Introduction

Artificial Intelligence is increasingly integrating into our daily activities, appearing in fields ranging from healthcare to entertainment. Despite its remarkable capabilities, there are areas where AI doesn’t quite match human prowess. This examination aims to clarify AI's strengths and limitations. Consider AI like "Nemo" from the movie Finding Nemo — incredibly adept at picking up new skills, becoming more intelligent by processing vast amounts of data. Competitors such as OpenAI, Google, and Microsoft contribute to the early development stages of AI.

What are the shortcomings of artificial intelligence?

Deep artistic and literary creativity

AI may create text and images, yet human creativity intertwines with personal inspiration, emotional depth, and life experiences that machines struggle to replicate. Creativity stems from a lifetime of unique interactions with the world, not just content creation. For instance, an AI-written love poem could resemble an attempt to explain the concept of a microwave that doesn't heat.

Empathy and human relationships

Artificial Intelligence has the capability to process emotions and respond accordingly to data, yet it lacks the capacity for genuine empathy or fostering authentic human connections. Human bonds are forged through mutual experiences and authentic emotional exchanges, aspects that are challenging for AI to replicate. For instance, when an AI attempts to console someone in sorrow, its words might come across as robotic, reminiscent of a standard service reply along the lines of "Your emotional response is noted, we appreciate your interaction with our service."

Moral judgment

Ethical decisions rely on culturally and personally varied values, too intricate for algorithmic coding. While AI aids in decision-making, it fails to fully grasp ethics or resolve conflicts, such as suggesting universal headphone use to address noise issues, including impractical settings like bathrooms.

Intuition

Humans often rely on intuition and common sense to make quick decisions without having to analyze accurate data. This innate ability, which develops through life experiences, is difficult for AI to fully imitate. For example, AI might try to guess the taste of food based on a recipe, but guessing it would be like mixing sugar with salt because it "looks the same."

Dealing with uncertainties and contradictions

Artificial intelligence needs clear and specific data to work efficiently. Ambiguous or contradictory situations that require sensitivity and deep understanding of the human context remain a challenge for it. Humans are able to adapt to unclear situations thanks to their ability to use context and personal experience. For example, AI might try to solve a puzzle, but it would say, "If answer A and B are correct, let's choose C.

Creativity in problem solving

While AI can find solutions based on past patterns and data, thinking outside the box and finding innovative and unexpected solutions is an area where humans still excel. Innovation requires imagination and the ability to see things from new angles, skills that are difficult to code. For example, artificial intelligence may try to fix a broken computer by restarting it a thousand times, while humans may discover that the problem with the cable is not connected to power.

Learning from personal experiences

AI learns from available data but cannot experience life like humans or learn personal lessons from everyday experiences. Personal experiences provide humans with deep understanding and applied knowledge that AI is difficult to acquire. For example, AI may learn that a fire burns after reading thousands of books, while a child learns this from a single experience with a candle.

Tasks that require a complex physical interaction

Businesses that require navigating unregulated environments or handling sensitive and delicate objects in a human

way can be difficult for robots and AI. Humans have the flexibility and ability to adapt to rapid environmental changes

and subtle interactions. For example, AI may try to cook a meal, but end up putting ketchup in coffee and salt in dessert.

Educational platforms provide free training, information and certificates about artificial intelligence;

AWS Skill Builder (Amazon)

Amazon has more than 100 free, low-cost AI courses and educational resources available through AWS. Learners can get essential skills in machine learning generative AI and foundational models. Overall, the company is committed to providing free AI skills training to two million people by 2025.

The machine learning plan contains approximately seven hours of free content through which individuals can learn the foundations of technology, including relevant terminology and decision-making processes. It also teaches users how to use Amazon SageMaker, the company's machine learning platform used by companies like AT&T and LG.

Google: Google AI for everyone

Google offers a beginner course through its educational platform for anyone who might be interested in how to use AI in the real world. Google AI for All , which is offered through the online education platform edX , is a self-paced course that takes about four weeks to complete, assuming you dedicate two to three hours per week to the course. Participants learn about both the principles of artificial intelligence, machine learning, and real-world applications of technologies.

Google also covers the form of AI programming and the process of teaching a computer how to learn. The course is taught by Lawrence Moroni, who leads  Google's AI Advocacy as part of the  Google Research in Machine Intelligence (RMI) team. Nearly 12,000 people have enrolled in this free online course, according to edX.

Harvard University Platform: Introduction to Artificial Intelligence Using Python

If you are one of 5.7 million people who took  Harvard's CS50 Introduction to Computer Science course through edX, the university's introductory AI class may be the best option for you. CS50, which is one of the most popular free online courses of all time, is a prerequisite for the Harvard Introduction to AI course with Python.

This seven-week course covers artificial intelligence algorithms, game engines, handwriting recognition, and machine translation. Students must commit to between 10 and 30 hours per week to complete the course, which includes practical projects and lectures. The course is taught by David J. Malan , a renowned computer scientist and Harvard professor.

IBM: The foundations of AI for everyone

Recognized as a revolutionary leader in emerging technologies, IBM offers an AI specialization in foundations for everyone through Coursera. The specialization includes three courses:

• Introduction to Artificial Intelligence (AI)
• Get started with AI with IBM Watson
• Building AI-powered chatbots without programming 

The entire major takes about three months to complete, assuming you dedicate two hours per week to coursework. Students will learn the basics of what AI is, as well as its applications and ethical concerns. They will also hear from experts about starting a career in AI. The program is taught by Rav Ahuja and Antonio Cangiano, who work in the IBM Skills Network. Participants receive a certificate upon completion.

Intel Electronic Platform

Intel aims to equip more than 30 million people with AI skills by 2030. As part of this commitment, the company offers dozens of free self-paced online courses on topics such as deep learning for robots, deep learning, and natural language processing.

Intel also has several "AI Concepts" educational platforms that will guide you through definitions, real-life examples, tools, and resources for topics such as generative AI, AI reasoning, and learning transfer. In addition, the company provides free on-demand webinars on more advanced AI use cases such as optimizing switching models, optimizing AI workloads, and tuning AI performance.

UC Davis Platform: Big Data, Artificial Intelligence, and Ethics

As part of its specialization  in computational social sciences through Coursera, UCDAVIS offers a course focused on artificial intelligence: big data, artificial intelligence, and ethics. During this four-week course, participants learn about big data and its limits, the history of artificial intelligence, and research ethics. The entire self-paced course takes about 12 hours in total to complete.

The course is taught by Martin Hilbert, a professor at the University of California at Davis who serves as chair of computational social sciences. The course uses case studies to help participants learn AI concepts. More than 31,000 participants have completed this course, and those who earn a certificate can be shared on LinkedIn.

University of Pennsylvania Platform: Artificial Intelligence for Business

For someone who may be looking to break into AI or want to learn more about the applications of this new technology in different industries, the University of Pennsylvania offers a series of courses focused on artificial intelligence. The Artificial Intelligence Business major includes four courses:

• AI Basics for Non-Data Scientists
• Applications of artificial intelligence in marketing and finance
• Applications of artificial intelligence in people management
• AI Strategy and Governance 

These beginner courses take a total of about four months to complete and culminate in an applied educational project. Program participants complete peer-reviewed exercises to demonstrate what they have learned about data analytics, machine learning tools, and people management. The specialization is taught by eight UPenn professors from  the Wharton School, a high-profile business school by Fortune Education, and other professors from the university. Courses are offered through the online learning platform Coursera,  Students can earn a certificate that can be viewed on their LinkedIn profile.

Artificial intelligence is a powerful and useful tool that has revolutionized many fields, but it is not a complete alternative to humans. AI still needs human guidance and supervision to achieve the best results. Humans and machines can collaborate to achieve more than they can each alone. Thus, we can use AI's strengths to enhance our human capabilities rather than try to replace them. For example, we can rely on artificial intelligence to suggest new recipes, but we'll still need to taste the food ourselves to perfectly adjust the flavors and spices.