Why is Artificial Intelligence Trending?

What is Artificial Intelligence? 

Artificial intelligence (AI) encompasses machine learning technology, a term first coined by John McCarthy, recognized as the "father of AI," during his 1956 conference on the subject. However, prior explorations by Vannevar Bush and Alan Turing had already delved into the notion of machines capable of thought for years.

AI endeavors to replicate human intelligence in machines, employing diverse algorithms to execute autonomous actions. It relies on mathematical algorithms to enable computers to discern relationships between various types and pieces of data, leveraging this comprehension to draw accurate conclusions or decisions. Yet, the effectiveness of AI hinges on the availability of ample data for learning.

The size of the data pool used to train AI models directly impacts the accuracy of predictions or decisions, with smaller datasets often yielding diminished accuracy.

Early AI algorithms, like the A* search and sort algorithm introduced in 1968 by Peter Hart, Nils Nilsson, and Bertram Raphael of Sanford Research Institute, typically had specific objectives. Over time, AI technology has evolved, incorporating modern principles of machine learning, deep learning, and artificial neural networks.

Broadly, AI involves three key steps: learning, reasoning, and self-correction. Deep learning and machine learning discern patterns and trends within datasets to unearth embedded goals, while artificial neural networks, akin to human neurons, accumulate knowledge over time to execute actions.

The interpretation of AI varies across industries, often serving as a catchall term. Yet, historically, AI denotes the process wherein a computer emulates human behavior.

AI Evolution beyond mere  Adoption 

The trajectory in artificial intelligence is transitioning from mere adoption towards profound integration within business frameworks. Companies are increasingly realizing the potential of AI technologies not just for product recommendations, but for automating supply chain prediction, refining inventory management, and elevating operational efficacy to unprecedented heights.

AI centric Operations 

A notable trend emerging in the business arena is the evolution of companies into AI-focused entities. By centralizing AI in their operations, businesses can innovate their customer experiences and optimize multiple facets of their operations.

AI Careers 

Similar to data analysts, statisticians, and business analysts, AI stands out as one of the most rapidly expanding and sought-after fields, offering lucrative career prospects.

These professions share overlapping skill sets, akin to a Venn diagram, where research into each reveals the interconnectedness with various facets of artificial intelligence. Acquiring a blend of requisite skills through education and training provides individuals with a competitive edge, paving the way for a career path characterized by substantial growth opportunities.

Within the realm of computer science and intelligence research, professionals focus on propelling AI technology forward. While other careers explore AI applications, computer scientists drive technological advancement through tasks such as managing AI-related data systems, developing innovative software, and ensuring the ethical and accountable implementation of AI tools. According to the Bureau of Labor Statistics (BLS), computer and information research scientists boasted a median annual salary of $131,490 as of May 2021.

For computer scientists delving into AI research, a solid foundation in applied statistics and mathematical theory is essential. Typically, an undergraduate degree in computer science serves as a starting point, although many AI research roles mandate advanced qualifications like a master's or Ph.D. in computer science.

Data analytics plays a pivotal role in AI and machine learning processes, with data analysts possessing crucial skills in managing, analyzing, and storing vast datasets. Additionally, effective communication of findings and proficiency in visualization tools are imperative. Operations research analysts, who often leverage their data analytics expertise in corporate settings, earned a median annual salary of $82,360 in 2021 according to the BLS.

To pursue a career in analytics pertinent to AI and machine learning, individuals may consider obtaining a master's degree in analytics, computer science, or data science, thereby enhancing their qualifications and prospects in this dynamic field.

 Natural Language Processing

As the title suggests, natural language processing (NLP) involves applying machine learning to language and there are numerous applications for this skill.

Responsibilities in this field vary but generally consist of applying a complex understanding of language and technology to create systems to allow computers to successfully communicate with humans. Examples of natural language processing and AI include:

• Chatbots
• Virtual assistants
• Predictive texting

There is a high demand for this skill set and the job outlook is very positive for the foreseeable future. The median annual salary for individuals with NLP skills is $100,90 by BLS estimates, but the highest-earning, most experienced data scientists with this skillset may earn closer to $167,040.

Education: Consider a bachelor’s or master’s degree in computer science with a specialization in natural language processing or computer linguists. 

Common Pre-Requisite Skills for Artificial Intelligence Jobs

Essential prerequisites for roles in artificial intelligence encompass a robust grasp of mathematics,

 fundamental understanding of statistics, data analysis, and modeling, 

proficiency in tools like Tensorflow, 

Keras, Python, Scikit, 

Pytorch, adeptness in comprehending intricate algorithms, 

sharp analytical capabilities, practical experience in statistical methods,

 familiarity with distributed computing principles, and mastery of various machine learning algorithms.

Summary Data Science and AI 

While Data Science and AI are often used interchangeably and share significant overlap, Data Science encompasses a broader spectrum, utilizing AI tools like Deep Learning algorithms for robust data classification and prediction.

According to a 2021 LinkedIn report, Data Science is witnessing substantial year-over-year career growth. However, Artificial Intelligence specialists are spearheading the emergence of new jobs in the United States, boasting an annual growth rate exceeding 74 percent over the past five years. Given the demanding nature of this field, mastering these technologies through industry-focused education equips individuals with the necessary tools to establish a challenging and financially rewarding career path.