Common task of Company Secretary Penang

A Company Secretary Penang could be considered the adhesive that holds an entire company together. He/she is accountable for ensuring the business stays in compliance with both regulative and legal requirements while additionally implementing all of the decisions, resolutions and changes presented by the corporation’s Board of Supervisors.

What Is a Company Secretary?
Generally, states require that companies assign a Corporate Secretary, which he/she is present in any way Board of Supervisor meetings. The Corporate Secretary is an officer of the company.

The exact commitments that a business’s Corporate Assistant meets might be various among companies; however, every company commonly lays out the Corporate Secretary’s role in its corporate bylaws.

What Are a Company Secretary’s Responsibilities?
Lots of people erroneously believe a Company Assistant’s primary duty is to take as well as tape meeting mins. While doing so is, certainly, among the Corporate Assistant’s responsibilities, this task is no place near the totality of this critical corporate role.

 

Board conferences: The Company Secretary plans as well as carries out all Board of Supervisor meetings and also committee meetings, consisting of strategic preparation; producing schedules; welcoming the ideal participants; scheduling the meeting space as well as covering all feasible logistical concerns. He/she also looks after the corporation’s investor meetings.
Document Keeping: The Corporate Secretary is not just in charge of taking meeting mins however also for the compound as well as dissemination of them. The meeting mins must precisely describe and successfully communicate the final decisions of the Board of Directors. Far more than just a scribe, the Corporate Assistant is the officer who implements every one of the board’s declarations.
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The Company Secretary Penang also keeps and also arranges every one of the firm’s substantial papers along with documents; a few of these may include its Certificate of Good Standing, business licenses, SEC compliance paperwork, stock transfers, proxy statements, investor communication, contracts as well as the firm’s Capitalization Table.
Expert: A Corporate Secretary ought to be willing and able to suggest a Board of Directors on its objectives as well as duties in addition to the police officers’ private duties. If the firm has any type of subsidiaries, the Corporate Secretary will certainly frequently counsel the board on how to manage as well as regulate them.
Fitness instructor: When brand-new board participants are caused to a firm’s Board of Directors, it is the Corporate Secretary that is charged with overseeing their alignment, training and also rundowns.
Traits of a Great Corporate Assistant
The most effective prospect to hold the setting of a Corporate Assistant would certainly be:

Very arranged as well as detail-oriented
An effective and also patient communicator
An exceptional problem solver
Experienced at handling entire divisions as well as private staff members
Accustomed to company regulations as well as guidelines
Exceptionally discreet
Accustomed with, as well as not bothered by, governmental red tape
Able to do under pressure
A tranquil as well as sensible conciliator
You may additionally have an interest in these relevant articles:

What Is the Role of Policemans in a Delaware Firm?
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The Difference Between Artificial Intelligence, Machine Learning and Deep Learning

Artificial Intelligence (AI) and its subsets Machine Learning (ML) and Deep Learning (DL) are playing a major role in Data Science. Data Science is a comprehensive process that involves pre-processing, analysis, visualization and prediction. Lets deep dive into AI and its subsets.

Artificial Intelligence (AI) is a branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is mainly divided into three categories as below

  • Artificial Narrow Intelligence (ANI)
  • Artificial General Intelligence (AGI)
  • Artificial Super Intelligence (ASI).

Narrow AI sometimes referred as ‘Weak AI’, performs a single task in a particular way at its best. For example, an automated coffee machine robs which performs a well-defined sequence of actions to make coffee. Whereas AGI, which is also referred as ‘Strong AI’ performs a wide range of tasks that involve thinking and reasoning like a human. Some example is Google Assist, Alexa, Chatbots which uses Natural Language Processing (NPL). Artificial Super Intelligence (ASI) is the advanced version which out performs human capabilities. It can perform creative activities like art, decision making and emotional relationships.

Now let’s look at Machine Learning (ML). It is a subset of AI that involves modeling of algorithms which helps to make predictions based on the recognition of complex data patterns and sets. Machine learning focuses on enabling algorithms to learn from the data provided, gather insights and make predictions on previously unanalyzed data using the information gathered. Different methods of machine learning are

  • supervised learning (Weak AI – Task driven)
  • non-supervised learning (Strong AI – Data Driven)
  • semi-supervised learning (Strong AI -cost effective)
  • reinforced machine learning. (Strong AI – learn from mistakes)

Supervised machine learning uses historical data to understand behavior and formulate future forecasts. Here the system consists of a designated dataset. It is labeled with parameters for the input and the output. And as the new data comes the ML algorithm analysis the new data and gives the exact output on the basis of the fixed parameters. Supervised learning can perform classification or regression tasks. Examples of classification tasks are image classification, face recognition, email spam classification, identify fraud detection, etc. and for regression tasks are weather forecasting, population growth prediction, etc.

Unsupervised machine learning does not use any classified or labelled parameters. It focuses on discovering hidden structures from unlabeled data to help systems infer a function properly. They use techniques such as clustering or dimensionality reduction. Clustering involves grouping data points with similar metric. It is data driven and some examples for clustering are movie recommendation for user in Netflix, customer segmentation, buying habits, etc. Some of dimensionality reduction examples are feature elicitation, big data visualization.

Semi-supervised machine learning works by using both labelled and unlabeled data to improve learning accuracy. Semi-supervised learning can be a cost-effective solution when labelling data turns out to be expensive.

Reinforcement learning is fairly different when compared to supervised and unsupervised learning. It can be defined as a process of trial and error finally delivering results. t is achieved by the principle of iterative improvement cycle (to learn by past mistakes). Reinforcement learning has also been used to teach agents autonomous driving within simulated environments. Q-learning is an example of reinforcement learning algorithms.

Moving ahead to Deep Learning (DL), it is a subset of machine learning where you build algorithms that follow a layered architecture. DL uses multiple layers to progressively extract higher level features from the raw input. For example, in image processing, lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as digits or letters or faces. DL is generally referred to a deep artificial neural network and these are the algorithm sets which are extremely accurate for the problems like sound recognition, image recognition, natural language processing, etc.

To summarize Data Science covers AI, which includes machine learning. However, machine learning itself covers another sub-technology, which is deep learning. Thanks to AI as it is capable of solving harder and harder problems (like detecting cancer better than oncologists) better than humans can.

For more about AI, refer to Skymind Global.