome that our muscles ache at the end of the day.

Businesses develop their next iOS apps using Swift 5- Reasons

Why should Businesses develop their next iOS app using Swift 5 | infotech.report

Swift is a highly intuitive programming language for Apple’s operating systems like iOS, macOS, and watchOS. The programming language has been growing in popularity and it can be attributed to its unique and valuable features. Swift is a widely used language for iOS app development globally. The iPhone app development platform has evolved considerably in the past. After going through four massive version updates, Swift released the latest two versions, Swift 5.0 and Swift 5.1. The remarkable functions of both these versions play a significant role in strengthening the language. The programming language is poised to become a game-changer in the mobile app development industry, with its latest version, Swift 5.

Whether you want to grow your business as an entrepreneur or looking for ways to scale as a startup, Swift offers you all the advantages of developing the best in class, highly functional and completely customised iOS applications. That’s one of the reasons why LinkedIn, Lyft and others have upgraded their iOS mobile application in Swift.

Let us first look into what both these versions have to offer. Then, we’ll look into Swift 5 features that make the updates an ideal choice for iOS app development companies.

What was introduced with Swift 5 Update?

Apart from the revolutionary ABI stability, the Swift runtime is also now added in the present and future Apple platform’s OS versions: iOS, macOS, watchOS, and tvOS.

Swift 5 features also come with a plethora of new capabilities that act as the building blocks of Apple’s vision and give a new direction to the advantages of the swift programming language.

*For in-depth insights, head on to Swift 5 release notes.

Language Updates

1. Binary Compatibility and a Stable ABI

Shipping Binary Frameworks With Swift 5.0 | Square Corner Blog

ABI was declared stable for Swift 5 app development. As a result, Swift libraries have been incorporated in every iOS, tvOS, watchOS, and macOS, which was earlier a problematic element whenever engineers had to develop apps for iOS. The applications will now be easier to develop and much smaller in size since they will not include any libraries.

2. Standard Library Updates

On the future of Windows 10's feature releases | Computerworld

Swift 5’s standard library comes with the following new feature set:

  1. The string has been reimplemented with the UTF-8 encoding which results in faster code.
  2. Better support for raw texts in the string literals.
  3. The SIMD vector and Result types have been added.
  4. Performance improvements in Set and Directory.
  5. Enhancements in String implementation, giving flexibility for constructing text from data.

3. Additional Compiler and Language Updates

Swift mobile development facilitates exclusive access to the memory, both for debugging and releasing builds. It supports dynamically callable types which help in improving interoperability with dynamic languages like JavaScript, Python, and Ruby.

It also implements these language proposals:

  1. Handling future enum cases
  2. Literal initialization through coercion
  3. Introduce user-defined dynamic “callable” types
  4. Supports ‘less than’ operator in the compilation conditions
  5. Identity key path
  6. Flatten nested optionals emerging from ‘try?’

4. Package Manager Updates

Bro Package Manager - Icon Clipart (#5076022) - PikPng

The Swift Package Manager comes with a series of new features in the Swift 5 app development version, which includes: Dependency mirroring, customized deployment targets, target-specific build settings, and the capability to generate the code coverage data. In addition to this, the swift run command includes a capability to import libraries in REPL with building an executable.

Swift 5 also implements these Package Manager proposals from Swift evolution process:

  1. Dependency Mirroring
  2. Platform deployment settings
  3. Target specific build settings

What was introduced with Swift 5.1? 

Swift 5.1 grows on the strength of Swift 5 with features like module stability and other new features that extend the ability of language and standard library like: opaque result types, property wrappers, new APIs for String, diffing for appropriate collection types, etc.

Together, Swift 5.1 makes it easy to design APIs and lower the common boilerplate code.

Here are the features that Swift 5.1 comes with:

1. Module Stability

Family house clipart 7 » Clipart Station

Swift 5.1 makes it possible to create binary frameworks which can be shared with others who leverage language’s added support for module stability. This, in turn, makes it extremely convenient and speedy for developers to develop apps for iOS.

It defines a new text based module interface file which describes the binary framework API, enabling it to get compiled with codes with the help of different compiler versions.

2. Standard Library Updates

C Standard Library PNG Images, C Standard Library Clipart Free Download

The Swift 5.1 standard library comes with the following new features, making it extremely easy to understand how to make apps with Swift 5:

  1. Support for updating and handling diffs on the collection of appropriate types.
  2. Greater flexibility for initialization of an array.
  3. APIs for working with Strings – developing and handling contiguous strings, helper for working with Unicode text, and general initializers for Range and String.index.
  4. Identifiable protocol for extending reductions, vector swizzles, and vectors.

3. Language Server Protocol

Language Server Protocol - NSHipster

The Swift 5.1 OSS toolchain packages for Ubuntu and macOS include binaries for the SourceKit-LSP, which is an implementation of LSP for C-based languages and Swift.

4. SwiftSyntax Updates

What's new in Swift 5.0 – Hacking with Swift

It has been re-architecture with a separate focus on improving the performance by using a parser from the Swift compiler. Additionally, the performance of the syntax tree visitation and its related operations have been improved through the re-architecture of internal data structures.

5. Additional Language and Compiler Updates

Android Developers Blog: New language features and more in Kotlin 1.4

Swift 5.1 comes with these new language features:

  1. Property wrappers introducing consistent context for defining the custom access patterns for property values like – delayed initializers, thread-specific storage, atomic operations, etc.
  2. The return keyword is not needed for single expression getters or functions.
  3. Self can be used for value types and classes.
  4. The compiler synthesizes default values for the properties with default initializers.

How do Businesses benefit from it? 

Although the majority of the features introduced with Swift 5 and Swift 5.1 are in favor of Swift app builders, some of them can be translated into business benefits as well.

One of the key features that directly impact businesses – the one that the Apple industry had been waiting for since Swift 1.0 – is ABI (Application Binary Interface) stability.

Hacking with Swift Live 2019

While sounding much like a developer’s problem, what this means in practicality is that Apple couldn’t include Swift programming language support in the operating systems, because an app written in Swift 2 couldn’t run with Swift 3. Simply because it wouldn’t work with the language support binaries of Swift 3.

The solution that was available to the developers was to include the Swift libraries in the app bundle which would get downloaded from the App store. This, in turn, increased the size and the storage requirement of the application. And became one of the biggest disadvantages of the swift iOS programming language.

But with Swift 5 making ABI stable, the industry has now received a permanent solution to these user-side issues. It would enable the developers to run the application in all the upcoming Swift versions. Meaning, the code is written in the Swift 5 app development process will run on Swift 6, 7, and so on, an event that makes Swift a preferred language for Enterprises and Startups.

This move is speculated to be the one that would bring language several strides ahead in the Swift vs Objective-C comparison.

Here are the business benefits of the Swift 5 update:

  • Smaller app size: Swift 5 makes the language binary compatible. Meaning, the end result of Swift mobile development would be significantly smaller for the users to run on their new operating system – iOS 12.2, watchOS 5.2, macOS 10.14.4, and tvOS 12.2.
  • Faster Launch: Another advantage of this is the faster launch time, since every dynamic library which is used by an application (which increases the launch time) will be cached in the memory and shared among the applications.
  • Greater Performance: Users do not want to work in a broken application. And with app freeze and glitches being the biggest reason behind app uninstallation rate, it is imperative for a business to avoid it. The Swift 5’s ABI stability helps apps in behaving better and offering enhanced performance.

But.

How small is too small? Let’s answer through the help of some live cases of Swift app development for iOS –

  • Apollo for Reddit: comes with an app size of 35.7 MB. Here, the 7.5 MB is made up of Swift libraries. Now when the app gets updated to Swift 5, the size will be reduced by over 20% and come around at 30 MB.
  • Chirp an app that brought Twitter to Apple Watch comes with a size of 28.8 MB, which is inclusive of 11.6 MB made of Swift libraries. This, when updated to Swift 5, gets reduced by over 30%, bringing the size down 20 MB.
  • Readability: One of the key reasons why it is best to choose Swift is due to its readability. It is relatively easy to modify, read and write and the clean syntax renders it a special uniqueness. It requires a lesser number of lines of code than Objective-C when compared to Swift apps.

Apps created with Swift not only decrease the development cost but also the development time.

In a blog post talking about the future of Swift language, Donny Wals said, “Now that we have Module Stability and ABI Stability in Swift, the language is likely to change at a slower rate than we’re used to. We should see less radical, source-breaking changes and the language should slowly mature into a beautiful, fast and stable language that will be a great basis for your applications for years to come.”

Is it good to build an app in swift 5? Yes. The time is right for businesses with iOS apps to get the code re-written in Swift 5 and for new businesses to build apps on Swift 5 and benefit from the impeccable user experience.

Why Use WordPress? An in-depth look at 7 compelling reasons

What Is the WordPress Admin Dashboard? (Overview and Tips)

WordPress remains the single most popular way to build websites and for business owners, it offers a multitude of highly useful tools to improve the way your website functions. What’s more, it’s free to use, easy to manage and its popularity means there’s an encyclopaedic knowledgebase online to help you with every aspect. Here are the reasons why it is the number one choice for business.

1. Easy setup

What is WordPress? What Can it do & Is it Right for You? A Beginner's Guide

Business owners don’t want to waste time getting their website set up, there are much more important business-focused tasks to achieve. If you are looking to get to market quickly and without the need for technical know-how, WordPress is ideal. Setting it up is usually just a simple, 3-step process: open a hosting account with a reliable web host, register your domain name (i.e. your website name) through your host, log into your hosting account’s control panel and install WordPress.

Once you’ve done that, your website is created – all you’ll need to do then is pick the best theme and create the pages you want on your site. All of this can be done in a user-friendly interface and there’s no need to know any coding.

2. Versatile WordPress is suitable for all business sites

29 Best WordPress Multipurpose Themes (2021)

Unlike Magento, which is purposely created for eCommerce, WordPress is highly versatile and can be used to create websites for any kind of business: online stores, estate agencies, membership sites, professional services, building and other trade sites, venues and events, blogs, wholesale, you name it.

Indeed, there are plugins available that can help you add the specific features you need to create specialist types of website, such as the free and very useful WooCommerce plugin which is used to create online shops and other eCommerce stores.

3. Dedicated WordPress hosting

Shared vs Dedicated vs Cloud Hosting for Faster Websites

For your WordPress site to perform at its best you need high-performance, reliable and secure web hosting. However, as WordPress has its own quirks, not all hosting packages are configured to provide optimal performance. For this reason, many businesses opt for dedicated WordPress hosting where the hosting set up is designed around the specific needs of the WordPress platform. This helps it load faster, handle more traffic, prevents issues that cause downtime and makes it less vulnerable to intrusion. It often has WordPress preinstalled too, so you have everything you need to get going the first time you log in. Few other platforms have their own, dedicated hosting solutions and this makes it another reason to choose WordPress.

4. Huge range of website themes

44 Popular Multipurpose WordPress Themes 2021 - Colorlib

Being unique is what will set your brand apart from your competitors and so having a website that has your own identity clearly stamped upon it is key to attracting and retaining customers. One of the very best things about WordPress is the thousands of free themes you can choose from to create different types of website. For many, the problem is not that you can’t find the right theme but that you are spoiled for choice when it comes to making the final decision. If you are still stuck, there are thousands of paid-for themes available from developers across the internet.

Themes come with a wide range of colour schemes, fonts and layouts to help you create the perfect site and each individual theme has its own range of options and special features. You can also customise your themes to make them work better for your business.

5. An SEO-friendly platform

WordPress SEO Made Simple - A Step-by-Step Guide (UPDATED)

Search engine optimisation (SEO) is key if you want your website to perform well in search engine results. While SEO is an ongoing task, WordPress has many built-in features, such as the way it structures websites, which help your pages to perform better. Additionally, there are some professional standard SEO plugins that can help you implement highly effective SEO strategies. One of the most popular and highly regarded is the free Yoast SEO plugin that can help with both on-site and on-page aspects of SEO.

6. Unparalleled functionality

Achieving Unparalleled Business Growth, WP Engine, and HubSpot

A plugin is a piece of software which provides additional functionality to your WordPress website. With nearly 55,000 free plugins available directly from your website’s dashboard, you can add every conceivable type of feature to your website – whether that’s analytics, security, email marketing, sales features, eCommerce, SEO, image optimisation, the list goes on.

No other platform comes anywhere close in regard to the number of plugins on offer, and perhaps even better, you can install them with a single click.

7. Built-in and bolt-on security

Data centre security: from bolt-on to built-in - The Digital Transformation People

Having a secure website is essential, not just to prevent your site from being hacked or infected but to protect the data your customers share with you and to help you stay compliant with the many regulations that website owners have to follow, such as PCI DSS or GDPR. It is good news, therefore, that WordPress has plenty of security features to help your site stay safe – some which are built-in and some which you can bolt on through the use of a plugin.

You’ll find that the WordPress core is regularly and automatically updated whenever a patch has been created to deal with newly discovered threats and that plugins are updated regularly for the same purpose. It is also possible to set up automatic plugin updates so you don’t leave your site vulnerable.

Conclusion

34% of the world’s websites are built with WordPress and it’s used by brands such as Facebook, Microsoft, Mercedes-Benz, BBC and Bloomberg –  just to name a few. Why do these leading companies use it? Certainly not just because it is free. Far more important are the amazing things that WordPress is capable of and this is why it is still the number one choice for businesses, large and small.

Five essential pillars of AI-enabled business

Artificial Intelligence (AI) in business

Successful AI implementations rarely hinge on the unique innovation of a specific algorithm or data science technique. Those are important factors, but even more foundational to successful AI enablement are the core data operations and enabling platforms. These act as the fuel and chassis of the AI machine that a business must build and evolve for continued competitive advantage.

Here are the five foundational elements to be addressed to enable a successful transformation to an AI-empowered business:

1. Define an integration strategy for embedding AI and analytic insights into business operations

Successful digital transformations focus on evolving and optimizing business operations through the better use of data assets combined with modern technologies such as machine learning, AI, and robotics. These paradigm shifts result in the creation of new operating patterns rather than simply more efficient legacy operations.  In this way, digital transformation represents the enterprise operations in the way the business wants to be run, rather than the way it has been running due to technical and operational limitations and barriers constraining it.

To go beyond siloed or single-use insights and fully benefit from AI and analytics, it must first be decided how the business desires/needs to function in the future.  Determining your business transformation priorities then evaluating the advanced technology and data science options for addressing them is a key step towards maturing and evolving to a data-driven enterprise. This understanding will identify the type of AI and analytics that will be the most beneficial for your business and the technology required to accomplish it.  Additional thoughts on overall data strategy can be found in the white paper “Defining a data strategy: An essential component of your digital transformation journey.”

AI in business

2. Establish a holistic data and analytics platform

Selecting and configuring an integrated set of technologies to support data management and applied analytics is a complex challenge. Fortunately, solutions to such technical integration have matured in recent years into pre-built core platform components and best practices that can be accelerated and augmented further through value-added third party software and partner services.

Cloud-based modular platform environments bring together technical flexibility and financial elasticity with an ever-maturing technical set of capabilities, including interoperability across hybrid environments that include legacy on-premises deployments and geographical federation. In addition to open source components, such platforms include the option to integrate select native modules and commercial technology components for broader flexibility and a customizable architecture that can be deployed as prebuilt services for simpler adoption and integration.

The tools to support and enable AI integration into business operations are beginning to leverage the same capabilities they enable. For example, data pipeline tools are beginning to use machine learning (ML), metadata tools are using AI and ML to identify content and auto-generate the metadata on the fly, and user interfaces are embedding chatbot and digital assistant AI technology to guide end-users through the complexities of data science for accelerated insights.  By adopting toolsets and platforms that have embedded AI and analytics in their core, the use and integration of AI into business operations will be more natural and accelerated across the enterprise community.

3. Know your data

Fully understanding the data your enterprise has access to may seem like a fundamental need when supporting operational reporting and analytics within the enterprise. Many organizations, however, stop with simple source systems listings and maybe some high-level business definitions and schemas.

Truly knowing your data includes a lineage-based view of where the data comes from and what business process it represents, what operations are performed on it prior to your access, what transformations are performed thereafter, the associated level of quality and, of course, the core “Vs” of big data; volume, velocity, variety, veracity and value.

Building an easily searchable, enterprise-wide data catalog of information is one of the first steps towards empowering the enterprise with data. Exposing the catalog to a crowdsourced editing model ensures richer content and wider adoption of such information across the enterprise.

4. Control and govern your data

Understanding the types of controls and governance your data needs is a natural extension of knowing your data.  By reviewing the types of data and their business content with associated metadata, enterprises can align and define proper governance and compliance policies related to internal policies and to external standards such as HIPAA for healthcare, PCI DSS for secure payments, and PII and GDPR for data privacy.

It is also important that source data retains its original state integrity without over processing or over-filtering it. Aligning to the data pipeline workflow principles of “ingest, refine, consume” allows the same data to be leveraged efficiently for different uses with different policies and operational needs while ensuring security.  Such controls can also be extended to support and define quality standards required for using the available data and to trigger any necessary control processes to correct or adjust for deviations in such standards.

You can safeguard proper policy compliance, improve ease of use and increase trust and adoption by the end user community by ensuring that governance controls are built into your data management operations from the start.

5. Simplify access to your data

To further expand the adoption of AI and analytics, it is important to simplify and automate data workflows and the use of analytical tools. Reducing manual process overhead can significantly improve time to market and quality of results. Providing clear and flexible governance allows enterprises to control such access without it becoming a barrier for use.

Self-service leads to rapid user community adoption and better integration of data and insights into business operations. By reducing the dependency on IT resources for complex data integration and preparation tools, average business users can interact with the data through simple common interfaces and receive results in simple and easily consumable formats.

 

Once these foundational elements are in place, organizations can take full advantage of the unique value proposition offered by advanced analytics and AI. And they can do so with the confidence that the resulting solutions are enterprise-grade in their scalability, security, quality and usability. It is this kind of confidence that leads to business user adoption and, in turn, successful digital transformation.

Hiring Challenges in Design Studio and How to Solve them

Hiring Challenges in Design Studio

Being an HR is one thing but being an HR in a design studio is a different ball game altogether. And, if you are hiring for the stream of UX and UI in India, the most sought-after skill today, well buckle up, it is not going to be an easy ride. But, after reading this article, I am sure you would be well prepared.

Fairly disrupted industry w.r.t. Quality vs. Cost

The first step for every HR is understanding the market space and expectations to chalk out an in-house budget for each role. But, like every other industry, this would not be an easy task. Since the industry is fairly new, you would come across many expectations that are exuberantly high as compared to experience. The best way to go about this is defining budgets based on your company’s standards and later it would just be a matter of finding a suitable candidate.

A readily available portal for hiring designers

We all are extremely used to various hiring portals that provide us with a varied number of services, but, in this industry, you must create your own channel. Use your networks, be more responsive and visible, visit design colleges and make ample use of references. This would definitely save a lot of your time and energy. Basically, keep your antennas switched on always!

Outstanding communication skills

This would come as a surprise but there will be instances where you would fall in love with designer’s creativity & skills but would be in two minds because communication would not be their strength. It’s advisable to chalk out the level of communication required for each role and your new team will be joining in no time because not every role calls for exceptionally good communication.

Designers are always BUSY

This is an amusing trait, you would find thousands of applicants but the ones who are willing to prove it out to the world and ready to go that extra mile is comparatively less. If your selection criteria demand’s some time off their current lifestyle don’t be disappointed if you do not receive a lot of responses. In fact, this would serve as an amazing yardstick in filtering out candidates.

Start-up Culture & Design Studio Culture – It’s Lethal

Most of the dedicated design studio in India are in Start-up phase and we all know that the culture is already laid back with a lot of flexibility. But, design studio goes an extra mile here because designer’s function differently and they are disciplined in their own way. But, sadly rest of the world does not function like this. So, hiring the right attitude and character becomes absolutely critical; next time when you are out on a look for some designer make sure this is always ticked off.

MeWe App Development and Determining Its Cost

How To Determine The Cost of MeWe App Development?

When it comes to social media networks, Facebook is certainly one of the most popular choices available. However, a lot of people who care about their privacy have been looking for an alternate, and that’s where MeWe comes into play.MeWe’s CEO, Mark Weinstein, in his Wall Street Journal op-ed, wrote, “MeWe is a full-featured social network engineered with privacy-by-design that’s freemium-based with no ads, targeting or news feed manipulation. Marketers and election meddlers cannot target or boost anything to anyone. These are significant competitive differentiations.” Weinstein also adds that, “It’s gratifying to see MeWe flourishing worldwide. MeWe is the uplifting social network with the features people love, and the respect, control and data privacy we all deserve.”

Technology is taking social media by storm, let’s see the most buzzing social platform that is taking the internet and individuals into a completely new and safe arena.

What is MeWe?

MeWe - Apps on Google Play

MeWe is a social media network based on a subscription model that focuses on privacy. The MeWe site terms itself as a ‘Next-Gen Social Network’ by providing users an ad free experience.

It has become extremely popular as a business-focused product that takes enterprise networking and communication to a completely new level.

The application is found by Mark Weinstein, an entrepreneur who considered himself as one of the early developers of the concept of social media. As of now, the MeWe platform has millions of users and is thriving as a popular privacy-focused alternative to Facebook.

Earlier, Weinstein launched a company named Ello, and based on the challenges he faced during that time, he learned several lessons that allowed him to shatter the social media dominance of Facebook.

Although the platform is free to use for personal users with several features like 8 gigabytes of storage, customized stickers, voice and video support, and newsfeed, enterprises are required to pay $1.99 per month to access additional features.

Why There is a Need for MeWe App Development? 

It’s a no-brainer that Facebook is the most dynamic and popular social media network that has dominated the social cult ever since its initial launch. From job postings to community management, it includes a myriad of features that keep a user hooked and engaged to the app.

However as they made changes in their privacy policy, a lot of people started realizing that their privacy is being compromised by the platform.

According to their most recent update, Facebook has employed an algorithm that observes your behavioral patterns and deciphers them to serve you manipulated content in the application. This makes it more of a target-based platform that displays content as per your past preferences and choices.

In the wake of WhatsApp and Facebook data breach controversy, people are looking out for new social media platforms that are safe and secure. MeWe, a US based social network has come to the rescue and becomes the top downloaded social app in the Play store. MeWe app for android and MeWe app for iPhone has led to the increase of new users in the apps counting to more than 2.5 million users.

With the help of MeWe app development, you can keep your privacy protected by preventing targeting, ads, and political biases.

Essential Features in MeWe App Development 

Mobile App Development Company | Python Mobile App Development Experts

If you take a look at several social media networks available, you will notice that there are certain common features that each of them share. To be able to determine the cost of MeWe app development, you need to consider keeping these essential features in mind.

Moreover, as you introduce other specific features to your application, you will notice that the MeWe app cost will definitely bump further. With that said let’s take a look at some fundamental features required while developing the MeWe app:

What do you get with MeWe?

  • Profile creation 

Your application needs to provide users the ability to express themselves through their personal profiles. It includes allowing them to enter their personal details such as name, address, website, email, birth date, and even mobile number. 

  • Authorization 

A proper authorization mechanism acts as the foundation block of the privacy and data of your users. Therefore it’s certainly a must-have feature in your MeWe application. It involves letting users signup and login in to your platform through their phone numbers or email addresses. Additionally, it also requires a password recovery and reset mechanism, some security interventions, and several other features. 

  • Messaging 

As you’re trying to make MeWe social media platform you surely need to ensure that your users have a proper communication channel. Moreover, in addition to simply sending texts, you may also need to add the ability to send media files such as messages, videos, and stickers through chat. The development cost may even vary depending on whether you want to allow your users to have group conversations or not.

  • Search function 

To make the usability of your application easier for users, you need to include a search function that allows them to access the profile of their friends, communities of their interest, and posts they find engaging. 

  • User interface 

Apart from the crucial features, the design of an application is certainly one of the most important aspects because that’s what makes your creation unique. This may also be the costliest part of your MeWe social media app development process. While getting the user interface designed for your application, you need to make sure it looks attractive and provides an aesthetic feel to your users.

How is MeWe different from Facebook and Other Social Media Platforms? 

Unlike other social media apps, MeWe social app has a different concept which does not replicate every other social media site. The MeWe creator’s intent is very clear when it comes to marketing the platform, as it has been directly indicated in interviews that MeWe wants to be the alternative to Facebook.

This most likely clarifies why the site attempts to imitate Facebook’s UI. Users can offer thumbs up, hearts, and smiley icons to posts. They can share their posts on their different feeds. There are user profiles and separate pages, and groups feature for individuals to assemble around a particular theme or topic.

The below image will show you which are the top categories and apps used by users.

Determining The Development Cost

When you’re developing an application like MeWe, it’s evident to say that there’s no specified cost associated with it. The expenses that you may incur depend on the functionality, complexity, and comprehensiveness of your application.

Moreover, if you’re outsourcing the development part, the MeWe app development cost becomes majorly dependent on the social media app development company you hire. On the other hand, if you have an in-house team of social media app developers, you need to keep their salaries in mind while determining the estimated development cost of your application.

Additionally, as you keep adding more features, the costs will keep piling up. It’s also worth determining the total number of hours required to complete the development phase of your application, in case you hire social media app builders on the basis of hourly payment. Therefore, make sure you keep all these things in mind while determining the social media app development cost of your MeWe Application.

The Takeaway 

As Facebook made changes in its policies and tampered with its user’s privacy, people began looking for safer and more privacy-oriented platforms. This calls for the need for MeWe application development. While making an application like MeWe, you need to consider several things such as core features, UI design, and a lot more.

Additionally, to determine the costs associated with the development of this application, you may also need to consider several aspects like mode of development and required time. Hopefully, you may have found this guide helpful to come up with an estimated development cost for your application.

Still if you have any doubts, or are finding difficulty in hiring a social media app development agency in USA, just contact us.

 

Digital Technologies: Transforming pharma’s customer value chain

Biggest influencers in digital pharma in Q4: The top individuals to follow

Pharmaceutical companies struggle with a complex and, often, poorly managed partner, customer and distribution network. It’s not surprising, given the makeup of most large pharma companies. Large, often disconnected product portfolios are built through discovery — both internally and externally with academia and biotech partners — and global clinical trials, using a network of clinical research organizations, investigators, other experts and patients. Suppliers, distributors and often contract manufacturers are all integral to making and supplying products. And at the customer level, companies work with healthcare practitioners, pharmacists, payers and patients.

This web of partners and customers is growing in complexity — both logistically and from a compliance point of view. Yet this way of doing business remains the same. Communication and requests are conducted via email and through call centers without a connected and intelligent way of routing work and queries. Service level agreements are often poorly developed, and governance processes are often inconsistent across the distribution and customer ecosystem.

While different parts of the pharmaceutical business are deploying digital technologies, an opportunity exists to transform the customer and partner value chain with progressive digital tools and platforms. Customer service and support centers are now implementing artificial intelligence (AI) by analyzing both structured and unstructured data and also leveraging natural language processing (NLP) for omnichannel engagement models with the customers. But how is this actually achieved?

A single source of truth

Synchronizing systems around the customer for a customer-centric approach begins with bringing together data from disparate sources and creating a single view of the truth through a common data model. In this way, companies have a big-picture view of every customer service request, including the distribution chain.

Once the data is in place, the next step to improving customer engagement and ensuring regulatory compliance is to embed the common platform with digital tools and technologies. Combining NLP with AI, machine learning and workflow automation enables increased customer engagement with sound governance and improved compliance.

Digital solutions for the pharmaceutical industry

How do these digital technologies improve engagement and compliance?

Customer service support and the operations space have evolved over the years from a manual, labor-intensive and software-centered business model to a more dynamic multichannel customer engagement business model. This new model facilitates omnichannel engagement with the customer using multiple devices. AI- and machine learning-powered chatbots are being leveraged for quick response management, and digital capabilities are tightly integrated with intelligent workflow management tools.

For example, today a customer can raise a service request through an email, phone call or a text message, or even talk to a live chat agent. Digitally enabled customer service engagement centers can now seamlessly bring in the request from different channels into one homogenous customer engagement platform for action. From there, the request is processed using digital tools to identify the intent of the case or request — who it is aimed at, what the objective is – and to create groups in which to classify the case based on importance. This is achieved by using NLP to create an entity score, match this score with a subgroup and route it to the right place to ensure proper follow-up.

The customer may then choose to follow up with a phone call or through a chatbot or online feedback form. This is where an AI capability (or the more traditional customer service agent) should be able to view all of the various communication forms and frame the response accordingly.

To achieve this, AI and ML tools learn from previous interactions, continuously improving on the quality of responses. The AI learning also needs to extend to compliance, adherence to SLA guidelines, as well as any regulatory restrictions on what can and cannot be shared. For example, if a customer asks for the available stock of a particular drug, the pharma company is not allowed to address that question according to U.S. government regulations. So, the response needs to be framed appropriately. The rules will be different in each country, so the AI/ML-enabled automated response app should be able to learn and adapt accordingly.

Preconfigured responses based on the type of the request are then configured using data science and AI/ML techniques. AI and ML capabilities also help to determine the urgency or sensitivity of a case, and how best to ensure that compliance requirements are met within the timelines and SLA metrics.

In addition, analytics will play a key role in verifying, validating and improving customer service. Predictive models can be used to strengthen the human response team by understanding peak cycles, such as a new drug launch, natural disaster areas and so on.

By taking a progressive digital approach to managing the communication network with partners and customers, companies can mitigate many problems while improving customer engagement. This is enabled by having a single view of the customer, using robust data analytics capabilities thanks to AI and ML — to predict risk and compliance needs, and ensuring that the company is always ready for regulatory inspections and has the necessary information at hand. With the emergence of AI and ML techniques, it has become easier to achieve customer engagement needs with more enriched analytics and insights, thus allowing enterprises to not only automate customer engagements but also excel in customer experience.

Ways to better data processing in Self-Driving Cars

autonomous vehicle development

Autonomous cars promise to change the face of transportation, offering many more mobility options for individual motorists and companies alike. In moving forward with this new technology, our automotive clients have a very important challenge to overcome: processing the petabytes of data that gets collected during the development and testing of autonomous driving systems.

KPIs have always been important to car makers. They are necessary to attain road approvals and to track key competitive differentiators. With autonomous cars, however, car makers are accumulating – and must find ways to process and manage – 10, 20, sometimes 30 times the data as before.

As a result, they need much more efficient data analysis tools that can help them analyze the data for the specific autonomous car KPIs they are looking for. To make this happen, they need to take the following four steps:

  1. Make sure the car’s sensors are working. There are typically eight to 12 sensor systems in an autonomous vehicle test car. It’s important to look at the data at the very beginning of the workflow by checking the KPIs to ensure that the system works properly. Some of the KPIs car testers evaluate include the following: vehicle operations, safety, environmental impact and in-car network efficiency.
  2. Scale the workflow to process the data. Traditional architectures of automotive frameworks are not suited for the large-scale data processing workloads required for testing the algorithms used in autonomous car tests. In using traditional data storage methods, vehicle test data gets stored in NAS-based storage and gets then transferred to workstations, where engineers test algorithms under development. This process has two downsides:
    • Large amounts of data must be moved, requiring considerable time and network bandwidth.
    • Individual workstations do not offer the massive computing power required to return test results fast enough.

    Today, testers are extracting each frame of video data with its associated Radar, Lidar and sensor data by using open source Hadoop. The major benefit of Hadoop is that it scales processing and storage to hundreds of petabytes. This makes it a perfect environment for testing autonomous driving systems.

  3. Make the most of data analytics. In processing petabytes of automotive data, we have to look at how we present the data to higher level services. New data analysis tools can read different automotive formats to give us proper levels of access to the metadata and data. For example, say we have 700 video recordings, we now have tools that can pinpoint footage from the front-right camera alone to show how the car performed making right-hand turns. We can also use the footage to determine the accuracy of a model depicting the autonomous car’s perception of its ambient physical surroundings .
  4. Run the data analysis. In the end, we want to use data analysis tools to give R&D engineers a complete view of how the car has performed in the field. We want to generate information on how the systems will react under normal driving conditions.

Overcoming these data analysis challenges is critical. Manufacturers can’t obtain permits for releasing their cars until they can show that the cars performed up to certain standards in road tests. And when autonomous cars do start to hit the roadways in the next few years, auto manufacturers might need the KPIs they generated in testing. A few accidents are inevitable and, when questions arise, car makers can use KPIs to show the authorities, insurance companies and the general public how the cars were tested and that proper due diligence was performed.

Right now, there’s some distrust among the driving public of autonomous cars. It will take a massive public relations effort to convince consumers that autonomous cars are safer than traditional manually-driven cars. But proving that case all starts with the ability to process the data more efficiently

Autonomous cars promise to change the face of transportation, offering many more mobility options for individual motorists and companies alike. In moving forward with this new technology, our automotive clients have a very important challenge to overcome: processing the petabytes of data that gets collected during the development and testing of autonomous driving systems.

KPIs have always been important to car makers. They are necessary to attain road approvals and to track key competitive differentiators. With autonomous cars, however, car makers are accumulating – and must find ways to process and manage – 10, 20, sometimes 30 times the data as before.

self-driving vehicle technology

As a result, they need much more efficient data analysis tools that can help them analyze the data for the specific autonomous car KPIs they are looking for. To make this happen, they need to take the following four steps:

  1. Make sure the car’s sensors are working. There are typically eight to 12 sensor systems in an autonomous vehicle test car. It’s important to look at the data at the very beginning of the workflow by checking the KPIs to ensure that the system works properly. Some of the KPIs car testers evaluate include the following: vehicle operations, safety, environmental impact and in-car network efficiency.
  2. Scale the workflow to process the data. Traditional architectures of automotive frameworks are not suited for the large-scale data processing workloads required for testing the algorithms used in autonomous car tests. In using traditional data storage methods, vehicle test data gets stored in NAS-based storage and gets then transferred to workstations, where engineers test algorithms under development. This process has two downsides:
    • Large amounts of data must be moved, requiring considerable time and network bandwidth.
    • Individual workstations do not offer the massive computing power required to return test results fast enough.

    Today, testers are extracting each frame of video data with its associated Radar, Lidar and sensor data by using open source Hadoop. The major benefit of Hadoop is that it scales processing and storage to hundreds of petabytes. This makes it a perfect environment for testing autonomous driving systems.

  3. Make the most of data analytics. In processing petabytes of automotive data, we have to look at how we present the data to higher level services. New data analysis tools can read different automotive formats to give us proper levels of access to the metadata and data. For example, say we have 700 video recordings, we now have tools that can pinpoint footage from the front-right camera alone to show how the car performed making right-hand turns. We can also use the footage to determine the accuracy of a model depicting the autonomous car’s perception of its ambient physical surroundings .
  4. Run the data analysis. In the end, we want to use data analysis tools to give R&D engineers a complete view of how the car has performed in the field. We want to generate information on how the systems will react under normal driving conditions.

Overcoming these data analysis challenges is critical. Manufacturers can’t obtain permits for releasing their cars until they can show that the cars performed up to certain standards in road tests. And when autonomous cars do start to hit the roadways in the next few years, auto manufacturers might need the KPIs they generated in testing. A few accidents are inevitable and, when questions arise, car makers can use KPIs to show the authorities, insurance companies and the general public how the cars were tested and that proper due diligence was performed.

Right now, there’s some distrust among the driving public of autonomous cars. It will take a massive public relations effort to convince consumers that autonomous cars are safer than traditional manually-driven cars. But proving that case all starts with the ability to process the data more efficiently

Significance of “design for operations” approach for service-based IT

Service based IT companies

To deliver on digital transformation and improve business performance, enterprises are adopting a “design for operations” approach to software development and delivery. By “design for operations” we mean that software is designed to run continuously, with frequent incremental updates that can be made at scale. The approach takes into consideration the end-to-end costs of delivering and servicing the software, not just the initial development costs. It is based on applying intelligent automation at scale and connecting ever-changing customer needs to automated IT infrastructure. DevOps is the set of practices that do this, enabled by software pipelines that support Continuous Delivery.

 Design Operations

The challenge: Design for operations

Products and services pass through various stages of design evolution:

  • design for purpose (the product performs a specific function)
  • design for manufacture (the product can be mass produced)
  • design for operations (the product encompasses ongoing use and the full product life cycle)

Automobiles are a good example: from Daimler’s horseless carriage, to Ford’s Model T and finally to Toyota’s Prius (or anything else that’s sold with a service plan). Including the service plan means the auto maker incurs the costs of servicing the car after it’s purchased, so the auto maker is now responsible for the end-to-end life cycle of the car. Information technology is no different — from early code-breaking computers like Colossus, to packaged software such as Oracle, and then to software-based services like Netflix.

The key point is that software-based services companies like Netflix have figured out that they own the end-to-end cost of delivering their software, and have optimized accordingly, using practices we now call DevOps.

There are efficiencies that can be achieved only with software designed for operations. This means that companies running bespoke software (designed for purpose) and packaged software (designed for manufacture) have a maturity gap, where the liability is greater than the value. If that gap can be closed, delivery can be better, faster and cheaper (no need to pick just two).

It’s essential to close that gap, because if competitors can deliver better, faster and cheaper, that puts them at an advantage. This even includes the public sector, since government departments, agencies and local authorities are all under pressure to deliver higher quality services to citizens with lower impact on taxation.

The reason we “shift left”

A typical outcome of the design-for-purpose approach is that functional requirements (what the software should do) are pursued over nonfunctional requirements (security, compliance, usability, maintainability). As a result, things like security get bolted on later. In many cases, this lack of functionality starts to accrue as technical debt — that is, decisions that may seem expedient in the short term become costly in the longer term.

The concept of “shifting left” is about ensuring that all requirements are included in the design process from the beginning. Think of a project timeline and “shifting left” the items in the timeline, such as security and testing, so they happen sooner. In practice, that doesn’t have to mean lots of extra development work, as careful choices of platforms and frameworks can ensure that aspects such as security are baked in from the beginning.

A good example of contemporary development practices that support this is manifested when we ask, “How do we know that this application is performing to expectations in the production environment?” This moves way past “Does it work?” and starts asking “How might it not work, and how will we know?”

Enterprises need to adopt a “design for operations” model that includes a comprehensive approach to intelligent automation that combines analytics, lean techniques and automation capabilities. This approach produces greater insights, speed and efficiency and enables service-based solutions that are operational on Day 1.

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