20 AI Features to Re-organize the World

Artificial Intelligence is becoming the new support system for human to create a futuristic world. Acclaimed for its ability to memorize, anatomize, analyze and predict of all the human qualities and instincts, no doubt it is as smart and functional as human beings. Humans were curious to know; if a machine can behave, understand, learn, think, and work as humans do. As a matter of fact, humans have surpassed the initial answer “yes”, though, we are yet to unfold its full potential. Today, AI’s major growth focuses on problem-solving, learning and reasoning.

According to John McCarthy, one of the “founding fathers” of AI “The study is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.”

Advantages of AI in business is undeniable. Modern business depends on it a lot, and along with that, it is showing great prominence in acquiring a lot of futuristic qualities. Let’s see how features of artificial intelligence technologies is vowing to revolutionize the world with its immense potentiality.

1. Virtual Agents

A virtual agent is a PC operator or program that is equipped for communicating with humans. The well-known case of this sort of innovation is chatbots. Virtual specialists are at present being utilized for client support service and reliable home managers. It is a chatterbot program that uses a computer-generated, animated, and artificially intelligent virtual character acting as a customer service agent. It is a combination of AI and a graphical representation, increasingly used in CRM to help people perform tasks, such as making reservations, placing orders, or locating information, and answer questions about a company’s products and services. In an age of online shopping, banking and other such activities, the importance of virtual agents is rising rapidly.

2. Speech recognition

Speech recognition is an innovation that can perceive verbally expressed words, which would then be able to be converted to text. Voice recognition is a subset of speech recognition, which is the innovation for identifying a person depending on their voice. Amazon, Microsoft, Google and Apple — four of the world’s top tech companies are already offering this feature on various devices through services such as Alexa, Coratana, Google Voice assistant and Siri. From smart home gadgets to mobile operating, this speech recognition of AI has a high potential for future security services and personal help.

3. Emotion recognition

This innovation permits the product to “read” the feelings on a human face utilizing image processing or sound data processing. We can catch ‘micro-expressions,’ ‘scale articulations,’ or unpretentious non-verbal communication signs, and vocal pitch that sells out an individual’s sentiments. Gartner predicts that by 2022 ten percent gadgets will be fitted with emotion-recognition technologies. Emotion recognition has its use in security, customer focus, recruitment, education sector, medical diagnosis and patient care, video gaming, call centre intelligent routing, car safety instruction, connected home, retail, public service and so on. and a few other such sectors to ease human involvement.

4. Image recognition

Image recognition is the way toward distinguishing and recognizing an object or feature in an advanced picture or video. AI is progressively being stacked over this innovation for an incredible impact. Interestingly, features of AI makes all the image recognition possible, including facial recognition, object recognition, text detection, pattern recognition, image analysis, and so on. AI can look at social media platforms for photographs and contrast them with a full scope of data sets to choose which ones are generally significant during image searches. Amazon Rekognition, Google Vision are some of the platforms which are working relentlessly to make the feature of AI more convincing to elevate its usability more effectively in the coming days.

5. Natural Language Production

In reality, processing language and turning it into meaningful information is an extremely complex and challenging task. Humans do that all the time without consciously thinking about it. We correct grammar mistakes, resolve ambiguities, and infer meaning that isn’t explicitly stated. Natural Language Generation (NLG) is a method of creating content from computer data. It works as an interpreter and changes over the modernized information into natural language. In this, content is created based on gathered data and information given by the client. It is the particular language preparing errand of creating a natural language from a machine language framework. NLG has the potential to replace human writers in future, but to maintain the ideal emotion can be a challenge. It is a complex challenge for AI to imitate an exact human feeling and emotion in writing! Companies such as MindMeld, Yummly, EnglishCentral are working towards more clarity when it comes to natural language processing.

6. AI-Based hardware

Through new illustrations and central processing and handling gadgets precisely planned and organized to execute AI-based tasks. AI-based silicon chips can be embedded directly into portable devices. AI performance has improved by infusing machine-learning capabilities with high-bandwidth CPUs and GPUs specialized AI accelerators and high-performance networking equipment. To maintain this trajectory, new thinking is needed to accelerate AI performance scaling to match to the ever-expanding AI workload complexities. Such amalgamation can open new vistas in AI-Based hardware in the coming years.

7. Decision management

Intelligent machines are fit for acquainting rules and rationale with AI frameworks so one can utilize them for introductory arrangement/preparing, progressing support, and tuning. AI and decision management systems can support companies in making logical decisions by providing up-to-date and relevant information and performing analytic functions. AI’s capabilities help these decision management systems in translating customer data into predictive models of critical trends. Decision management includes various applications to support and execute mechanized choices, making the business beneficial. IBM and Oracle offer this feature already.

8. Robotic Process Automation

The acronym RPA stands for robotic process automation. RPA automates business workflows, or clerical processes, by emulating human interaction within a graphical user interface (GUI). Boston Dynamics-style robots are not involved here, as they don’t have a physical presence. In essence, the “robots” are software agents that, like all software, do work in a digital space, processing inputs and data.

Robotic processes automation utilizes contents and strategies that copy and robotize individual assignments to help corporate procedures. It is especially valuable for circumstances while procuring people for a particular activity or task is excessively costly or wasteful.

9.Biometrics

The physical biometric solutions use distinctive and measurable characteristics of particular parts of the human body, such as a person’s face, iris, DNA, vein, fingerprints, etc., and transform this information into a code understandable by the AI system.

This innovation can distinguish, gauge, and dissect human conduct and physical parts of the body’s structure. It takes into consideration increasingly regular collaborations among people and machines, including associations identified with contact, picture, discourse, and non-verbal communication acknowledgement. It is significant for the statistical surveying field.

10. Cyber Defense

Cyber defence is a computer organized protection system that spotlights on forestalling, distinguishing, and giving favorable reactions to threats or dangers to infrastructure and data. Artificial Intelligence and Machine Learning are used to move cyber defense into another transformative stage. Interestingly, when security teams struggle to perform adequately, AI supports security teams to scale their operations, monitor cyber systems and detect cyber breaches, data theft and other such issues along with detecting complex cyber attacks. 

Today, systems generate a colossal amount of data, and AI is rapidly surpassing human ability for this challenging task. Humans cannot find the attack elements fast enough, while in comparison, computers excel in these operations. It can even help by offering suggestions to security teams of processes to handle them and aware them of any possible risky scenario.

11. Digital Twin

Digitalization and new technologies, such as digital twins are helping business to step ahead further. It allows industrial companies to develop speed, efficiency, quality and flexibility in an unprecedented way. The first benefit of a digital twin is the ability to produce simulated data. The second benefit is the ability to plan and test new features. A digital twin is a product that conquers any hindrance between physical frameworks and the advanced world. The twins are essential lines of programming code, yet the most intricate renditions appear through 3-D PC computer-aided drawings loaded with intuitive graphs, outlines, and data points.

12. Peer-to-peer networks

With the advancement of network technologies, availability and popularity of streaming media contents over the P2P (Peer-to-Peer) networks have proliferated in recent years. However, how to efficiently search a requested streaming media among P2P peers is still a problem which causes a severe user delay and limited hit ratio. peer-to-peer networks are the most democratic networks in the computer world. Each peer is equal to the other, and each peer has the same right and duty as the others. The primary goal of peer-to-peer networks is to share resources and help computers and devices work collaboratively, provide specific services, or execute specific tasks.

13. Marketing Automation

Marketing automation permits organizations to improve commitment and increase proficiency to develop revenue faster. It utilizes programming to automate client division, combine client information and campaign management, streamlines iterative assignments, permitting strategic personalities to return to do in what they specialize. AI-powered intelligent orchestration helps many of the manual and rule-based aspects of marketing automation. This automation can increase efficiency and reduce errors which is often created by manual processes. The difference between lead generation and account-based marketing strategies will become minimal, which will help companies to move to hybrid strategies depending on the target market, business goals, channel performance, and level of sales engagement.

14. Leading Big Data to innovation

The folks at McKinsey in their May 2011 report, ‘Big data: The next frontier for innovation, competition, and productivity’ come up with the term “Big Data.” Big data helps in deep learning which will serve as a vital variable in the new AI growth equation. Big data’s tools continue to provide solutions for managing the constant flood of data and information. A recent study conducted by IDC expects the worldwide data creation may grow upto 79.4 zettabytes by 2025, surprisingly it is ten times the amount of data produced in 2017.

The most energizing part about experiencing an advanced transformative stage is that it keeps the organizations on their feet while working in an on-request advanced world. Through big data, AI can fetch information which uplifts advanced targeted marketing, predictive product development, proactive customer service, efficiency improvements, cost reduction, and so on. Be that as it may, overall, the arbitrariness, such factors can be combined utilizing Artificial Intelligence and Data Abilities.

15.Driving to better business decisions

To turn into an intelligent enterprise, associations need to place assets into three key zones: an insightful suite, keen advancements, and a digital platform. Information is the core of any association even though IT groups need to buckle down concerning delivery operations and data management.

The organization’s product portfolio incorporates a SaaS-based gathering associate and a memory enhancement device. They are ceaselessly putting resources into growing new advances to make programming items increasingly coordinated, client-cantric investigation driven, and AI driven. The organization’s key center territories incorporate cloud infrastructure, digital transformation, business analytics and data engineering. AI comes with a lot of possibilities when comes to driving better business decisions.

16. Help in Unbiased Decision Making

AI has entered in diverse sectors of human existence where its importance lies in a great number of things, starting from assessing loan applications, helping to identify patients who should receive treatment, or supporting courtroom decisions and so on. AI module in decision making is getting acceptance as it is free from the most fundamental flaws of humans which is ‘bias’. Algorithms are good for an unbiased judgement, as it is run by code that governs them, and the data to teach them. But the problem is it can carry the watermark of human preconceptions, for example, facial recognition software misclassifies dark faces or fail to identify women, and the criminal profiling algorithms have ranked according to skin color or birth place, and recruitment tools have scored women lower than men. But these biased challenges in AI module can be solved. There has been mounting responsibility on technology giants to fix them for a more unbiased and quick decision making.

17. Supporting Emergencies

The world has witnessed its worst humanitarian crisis, from drought, to famine or war; not to forget about the ongoing pandemic. But artificial intelligence can help to control these situations and come up with smart solutions. Researchers working with the UN and other world organizations have been building algorithms which can use data on economic growth, energy generation, population control and food production to predict future migration crisis or other possible disaster situations. The US’s Political Instability Task Force and the Alan Turing Institute in the UK to name a few, have been building AI that is capable of predicting where future conflicts may occur or some such future scenarios. The machines can estimate the likelihood of violence escalating in trouble spots using statistical data, military reports, and analyzing news reports for signs of rising tensions. The statistical data also helps in predicting any natural disaster and supporting amid those situations.

AI for more humanitarian use……

Advantages of AI in business is undeniable. It has curved the path for a brighter future in the world economy, through better technology, business model, market strategy, and personal wellbeing. But apart from all these, features of artificial intelligence technologies are showing great possibilities for a better sustainable world. It is showing real prominence in supporting the three primary and instinctive needs of human existence, i.e. food, healthcare and education.

18. Digital Education and Workforce Development

AI applications accelerate across many sectors, we must reimagine our educational institutions for a world where AI will be ubiquitous, and students will be able to get different kind of training than they are receiving currently. The student fraternity yet not fully receiving education and instruction to build the types of skills that will be required for an AI-dominated landscape. But those days are not far when AI will take charge to train human brains! It is not only the technical skills that are needed in an AI dominated world but skills of critical reasoning, collaboration, visual display of information, design, and independent thinking, are among others. An AI trained brain is more likely to use AI more aptly to rebuilt the future world.

In 2017, the National Science Foundation funded for over 6,500 graduate students in computer-related fields and launched several new initiatives thoughtfully designed to encourage data and computer science at all levels. 

19. AI Enabled Agriculture

The world’s population is expected to upsurge significantly over the next three decades, but the capacity for food production may struggle to keep up the pace with crop production. AI is adding efficiency in the current farming methods to increase production and reduce wastage without adversely affecting the environment. Reduce overlap in agricultural processes such as planting, tilling, and fertilizing, can reduce chemical use and increase productivity in farming. Sensors proliferate on farms, and drones can capture real-time images of the vast amounts of farmland condition amid any natural disaster or crop disease. AI machines will be able to support farmers foresee the requirements of the crops and farms potentially over a year in advance, to give them enough time to get ready to deal or cope up with the upcoming adverse conditions.

Cainthus, a machine vision company, has come up with another approach. It has created a facial recognition system using deep learning, that can identify individual cows by their facial features in maximum six seconds, enabling vast herds to be monitored with minimal human involvement. The company is heading to detect early signs of injury or illness in a farm animal based on its body shape and can alert the farmer accordingly.

20. Making health care smarter

Diagnosis and treatment of disease have been a focus of AI since at least the 1970s. But the support is mostly present in research labs and tech firms, rather in clinical practice. Tech firms and startups are working assiduously on the same issues. Google is collaborating with the health delivery networks to build prediction models with the help of big data to aware the clinicians of high-risk conditions, such as sepsis and heart failure and so on.

Patient engagement and adherence have long been seen as the ‘last mile’ problem of healthcare, as the final barrier is between ineffective and good health outcomes. The more patients proactively participate in their wellbeing and care, the better the outcomes – utilization, financial results and member experience. Such healthcare factors are increasingly being addressed by big data and AI.

Conclusion

In the end of the discussion one can say, AI has made tremendous efforts in understanding intelligence and has given a breakthrough variety of applications in every field. It always excites and surprises with innovations and ideas. Though a number of inventions are still waiting. AI is keen on building an entire world functioning on AI for us. We can conclude by saying, yes, machines can learn and fit-in, when the information is imparted in an appropriate scientific way, and AI features can re-organize the world in its own interesting way!