How is AI poised to transform our future?

“Artificial Intelligence is the new electricity. It has the potential to transform every industry and create huge economic value”, says Chinese-English scientist and entrepreneur, Andrew Ng. The impact of artificial intelligence on our daily lives cannot be overlooked. From smartphones to ride-sharing apps, smart home devices, Google search, and Social media- there is hardly any industry or sector that is left untouched by AI. 

There has been a huge surge in patenting of artificial intelligence in the last few years. PwC estimates that by 2030, AI would contribute a whopping $15.7 trillion to the global GDP. Analysis by the World Intellectual Property Organization (WIPO) states that the number of AI-related patent applications rose from 18,995 in 2013 to 55,660 in 2017. WIPO Director-General, Francis Gurry says that “We can expect a very significant number of new AI-based products, applications, and techniques that will alter our daily lives and also shape future human interaction with the machines we created”.

Industries such as healthcare, automotive, and financial services were the fastest to adopt AI.

Following are a few key domains that would be impacted most by AI in the coming years:

Related Reading: How AI Integration Helps Maximize Your Business ROI

AI will transform these areas in the coming years:

1. Transport

The general public would widely adopt self-driving vehicles. Apart from cars, self-driving vehicles would also include delivery trucks, autonomous delivery drones, and personal robots. Commutes may shift towards an on-demand approach like the Uber-style “cars as a service approach”. Commute-time would be viewed as a time to relax or just another way to work productively. People would live further away from their homes, reducing the need for parking space. This would change the face of modern cities. 

However, enhanced connectivity, real-time tracking, traffic gauging, route calculations, peer-to-peer ride-sharing, and self-driving cars would be impossible without personal user data. This calls for the need to implement more stringent measures to secure the data and privacy of citizens.

2. Home/ service robots

Robots have already entered our homes in the past fifteen years. Recent advances in mechanical and AI technologies substantiate the increasing safety and reliability of using home robots. In the foreseeable future, we can expect special-purpose robots to deliver packages to our doors, clean offices and enhance security. 

We are already familiar with the vacuum cleaning robot – Roomba, which has gained its place in millions of homes across the world. The AI capabilities of these kinds of robots are being increased rapidly with drastic improvements in the processing power and RAM capacity of low cost embedded processors. Low cost and safe robot arms are being used in research labs all over the world. Further advances enabled by deep learning will enable us to better interact with robots.

3. Healthcare

Healthcare is a promising domain for the use of AI technologies. AI-based applications have started gaining the trust of doctors, nurses, and patients. By revising the policies and other commercial regulations regarding the development and usage of such applications, AI can be used to improve health outcomes and quality of life for millions of people in the coming years. Patient monitoring, clinical decision support, remote patient monitoring, automated assists to perform surgeries, and healthcare management systems are some of the potential applications of AI in healthcare. 

4. Education

AI has the potential to enhance education at all levels, by providing personalization at scale. While computer learning will not replace human teachers, Massive open online courses (MOOCs) will help students learn at their own pace with techniques that work for them. AI technologies such as Natural language processing, machine learning, and crowdsourcing are giving an impetus to online learning. If these technologies can be meaningfully integrated with face-to-face learning, AI will find more applications in our classrooms

5. Entertainment

AI has already transformed this domain to a considerable extent. AI-driven entertainment is gaining huge traction and response from the masses with overwhelming enthusiasm. AI-enabled entertainment will become more interactive, personalized and engaging by 2030. However, the extent to which technology replaces or enhances sociability is debatable. More research is required to understand how to leverage these attributes of AI for the benefit of society.  

Related Reading: Building Incredible Mobile Experiences by Combining AR and AI

Concerns about AI

Advances in AI have already impacted our lives. However, you may also have heard of the dire predictions regarding AI made by some of the brightest minds such as the late scientist Stephen Hawking and Elon Musk (Tesla and SpaceX chief). Pew Research Centre surveyed some 979 technology experts to find out whether advancing AI and related technology would help or harm humanity. 63% of the respondents were hopeful of a better future in 2030. Many of them said that all would go well only if the concerned authorities paid close attention to how these tools, platforms, and networks are engineered, distributed and updated. 

Following were the concerns that were mentioned most often:

  1. Individuals would lose control over their lives due to the use of AI
  2. Surveillance and data systems that favor efficiency over human betterment would be dangerous.
  3. AI would cause millions of people to lose their jobs leading to economic and social upheaval.
  4. As people continue to depend on AI, their cognitive, social and survival skills would be diminished. 
  5. Cybercrime, cyberwarfare and the possibility of essential organizations being endangered by weaponized information would open new facets of vulnerabilities. 

Overcoming the concerns

Following are a few solutions to take positive advantages of AI:

  1. The global population should join hands and create cohesive approaches in tackling AI’s challenges.
  2. The development, policies, regulation, and certification of autonomous systems should undergo essential transformations to ensure that any kind of AI development would be directed towards the common good.
  3. Corporate and government organizations should shift their priorities towards the global advancement of humanity rather than profits and nationalism. AI advances should be aimed at human augmentation, regardless of economic class. 

Nicholas Beale rightly said, “AI done right will empower.” As artificial intelligence continues to be embedded in most human endeavors, let us make broad changes for the better. Let us be more thoughtful about how these technologies are implemented constructively.   

If you would like to know more about Fingent’s development and implementation approach on AI, give us a call

 

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    About the Author

    ...
    Sachin Raju

    Working as a Project Coordinator and Business Analyst at Fingent, Sachin has over 3 years of experience serving industries across multiple domains. His key area of interest is Artificial Intelligence and Data Visualization and has expertise in working on R&D and Proof Of Concept projects. He is passionate about bringing process change for our clients through technology and works on conceptualizing innovative technologies for businesses to visibly enhance their efficiency.

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      How AR and AI work together to build unique mobile experiences?

      The intriguing partnership of Augmented Reality (AR) and Artificial Intelligence (AI) is a match made in the digital heaven. An AR application can become more beneficial when AI is incorporated into it. The natural bridging of AR and AI enables mobile app developers to build more interactive and intriguing apps. This article explores a few practical ways in which AR and AI can be combined to build incredible mobile experiences.

      Awesome Ways AI and AR Complement Each Other

      The partnership between AR and AI is likely to have a profound impact on customer experience. Companies are developing next-generation applications for mobiles that employ AR and AI technologies. In fact, AI is the heart of AR platforms.

      Related Reading: How Top Brands Embrace Augmented Reality for Immersive Customer Experiences

      Though Artificial Intelligence and Augmented Reality have distinct technologies, they can sync with one another on a variety of applications. They can leverage each other’s best features and aspects building incredible mobile experiences. AI enables AR to have a multidimensional interaction with the physical environment. It allows you to manipulate 2D and 3D virtual objects with your words, eyes, and hands. 

      It is anticipated that the demand for AR apps is bound to soar in the next four to five years. Hence, the search for appropriate software development kits (SDK) and application program interfaces (API) for AI and AR is on.

      Current State of SDKs and APIs For AR and AI

      As the capabilities of current SDKs (Software Development Kits) and APIs (Application Programming Interfaces) rapidly expand, the number of commercial opportunities increase exponentially. Consider a few examples:

        • Vuforia: It is an Augmented Reality SDK that enables app developers to build mobile-centric, immersive AR experiences. It is capable of supporting both IOS and Android, allowing brands to develop apps with minimal commercial and technical risks. 
        • ARCore: It is Google’s proprietary AR SDK. It enables developers to get their AR apps up and running on mobile devices. ARCore supports IOS devices and allows developers to build rich and immersive AR experiences supported by mobile devices.  
        • Core ML: It is a Machine Learning framework used across Apple devices. This API allows you to perform real-time predictions of live images on your device. Its low latency and near real-time results are its biggest advantages. Core ML is an application that can be run without network connections. 
        • TensorFlow Lite: It is an open-source deep learning framework focused on mobile device inference. TensorFlow Lite enables developers to insert their own custom models.

      Practical Ways to Combine AR and AI

      The marriage of AR and AI opens up endless opportunities. Here are a few ways in which this combination is working to create digital miracles.

      1. Speech recognition: As an AI model listens to what you say, AR effects appear in front of you. For example, if you say ‘pizza,’ a virtual pizza slice appears in front of your mouth. 

      2. Image recognition and image tracking: It allows customers to see how an object would look and fit in a given space. Combining AR with AI technology allows users to move still photos of items into a still image of a room and assists them in making a decision. Example: IKEA Place

      3. Human pose estimation: It is a technique that detects human figures and poses. It predicts the positions of a person’s joints in an image or video. This can be used in controlling AR content. Yopuppet.com is one example. 

      4. Education: It allows students to have new perspectives through interaction with virtual reality. For example, it enables them to visualize and interact with a 3D life-size version of the human body. 

      Related Reading: Impact Of Augmented Reality In Education Industry

      5. Recognizing and labeling: When the camera is pointed to a scene or an image, the AR app displays a label that indicates the object or the item when it recognizes it. 

      6. Car recognition: Using a smartphone camera, it allows its customers to sit inside the car and explore the car’s interiors. There isn’t even a need to download the application. 

      7. Object detection: AR-AI combination can be applied to automatically learn and detect the position and extent of the objects within an image or a video. This mobile-friendly model facilitates interaction between physical and digital objects. 

      Take Away

      The bridging of AR and AI is offering businesses an opportunity to empower their customers more than ever before with information shared in captivating ways. Together, AR and AI continue to enhance mobile experiences.  It enables developers to design richer and more intuitive, relevant experiences for their diverse consumers. As we noted earlier, the applications of AR and AI are numerous. 

      To know more about how Fingent can help you build incredible mobile experiences by combining AR and AI, get in touch with our experts today!

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        ...
        Girish R

        Girish R, Programmer for 17 yrs, Blogger at Techathlon.com, LifeHacker, DIYer. He loves to write about technology, Open source & gadgets. He currently leads the mobile app development team at Fingent.

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          Why Clutch Ranks Fingent As The Top Software Development Company In Australia?

          Over the past 16 years, Fingent has partnered with clients across 4 continents and collaborated with start-up, mid-market, and large enterprises to solve business challenges with the latest custom software development practices. Our core values make us highly attentive to society, peers, family & self, and above all, customers. We are grateful that this client focus is recognized in reviews on Clutch and has enabled us to achieve the position of the leading software developer in Australia.

          Clutch

          Clutch is a B2B rating and review platform with thousands of company profiles. Clutch carefully analyzes and evaluates industry data, brand reputation, and most importantly, client testimonials to craft authentic descriptions of development companies and their services. When a company is facing a business challenge, Clutch stands as a directory to browse through and find the right solution provider. Clutch connects businesses with leading performers, who receive industry recognition for their excellent services. When it comes to software development, Fingent ranks as the Top Software Developer in Australia. Here’s a peek into Clutch’s leader matrix, where Fingent stands top on the charts of Market Leaders in comparison to the competing companies.

          We are extremely thankful to the clients who took the time to share their experiences about Fingent solutions and services on Clutch. Most recently, Sapra & Navarra LLP left us a review on our ongoing development services for their law firm. We were hired by Sapra & Navarra LLP to build a web-based AI machine learning program. Besides receiving 5.0 stars in the Clutch evaluation categories of cost, scheduling, quality, and willingness to refer, Sapra & Navarra LLP appreciated our accessibility and efforts to prioritize being available to answer any questions or concerns. They also applauded our organization, including our robust agendas of maintaining transparency through meetings and conference calls. 

          Check out a summary of the perfect 5.0 review below! 

          clutch

          Once again, we are very grateful to our clients for sharing their positive feedback on Clutch. It inspires us to continue delivering unique, budget-friendly solutions on time. 

          “We are excited to have been chosen as a top ASP.NET developer and NodeJS developer for 2020 by Clutch.” 

          – Stephen Cummings, Senior Vice President – Business Development, Fingent

          If you’re looking for a technology partner who can build a web or mobile app, deploy RPA or AI technology, or provide software consulting, please get in touch! We’d love to discuss your latest project.

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            Tony Joseph

            Tony believes in building technology around processes, rather than building processes around technology. He specializes in custom software development, especially in analyzing processes, refining it and then building technology around it.He works with clients on a daily basis to understand and analyze their operational structure, discover (and not invent) key improvement areas and come up with technology solutions to deliver an efficient process.

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              How to prepare for IoT in 2025?

              In coming years the Internet of Things (IoT) is here to stay. We’re at the cusp of a new era wherein intelligent digital connectivity is a part of our day-to-day lives. Gartner predicts that there will be 25 billion connected devices by 2021. Thus, IoT has made its presence felt across various industries.  

              Upcoming IoT trends that can shape the business landscape

              1. Industrial IoT and Digital Twin technology:

              IoT has made manufacturing smart, efficient and less risky. Using digital twin technology, organizations can access the context, structure, and behavior of an asset. Thus, you have the information regarding the past and present state of an asset with an ability to look into the future. Organizations are therefore receiving warning alerts and predictions faster than ever before. Investing in a digital twin can be a part of your IIoT strategy so that after implementing sensors into your machines, you can document their operations and fine-tune them.

              2. Computing would be balanced between the cloud and the edge:

              While those new to IoT consider cloud as inevitable, high data transmission costs for remote business environments have moved computing to the edge. In many industrial sectors, shifting some analytics intelligence to the edge may prove cost-effective. With edge devices becoming more affordable and centralized infrastructure becoming more stressed, there would be a balance between cloud and edge. 

              3. Sustainability will become important:

              Sustainability efforts have become a key business priority across the globe. The World Economic Forum reports that IoT projects can help to accomplish the UN’s 2030 Agenda for sustainable development. IoT can have a large impact on global sustainability as it connects people and things. IoT can be used to reduce e-waste, promote agricultural sustainability, save energy, protect species, reduce emissions and so on.  

              How to gear up for the IoT boom in 2024?

              While IoT promises attractive growth potential, many companies lack the technical capabilities and know-how to make their IoT projects work. A recent survey found that almost 75% of IoT projects end up as failures. Following are some of the ways in which you can prepare for the IoT surge:

              Related Reading: IoT Implementation: Common Mistakes And Strategies To Tackle Them

              • Plan Ahead: The major challenges that cause IoT projects to fail are budget overruns, limited internal expertise, long completion times, lack of proper data. All of this boils down to planning. You need to organize your projects, asses your budget needs, calculate the time requirements and assess whether your team has the expertise to handle the project. If you lag on any of these points, it is better to postpone the project rather than not finishing it at all.
              • Establish partnerships: Implementing IoT products can be very taxing due to the complex technology involved. The task can become almost unmanageable without a network of partners. You can establish partnerships for technological expertise or data and content delivery. Pioneers like Facebook, Amazon or Google have built entire ecosystems by establishing partnerships with hundreds of thousands of specialized developers.   
              • Integration: Successful IoT implementation requires robust connectivity, infrastructure, and seamless integration of your enterprise application/ systems with proper third-party wares. Challenges such as integration of the IoT platforms to enterprise applications and integration of edge/ cloud computing devices to the IoT platforms are most prevalent. By forming a strong IoT solution team with IoT architects and other subject matter experts, you can solve challenges across the IoT solution landscape.       
              • Ramp up the security: Cybersecurity is going to be one of the biggest risks in an increasingly connected world. Since everything that can be connected to the internet is exposed to a security risk, it is critical to secure every connected device. You need to be prepared with a game plan to tackle such types of data breaches. If you find that your business is ill-equipped to meet the security needs of your IoT network, don’t worry; you can always outsource.

              Related Reading: The Pros and Cons of Outsourcing Mobile App Development

              • Data storage: IoT is all about data. Cisco estimates that IoT devices would generate about 847 zettabytes of data per year by 2021. You can invest in your own local data storage system (which would be expensive) or you can find a cloud storage provider. Edge computing is another possible solution that is preferable over the aforementioned ones. In this system, the data is pushed to the ‘edge’ for quick access and to prevent data overload.
              • Be ready to transform: Partnerships are important. But you’ll also have to set up your own software and big data capabilities which are far beyond the existing levels. The team should focus on transforming itself into a technology company that understands the capabilities of IoT. Be responsive and address all concerns that rise up during the course of the project.
              • Innovate dynamically: A dynamic operating model requires cooperation. Innovative approaches like hackathons can be used to advance new ideas that meet the market demands of the digital world. Having the courage to take risks is an important part of dynamic product development. Even if ideas fail, it is important to keep trying and be consistent.                             

              The Internet of Things (IoT) is set to bring about lasting changes across various industrial sectors. Business leaders who stay agile can rest assured that they won’t be left behind.

              Need any tips on how to harness the power of IoT in your business? Contact us now!   

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                About the Author

                ...
                Vinod Saratchandran

                Vinod has conceptualized and delivered niche mobility products that cater to various domains including logistics, media & non-profits. He leads, mentors & coaches a team of Project Coordinators & Analysts at Fingent.

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                  How is RPA turning into a highly sought-after technology

                  Robotic Process Automation or RPA is one of the fastest-growing segments in the global enterprise software category. Research analyst Gartner says that the market growth rate of RPA was a whopping 63% in 2019. With more enterprises using this innovative technology, RPA’s market value is set to reach 3 billion USD by 2022, shows a prediction by Statista. Early adopters of the RPA software are already raking in benefits as RPA streamlines workflows, automates tasks and allows human workers to focus on high-value work. RPA software appeals to organizations across the world due to its quick deployment cycle time.

                  How RPA helps businesses: A quick recap

                  Robotic Process Automation or RPA refers to software programs or ‘bots’ that are programmed to mimic human actions. An average back-office employee has to carry out lots of repetitive, time-consuming and dreary tasks such as producing reports, filling out forms, updating records and other high-volume transactions that do not require judgment or reasoning.  RPA simply offers an easy way to perform these tasks more accurately and quickly. 

                  Since RPA does not require any specialized coding knowledge, businesses have welcomed RPA into their processes with open arms. Let’s now have a look at some jaw-dropping statistics and facts about RPA.

                  Related Reading: How Robotic Process Automation Is Revolutionizing Industries?

                  Jaw-dropping statistics and facts about RPA

                  Statistics

                  The statistics behind the widespread use of this technology can provide us valuable insights into how RPA is impacting the world. 

                  1. According to the National Association of Software and Services Companies (NASSCOM), organizations that implement RPA can reduce costs from 35-65% for onshore process operations and 10-30% in offshore delivery.
                  2. McKinsey and Co. suggest that around 45% of the tasks in a business can be automated.
                  3. In their Annual Global RPA survey, Deloitte found that 53% of the survey respondents had already started their RPA journey. Deloitte predicts that we would witness the worldwide adoption of RPA within the next two years.
                  4. Among those surveyed, the ROI was reported at less than 12 months with an average of 20% full-time equivalent capacity provided by robots. 
                  5. The Deloitte RPA survey respondents also reported an improvement in compliance (92%), quality/accuracy(90%), productivity(86%) and a reduction in costs(59%).
                  6. The Institute for Robotic Process Automation claims that RPA software robots cost about one-third of the price of an off-shore employee and one-fifth of the price of an onshore worker.

                  These compelling figures help us to see how RPA is adding value to organizations looking to operate with maximum efficiency.

                  RPA Facts

                  • RPA cannot replace humans: One of the biggest misconceptions about RPA is that it will eat up human jobs. RPA works alongside humans to make their lives easier. RPA software carries out jobs that are repetitive and mundane. This can enable us to focus on fruitful endeavors thus improving efficiency.
                  • RPA will change the nature of outsourcing: RPA has disrupted the outsourcing industry. The increased efficiency and usability that comes with RPA implementation, has threatened traditional BPO relationships. Since RPA can handle more transactions without making mistakes or taking breaks, traditional outsourcing relationships have declined over the last few years. However, if BPOs embrace the benefits of RPA or any other transformative technology they’ll continue to work.
                  • RPA software implementation is complex: It’s true that RPA has delivered huge benefits to its users. However, many users have also found that the implementation of RPA was quite challenging. Selecting the wrong RPA is one reason that can cause the RPA project to become more complicated than it actually should. If your company doesn’t have an interconnected system that updates cloud or on-premise infrastructure, then RPA implementation can be a big challenge.
                  • RPA cannot improve a flawed business process: RPA automates processes but does not improve any defects in the existing processes. Due to the hype surrounding RPA, organizations view it as a solution to all their woes. While RPA does help to streamline and modernize processes that are well established, it does nothing to improve a flawed process. So before automating, it’s better to have a clearly defined business process.
                  • RPA cannot be used to automate all kinds of processes: RPA can be used where high volumes of repetitive transactions based on business rules are carried out. For eg: banking and financial services, insurance, healthcare, pharmaceuticals, manufacturing, travel, logistics, etc. However, if the processes involve reasoning, making decisions, taking different actions according to scenarios, then those processes will not be able to enjoy the full benefits of business automation.
                  • Future of RPA: RPA has advanced considerably and is the future of IT automation. RPA will be increasingly adopted in various industries such as manufacturing, oil, and gas, retail, etc. Humans will no longer perform data entry and data rekeying jobs. All such jobs would be automated. RPA would evolve to SPA (Smart Process Automation) making business processes smarter. By integrating emerging technologies such as machine learning, AI, big data, with RPA enterprises can promote new levels of productivity and efficiency.   

                  https://www.fingent.com/insights/portfolio/robotic-process-automation-simplifying-business-operations/

                  Organizations need not scrap their legacy systems while implementing RPA. The ability of RPA software to integrate legacy systems has helped organizations to accelerate their digital transformation initiatives. They have also unlocked the value associated with past technological investments. As businesses look for new solutions to increase gains, RPA will continue to develop and gain relevance.

                  Related Reading: How Can Businesses Overcome The Barriers To RPA Adoption?

                  Have you implemented RPA in your organization? Do you have any insights to share? Do let us know!

                   

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                    About the Author

                    ...
                    Sachin Raju

                    Working as a Project Coordinator and Business Analyst at Fingent, Sachin has over 3 years of experience serving industries across multiple domains. His key area of interest is Artificial Intelligence and Data Visualization and has expertise in working on R&D and Proof Of Concept projects. He is passionate about bringing process change for our clients through technology and works on conceptualizing innovative technologies for businesses to visibly enhance their efficiency.

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                      Industry 5.0 Is All Set to Highlight the Significance of Humanity at Workplace******

                      “The industrial revolution was another of those extraordinary jumps forward in the story of civilization.”

                                                       – Stephen Gardiner, English bishop, and statesman.

                      Standing at the threshold of the 5th industrial revolution (also known as Industry 5.0 or 5IR), we are poised for another jump forward.  And yet, we have seen in the past that the march of these successive industrial revolutions has left an element of dehumanization in their wake. Will that be true of the 5th industrial revolution as well? Experts disagree, which is good news indeed. 

                      This blog takes a look at how the 5th industrial revolution is bringing the focus back to humanity.

                      A Phenomenal Journey Towards the 5th Industrial Revolution

                      5IR

                      The journey started in 1760 when the first industrial revolution ushered in urbanization, providing work for people at factories. 

                      The second industrial revolution changed the socio-economic situation of the world, improving transport and communication. Also, better automation provided better employment opportunities.

                      The third industrial revolution saw the invention of the computer, enabling automation in both the office and production lines.

                      The fourth industrial revolution brought in better communication and connectivity across the globe. It saw the advent of intelligent technologies like robotics, blockchain, IoT, and more.

                      Artificial Intelligence, Robotics, Augmented Reality and more such technologies have changed the technological landscape like never before. Let’s not forget how Artificial Intelligence has tremendously transformed, customer experience, in recent years. Here’s a look!

                      That leads us to the question: What can we expect from the 5th industrial revolution and will it help improve humanity? 

                      Before that, let us find out what the 5th industrial revolution is exactly.

                      The 5th Industrial Revolution

                      Though different experts have different explanations about what the 5th industrial revolution is, most of them agree that the 5th would be based on the 4th. 

                      Why?

                      A look at history shows that each revolution became the foundation for the next revolution. We can thus expect the 5th revolution to be built over the 4th revolution, but it will go one step further. 

                      An article developed in collaboration with the World Economic Forum puts it this way: “In contrast to trends in the Fourth Revolution toward dehumanization, technology and innovation best practices are being bent back toward the service of humanity by the champions of the Fifth … In the Fifth Industrial Revolution, humans and machines will dance together, metaphorically.” 

                      5IR

                      (Sorce: DataProt)

                      With this in mind, we can foresee the 5th industrial revolution to be an AI (artificial intelligence) revolution with the potential of quantum computing which will draw humans and machines together at the workplace. It is about harnessing the unique attributes of AI by recruiters and employers who in effect will be more equipped to make even better and more informed decisions.

                      “AI is becoming more prominent with 50 percent of workers currently using some form of AI at work. However, 76 percent of workers (and 81 percent of HR leaders) find it challenging to keep up with the pace of technological changes in the workplace.”

                      How Industry 5.0 Brings Back the Focus to Humanity

                      1. Uncaging recruiters

                      The 5th industrial revolution (5IR or Industry 5.0) places greater importance on human intelligence than ever before. Even today in the war on talent, AI enables recruiters to capture better profile matches. 5IR brings huge benefits in providing the candidates with a more personalized experience in their job search. 

                      “According to an article in Forbes: 34% of HR leaders are investing in workforce learning and reskilling as part of their strategy to prepare for the future of work!”

                      5IR will also uncage human resource teams from the major part of daily administration. This will give them time to fine-tune and meet talent requirements, allowing them to focus on the growth and productivity of their organization.

                      Read more:  Learn why you need to develop a custom platform for remote employee hiring and onboarding.

                      Hiring and Onboarding

                      2. Puts women at the forefront

                      Martha Plimpton said, “Women have always been at the forefront of progressive movements.” This is true even with regard to 5IR. It will play a critical part in shaping the role of women. As businesses hire unbiasedly, women and girls worldwide will be empowered. 

                      3. Prevents the repetition of Engels’ pause

                      During the first industrial revolution, though per worker output expanded, real wages stagnated for about 50 years. This stagnation was called Engels’ pause. It is estimated that 5IR has the potential to prevent such stagnation. Though 5IR will take away mundane and repetitive tasks, it opens the way to curiosity, creativity, empathy, and judgment ensuring a balance between people and technology. 

                      4. Changes the way we work

                      Most of us no longer want to work at 9-5 jobs. The way we work is dramatically changing. As our preferences in job and timings change, companies are forced to change too. Surely 5IR will change this even further. 

                      New employees will no longer have to read a pile of documents or sit through meetings to get all the current and accurate information. This would mean that you can onboard them very easily without having to invest a great deal in training. 5IR will help companies make the most of existing resources helping management teams to focus on more strategic tasks.

                      The recent pandemic situation has also paved the way for remote working culture, which is now gaining fast popularity. Innovative cloud platforms, such as InfinCE, are supporting this rapidly evolving work culture with streamlined collaboration and smooth communication solutions. Enabling enhanced communication channels, video conferences, and a secured environment for task sharing, monitoring, and collaboration; InfinCE and such other integrated cloud platforms are revolutionizing the work culture of the future. Let’s not forget that with the revolutionary 5G technology, remote collaboration is expected to take new heights with virtual meetings and augmented solutions. Here’s a deeper look into how 5G is reinventing the way we work.

                      5G

                      Although the advanced communication channels and collaboration apps, along with 5G technology is creating an impact on work culture, experts call AI and Remote Work, a match made in the future. Why? Here are a few reasons!

                      • Monitoring the outputs of the remote workforce has always been a concern. But with machine learning and artificial intelligence, tracking remote tasks in real-time is not just possible but also effective and seamless.
                      • The HR management has to comply with company policies and other legal requirements before recruiting, and these tasks prove quite tedious. Utilizing intelligent technologies to create remote positions can streamline these procedures and turn down the load of the people management department.
                      • Implementing survey-based tools can simplify collecting reviews and reports on employee performance which in turn can help strengthen the workforce of a company.

                      Intelligent technologies are sure to take a lead when it comes to human resource management, and 5IR is sure to embrace this change!

                      5. Paperless technology

                      As mentioned earlier in this blog, 5IR is all about embracing digitization and intelligent technologies to enhance human efficiency. And paperless technology is doing just that! 

                      Simplifying strenuous paperwork across industries, paperless technology is turning to become the future! Reducing excessive manual effort, to reducing duplication of work and errors, paperless technology is already highly streamlining complex work processes in Banking, Finance, and Law sectors. 

                      Another industry that has hugely benefited from this technology is the field service industry. Going paperless on the field is not just enhancing field service management efficiency but is also enabling field technicians to leverage complete digitization. Mobile field service apps like ReachOut Suite are utilizing these evolving capabilities of mobility and digital forms to empower field workers with streamlined collaboration, easy management, and instant report generation solutions to deliver enhanced customer experiences.

                      When talking about paperless technology and the future, let’s not forget how machine learning is impacting and shaping this new paperless era. With advanced tools to print, scan, and sign digitally, ML is taking the paperless revolution to the next level, providing a wider scope for paperless offices and digital environments. Here’s a deeper look into how Machine Learning edges us closer to paperless offices!

                      Machine Learning

                      The 5th Industrial Revolution is Just What We Need

                      In 5IR, technology will bend back towards the service of humanity, marked by creativity and a common purpose. 5IR will empower us to close the historic gap and create a new socio-economic era. Isn’t that exactly what the world needs?

                      Fingent offers custom software solutions to address your unique business needs. If there is anything that we could help you with, please connect with us

                       

                       

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                        About the Author

                        ...
                        Tony Joseph

                        Tony believes in building technology around processes, rather than building processes around technology. He specializes in custom software development, especially in analyzing processes, refining it and then building technology around it.He works with clients on a daily basis to understand and analyze their operational structure, discover (and not invent) key improvement areas and come up with technology solutions to deliver an efficient process.

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                          Knowledge Representation in AI and Its Business Significance

                          Artificial Intelligence is the most innovative technology that has always captivated human beings. Robots that can think, act, decode complex information, and make smart decisions continue to inspire tech enthusiasts, sci-fi novels, and movie makers.
                          Humans know things, which we term knowledge, and all our abilities to perform various actions in the real world originates from the knowledge we have gathered so far.
                          If we were to make Artificial Intelligence programs more sophisticated and capable of imitating human intelligence in a given scenario, we would be required to feed the AI systems with more and often complex information about the real-world. Now that leads us to the concept of Knowledge Representation in Artificial Intelligence.

                          What is Knowledge Representation?

                          Knowledge representation is a field of artificial intelligence that allows AI programs to answer questions intelligently and make deductions about real-world facts. It refers to representing information about the world in a way that a computer system can understand and use it to solve real-life problems or handle real-life tasks.
                          Knowledge representation in AI concerned with how knowledge can be represented symbolically and manipulated in an automated way by reasoning programs. For instance, an AI software can be trained to solve complex tasks such as diagnosing a medical condition only if the relevant knowledge is made available to the AI system as required.

                          There are two primary concepts in Knowledge Representation:

                          #1Knowledge

                          Knowledge refers to the fact of knowing something that has been gained through an experience and learning which makes the agent (AI application like a chatbot) familiar.
                          In Artificial Intelligence, a machine will perform a specific action based on a specific condition only if it has gained an experience from the past. For example, an AI agent can solve a chessboard puzzle only if it has gained sufficient knowledge on how to solve the puzzle and win the game.

                          #2Representation

                          Representation refers to the process of representing what has been gained from the knowledge. Representation consists of the objectives that are used to express the knowledge that is required to solve a specific problem.
                          The different kinds of knowledge that need to be represented in AI systems include:

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                          Different Types of Knowledge Represented in AI

                          In a broad sense, knowledge is the awareness or familiarity gained by the experiences of facts, data, and situations. Following are the different types of knowledge that need to be represented in artificial intelligence.

                          Declarative Knowledge

                          Refers to the facts, objects, and concepts that allow us to describe the world around us. It shares the description of something expressed in declarative sentences which is simpler than procedural language.

                          Structural Knowledge

                          Constitutes the problem-solving knowledge that describes the relationship between various concepts or objects and their descriptions.

                          Procedural Knowledge

                          Also known as imperative knowledge, procedural knowledge is used to complete any task with specific rules, strategies, processes, or agendas. It’s the type of knowledge which is responsible for knowing how to do a particular task and hence relies on the task we are trying to finish.

                          Meta Knowledge

                          As mentioned above, meta knowledge refers to predefined knowledge about things that we are already aware of. This knowledge typically includes the study of tagging, planning, learning, etc.

                          Heuristic Knowledge

                          Also known as shallow knowledge, heuristic knowledge is highly used in the process of reasoning as it can solve issues based on the experiences of past problems. Thus, it provides a knowledge-based approach to define a problem and take action.

                          Four Fundamental Knowledge Representation Techniques in AI

                          In artificial intelligence, knowledge can be represented in different ways depending on the structure of the knowledge, perspective of the designer or even based on the type of internal structure used. An effective knowledge representation should be rich enough to include the knowledge required to solve the problem. It should be natural, compact and maintainable.
                          Here are the four fundamental knowledge representation techniques used in AI:
                          1. Logical Representation
                          Knowledge and logical reasoning play an integral role in artificial intelligence. However, you often require more than just general and powerful methods to ensure intelligent behavior. Formal logic is the most helpful tool in this area. It is a language with unambiguous representation guided by certain concrete rules.
                          Knowledge representation relies heavily not so much on what logic is used but on the method of logic used to understand or decode knowledge.
                          Logical representation technique allows designers to lay down certain vital communication rules to share and acquire information to and from agents with minimum errors in communication. Different rules of logic allow you to represent different things resulting in an efficient inference. Hence, the knowledge acquired by logical AI agents will be definite which means it will either be true or false.
                          Although working with logical representation is challenging, it forms the basis of most of the programming languages used currently and enables you to construct logical reasoning.
                          2. Semantic Network
                          A semantic network allows you to store knowledge in the form of a graphic network with nodes and arcs representing objects and their relationships. It could represent physical objects or concepts or even situations. A semantic network is generally used to represent data or reveal structure. It is also used to support conceptual editing and navigation.
                          A semantic network is simple and easy to implement and understand. It is more natural than logical representation. Semantic network allows you to categorize objects in various forms and then link those objects. It also has greater expressiveness than logic representation.
                          3. Frame Representation
                          A frame is a collection of attributes and its associated values, which describes an entity in the real world. It is a record-like structure consisting of slots and their values. Slots could be of varying sizes and types. These slots have names and values. Or they could have subfields named as facets that allow you to put constraints on the frames.
                          There is no restraint or limit on the value of facets a slot could have, or the number of facets a slot could have or the number of slots a frame could have. Since a single frame is not very useful, building a frame system by collecting frames that are connected to each other will be more beneficial. It’s a flexible knowledge representation technique used by various AI applications.
                          4. Production Rules
                          Production rule-based representation has many properties essential for knowledge representation. It consists of production rules, working memory, and recognize-act-cycle. It is also called condition-action rules. If the condition of a rule is true according to the current database, the action associated with the rule is performed.
                          Although production rules lack precise semantics for the rules and are not always efficient, the rules lead to a higher degree of modularity. And it is the most expressive knowledge representation system.

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                          Cycle of Knowledge Representation in AI

                          When building an AI system, it’s important to come up with a knowledge representation system that will help in feeding the AI system with the essential knowledge. The AI knowledge cycle consists of some major components to demonstrate intelligent behavior that make knowledge representation possible.

                          Approaches to Knowledge Representation in AI

                          There are four main approaches to knowledge representation in artificial intelligence. Each approach corresponds to a technique used to represent the knowledge discussed above.
                          1. Simple Relational Knowledge
                          2. Inheritable Knowledge
                          3. Inferential Knowledge
                          4. Procedural Knowledge
                          The AI machine learning program discussed aims to simplify and enhance claims management processes. Leveraging advanced algorithms and analytics, this solution automates tasks, improves accuracy, and streamlines the claims processing workflow. For more information on how this AI-driven program can benefit your business, please visit the provided link.

                          Properties of a Good Knowledge Representation System

                          A good knowledge representation system should meet the following requirements:

                          Representational adequacy

                          The knowledge representation (KR) system should be capable of representing each kind of required knowledge in a way the AI system can understand.

                          Inferential adequacy

                          The KR system should be flexible enough to manipulate existing knowledge to make way for new knowledge corresponding to the present structure.

                          Inferential efficiency

                          Inferential efficiency refers to the ability of the KR system to direct the inferential knowledge mechanism toward the most productive directions using appropriate guides.

                          Acquisitional efficiency

                          Acquisitional efficiency is the ability of the knowledge representation system to automatically acquire new knowledge, integrate the new information into the existing knowledge base, and use the same to improve efficiency and productivity.

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                          Why is Knowledge Representation Important for AI Systems?

                          Knowledge representation equips AI agents with the capabilities to solve the most complex tasks based on what they have learned from the knowledge given to them. The knowledge given to them could be human experiences, problem-solutions, if-then rules, response to specific scenarios, etc. which are represented in a specific way for the AI agent to understand and learn.
                          Knowledge representation is the technique that runs behind several technologies and machines that are around us. An AI software development can solve complex problems or complete difficult tasks successfully only by relying on a knowledge base which describes how to approach and perform each task.
                          Knowledge representation is a field of AI concerned with understanding, designing, and implementing ways of representing information in a comprehensible manner for the machines, so the AI programs can use this information to:
                          The innovative solution, driven by AI algorithms and advanced data analysis techniques, revolutionizes the process of estimating project costs. By automating and optimizing the estimation process, organizations can improve accuracy, reduce manual effort, and achieve faster turnaround times. With AI-enabled capabilities, such as pattern recognition and predictive modeling, project managers can make informed decisions and allocate resources more effectively.

                          Benefits of Knowledge Representation in AI

                          Knowledge representation is the driving force that equips your AI program to support you in improving productivity, increasing competitive advantage, and minimizing risks and errors. Knowledge representation in AI delivers several benefits.
                          AI technology is utilized to enhance various aspects of aviation operations, including flight planning, maintenance scheduling, passenger experience, and safety management. By leveraging AI algorithms and data analysis, organizations in the aviation sector can improve efficiency, accuracy, and decision-making processes. AI brings automation, predictive capabilities, and data-driven insights to drive transformation and innovation in the aviation industry.

                          How Can Fingent Help

                          Knowledge representation is the key to designing AI agents that can think and act smart while ensuring that such thinking can constructively contribute to their behavior and allow them to respond effectively to each scenario. However, it is important to choose the right type of knowledge representation if you want to ensure business success with AI.
                          There are certain considerations to keep in mind when designing a knowledge representation system. Factors such as the structure for storing knowledge, depth of information required for representing a subject adequately, etc. are some of the common dilemmas faced during the creation of knowledge systems.
                          At Fingent top custom software development company, we help you build custom AI applications that are well-tested and configured to process specialized data sets in order to produce expected results. Our AI experts can collaborate with you and help provide different types of knowledge to your AI systems to make your AI applications more competent and sophisticated.
                          If you are planning to build an AI software development for your business or want to know more about the scope and business benefits of AI or want to upgrade from legacy software to a modern technology platform, feel free to connect with our team.

                          Frequently Asked Questions

                          Knowledge representation is a subfield of artificial intelligence that solely focuses on representing information about the real world around us in a way that computers can understand. For instance, knowledge representation takes all the concepts in a domain, describes how these concepts link to each other, and defines the rules that govern the behavior of the AI system based on each condition.
                          Following are the different types of knowledge representation used in artificial intelligence.
                          • >> Declarative Knowledge: Constitutes the facts, objects, and concepts that allow us to describe the world around us.
                          • >> Structural Knowledge: Includes the problem-solving knowledge that describes the relationship between various concepts or objects and their descriptions.
                          • >> Procedural Knowledge: Used to complete any task with specific rules, strategies, processes, or agendas.
                          • >> Meta Knowledge: Constitutes the predefined knowledge about things that we are already aware of.
                          • >> Heuristic Knowledge: Used in the process of reasoning as it can solve issues based on the experiences of past problems.
                          AI agents can express intelligent behavior only if they acquire the knowledge and experiences that we, humans, have gained from the real world around us. Knowledge representation allows AI programs to use the information they’ve learned to:
                          • >> Derive information that is implied by the AI agent,
                          • >> Communicate with people in natural language,
                          • >> Decide what to do next,
                          • >> Plan future activities, and
                          • >> Solve problems in areas that normally require human expertise.
                          It’s important to choose a knowledge representation system with the following characteristics:
                          • >> KR system should be extensive, well-represented, and easily decipherable
                          • >> Should cover a wide range of standard computing procedures to support large scale application
                          • >> Must be easy to access and provide the options to identify events and decode the reaction of different components
                          The AI knowledge cycle comprises multiple elements or entities that are used to represent and utilize knowledge. These entities include perception, learning, knowledge, reasoning, planning, and execution.

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                            About the Author

                            ...
                            Sachin Raju

                            Working as a Project Coordinator and Business Analyst at Fingent, Sachin has over 3 years of experience serving industries across multiple domains. His key area of interest is Artificial Intelligence and Data Visualization and has expertise in working on R&D and Proof Of Concept projects. He is passionate about bringing process change for our clients through technology and works on conceptualizing innovative technologies for businesses to visibly enhance their efficiency.

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                              How Extended Reality Is Transforming Business Environments?

                              Picture yourself diving into crystal-clear Grecian waters or taking a walk on the moon, all the while sitting in the comfort of your home.  As fantastical as this may seem now, Extended Reality is making this possible as we speak. What is Extended reality and what are its powerful real-world applications? Let’s check.

                              Understanding What Extended Reality Is

                              Extended Reality is a blanket term that encompasses all virtual and real environments generated by computer technology. This includes components such as Virtual Reality, Augmented Reality, and Mixed Reality. Extended Reality is poised to completely revamp the way businesses interact with the media and has the potential to allow seamless interaction between the real and virtual worlds allowing its users to have a completely immersive experience. 

                              Three Remarkable Components of Extended Reality

                              These components fall under the category of immersive technologies that can affect our perceptions. Here is a little bit about them:

                              Virtual reality: Virtual reality transposes its users to a different setting through a simulated digital experience. It makes use of a head-mounted display (HMD) to create an immersive experience by simulating as many experiences as possible. Virtual reality app development has witnessed significant adoption in industries like healthcare and real estate. 

                              Augmented reality: Augmented reality services have emerged as a powerful tool in various industries, including healthcare and real estate. With the development of augmented reality apps, businesses can enhance user experiences by overlaying digital elements onto the real world. This technology offers exciting opportunities for immersive and interactive interactions, transforming the way we perceive and interact with our surroundings.

                              Mixed reality: Being the most recent advancement among reality technologies, mixed reality is experienced through mixed reality glasses or headsets where you can interact with physical and digital objects in real-time. 

                              Related Reading: Augmented Reality Vs. Virtual Reality – The Future Technology

                              The implementation of these technologies through extended reality is enabling businesses to create innovative solutions and increase customer engagement, reduce human error and improve time efficiency. 

                              5 Powerful Real-World Applications 

                              “The market for Extended Reality is expected to have a compound annual growth rate of more than 65% during the forecast period of 2019-2024,” says Mordor Intelligence. 

                              Check out these five real-world applications of extended reality:

                              1. Entertainment and Gaming

                              The entertainment and video games industries are the foremost users of Extended Reality. Camera tracking and real-time rendering are combined to create an immersive virtual environment, allowing actors to get the real feel of the scene, thereby improving their performance. The extended reality also allows for multipurpose studio environments, thus reducing the cost of an elaborate movie set.

                              Video gaming is enhanced by the ability of Extended Reality to create a comprehensive participation effect. This allows users to dive into a completely different reality. Other entertainment events such as exhibitions and live music can also be enhanced by the capabilities of Extended Reality. 

                              2. Employees and Consumers

                              • Training: Extended Reality allows employees to be trained and educated in low-risk, virtual environments. Medical students, surgeons, firefighters, pilots, and chemists can closely simulate risky scenarios with minimal risk and less expense. The experience they gain will prove invaluable when they handle real-life situations.
                              • Information: Replacing physical manuals, Extended Reality can enable technicians to focus on the task without having to flip the pages of a manual. It can even connect an expert remotely to the real-time issue for his expert advice. This would save organizations a whole lot of money, and more importantly save them valuable downtime as they wouldn’t need to wait for experts.
                              • Improve customer perspective: Simulating virtual experience brought on by specific diseases and impairments can help doctors and caregivers receive empathy training. 

                              Related Reading: How Top Brands Embrace Augmented Reality for Immersive Customer Experiences

                              3. Healthcare

                              Extended Reality is improving healthcare by streamlining medical procedures while enhancing patient care. Allowing surgeons to visualize the complexities of the organs in 3D, it is enabling them to plan each step of a complicated surgery well in advance. Essentially, it is ensuring that surgeons can perform surgeries in a more safe, effective and precise way.

                              4. Real Estate

                              Extended Reality makes it easier for real estate agents and managers to close a deal by enabling prospective homebuyers to get a real feel of the property. The layout scenarios that are enabled by Extended Reality enhance customer experience while providing strong business opportunities. 

                              Related Reading: AR and VR- Game Changers of Real Estate Industry

                              5. Marketing

                              Extended Reality enables marketers to give their consumers a ‘try before you buy’ experience. It allows consumers to be transported to a place, immerses them in that world and motivates them to explore it. As an example, Cathay Pacific used a 360◦ video with hotspots to help potential customers experience the brand firsthand. That increased customer awareness by 29% and brand favorability by 25%. 

                              Face the Future with Extended Reality

                              There are many more advancements and applications to be discovered with Extended Reality, and it is soon going to be imperative to competitive advantage. Don’t let your business fall behind. Consult with Fingent, a top custom software development company, today and ensure you stay ahead of the curve. 

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                                About the Author

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                                Girish R

                                Girish R, Programmer for 17 yrs, Blogger at Techathlon.com, LifeHacker, DIYer. He loves to write about technology, Open source & gadgets. He currently leads the mobile app development team at Fingent.

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                                  3 Reasons to Embrace Prescriptive Analytics in Healthcare

                                  From flagging an unsafe drug interaction to activating a yearly reminder call for a mammogram, healthcare providers are leveraging patient data for a wide array of healthcare tasks. Yet, a worrying number of healthcare providers struggle to understand which one of the big data analytics methods, prescriptive or predictive, is most effective for their business.

                                  Related Reading: 5 Ways Big Data is Changing the Healthcare Industry

                                  Understanding the difference between prescriptive analytics and predictive analytics is the key to finding the right path to viable and productive solutions for your healthcare industry. This blog discusses why you should consider prescriptive analytics rather than predictive analytics to drive value to your business.  

                                  Predictive Analytics: The Ability to Forecast What Might Happen

                                  Predictive analytics has been helpful to healthcare providers as they look for evidence-based methods to minimize unnecessary costs and avoid adverse events, which can be prevented. Predictive analytics aims to detect problems even before they occur using historical patterns and modeling. As the word itself suggests, it predicts. It gives you collated and analyzed data that could serve as raw material for informed decision making. 

                                  Related Reading: Data Mining and Predictive Analytics: Know The Difference

                                  However, the healthcare industry demands a more robust infrastructure. It needs access to real-time data that allows quick decision-making both clinically and financially.  It also requires medical devices that can provide information on the vitals of a patient up to the nanosecond. Based on the information available for the individual patient, clinical decision support systems should be able to provide an accurate diagnosis and the treatment options available. This must take into consideration the latest advances in medicine available as well. That is where prescriptive analytics comes into the picture.

                                  Prescriptive Analytics: Reveals Actionable Next Steps

                                  Prescriptive analytics takes it a step further by providing actionable next steps. If predictive analytics sheds light on the dark alley, prescriptive analytics reveals the stepping stones that would help map out the course of action to be taken. It empowers you to make more accurate predictions and gives you more options so you can make well-defined split-second decisions, which is critical for the healthcare industry. 

                                  According to Research and Markets, the global prescriptive and predictive analytics market is expected to reach $28.71 billion by 2026. The reason for such an increase is because prescriptive analytics has the capacity to analyze, sort and learn from data and build on such data more effectively than any human mind can. Hence, the most outstanding benefit of prescriptive analytics is the outcome of the analysis. 

                                  Three Reasons to Consider Prescriptive Analysis

                                  MarketWatch states that Healthcare prescriptive analytics market is poised to grow significantly during the forecast period of 2016-2022. Here are 3 reasons why.

                                  1. Sound Clinical Decision-Making Options

                                  Unlike predictive analytics which stops at predicting an upcoming event, prescriptive analytics empowers healthcare providers with the capability to do something about it, helping them take the best action to mitigate or avoid a negative consequence. 

                                  To illustrate, a healthcare service provider might be experiencing an inordinately increased number of hospital-acquired infections. Prescriptive analytics wouldn’t just stop at flagging the anomaly and highlighting who would be the next possible patient with vulnerable vitals. It would also point to the nurse who is responsible for spreading that particular infection to all these patients. It could also prevent similar outbreaks in the future by helping healthcare providers develop a sound antibiotic stewardship program.  

                                  2. Sound Clinical Action

                                  Prescriptive analytics doesn’t limit itself to interpreting the evidence. It also allows health care providers to consider recommended actions for each of those predicted outcomes. It carefully links clinical priorities and measurable events such as clinical protocols or cost-effectiveness to ensure that viable solutions are recommended. 

                                  To illustrate, a healthcare provider might be able to forecast a patient’s likely return to the hospital in the very next month using predictive analysis. On the other hand, prescriptive analytics would be able to drive decisions regarding the associated cost simulation, pending medication, real-time bed counts, and so on. Or, it could help you decide if you need to adjust order sets for in-home follow-up. It empowers the hospital staff to identify the patient with a greater risk of readmission and take needed action to mitigate such risks.

                                  3. Sound Financial Decisions

                                  Prescriptive analytics has the capability to lower the cost of healthcare from patient bills to the cost of running hospital departments. In other words, it helps in making sound financial and operational decisions, providing short-term and long-term solutions to administrative and financial challenges. 

                                  Gain the Benefits of Prescriptive Analysis

                                  Prescriptive analytics provides enormous scope and depth as developers improve technologies in the future. It is making truly meaningful advances with regard to the quality and timeliness of patient care and is reducing clinical and financial risks. Are you ready to get on board? Contact us top software development company for help.

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                                    About the Author

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                                    Dhanya V G

                                    Working as a Tableau Developer at Fingent, Dhanya has an experience of 3+ years serving industries with the latest technology advances like Business intelligence, Data Visualization and Reporting. With passion in Analytics and Tableau, Dhanya works on articulating data insights to compelling stories that helps our clients make better business decisions.

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                                      Turning The Year Of Multi-Cloud Adoption for Enterprises

                                      There has been a lot of hype going on around businesses adopting multi-cloud strategies that make use of public, private, and hybrid cloud services. Businesses, especially the mid-market and enterprise-level industries can utilize multi-cloud strategy as a smart investment by leveraging the benefits of its resilient performance and virtual infrastructure.

                                      A multi-cloud strategy is all about adopting a mixture of IAAS (Infrastructure As A Service) services from multiple cloud providers and sharing workloads among each of these services which are reliable, secure, flexible, and of course cost-effective. 

                                      Why Must Businesses Opt For A Multi-Cloud Strategy?

                                      Businesses can adopt a multi-cloud strategy to acquire an optimal distribution of assets across the user’s cloud-hosting environments. With a multi-cloud strategy, businesses can have access to multiple options such as favorable Service Level Agreement terms and conditions, greater upload speed selection, customizable capacity, cost terms, and many more.

                                      How Can Businesses Make A Multi-Cloud Adoption Decision?

                                      Multi-cloud adoption decisions are based on 3 major considerations:

                                      • Sourcing – Agility can be improved and chances of vendor lock-in can be avoided or minimized by sourcing. This decision can be driven by factors such as performance, data sovereignty, availability, regulatory requirements, and so on.
                                      • Architecture – Architecture is a major decision-driver as many modern applications are mostly of modular fashion that can span multiple cloud providers and obtain services from any number of clouds.
                                      • Governance – Businesses can now standardize policies, procedures, processes, and even share tools that can enable cost governance. By adopting services from multiple cloud providers, enterprises can now ensure operational control, unify administrative processes, and monitor their IT systems more effectively and efficiently.

                                      Better disaster recovery and easier migration are the other key benefits that drive enterprises to adopt multi-cloud strategies.

                                      Related Reading: Cloud Computing Trends To Expect In 2020

                                      Top 7 Reasons To Adopt Multi-Cloud For Your Business

                                      • Ability To Find The Best-In-Class Multi-Cloud Providers

                                      Businesses administrators can bring in the best-in-class cloud hosting providers for each task that best suits their requirements. In a recent survey by Gartner, 81% of respondents said that the multi-cloud approach proved beneficial to them. Businesses are free to make their decisions based on the sourcing, architecture, and governance factors as mentioned above.

                                      • Agility

                                      According to a recent study by RightScale, organizations leverage almost 5 different cloud platforms on average. This figure shows the transformation of enterprises increasingly towards multi-cloud environments. Businesses struggling with legacy IT systems, hardware suppliers, and on-premise structures can benefit from adopting multi-cloud infrastructures to improve agility as well as workload mobility amongst heterogeneous cloud platforms.

                                      • Flexibility And Scalability

                                      With a competent multi-cloud adoption, enterprises can now scale their storage up or down based on their requirements. A multi-cloud environment is a perfect place for the storage of data with proper automation as well as real-time syncing. Based on the requirements of individual data segments, businesses can depend on multiple cloud vendors specifically. For improved scalability, enterprises must focus on achieving the following 4 key factors:

                                      1. A single view of each cloud asset
                                      2. Portable application design
                                      3. The capability to automate and orchestrate across multiple clouds
                                      4. Improved workload placement
                                      •  Network Performance Improvement

                                      With a multi-cloud interconnection, enterprises can now create high-speed, low-latency infrastructures. This helps to reduce the costs associated with integrating clouds with the existing IT system. When businesses extend their networks to multiple providers in this manner, proximity is ensured and low-latency connections are established that in turn improves the application’s response time along with providing the user a better experience. 

                                      • Improved Risk Management

                                      Risk management is a great advantage that multi-cloud strategies can provide businesses with. For instance, consider the case where a vendor has an infrastructure meltdown or an attack. A multi-cloud user can mitigate the risk by switching to another service provider or back up or to a private cloud, immediately. Adopting redundant, independent systems that provide robust authentication features, vulnerability testing as well as API assets consolidation ensure proper risk management. 

                                      • Prevention Of Vendor Lock-In

                                      With a multi-cloud strategy, enterprises can evaluate the benefits, terms, and pitfalls of multiple service providers and can choose the option to switch to another vendor after negotiation and careful validation. Analyzing terms and conditions before signing a partnership with a vendor can prevent vendor lock-in situations.

                                      • Competitive Pricing

                                      Enterprises can choose between the vendors and select the best-suited based on their offerings such as adjustable contracts, flexible payment schemes, the capacity to customize, and many other features.

                                      To learn more about adopting an effective multi-cloud strategy and the benefits it offers, drop us a call and talk to an expert. 

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                                        About the Author

                                        ...
                                        Sreejith

                                        I have been programming since 2000, and professionally since 2007. I currently lead the Open Source team at Fingent as we work on different technology stacks, ranging from the "boring"(read tried and trusted) to the bleeding edge. I like building, tinkering with and breaking things, not necessarily in that order.

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