Emerging Technologies: Artificial Intelligence

Emerging Technologies: Artificial Intelligence

Introduction

Artificial intelligence has been a focus of much research for years and is still the most comprehensive subject of computer studies. AI is basically the capability of a machine to think of logarithms applied in various issues, such as playing board games.  It has applications in varied away in which computers are operated in the society.

Artificial intelligence is actually the simulation of human intelligence in devices such as computers. The machines are programmed to mimic the actions of human beings, such as solving problems and even learning. AI can be rational and be in a position to execute specific goals and purposes. Due to technological advancement, the objectives and goals of artificial intelligence seem to be ever-changing and advancing as well. The evolution of AI tends to benefits society in various sectors. For instance, machines are designed by the use of a cross-disciplinary strategy based on computer science, psychology, linguistic, and more. Artificial Intelligence, as a term, was originally suggested by John McCarthy in 1956. There have been various efforts in trying to make a machine to handle some task that was meant for human beings, Alan Turing in his book remarked that devices could be developed to mimic humans and have the ability to handle specific intelligent things such as playing chess. There have been recommendable advances made in search algorithms, in which machines are able to learn algorithms and incorporate statistical analysis in comprehending and perceiving the world. For example, the machine is currently used to pilot space, examining the history of purchase and influencing the decision in the marketing and business world at large. There has been a tendency to redefine the meaning attached to the term ‘intelligence.” This study is to determine the trends and emerging issues in Artificial intelligence as one of the emerging technologies.

Literature Review

The research on artificial intelligence (AI) has been conducted several in an attempt to determine how machines can be designed to use language, solve problems, form context, and improve their operations. Many researchers and inventors had a different definition of the term AI.

Baker and Smith (2019) gave a full description of AI as computers that perform cognitive tasks such as learning and solving problems, normally linked with the minds of human beings. They further stated that AI defines various technologies and approaches, which may include natural language processing, learning, an algorithm, data mining, or neural networking.

AI in education (AIEd)

AI has been significantly applied in education to assist in training students in almost all level from high school to higher education level, some of the software applications that are used in education include: intelligent virtual reality, intelligent support for collaborative learning and personal tutors. For instance, the smart tutoring system (ITS) can be applied to facilitate direct private tutoring. The ITS can be used in making decisions about a learner’s learning path and selection of content and involve the specific student in a dialogue based on algorithms, neural network, and learner models. AIEd has to be regarded be of significance when it comes to distance learning institutions that operate modules with numerous students.

Learning in a social exercise such as collaboration and interactions are at the core of the process of learning (Jonassen et al.,1995), but the online interaction needs to be effectively moderated(Salmon, 2000). AIEd can enhance collaborative learning an=d teaching by promoting the formation of groups based both teaching and learning models, for example, a summary of discussions, enhancing online interaction of different groups hence guiding students in achieving the set objectives of a course.

AIEd has been able to offer immediate feedback and assessment due to the availability of big data and learning analytics. The systems in place have enabled for an ongoing student achievement. For example, algorithms have been applied to enhance predictability that a student is probably going to fail or drop out of a course with a high degree of accuracy (Bahadır, 2016).

Currently, AIEd is perceived in a different dimension, that is, system-facing, tutor-facing, and learner-facing (Baker and Smith 2019). The AIEd tools offer insight into the process of learning of students to enable tutors to provide assistance and support where required proactively. Every system has its unique role to play, but all are inter-linked to serve a common purpose of promoting and enhancing learning, for example, the system-facing tool tends to offer the needed information for the administration at the institutional level.

AI and the Internet of Things

The Internet of Things (IoT) and sensors can manage big data; however, artificial intelligence can effectively learn patterns in the data to automate various tasks for various purposes, such as in the business sector. AI can be integrated into any Analytics Program by feeding the strategy around it into a business strategy by considering the process, the convergence of people, and the existing technology.

Opportunities due to Working together with AI: AI partnership

Artificial intelligence tends to compliment the human in conducting various tasks by augmenting the human abilities and enhance even a more effective production. There are several opportunities than encompass the partnership with AI. The benefits include the following: promoting analytics to firms and domains in cases where it is under used, facilitating the performance of existing analytic technologies, breaking down economic barriers such as translation barrier, and providing a more convenient understanding and better memory.

Importance of artificial intelligence

Over the decade, many researchers have tried to focus on the various importance of AI to humanity, economy, and society. There is an argument that AI was never developed to replace humankind but rather assists in multiple tasks and makes work relatively more comfortable, more convenient, and faster. AI has currently enhanced repetitive discovery via data by conducting regular high –computerized volume roles without getting bored or feeling of fatigue; regardless of the automation, the human is still considered vital in designing and programming the systems.  AI further enhances the existing products by adding intelligence; the device with already installed systems of AI is offered to people. The installation of AI has assisted in improving various technologies in various sectors, such as in the workplace.

Moreover, I tend to adapt via progressive learning algorithms to enable data to initiate programming by finding regularities in data for the algorithm to attain a skill. The AI has a propagation tool that makes it to adjust via training. Again, AI analyses more data by the application of a neural network that have several hidden layers. Due to computer big data even fraud detection system is currently operational, that is, the more data fed, the more accurate the system tends to be. Finally, AI attains recommendable accuracy via a deep neural network. For instance, interaction with Alexa is due to deep learning; the deep leaning has also enabled the detection of cancer on MRIs with a high level of accuracy.

The challenges of using artificial intelligence

Artificial intelligence has been of significance to various industries; however, it has some limits. One of the limitations is that AI tends to learn from the fed data into the system exclusively, and this proves to bet the only way in which knowledge can be incorporated and leaving no space for alternatives. Therefore, any layers that are added or analyzed have to be conducted separated. Currently, the systems are designed to carry out strictly defined tasks. For example, a system that plays poker cannot perform a double task and maybe drive a car; that is, the systems vary in terms of specialties.

Methodology   

Assessing and evaluating artificial intelligence as one of the emerging technologies in the digital world is critical to find the real picture of the innovation. AI is obliged to identify the needs, demands, requests, and expectations of machines in trying to mimic human actions. This study focused on the AI. AI analysis was initiated, and then a survey to Information Technology supervisors and experts was administered. The information that was retrieved was then cross-checked. Firstly, the web-page was analyzed, and physical visits to the location were conducted to validate the information provided on the AI support systems in various sectors. In the research, the Systems Development Lifecycle (SDLC) was used to provide a template for the designing process. The SDLC approach specified particular activities allocated to every stage of development. It has been the most widely used methodology for system development, and although modern techniques and processes are gaining popularity is still seen as having a significant place in system development.

How artificial intelligence works

AI operates by incorporating a large amount of data with interactive quit processing and intelligent algorithms, enabling the software to learn from the characteristics of data automatically. The AI as a field has many theories and technologies.it also has various subfields, some of which include:

• Machine learning-this This automates analytical model building. It applies strategies from neural networks, operations research, and statistics to retrieve hidden insight in data with not being programmed on what to conclude.
• A neural network-this is made up of interlinked units which process information by way of responding to external groups and having to relay information between every unit. However, the process needs several passes at the data point to be able to retrieve connections and derive meanings based on the data that is not defined.
• Deep leaning-it applies big neural networks in several layers of processing units to be in a position to learn complicated patterns. Some of such applications include speech recognition and visualization.
• Cognitive computing-it strives to mimic human-like interaction with devices. This is employed to enable machines to effectively stimulate human processes via the capability to interpret images and speech and coherently speak in response accurately.
• Computer vision-this depends on the recognition of pattern and deep learning to identify and interpret picture and videos. Therefore, machines can be in a position to capture videos and images in real-time and even interpret their surroundings. Natural language processing (NLP) allows computers to analyze, generate, and comprehend human language.

Other technologies that support AI

Graphical processing units which provide computing power that is needed for effective iterative processing. The internet of things generate huge massive amounts of data from connected machines.  Advanced algorithms employed to analyze more data comprehensively and in a faster way. Again, intelligent processing is critical in determining rare events, comprehending complicate systems, and optimizing unique scenarios. Moreover, application programming interface technologies also support AI since they are portable packages of codes, and they can add image recognition that defines data and build captions. Overall, the goal of AI is to offer software solutions that can be rational in terms of input and output by providing human-like interactions with software and support specific tasks.

Would you recommend the technology or practice? What factors guide your decision?

I would recommend artificial intelligence to be adopted in various sectors as it tries to help in solving multiple human tasks and even make them more effective and faster. I fell that AI would probably have to deal with lower errors as compared to human beings, if code in a right manner, and would enhance speed and accuracy. AI cannot be negatively impacted by the adverse environment when conducting a specific task by enduring tasks that would otherwise kill humans if done directly.  AI systems are also recommendable in performing task that tends to be repetitive and laborious.  They can also recommend or even direct actions by predicting what a user search due to the advancement in technology,  a system that has in detection of fraud in cared-based systems. Additionally, AI can logically think within having to initiate emotions and thus working more accurately with speed.

Some of the elements, such as the Virtually-reality continuum, tend to inform my decision; for example, Replika is available on smartphones.

How does artificial intelligence relate to data visualization?

Artificial intelligence and data visualization are connected through data. Data is exclusively applied in AI in ether teaching or creating content. For instance, a humanoid robot is designed based on data. The machine is fed with specialized algorithms to enhance deep machine learning and also developed to respond while at the same time processing each piece of available information for the purpose of predictive analysis.AI systems tend to function almost in a similar manner to that of data analysts since both use incoming aggregate data to be able to efficiently make decision and predictions.

Data visualization applies algorithms to develop images from data to enable humans to understand and react to that particular data adequately. Artificial intelligence development is aiming to understand specific data the same as a human. Nonetheless, AI development is due to human striving, and its designers apply data visualization to achieve that purpose. AI techniques have the potential to transform how data visualization is conducted.

Conclusion

The artificial intelligence system has attempted to address some of the issues to try and assist human beings in conducting various tasks. AI has been more acute and speedy. The research attempts to address the general problems regarding AI from advantage, importance, and changes, and even how it works. However, one of the problems is in finding out how AI enhances how to teach a machine to think; yet, to articulate “feelings,” current computers can understand and analyze intelligence and though same as human beings. There is still more advance regarding AI in trying to effectively find a way in which a machine can effectively mimic the action of human and feelings and also design programs that prove interesting to interact within our society.

References