Article | July 30, 2020
With the release of MariaDB Platform X5, we’ve added new tooling and features that offload development complexity so developers can focus on creating innovation solutions. MariaDB Platform X5 includes MariaDB Enterprise Server 10.5, pluggable engines (such as InnoDB, ColumnStore, MyRocks, Spider and now Xpand), connectors, and the MaxScale database proxy. And because there’s so much that’s included with the MariaDB Platform X5 release I figured it might be best to start with the high points before drilling down into more details in the future.
Article | July 30, 2020
If you think the conventional way of designing and testing an Internet of Things (IoT) device is still relevant today, you might be wrong. Tens of billions of IoT devices surround us today. Billions more will connect to the internet in the next few years. On top of that, IoT deployment is diversifying from consumer-based to mission-critical applications in the areas of public safety, emergency response, industrial automation, autonomous vehicles, and healthcare IoT. While IoT devices offer great convenience, having large numbers of them in a small space increases complexity in device design, test, performance, and security.
Article | July 30, 2020
With the introduction of Siri and Alexa, AI has transformed our lives with speech-to-text implementations. Scientists are working their brains to make machines as intelligent as they can be. The introduction of AI in the fields of healthcare, security, entertainment is already at its peak. Thus, parallelly AI is being introduced to make work easy in the field of education, transportation, and everything else.
The implementation of artificial intelligence in LMS- learning management systems is proved to be a breakthrough in education. The company with AI implementation is paid 40% more than the one without AI.
In the current scenario, the world had adapted to the e-Learning platform and its techniques tremendously. Standard LMS is already being utilized widely. However, although it has proved to be a great success in revolutionizing the education sector, it still has a long way to go. And this long way can be easily covered with its opportunity with AI.
Before we learn the advantages of artificial intelligence in education, let us educate you about the limitations of standard LMS.
Limitations of standard LMS
The age-old teaching methods were scientifically and innovatively transformed into a standard LMS. The learning management systems have all the content managed in one place. Evaluators can track progress, give ratings and recommend courses on one platform. The digital learning platform offers a plethora of learning, teaching, and evaluating techniques, but it still has its limitations.
• The standard LMS requires a lot of manual labor.
• They require human effort to keep the content up-to-date.
• They are trainer-focused rather than learner-focused.
• It requires tedious effort to introduce different learning styles.
The application of AI-based LMS removes all the above limitations and much more. It will streamline the learning process in a better way and provide endless learning opportunities.
How will artificial intelligence in LMS prove to be valuable?
The standard LMS has standard content data fed into it. Therefore, all the employees, students, or trainees follow the same procedure of the standard learning module. This is where the application of artificial intelligence in LMS transforms the system.
AI enables the LMS to design the learning process according to the individuals opting for the course. For example, if a student/employee chooses a particular course, he can choose whether to read the lessons, watch videos, or study it in any other way. Thus, when a learner learns a course in his kind of way, he grasps and understands well.
AI also understands the weaknesses and strengths of the learner and recommends future courses accordingly. Even the quizzes and tasks are determined based on the learner’s knowledge level. So, every learner has a personalized learning course, and a content module in AI-based LMS curated exclusively for him.
Automated evaluations and suggestions
This is the best advantage when you are transforming AI with LMS. The evaluation process and the suggestions for the future (based on those evaluations) will be immaculately automated. Also, the employers will benefit as they will not have to keep track of employers progress, learning, or training schedules. The support of artificial intelligence in LMS will make this process seamless for employers.
It gets more manageable for the managers to track employee’s growth and training. The AI process guarantees faster, convenient, and reliable results. Based on the performance and the results generated, the employer can grant rewards, growth, recognition, and appraisals to the employees. In addition, advanced analytics allows employers to obtain detailed information about the learner’s progress and understanding.
With such a positive outlook towards growth, learning, and training, companies' employee retention rate and ROI with artificial intelligence in LMS are high.
Personalized Learning Module
The learning module of artificial intelligence in LMS is designed to increase the effectiveness of any learning course. The system design courses for learning in minimal time. As a result, the functioning of the LMS module in AI is made engaging and intuitive.
Why is it that a learner does not complete his training or does not find it engaging enough? 70% of learners have blamed the content or activity procedure for being boring. This is where the AI-induced LMS proves its worth.
This system curates content based on the learner’s interests and then designs the training module accordingly. Thus, the exclusive learning experience is what makes your employer feel connected to the organization.
Chatbots and virtual assistants
When an employer seeks training, he/she has several questions. These questions need to be answered by the trainer as per the standard LMS. However, some employees will refrain from asking questions due to many possible reasons. This is where chatbots play an essential role.
Chatbots are an essential part of artificial intelligence in LMS. Chatbots can answer the queries number of times till the concept is clear. Also, chatbots can predict the questions in a learner’s mind by analyzing their course and study behavior. Chatbots and virtual assistants provide all types of help needed by the trainees. They are a ‘learners guide’ for students.
Training beyond territories
Organizations have multiple offices across different geographical locations. Therefore, to have a training program schedule for the same department at the same time is difficult. Also, setting up the same programs for different time zones is a tedious task. This is where artificial intelligence in LMS comes to the rescue.
This enables offices to train their employees according to the convenience of the employees. In addition, the AI with LMS infrastructure allows the employer to complete the training according to their time zones with no loss of the trainer’s time and organization’s resources.
Benefits of introducing LMS with AI in organizations
If an organization introduces artificial intelligence in LMS for its organizations, it can work wonders for them. These are some of the benefits of introducing LMS with AI in your organization.
• Increase employee retention and engagement by 60%.
• Shows the employee that you care about their growth.
• Save time and money.
• Upskill your current employees efficiently.
• Generate personalized content to meet learner’s proficiencies.
To sum it all up,
By 2025, the investment of companies in AI technology is set to reach $190.61 billion. Thus, this technology assures that employees are well trained, upskilled, and perform complex tasks with minimal issues.
Duolingo is one of the best examples of using artificial intelligence in LMS. It uses natural language processing to train its chatbots and provide a personalized experience to the user. It studies the user intricately and then trains them.
Artificial intelligence in LMS can be made a part of the current HRIS/HRA system of the organization. This helps the organization achieve growth and development with minimal efforts and shows employees that they matter.
There are many factors by which AI with LMS proves better than the standard LMS - personalization being the best one. The streamlining of the training process and providing opportunities to learn in one’s way, time, and language is a win-win situation for both employer and employee.
AI may take some time to be utilized entirely as the future of learning management. But when it is executed, it will do wonders for organizations in various sectors. Of course, it will never replace humans in the training programs but will be their biggest support system.
Frequently Asked Questions
How has AI changed LMS?
Artificial Intelligence has played a significant role in changing the standard LMS. AI offers personalized learning, easy evaluation, and automation of all the tasks required in a training program. As a result, it has reduced manual efforts while enhancing the learner’s experience.
How is AI used in LMS?
AI uses the data fed into it to make decisions. It also determines the activity of the learner and provides him with personalized suggestions. It is used in a chatbot to provide answers and guidance to learners anywhere and anytime.
What is the future of AI in LMS?
The future of AI in LMS is as bright as it can. AI will suggest, evaluate and automate pieces of training for the learner. It will answer questions and let the learner study according to his convenience and interests. Employers will have a reduced cost of training and a high retention rate once they implement AI in LMS.
"name": "How has AI changed LMS?",
"text": "Artificial Intelligence has played a significant role in changing the standard LMS. AI offers personalized learning, easy evaluation, and automation of all the tasks required in a training program. As a result, it has reduced manual efforts while enhancing the learner’s experience."
"name": "How is AI used in LMS?",
"text": "AI uses the data fed into it to make decisions. It also determines the activity of the learner and provides him with personalized suggestions. It is used in a chatbot to provide answers and guidance to learners anywhere and anytime."
"name": "What is the future of AI in LMS?",
"text": "The future of AI in LMS is as bright as it can. AI will suggest, evaluate and automate pieces of training for the learner. It will answer questions and let the learner study according to his convenience and interests. Employers will have a reduced cost of training and a high retention rate once they implement AI in LMS."
Article | July 30, 2020
Depicted as a natural predisposition to form groups of work, teamwork has been popularized through history as a central feature of organizational change programs that advocates empowerment and disruptiveness. The suasive force of discourse regarding the ineluctable essence of teamwork as a tradition and custom founded on some inclination for humans to work cooperatively, create a set of “rituals”, conventions and practices which invite to innovation, flexibility and creativity.
Teamwork as “human nature” was a common thread all through history and management literature. The team-based nature of early human activities can be traced to hunter-gathering in societies where orality was the prime source of communication. The locus communis was the collective memory (facts, rules, code of conduct, religious beliefs and practical knowledge). The pneumonic function of the verse will fulfil a didactic function as a way of memorizing any content in order to systematize a conceptual theoretical primitive language. In preliteracy times, doctrines and their conservation were highly dependent of the spoken word and memory (Havelock, 1957, 1992). Thus, in an oral culture experience is “intellectualized” mnemonically (Ong, 1982). In a sociobiological perspective, aspects of teamwork behaviour allude to a biologically determined “natural history of species”.
According to Katzenbach and Smith (1993) “teams- real teams and not just groups that management call “teams” should be the basic form of performance for most organizations, regardless the size”. This statement clearly sets the basis for the team as a natural building block of any organizational design. Buford (1972) in a comprehensive study of Ancient Greek and Roman craftmanship interpreted teamwork in a very familiar approach we understand it today: collaborative work, multiskilling, mutually interdependent tasks. There were technical divisions of labour based on skills, the relationship between mentor and apprentice and so on. The greatest craftsmen were expected to be versatile in different skills, but the coordination of work efforts was left to the so-called professional cadre of engineers, architects and masters.
With the advent of Capitalism, the massive growth of the economic activity claimed for reorganization. A new form of discourse emerged, our prehuman origins and modes of communication becoming codified and formalized as the scientific disciplines of evolutionary biology, economics and linguistics respectively (Foucault, 1972). Within the economic discourse, there was a creation of a distinct managerial object, which opened new domains of knowledge and professional practice.
The mythical traditions of teamwork replicated in today’s contexts and the “tribal” notion of team popularized by Codin (2008) paves the way to concrete changes in the form we perceived our working environment. The analogy of team as “family” so common in the corporate world which in its essence represents our first experiences as a community is not a happy term anymore, since in a manner it could go against the interests of today’s organizations. Therefore, in building a healthy sustainable workplace culture teams cannot be perceived as family. Teams have a commitment to a common goal, clear expectations and performance.
The MetaQuant: From siloed work to interdisciplinary collaboration
With the paradigm shift to automation, organizations are taking actions that promote scale in AI through the creation of a virtuous circle.
The central overarching question is: Are traditional ML teams good enough to develop models able to achieve long lasting competitive advantage?
“In a world spinning around AI, competition among institutions seems to be fierce while mayor obstacles appear on the way: recruiting top talents is not only time-consuming but also high-priced, or just trying to find a balanced approach to talent, meaning "reshaping" the old-school computer scientists into quants, is critical in terms of AI implementations. The big winners: those firms that integrate AI with human talent” (Litterio, 2020: 167).
Successful machine learning (ML) projects require professionals beyond engineering expertise. AI has the biggest impact when it is developed by dynamic creative cross-functional teams. The move from functional to interdisciplinary teams initially brings together the diverse skills and perspectives to build effective tools.
In order to bring theory into practice, and in the need of a novel conceptual framework design, I have coined the term MetaQuant.
The MetaQuant is a new breed of market players, who “translates human language into signals” and "reads" the data from a holistic perspective identifying patterns within the linguistic and symbolic constructs. The MetaQuant is the linguist, the semiologist, the sociologist, the cognitive psychologist and the philosopher or rather a combination of these intertwined profiles which will fuel the potential for information advantage providing a unique core differentiator transforming data into knowledge. In this sense, the MetaQuant has emerged as a crucial component of any AI model paving the way for a novel insight where hybridization is critical. The formula for a successful organization in a discovery-driven environment is the MetaQuant + The ML team. And eventually the Quantum Computing Expert. Finding the needle in the haystack can be a competitive difference maker.
Creative thinking, actionable insights, collaboration, proficiency, flexibility, shared vision and training are the ingredients for an elite team.
It is vital for organizations to establish workflows that empower everyone to play a role in order to move projects from test to deployed AI/ML. Yet, knowing how to do ML is not the same as being proficient with it and knowing how to implement a ML model end-to-end is not the same as using ML creatively to build solutions to real-world problems, to explore and assess potential applications specific in competitive contexts.
Ideally, when selecting members for your elite team, it is advisable to make a first distinction between those who wish to do research in ML from the ones who wish to apply ML to your business problems. Both are of major importance alike. The instreaming of new talent brings in novel ideas which can positively impact the work culture.
Demonstrating flexibility is a significant asset. Since ML projects may encounter all kinds of roadblocks, being able to easily change tactics to overcome obstacles without getting frustrated or losing sight of the end goal is key to deliver projects.
Mentoring and inspirational leaders is greatly valued when designing a ML team. An exceptional team leader is the one who shares a unique perspective and knowledge. Experience in the field is a substantial source of wisdom within the organization. Having a passion for diversity of input and fostering a healthy culture of support distinguishes average from excellent ML teamwork.
Educating everyone is the dictum to become an AI-first institution.
To ensure the adoption of AI, organizations need to educate everyone, from top leaders down. To this end most are launching in-house programs which typically incorporate workshops, on-the-job training to build in capabilities. Some others, and which reflects a common trend today, opt for partnerships with renowned academies or prefer the outsourced modality “training as a service” program or a bootcamp.
For an A-team, it is critical to make a mark in the ecosystem through journal publications, book chapters, white papers or lecturing in conferences. Disseminating their work and findings through meetups, workshops, and seminars is a must for building a thriving culture that promotes exchange and cross-fertilization of new ideas and technologies in a substantial way. Systematicity and coding belong to the ritualistic change of conscience.