The ‘ Software Development Kit(SDK) market’ study Added by Market Study Report, LLC, provides an in-depth analysis pertaining to potential drivers fueling this industry. The study also encompasses valuable insights about profitability prospects, market size, growth dynamics, and revenue estimation of the business vertical. The study further draws attention to the competitive backdrop of renowned market contenders including their product offerings and business strategies.
The research report covers an extensive gist of the Software Development Kit(SDK) market with regards to certain vital aspects. A brief synopsis of the business, in addition to the market share, growth potential, and an in-depth application spectrum are provided in the study. Also included in the report is a concise brief about the main manufacturers of this industry that accumulate the maximum returns. In essence, the Software Development Kit(SDK) market research report aims to provide a pivotal synopsis of the industry pertaining to current and future trends.
How will the report help prominent stakeholders & new entrants to appropriately plan investments in the Software Development Kit(SDK) market
The Software Development Kit(SDK) market report provides an intricate coverage of the competitive scenario of this industry. As per the study, the Software Development Kit(SDK) market share is controlled by companies such as
Apple Developer
UserTesting
Leanplum
Appsee
Instabug
Optimizely
Foresee
Stripe
Mapbox
.
Details about the distribution and sales area have been provided, in addition to important information such as company profile, product specifications, buyers, etc.
The report also enlists details pertaining to the overall revenue, sales of products, profit margins, and price prototypes.
What are the pivotal drivers and challenges of the Software Development Kit(SDK) market that are detailed in the research study
The report explores on the various factors that have been impacting the commercialization portfolio of the Software Development Kit(SDK) market and unveils what driving parameters will be responsible for influencing the industry trends in the future.
The Software Development Kit(SDK) market research study enumerates the numerous challenges that this industry is likely to encounter as well as the influence of these challenges on the market trends.
A vital parameter that this report covers is the market concentration ratio for the projected timeframe.
How has the geographical spectrum of this vertical been divided by the report
The Software Development Kit(SDK) market research report splits the regional landscape of this industry space into USA, Europe, Japan, China, India, South East Asia.
Details included in the report include parameters such as the product consumption spanning the various regions as well as the remuneration that these geographies account for.
The study delivers information pertaining to the consumption market share across these topographies as well as the market share accrued by each of these regions.
Not to mention, the product consumption growth rate is enlisted as well.
A concise elaboration of the segmentation of the Software Development Kit(SDK) market:
Pertaining to the product landscape, the Software Development Kit(SDK) market report segments the industry into
iOS
Android
.
Important information about the market share that each product type accounts for in tandem with the expected returns of the product segment in question are included in the report.
The research study is inclusive of information pertaining to the product consumption as well as sales.
The Software Development Kit(SDK) market, as per the report, has its application expanse segmented into
Phone
Tablet
PC
Other
.
The report delivers details about the market share that each of these applications hold as well as the target revenue of these segments.
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Technological innovation – most notably AI – is expanding the potential applications of automation to a wider range of tasks and job roles. For example, organisations are building Business Process Automation (BPA) into their operational strategy to remedy pain points in business areas such as marketing, sales and workflow, or Robotic Process Automation (RPA) to eliminate the need for humans to perform repetitive tasks. Ironically, the benefits of automation are even being applied to those we typically associate for building automated systems. As described by Andrej Karpathy, director of AI at Tesla, so-called “Software 2.0” will use automation to cause a shift in dynamic between developers and the machines they work on.
What is Software 2.0?
The current model of software development (Software 1.0) consists of programmers creating oft-repeated segments of code as a series of rules: if X happens then do Y. Software 2.0 will be based on a neural network that learns which instructions or rules are needed for a desired outcome, replacing the need for developers to “write” software with developers now focused on feeding data into machine learning systems.
A machine partner might determine what kind of function is being written and fill in the rest based on style, using high-level predictive analysis. Recent research findings in this area of program synthesisshow lots of potential. Essentially the machine writes the rest of the code, then the developer can adapt and approve it. Just like a smartphone uses machine learning to automatically check spelling and suggest a word, a similar tool can be used to highlight possible errors when writing code. Considering the advances in machine learning and conversational interfaces, it’s conceivable that a machine could one day be an indispensable member of a programming team.
How will it benefit software developers?
One successful approach to writing software is taking an iterative, test-driven approach. With AI-enabled Software 2.0, a human could write the tests while the machine partner searches for a suitable implementation, iterating millions of times to find the right piece of code to solve those tests. Instead of doing both jobs (i.e. writing the tests and making the pass tests) a developer constructs the former while a machine counterpart does the latter. As a result, less time is spent writing implementation code, freeing up developers to spend more time on identifying and understanding new areas in which business problems can be solved creatively through software.
Down the line, Software 2.0 might even help guide test-driven development and suggest the next test to be run, providing justifications along the way. Imagine marketing people go to the development team and say they want such and such functionality. If they can express what they want in a way the machine can understand, the machine could help choose the tests that are needed and then suggest next steps. This could help speed up idea-to-production cycles, improving business efficiency and the ability to respond to market changes.
What are the challenges?
Today, it’s clear that deep learning neural networks do well in supervised learning settings, if they’re provided training data with good examples and bad examples, they can learn what to output correctly. But those systems are only as good as the training data they’re fed. As a result, improving a model’s performance frequently involves not only improving the underlying code and deployment environment, but also improving the size and accuracy of the training data. The reality is that neural networks are not a silver bullet. Rather, we need to design neural networks to work with other solutions. There are certain parts of software development that will work well with deep learning, and there are other parts that won’t.
Collaborating with AI
AI-based automation stands more to help than to hinder software developers. As the effectiveness of pair programming shows us, software development is a process of constant collaboration with other colleagues. Every time a new pair comes together, the partners bring different experiences and different approaches to tackling a problem. With Software 2.0, a new partner is constantly available to help developers do their job better. This gives rise to a more energetic collaborative environment that leads to ever more effective solutions. And that’s good for everyone.
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Some of you got into software because your parents made you (if you grew up outside of the US) or because you figured you could make a lot of money this way. You didn’t start young because you were into computers, and you don’t really like software development. You’re always going to be mediocre. You’ll make money because our industry doesn’t know how to evaluate skill, talent, or achievement—but this article isn’t really for you.
If you got punished for taking apart electronics to see how they work. If you snuck online at all hours of the night to learn how to make a video game. If you spent precious free time learning when no one was making you and you weren’t actively pursuing a career. If you then found yourself in software as a career, this article is for you.
You need to change the way you think about your career. You’re not coding for love anymore; you’re coding for money. Save the love for your side projects. By all means, make sure you at least like your day job—even better if you love it. If not, find a better place while the economy is still hot.
However, your goal should be to open a 401(k), shove every tax-deductible dollar in it and still have enough left over to buy a house a car and do whatever it is you want to do. Otherwise, someone else is making your money.
Along the way, you need to think about your career, not just your current job. To do that you need to avoid these eight pitfalls.
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If you want to learn an in-demand programming language then Java has been a safe bet for many years.
As an enterprise mainstay and web fixture, Java is likely to remain popular among employers for a long time to come.
Though Java may have taken a hit on the mobile recently, with Google announcing it will prioritize Kotlin over Java when making tools and guides for Android developers, Java is still widely used for Android development.
It’s perhaps no surprise then, that Java is still ranked as the most popular programming language by the TIOBE index and as one of the programming languages most sought after by employers.
The pace of change in Java has also never been faster, with new releases of the language now being pushed out every six monthsand plenty of interesting changes in the pipeline, which will tackle everything from improving how the language handles concurrency to optimizing regularly called code.
There are plenty of free guides out there for learning Java, but if you’re looking for a place to start you could do a lot worse than GitHub, which has an array of tutorials, primers, and code examples.
Here are the 10 highest-ranked, English-language repositories on GitHub designed to help those learning Java.
1. Java design patterns
Design patterns offer a template for how to structure code for common software development tasks, based on years of best practice.
This repo provides diagrams illustrating how to implement a wide range of software design patterns in Java, with patterns classified as beginner, intermediate and expert difficulty.
Note, the author recommends reading up on software design principles such as KISS (Keep It Simple, Stupid) and YAGNI (You Ain’t Going to Need It) before delving into the design patterns.
2. Interview guide
Badged as “everything you need to know to get the job”, this overview of common technical topics has racked up more than 36,000 GitHub stars.
The repo offers a mix of text and diagrams explaining typical data structures, algorithms and more, as well as linking to useful books and tutorial videos. Even though it’s tagged as Java-related, the explanations would be useful to anyone learning about computer science.
3. The algorithms
Implementations of common sort, merge and other algorithms in Java, alongside one paragraph explanations, diagrams and demonstrations of the algorithms in action.
4. Android clean architecture
For those looking for guidance on using Java to build Android apps, this offers a sample application built using the clean code approach espoused by well-respected programming guru Robert C. Martin, better known as ‘Uncle Bob’.
The repo links to an accompanying walkthrough explaining the approach taken in more detail and a video showing the application in action.
5. A guide to Java 8
Java 8 may no longer be the most modern version of the language, but with so many developers and organizations still using it, this guide to the essentials should be useful.
6. Better Java
This opinionated list sets out the libraries, practices, and tools that the author perceives as most useful.
7. Android tips and tricks
A cheat sheet of advice for developers using Java to build Android apps, drawing on years of shared experience.
8. Awesome test automation
For those interested in test automation, this list rounds-up frameworks, tools, libraries and software that will come in handy.
9. Algorithms and data structures
An overview of how common algorithms and data structures are implemented in Java, alongside examples of how to answer interview questions.
10. Leetcode answers
Leetcode offers a platform for developers to hone their skills and to prepare for coding tests in interviews. This extensive list gathers up accepted answers to many different Leetcode challenges using Java.
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With developers accounting for some of the most in-demand job positions, companies should look toward these 10 countries for top talent, according to Diffbot.
Developers occupied nearly half of the job positions on Glassdoor’s most in-demand tech jobs of 2019. However, US companies are still facing a tech talent shortage when looking for quality software developers to join their teams.
This tech talent shortage has forced many US organizations to instead look overseas for necessary developer skills. To help guide companies toward top developers, artificial intelligence (AI) startup Diffbot compiled a list of the top EU countries with the best software development workforce.
Using the Diffbot Knowledge Graph, the report used 2.5 million records of identified skills to find the best locations with developer talent. Here are the top 10 countries in the EU with the best software developer talent:
Sweden
Netherlands
United Kingdom
Ireland
Finland
Denmark
Belgium
France
Italy
Portugal
Similar to the US, these foreign countries also have a tech gender gap. While the Netherlands was one of the top locations for software development talent, it also had the worst gender gap for software engineers, with men making up 74% of those in the field, while Ireland had the most even split, at almost 50/50 men/women, the report found.
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Website development is a crucial part of technological development. Websites give individuals and corporates a presence on the internet. The sites also act as platforms where different stakeholders can interact, exchanging products as well as ideas. With more people and companies moving to online spaces, it is no wonder that website development is growing in demand. Website development can be a tedious process, involving a lot of time as well as manpower. It is a process that often includes a lot of hurdles that need to be overcome in order for the website to work seamlessly. The coding process also has multiple areas that need to be taken care of before the website is up and running.
To make the website development easier, many programmers are now turning to PHP frameworks that make the process more efficient. These frameworks are designed to perform certain tasks during the coding process, thereby reducing the amount of work a programmer needs to put into the coding process. Even better, they come with in-built automated tasks to reduce on the number of codes that need to be developed when creating a website. Laravel development is an example of such a framework. It is increasingly being chosen over PHP frameworks for the following reasons.
User authentication
First, Laravel enables coders to input authentication features for websites and applications. Authentication plays a key role in securing personal information and company data found online. Laravel developer frameworks offer several authentication methods, allowing a programmer to choose one that fits that specific website perfectly. Examples include a feature that allows websites to ask users to re-enter their passwords again when trying to log in. For other sides, Laravel enables the website to send messages to their users, whenever the person’s details are used to sign in.
Mail communication services
Many online platforms are created to form spaces for interaction between different stakeholders. An example is online shopping websites where customers can shop and buy goods online. Many service providers also consider customer care integral to their businesses, and need a website that allows their customers to send them messages easily. These business owners can hire Laravel developer teams to help with this. Laravel has multiple mail services built for this exact purpose. The services make it possible for the website owner to receive messages as soon as they are sent by a client. This way, they can respond to the inquires immediately. Prompt and effective communication is at the heart of a great customer experience. This should not change just because a business decides to offer their services online.
Fast applications
Laravel also features multiple functions that are meant to make applications run faster. A slow application can often translate to poor customer experience, which in turn leads to reduced profits. This can prove very detrimental to business, beating the purpose of an online site in the fast place. Laravel frameworks are able to get rid of bugs that slow down applications. They also reduce website crashes, giving the site more stability even when it is receiving a lot of traffic.
Technical issues
The best Laravel developer clients also love the framework for being able to fix technical vulnerabilities within a website, during development. Such vulnerabilities include susceptibility to attacks by viruses. Viruses can slow a website down, lead to loss of information, as well access to confidential data by unwanted third parties. Laravel prevents this well in advance, allowing website owners to work safely.
Web errors
Configuration errors are bound to come up every so often when a user is interacting with the website. A good example is when they key in any incorrect information, meaning that a step by step process will not work as it is meant to. Such errors are very easy to correct because the client can easily be redirected and asked to provide the right details. This would only work on a website with the right configuration error set-up. A senior PHP Laravel developer would use the framework to create a redirection system for customers. In such an arrangement, a guide would pop up after a configuration error, prompting the customer to correct the problem. Without such an arrangement, customers will be at a loss on what to do when the error pops up.
Tests
There is also a need to hire teams for the purpose of testing if a website runs properly before it is launched. Laravel has automated testing features that are used during the programming process. They are aimed at fixing any errors and bugs before they begin to cause actual problems on the website. Without Laravel frameworks, the programmer would need to evaluate the entire code to make sure it is free of errors. Even then, there would be no guarantee that all the problems will have been fixed. Additionally, conducting a test run would be the only way to find out if the code actually works, and can sustain the website
Traffic control
Online consumer traffic is always fluctuating, but many business owners tend to experience an influx of customers at around the same period. Messages from the same customers will also be sent at around the same time, thereby increasing the chances of too much data being processed on the website at once. Laravel allows for controlled traffic flow, meaning that the data is processed in batches to reduce congestion. It also has important features such as mail scheduling, to be used when the business owner cannot respond to inquiries immediately they are sent.
Conclusion
All the above features can be created using codes, during the actual website development process. However, this usually involved a lot of hard work. In addition, the website developers might need to partner with other companies to get additional features for their sites. Laravel acts as a one-stop for all these solutions. The framework provides simple fixes that go a long way in making a website more efficient.In addition to making the coding process easy, it streamlines all the requisite procedures, making coding much less messy and consolidated.
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By the year 2025, Google predicts that the number of IoT and Smart Devices in operation will exceed that of non-IoT devices. Statista also predicts a similar growth pattern, in which the proliferation of IoT devices will be three times more than today’s usage.
Any way you slice it, the transformation to an IoT dominant world is going to cause a seismic shift in the way software is used, the way it’s made and the overall future of front-end software development. Soon enough, most computing activities will no longer revolve around the human-machine interaction. Rather, it will be about machine-machine interaction. And, of the human-machine interactions that remain, most will not involve a person that swipes a screen, clicks a mouse or types on a keyboard. Human-machine interaction will be conducted in other ways, some too scary to consider.
The days of GUI-centric development are closing. Yet, few people in mainstream software development seem to notice. It’s as if they’re the brick and mortar bookstores at the beginning of the Amazon age. As long as people kept walking through the door to make purchases, life was great. But, once the customers stopped coming, few were prepared for the consequences.
The same thing will happen to the software industry if we’re not careful.
And, unlike the demise of Big Box retailers — which took decades — the decline in the use of apps based on traditional GUI interactions might very well occur within a decade or less. Other means of interaction will prevail.
The shift to voice
In the not too distant future, the primary “front end” for human-machine interaction will be voice driven. Don’t believe me? Consider this:
My wife, who I consider to be an average user, no longer uses her phone’s keyboard to “write” SMS messages. She simply talks to the device. She uses WhatsApp to talk to her friends. She “asks” Alexa to play music. She still does most of her online shopping on Amazon, but I suspect once she learns how to use Alexa to buy stuff, her time spent on e-commerce websites will diminish.
She still has manual interaction with our television, which is really a computer with a big screen. But she uses the remote’s up/down/left/right buttons in conjunction with voice commands to find and view content. There’s no keyboard involved… ever.
Her phone connects to her car via Bluetooth. She makes phone calls via voice and controls call interactions from the steering wheel. If she needs directions to a location, she talks to the Map app in the phone which then responds with voice prompts.
On the flip side, each day I have a multitude of interactions with computers. And yet, those that require the use of a keyboard and mouse are confined mostly to my professional work coding and writing. The rest involves voice and touch.
In terms of my writing work, I find that I spend an increasing amount of time using my computer as a digital stenographer. My use of the voice typing feature of Google Docs and an online transcription service is growing. I too am becoming GUI-less.
GUI-less commerce
There’s a good case to be made that for the near future, there will still be a good deal of commercial applications that require human-GUI interaction. Yet, as the number of IoT devices expand, more activity will instead be machine-machine and not require GUI whatsoever. All those driverless vehicles, warehouse robots, financial management applications and calls to Alexa or Siri will just push bits back and forth directly between IP addresses and ports somewhere in the cloud.
But, the good news is that the foreseeable future of creative coding is still very much in the domain of human activity. However, this too is changing.
More machines make more software than ever before, and most machine-generated code is made with existing models. Thus, the scope of creative programming by machines is limited. Nonetheless, it’s only a matter of time until AI matures to the point where it will be able to make software from scratch and the software that humans make will be about something else.
Sadly, few people in mainstream, commercial software development think about what that something else will be. Today, front end still means iOS, Android or whatever development framework is popular to make those nice GUI front ends. Few people can imagine any other type for the future of front-end software development. Even the application framework manufacturers are still focused on the GUI world.
When was the last time you heard a tech evangelist caution their constituency about the dangers ahead? That the world soon won’t need any more buttons to click or web pages to scroll?
That’s like asking horseshoe manufacturers to warn blacksmiths about the impact of that newfangled thing called an automobile. It’s just not in their best interest. But, it is in our best interest because the future of front-end software development in the post GUI world will provide amazing opportunities for those with foresight.
The amazing opportunity at hand
There’s a good deal of wisdom in the saying, “once one door shuts another door opens.” Even the most disruptive change provides immense opportunity if you pay attention. Think of it this way, Amazon is killing brick and mortar retailers but it’s been a boon for FedEx and UPS.
There is always an opportunity at hand for those with the creativity and vision to see it. Fortunately, creativity or vision is in no short supply among software developers. We’ve made something out of nothing since the first mainframe came along nearly seventy years ago. All we need to do now is be on the lookout for the next opportunity.
The question is, what will that next opportunity be? What will the new front-end in human-machine look like? If I were a gambling person, I’d put my money on the stuff we might think is too scary to consider today: implants.
Let me explain: I have a dental implant where a molar used to be. Right now that implant is nothing more than benign prosthesis in my mouth.
But think about this: given the fact that computers continue to miniaturize, how far are we from a time when that implant will be converted into a voice sensitive computing device that interacts with another microscopic audio device injected beneath my ear? Sound farfetched? Not really.
Twenty years ago nobody could watch a movie on their cellphone. Today it’s the norm. As Moore’s Law reveals, technological progress accelerates at an exponential rate.
Regardless of whether the future of front-end software development is implants or something else, one thing is for certain: it won’t be anything like what we have today. Those who understand this and seize the opportunity will prosper. The others? Well, I’ll leave it up to you to imagine their outcome.
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inspired clone scripts. It offers hundreds of popular scripts that are used by
thousands of small and medium enterprises.
The use of open-source software has grown during the last decade. Open-source software itself has improved dramatically, offering comparable functions as professionally authored titles, as well as low up-front costs and creative features.
But while open-source systems have benefits, there are a number of sticking points to watch. To help your teams and leaders identify where trouble can develop — so you can best prepare, or go with a different system — I asked a panel of experts from YEC the following question:
What is a major challenge for using or starting to use open-source software in your business? How can savvy teams solve the issue?
Their best answers are below:
1. Security
Open-source platforms can increase the risk of security breaches. You should consult with an IT security expert before committing to an open-source platform. A security professional should be able to help install safeguards to protect your data and prevent a cyber attack on your business. – Matthew Podolsky, Florida Law Advisers, P.A.
2. Confusing Complexity
It can become so complex that it goes against the functionality you are trying to create. It helps to have a developer team that can work through all of the open-source work and systematically works on integrating what others are trying to do. Collaborating on these features and integrations also helps both our business and those we are trying to assist. – John Rampton,Calendar
3. Updates
Open-source software is accessible and easy to implement, but it also poses some challenges. For instance, this type of software does not have a vendor releasing updates. Instead, developers must seek them out. To ensure they do, leaders must implement governance programs that require IT teams to manage patch through and updates to ensure they remain secure and functional. – Blair Thomas, eMerchantBroker
4. Community and Licensing
Making sure the software is maintained and has a large community to carry on its support, is crucial. Savvy teams could research the software better to look at the community history and involvement and contributors to the project. Another thing to be aware of is open source doesn’t always mean that it’s free. Also, making sure the licensing agrees with your business model and use case is extremely important. – Ashish Datta, Setfive Consulting
5. Training
Open source typically doesn’t have as great a set of training manuals and resources as the paid-and-packaged stuff. It’s important to make sure that you are able to implement the right training strategy for your team when you are going this route. Not recommended for big teams, that’s for sure. –Nicole Munoz, Nicole Munoz Consulting, Inc.
6. Lack of Customer Support
One challenge we’ve found with using some open-source software is in the lack of customer support. Oftentimes, you’ll need to reference an online forum when it’s easier to get someone on the phone to help. One way that we’ve overcome the lack of human customer support is by seeking answers in forums and also contributing to those forums. If you’ve figured something out, share how and help someone. – Joel Mathew, Fortress Consulting
7. Mystery Sources
When using open-source software that you didn’t create, you run into a problem with figuring out which sources are making changes to the code you’re using. This poses a serious problem, especially for business owners, because with the use of some open-source software you could unknowingly expose your hard work to hackers and exploits. – Blair Williams,MemberPress
8. Compatibility
In addition to issues with certain closed-source programs not working well with open-source ones, compatibility can also be an issue when your company is staffed with professionals who aren’t familiar with the software in question that prefers a closed-source alternative. In both of these cases, there are no easy solutions: You just have to commit to the necessary changes to make it work. – Bryce Welker, Beat The CPA
9. Learning Curve
For business owners who aren’t especially tech-savvy, open-source software such as WordPress can sometimes come with a steep learning curve. So, before you decide to use open-source software, test it out first. Read some online tutorials to see if you can get a handle on it. Alternatively, you can also check to see if someone on your team is skilled with the software and have them teach you. – Stephanie Wells, Formidable Forms
10. Not Prioritizing a Policy
The first thing you need to do is outline a policy for your business or organization on your open-source usage. Without it, developers on your team will use any components that they choose, which could cause multiple issues down the line. Establishing a clear, written policy is the best way to ensure you don’t run into incompatibilities or issues later on. – Chris Christoff, MonsterInsights
11. Seeing the Big Picture
Open-source software is great for business and there is a ton of valuable software across all sectors. However, due to the complex nature of open-source software, it can be hard to step back and look at the big picture when you’re creating your website or using the software. You may have to practice with the software and view your results to grasp the big picture. –David Henzel, LTVPlus
12. Not Realizing the Cost
One of the appeals of open-source software is cost. However, many companies fail to calculate the time commitment necessary to run and maintain the open-source code. It often takes time to manage open-source software problems. To avoid this, teams should compare the net cost of supporting operating systems with commercial alternatives to ensure that they are getting the biggest bang for their buck — and time. – Shu Saito,Fact Retriever.
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A decade ago, when people spoke about connected vehicles, they thought it was just another fad. And today, we can see connected vehicles already plying on the roads with cars having algorithms that can take real-time decisions to make driving safer.
Increasing urbanisation and the growth of mega cities is set to change the way people move around very soon. Technological innovations such as autonomy, electrification, connectivity, and sharing are forcing the auto industry to rethink the way people commute.
“The software component in cars is going to be a trillion-dollar opportunity in the next decade. Each car will have a supercomputer talking to the infrastructure and other cars on the road,” says Elmar Degenhart, CEO of Continental AG.
When this happens, the future of mobility is going to be viewed very differently. If India can leapfrog these technologies, there can certainly be a revolution in mobility. However, one thing is certain, all automotive technology – at least the software component – will be built in India for the world. According to data from Continental the software part will be a $1 trillion opportunity by 2030. Currently, it stands slightly over $250 billion.
Here are some of the technologies that will be part of the future of mobility across the world.
Robo-Taxis
For large cities that are increasingly suffocating due to traffic congestion, robo-taxis offer an effective way of tackling the challenges of urban mobility.
Robo-taxis were introduced to help reduce traffic jams, accidents, air pollution, and to address the issue of parking spaces in cities.
According to a study by consulting firm Roland Berger, around one quarter of transportation tasks could be carried out by driverless vehicles by 2030.
After all, it is much smarter to operate less driverless vehicles on a near-continuous basis than to have countless private cars, which often sit in a parking space for long hours.
In addition, on campuses, amusement parks, and shopping malls, autonomous vehicles such as the “CUbE”, developed by German automaker Continental, could be used to reduce walking distances and to transport people.
To further advance the development of driverless mobility, Continental acquired a minority stake in the French company EasyMile SAS, a leading producer of driverless technologies and intelligent mobility solutions, in 2017. Continental is currently working on such mobility systems in the USA and Japan.
Similarly, Bosch and Daimler, which have a partnership to bring out autonomous vehicles in the next three years, have just been given a go-ahead by German authorities to test a fully autonomous parking valet technology. Both the companies are also working on robo-taxis.
Early this year, serial tech entrepreneur and Founder of Tesla Elon Musk also outlined his plans of launching robo-taxis next year. If Musk is to be believed, his company will be putting at least a million self-driving robo-taxis on the road in some parts of the US by 2020.
Blockchain-powered cars
Ethereum-based blockchain tokens are very popular with those who use crypto to trade items. The primary use case for blockchain is transparency, consensus, and a system of records. Above all, this works on decentralisation.
Now, companies such as Continental, Hewlett Packard Enterprise, and Crossroad.io have built a blockchain for data sharing with car companies.
So, here’s how it works. If you are driving through a new city, and don’t have required information of a particular route, you can make use of blockchain technology to connect to the cloud service of car companies operating in the area. These companies will then pull data from their customers driving on the particular route, and provide you with the details.
Individuals or drivers, who are fine with sharing their data, will provide details such as traffic jams and location landmarks. The data will be shared with a company like Continental, which will beam the data back to the person who has requested for it.
The payment made for subscribing that data goes in the form of rewards tokens to the drivers who provide the data. The drivers can then redeem these tokens on a blockchain exchange for normal or fiat currency.
“Sharing of vehicle data across vendors can solve some of the toughest traffic problems and improve driver experience by leveraging the power of swarm intelligence,” says Phil Davis, President, Hybrid IT, Chief Sales Officer, HPE.
“Together with Continental, we provide the key to unlock the value of this data treasure by not taking control of the data by ourselves, but by giving control to the drivers and car manufacturers,” he adds.
Apart from this, Bosch is working with an energy supplier, EnBW, on a prototype that uses blockchain technology to improve the electric car recharging process. The idea is to streamline and tailor the entire process to customers’ needs, so they can select, reserve, and pay for recharging services as they see fit.
For example, the operator can use the software to offer customers transparent pricing models, with options varying in real time, and according to the availability of charging stations.
The entire transaction – reservation and payment – will be a fully automated blockchain operation. This service can factor other customer preferences into the equation. For example, a customer who has kids and likes coffee could opt for a charging station with a playground and cafés nearby. Initial trials with this new system are underway.
A car that pays its own parking fees
To make parking less of a chore, Bosch and Siemens are jointly developing a second application, a smart parking-management system, based on blockchain. By making use of distributed ledger technology (DLT), cars will be able to communicate directly with parking facilities in their vicinity and negotiate the best terms.
As soon as the car reaches the entrance of a parking garage, it will identify itself at the entry barrier, which will then be raised without the driver having to remove a ticket from the dispenser. The driver will also be able to leave the parking garage without further ado, since the vehicle will have already communicated with the exit barrier and settled the parking fee in a virtual transaction.
At present, the prototype has been installed at Bosch’s Renningen research campus and at the Siemens campus in Munich.
Distributed structures
Distributed structures means data is decentralised. Rather than a few platform providers storing data in their data centers, here it is spread across numerous servers.
“To build trust in digital ecosystems, we need open platforms in which users have the power to decide for themselves,” says Volkmar Denner, CEO of Bosch.
This will ultimately benefit people. If users are “captive,” a web platform provider can change its terms of use at will. By gaining independence from the big internet players, users no longer have to blindly accept such changes.
“We are building trust in internet platforms with these distributed structures. They enable many players to participate,” says Michael Bolle, board of management member and CDO/CTO, Bosch.
Distributed platforms operated by an ecosystem encompassing numerous equal partners are also better protected against external attacks.
LED lights– Illumination to communication
While many people regard autonomous vehicles and electric mobility as the future of automotive industry, the automotive lighting market is also fast catching up.
For instance, Continental is exploring the future of modern lighting systems with its new joint venture – Osram Continental GmbH. While Osram supplies state-of-the-art lighting technology, Continental takes care of the electronics and software
“We have created a new company that will rethink the future of automotive lighting,” says Dirk Linzmeier, CEO of Osram Continental.
The first product to emerge from the development pipeline includes the Smartrix modules, which enable glare-free high beam light and dynamic low beam light, and laser headlights with a reach of 600 meters.
Another product is a system that can project warning messages while driving on the road. For example, if there is an alert telling the driver about an uncovered drain on the road, people can avoid driving through the drain, and also avert any accident.
Commenting about the future of mobility, Elmar says: “The future is already moving from electric vehicle technology to fuel cells, and we are looking at the impact of those technologies by 2030.”
A fuel cell uses chemical reactions to produce energy rather than using metals like lithium or lead that enable current battery technologies.
At least what is real is the software component that enables the bridge between all these technologies, which is a trillion-dollar opportunity according to all automobile companies.
This article is shared by www.itechscripts.com | A leading resource of inspired clone scripts. It offers hundreds of popular scripts that are used by thousands of small and medium enterprises.
Artificial intelligence (AI) and machine learning (ML) aren’t academic research subjects anymore. Businesses, especially the disruptors and those who are entrenched in digital transformation, have been setting a trend for the adoption of these principles and applying them to yield rich dividends. This trend is now rampant, and it is clearly a favorite when it comes to enriching customer experiences and using data to arrive at smarter decisions, faster deliveries and sustainable businesses.
But here’s the burning question: In a race to get their hands on new-age technology, are technology businesses overlooking the other perks of AI that can accelerate the speed of their IT operations and impact their entire software development life cycle? AI is not limited to automating workflows. When used well by your executive staff and system administrators, AI can make all lives stress-free.
Automating And Augmenting Your IT Department
Now, imagine having sophisticated monitoring and management tools in place that can enable a self-service IT infrastructure. Having infrastructure templates ready for configuration can give you the confidence to scale on demand to support an ever-increasing volume, variety and velocity of deployments. In that scenario, deployments will be as fun as making chocolates out of silicon molds. With AI, you can implement various tools to fit your varied needs, including those for data input and more. HCL Technologies, an Indian multinational company, said their ElasticOps applies AIOps to maintain their managed cloud infrastructure service (a 50,000-instance environment) with 30 engineers.
To name a few tools that can aid AIOPs, I’d start with the cloud. With AI, you can build an automated scaling solution for your cloud platform for future flexibility before taking it live. Monitoring tools can extract utilization metrics of live instances via APIs. Even further, incident management tools can trigger alerts and, in certain instances, pass a percentile threshold, causing pre-scripted response and escalation patterns to be applied, according to the situation. Through all this time, your metric analytics and visualization suite can generate reports based on actionable data. And, these tools don’t even cover half of what can be done with AI and ML during software development.
Managing Your Customer Experience
In addition, there are tools to implement that will help you manage your customer experience. This is particularly helpful, considering the deluge of data that flows in and out of your systems every second — with social media reactions, helpdesk complaints and more. Forward-thinkers can have an APM (application monitoring system) installed to provide real-time insights that help IT teams and the company to avoid revenue-impacting outages.
A few years ago, Netflix found a way to put several experimental machine learning algorithms to good use and started automatically recommending personalized content to subscribers. Their attempts to redeem viewership and constantly gain a new set of subscribers using AI and ML technologies have never let them down. Apparently, the world’s favorite video streaming platform saved and earned big bucks with all these initiatives.
Along the same lines, Amazon acquired Kiva to automate the picking and packing process in their warehouse. According to them, their click-to-ship time went from a peak of 75 minutes to 15 minutes.
To yield such best results, companies should strive for a conversational model that can drive self-service operations to a point where operations professionals can switch their focus to other strategic elements with the enterprise. With a proactive APM, along with automated remediation and declarative provisioning and deployment, employees can address build-level failures, manage pipelines and releases and apply guided code fixes.
Automation: Is It All Or Nothing?
All of this said, the rule of thumb here is that you should never try to automate functions if they aren’t (at least) 80% stable and unchanging. Otherwise, you’d need human interference each time there is a new scenario that requires a change in your scripts. This is not nearly as productive as you’d like it to be, as script maintenance is a huge cost to your company.
When there is a shortage of talent that can draft clear and precise test cases, when there are not enough datasets to train your algorithms continuously, when buying or building the required AI system costs more than the anticipated value or when your functions specifically need general intelligence to address emotional factors, it is nearly useless to bring in AI.
An ideal set of AI solutions will automate your mundane tasks, recognize serious issues at hand, streamline interactions between your various teams and altogether magnify your return on investment. But adopting and investing in these mechanisms is as much a business decision as a technical one. The trick lies in drafting as-is and to-be business process maps, identifying where time is wasted in the current system and focusing on the value that new adoption can bring into the picture. With the right automation tools in place, your workforce can focus on elements that need human intelligence, not artificial intelligence.
Financing AI solutions and machine learning without monitoring and tracking your value stream is a straight path toward failure. To make the transition smoother, aim for incrementalism — slowly adopting one solution at a time. Your executive staff and major stakeholders should familiarize themselves with each solution and its potential and performance within the delivery pipeline. Conducting a value stream mapping exercise can help you identify the waste and the value that come along with each solution, which is especially important if you’re building the solution in-house and will incur development costs.
AI is already working its magic for various e-commerce, retail, health care, banking, logistics and social media giants. It can certainly keep your software development business armed to survive in an automated world.
This article is shared by www.itechscripts.com | A leading resource of
inspired clone scripts. It offers hundreds of popular scripts that are used by
thousands of small and medium enterprises.
