Welcome to the Roaring 2020s: The Artificial Intelligence Decade

While 2019 was a remarkable year for the AI, but the stage is all set for it to make an even deeper impact in the year 2020. This is not being said by us! reveals that the evolution of AI will greatly impact the global GDP and make a great shift to $15.7 trillion by the year 2030. The survey report of MarketsandMarkets That’s not all! and get smart enough by the end of 2020. Businesses are greatly affected by AI technology You must be surprised, how and why AI has become a piece of cake for the various industries...let’s find the answer! Why AI is Gaining Popularity With Each Passing Year? Artificial intelligence automates repeated learning and discovery through various data information. But it is different from machine-based automation process. Instead of automating various manual tasks, artificial intelligence performs large-scale computer-based tasks reliably and without any fatigue. For this type of automation process, human research is still required to configure the system and ask the right query. Artificial intelligence also adds intelligence to existing products. In most of the cases, the artificial intelligence will not be sold as an individual mobile application. On the contrary, the products you already use will be improved considerably with the capabilities of artificial intelligence, just like Siri has been added as a feature of a new generation of various Apple products. Conversation platforms, automation, robots and smart machines can also be combined with large amounts of data in order to improve many software technologies at home and in the workplace, from investment analysis to security intelligence. Artificial intelligence is adapted through gradual learning algorithms that allow data to do programming. Artificial intelligence finds regularity and structure in data so that the algorithm acquires a skill: the algorithm becomes predictive or categorized. Hence, just as the algorithm can be taught how to play chess, the recommended software product can also be taught online. The models adapt when new data is given. Posterior diffusion is an artificial intelligence method that allows the model to adjust, through data collection and training, when the first response is incorrect completely. In addition to this, artificial intelligence analyzes deeper data using neural networks that have many hidden layers. Furthermore, it was almost impossible to create a five-layer hidden fraud detection system. All of these have changed thanks to the big computing power and big data. You also need lots of data to train deep learning models as they learn directly from the given data. The more and more data you can feed, the more precise it will be. Artificial intelligence also achieves incredible preciseness across deep neural networks, which was impossible previously. For instance, their interactions with Google Search, Alexa, and Google Photos are totally based on deep learning, and they get more precise as we use it. In the medical field, techniques of artificial intelligence can now be widely used for image classification, deep learning, and object recognition in order to find cancer in MRI with the same precision that well-trained radiologists use. Artificial intelligence also takes full advantage of the data. When the data algorithms are self-learning, the data itself can become intellectual property. Answers are in the data; you just have to apply artificial intelligence in order to get them out. Since the role of data is now more crucial than ever, it can create a competitive advantage. If you have the best-in-class data in this competitive industry, even if everyone is applying similar techniques, the best data will win. Various industries which are set to be impacted the most by artificial intelligence in the year 2020: Healthcare Industry Photo by Daniel Frank on Unsplash In the healthcare industry, artificial intelligence can offer surprising assistance in the analysis of complex medical data which is related to X-rays and CT, as well as other exams and health tests. Patient data and various external sources of knowledge, like clinical research, can be used to create a path of personal treatment for everyone. Artificial intelligence can also be used to offer medical advice to patients on a real-time basis. In addition to this, you can also provide clinical decision support on the website. The Babylon artificial intelligence-based doctor compares the patient's symptoms with a database and offers the appropriate treatment. This application uses voice recognition so as to consult patients. Microsoft Hanover Project also uses the language and process of natural machine learning in order to make precise predictions about the most effective drug treatment option for each patient, individually. Retail / E-tail segment Artificial intelligence seems to be widely known for its application in the retail / electronic commerce industry. For example, conversation intelligence software helps firms interact with customers and track potential customers by analyzing sales calls and then segmenting them using NLP and voice recognition. Various retail companies offer a 24/7 customer service to answer various basic questions without the intervention of a human, with the help of virtual customer service assistants and chatbots. Financial and banking industry The financial and banking industry is facing more and more sophisticated and complex fraud and theft cases, and online transactions also increase in popularity over time. Artificial intelligence can take financial cybersecurity to the all-new level by using deep learning techniques into the systems, which can easily analyze patterns and identify suspicious behaviours as well as possibly stop possible fraud. Technology-based companies Technology-oriented firms not only create artificial intelligence solutions but also benefit from them. In addition to this, technology giants, such as IBM, Google, and Apple, generally make artificial intelligence companies/startups smaller in order to gain a competitive advantage. In addition to the chatbot platforms used primarily by various medium and small businesses, other big players have also created intelligent voice assistants like Microsoft Cortana, Google Home, and Apple Siri. Furthermore, neural networks are also used to analyze human language and return appropriate responses. At this moment, there is a fourth industrial revolution. The systems of machine learning, artificial intelligence, data analysis, automation and deep learning revolutionize all the industries while creating enormous opportunities for the firms. How Traditional Software Gets a Boost From AI-based Techniques? Various important components such as front end product interfaces, data management, and security must be handled carefully by regular software. However, various techniques developed using the conventional SDLC can also benefit from methods of machine learning in the below mentioned ways: 1. Rapid Prototyping. Converting business requirements to technological products needs months, if not years, of planning, but machine learning services shorten this process by allowing less technical field experts to create technologies using visual interfaces or natural language. 2. Smart programming assistants. Software companies spend the majority of their time reading documents and debugging their software products. Smart programming assistants can also reduce this time by offering recommendations and timely assistance, such as best practices, related documents, and code examples. Examples of these particular helpers include Codota for Java and Kite for Python. 3. Automatic analysis and error handling. Also, programming assistants can learn from their previous experience to identify automatically and tag various common errors during its initial development phase. Once the technology is applied, machine learning or AI can also be used to analyze various system logs in order to quickly and proactively identify various software errors. In addition to this, in the near future, it will be possible to allow the program to change dynamically in response to a plethora of errors without human intervention. 4. Automatic code restructuring. Photo by Goran Ivos on Unsplash A clean programming code is essential for long-term maintenance and search engine rankings. As top AI mobile app development companies modernize their technologies, large-scale resettlement is inevitable and often painful. Machine learning or artificial intelligence can be used to code analysis and optimization automatically for performance and interpretation. 5. Accurate estimates. Custom software development far exceeds deadlines and budget. Reliable estimates need extensive experience and a familiarity with the implementation team and understanding of context. Machine learning or AI can be trained on data from the previous projects, such as feature definitions, user stories, estimates, and actual data, to more accurately forecast budget and effort. 6. Strategic decision making. An important part of the time is spent discussing products and features that should be prioritized and which can be reduced. Artificial intelligence solutions trained in both past development projects and various commercial factors that can evaluate the performance of existing mobile applications and help both business leaders and software engineering teams identify efforts that will minimize risks and maximize impact. As per the latest report by on the impact of artificial intelligence on software development, most of the interest in applying artificial intelligence to software development lies in error detection and automated testing tools. Forrester Research The Role of AI in Software Testing One of the biggest role of artificial intelligence in the life cycle of software development is played in software testing. Artificial intelligence in software testing basically denotes to the below mentioned things. Artificial intelligence-powered tools for software product testing Artificial intelligence-based products and other deliveries Either way, Artificial intelligence plays a huge role in enabling developers to convert software testing into a robust self-driving exercise with minimal manual intervention. At present, most of the leading software testing tools used by mobile app development companies have begun to incorporate the potential of artificial intelligence into their packaging. For instance, both and in their latest releases included some artificial intelligence-based features. TestComplete tools Eggplant Despite all the loud and great efforts of artificial intelligence to make our requests smarter, we are not in a position to grant full autonomy to the artificial intelligence tool to build a complete solution for our purpose. As of now, there are various artificial intelligence tools to expand our efforts to create and deliver a better software product. Therefore, while the role of mobile app developers will remain more important than ever, our ability to use these Artificial intelligence-powered tools will be more important. Let’s Wrap Up: No doubt, AI is winning the hearts of companies all across the world. And, now more and more companies are opting AI to enhance their profit. Businesses nowadays, hire best ai mobile app developers to make their software solutions foolproof and more advanced. Also, there are many Mobile App Development Companies that are using AI as their core technology to create feature-packed applications. References The survey report of MarketsandMarkets