Credit by Ankit Rathi
Artificial Intelligence (AI) is becoming an important part of our daily life, in social as well as the business environment. From healthcare to the military, this technology is being introduced in all the sectors to reduce human effort and give an accurate and faster result.
We are fortunate to live in this generation, which is full of technological advancements. Now we live in a time where a lot of work is taken over by machines & software. AI has a special place in all the advancement made today. As we know that AI is the science of computers and machines developing intelligence like humans. In this technology, the machines can do some of the simples to complex tasks that we as humans need to do regularly.
The AI systems are capable enough to reduce human efforts in numerous areas. To conduct different operations in the industry, many of them are using artificial intelligence to create machines that perform various activities regularly. The artificial intelligence applications help to get the work done faster and with accurate results.
While AI has been very useful in many domains like healthcare, automotive etc, there are some general advantages you get in any field by applying AI. Let us have a look at some of them:
1. Daily operations
Computed methods for automated reasoning, learning and perception have become a common phenomenon in our everyday lives. We have our Siri or Cortana to help us out.
The smartphone is an apt and everyday example of how we use AI. We are also hitting the road for long drives and trips with the help of GPS. In utilities, we find that they can predict what we are going to type and correct the spellings. That is machine intelligence at work.
When we take a picture, the AI algorithm identifies and detects the person’s face and tags the individuals when we are posting our photographs on social media sites.
2. Fewer Errors
AI helps us in reducing the errors and the chance of reaching accuracy with a greater degree of precision. It is applied in various studies such as exploration of space.
Intelligent robots are fed with data and are sent to explore space. Since they are more resistant and have a greater ability to endure the space and hostile atmosphere due to their metal bodies. They are built and acclimatized in such a way that they cannot be altered or get damaged or malfunction in a hostile environment.
3. Repetitive Tasks
Repetitive tasks are monotonous in nature can be carried out with the help of machine intelligence. Machines think faster than humans and can be put to multi-tasking. Machine intelligence can be employed to carry out dangerous tasks. Their parameters, unlike humans, can be adjusted. Their speed and time are calculation based parameters only.
When humans play a computer game or run a computer-controlled robot, we are actually interacting with artificial intelligence. In the game we are playing, the computer is our opponent. The machine intelligence plans the game movement in response to our movements. We can consider gaming to be the most common use of the benefits of artificial intelligence.
4. Difficult Exploration
Artificial intelligence and the science of robotics can be put to use in mining and other fuel exploration processes. Not only that, these complex machines can be used for exploring the ocean floor and hence overcome the human limitations.
Due to the programming of the robots, they can perform more laborious and hard work with greater responsibility. Moreover, they do not wear out easily.
5. Digital Assistants
Highly advanced organizations use ‘avatars’ which are replicas or digital assistants who can actually interact with the users, thus saving the need for human resources.
For artificial thinkers, emotions come in the way of rational thinking and are not a distraction at all. The complete absence of the emotional side, makes the robots think logically and take the right program decisions. Emotions are associated with moods that can cloud judgment and affect human efficiency. This is completely ruled out for machine intelligence.
6. Availability 24x7
Unlike humans, machines do not require frequent breaks and refreshments. They are programmed for long hours and can continuously perform without getting bored or distracted or even tired.
1. AI for Good
‘AI for Good’ is a United Nations platform. It is centred around an annual Global Summit that promotes the exchange on the beneficial use of AI by building specific projects. The purpose of organizing global summits that are action-oriented, came from an existing discussion in AI research being dominated by research streams such as the Netflix Prize (improve the movie recommendation algorithm). The AI for Good series aims to bring forward AI research topics that contribute towards more global obstacles, in particular through the Sustainable Development Goals, while at the same time avoiding typical UN-style conferences where results are usually more abstract.
The main purpose of healthcare AI applications is to examine relationships between prevention or treatment techniques and patient outcomes. AI programs have been built and implemented to practices such as diagnosis processes, treatment protocol development, drug development, personalized medicine, and patient monitoring and care. Many medical institutions have developed AI algorithms for their departments.
Large technology companies and even startups have also developed AI algorithms for healthcare. Additionally, hospitals are looking to AI solutions to support operational initiatives that increase cost-saving, improve patient satisfaction, and satisfy their staffing and workforce needs. Companies are also developing predictive analytics solutions that help healthcare managers improve business operations through increasing utilization, decreasing patient boarding, reducing the length of stay and optimizing staffing levels.
In agriculture, new AI developments show advances in gaining yield and to increase the research and development of growing crops. AI now predicts the time it takes for a crop like a vegetable to be ripe and ready for picking thus increasing the efficiency of farming. These advances go on including Crop and Soil Monitoring, Agricultural Robots, and Predictive Analytics. Crop and soil monitoring uses new algorithms and data collected in the field to manage and track the health of crops making it easier and more sustainable for the farmers.
More specializations of AI in agriculture is one such as greenhouse automation, simulation, modeling and optimization techniques.
Due to the rise in population and the increase in demand for food in the future, there will need to be at least a 70% boost in yield from agriculture to support this new demand. More and more of the public perceives that the adaption of these new techniques and the use of AI will help reach that goal.
The Air Operations Division (AOD) uses AI for the rule-based expert systems. The AOD has use for artificial intelligence for surrogate operators for combat and training simulators, mission management aids, support systems for tactical decision making, and post-processing of the simulator data into symbolic summaries.
The AOD also uses artificial intelligence in speech recognition software. The air traffic controllers (ATCs) are giving directions to the artificial pilots and the AOD wants the pilots to respond to the ATC’s with simple responses. The programs that incorporate the speech software must be trained, which means they use neural networks. This is an early stage of the program that has plenty of room for improvement. The improvements are imperative because ATCs use very specific dialogue and the software needs to be able to communicate correctly and promptly every time.
AI-supported Design of Aircraft is used to help designers in the process of creating conceptual designs of aircraft. This program empowers the designers to concentrate more on the design itself and less on the design process. The software also allows the user to focus less on software tools. The AIDA uses rule-based systems to compute its data. This is a diagram of the arrangement of the AIDA modules. Although simple, the program is proving effective.
Haitham Baomar and Peter Bentley are leading a team from the University College of London to develop an artificial intelligence-based Intelligent Autopilot System (IAS) designed to teach an autopilot system to behave like a highly experienced pilot who is faced with an emergency situation such as severe weather, turbulence, or system failure.
One of the more promising innovations is the idea of a personal AI tutor or assistant for each individual student. Because a single teacher can’t work with every student at once, AI tutors would allow for students to get extra, one-on-one help in areas of needed growth. There are many new possibilities due to what has been coined by The New York Times as “The Great AI Awakening.” One of these possibilities mentioned by Forbes included the providing of adaptive learning programs, which assess and react to a student’s emotions and learning preferences.
Many teachers fear the idea of AI replacing them in the classroom, especially with the idea of personal AI assistants for each student. The reality is, AI can create a more dystopian environment with revenge effects. It is inevitable that AI technologies will be taking over the classroom in the years to come, thus it is essential that the kinks of these new innovations are worked out before teachers decide whether or not to implement them into their daily schedules.
Artificial Intelligence has inspired numerous creative applications including its usage to produce visual art. The recent AI-based exhibitions provide a good overview of the historical applications of AI for art, architecture, and design. These exhibitions showcasing the usage of AI to produce art include the Google-sponsored benefit and auction at the Gray Area Foundation in San Francisco, where artists experimented with the DeepDream algorithm. The Association of Computing Machinery dedicated a special magazine issue to the subject of computers and art highlighting the role of machine learning in the arts.
8. Finance & Economics
The 1980s was really when AI started to become prominent in the finance world. This is when expert systems became more of a commercial product in t