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Five Motivations for My AI and Machine Learning Career That Might Inspire You

Manish Kumar
6 min readJan 27, 2024

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In 2016, I was introduced to the application of big data in industry, which had fascinated me since college when I worked on a Hadoop project. However, I soon realized that big data systems did not challenge me enough and were even replaceable, despite Apache Spark’s longevity, which is a story for another time.

I was determined to find something that would continually push my limits. Around that time, I began hearing buzz about machine learning and the cool use cases it was solving. To keep up with the latest developments in machine learning and artificial intelligence (AI), I subscribed to Google Alerts.

As a Google enthusiast, I closely followed the integration of AI and machine learning into core Google products like Search and YouTube. This inspired me to build my career in AI and machine learning.

In this article, I’ll discuss the detailed reasons for my career choice, which will be especially useful for those planning to enter the field of AI and machine learning. You shouldn’t switch to this field just because it’s trendy.

Sometimes, I questioned my choice when I didn’t see much progress in this field. Even so, I remained patient, aware that major companies were still heavily investing here. Although it was challenging to maintain this patience while watching software developers make significant strides, my faith in the field’s continuous progress kept me motivated.

Future Prospects of AIML

When I first encountered AIML in 2016, it was one of the most disruptive technologies I had come across. It was generating a buzz in the tech industry due to its vast potential and the revolutionary changes it could bring about. As I delved deeper into AIML, I realized it was not just a passing trend but had the potential to reshape the future of many industries. It was clear that AIML was here to stay.

Over the next couple of years, instead of fading away, the prominence of AIML only increased. Industries across the board started recognizing its potential and began investing heavily in incorporating AIML into their operations. The continued growth and disruption caused by AIML further solidified my belief in its future prospects.

Today, AIML continues to be a game-changer in many sectors, from healthcare and education to finance and e-commerce. The ability of AIML to automate tasks, make sense of large data sets, and even predict future trends is transforming the way businesses operate.

In conclusion, my decision to build a career in AIML was significantly influenced by the technology’s future prospects. Seeing the disruptive potential of AIML and its growing importance in various industries assured me that investing my time and effort in mastering this technology would be a worthwhile endeavor.

Love for mathematics

Another significant reason behind my decision to pursue a career in AIML was my profound love for mathematics. This field allows me to apply the mathematical concepts and theories that I enjoy learning and understanding.

Machine learning relies heavily on statistics, probability, and linear algebra, among other mathematical disciplines. It’s a field where mathematical models come to life and have real-world impacts. This application of mathematics to real-world problems is immensely satisfying for me.

Moreover, the process of developing and fine-tuning these models to make accurate predictions or to learn patterns within data is a challenging task that requires a deep understanding of mathematical principles. This challenge keeps me engaged and constantly learning, further fueling my passion for both mathematics and AIML.

My love for mathematics and the opportunity to apply it in practical and impactful ways played a crucial role in my decision to build a career in AIML.

A comprehensive and challenging domain

I realized that AIML was a comprehensive domain in itself, not a mere tool like big data, which I had previously been involved with. This understanding came with the realization that excelling in this field required a solid foundation. It wasn’t about rote learning or mugging up procedures, but about understanding the fundamental principles and concepts.

Unlike other fields where superficial knowledge might suffice, AIML demands a thorough understanding. If something doesn’t work as expected, you have the ability and knowledge to dig deeper, identify the problem, and develop a solution.

This approach provides a greater level of flexibility and problem-solving ability that’s unique to the field of AIML. It allows you to adapt to changing situations and requirements and find innovative solutions to problems. This realization was a key factor in my decision to build a career in AIML.

Solutions can be built without knowing in depth about business

A key allure of AIML is that it enables the creation of solutions without necessitating an in-depth understanding of the business. This is because AIML algorithms are designed to learn patterns and make predictions from data, irrespective of the business context.

Firstly, AIML models are trained on large datasets that encapsulate the complexities of the business environment. These models learn from the data, identifying patterns and correlations that may not be immediately apparent to human observers.

Secondly, once trained, these models can make predictions or recommendations based on new data. These outputs are derived directly from the data without needing explicit programming or business rule definition. This automated decision-making capability makes AIML a versatile tool that can be applied across various business contexts.

Lastly, AIML systems can continually learn and improve over time. They adapt to new data and changing conditions, making them exceptionally resilient and valuable in dynamic business environments. This ability to learn and adapt reduces the need for regular manual intervention and business-specific tuning.

AIML’s ability to learn directly from data, make data-driven decisions, and adapt to changing conditions reduces the need for in-depth business knowledge, making it a powerful tool for problem-solving across a wide range of industries.

Niche technology

One of the initial reasons I chose AIML as a career path was its status as a niche technology with several notable advantages. However, over time, I realized that career decisions should not be based solely on this factor. Luckily, my continued interest in this domain persisted because of my love for mathematics and the comprehensive, challenging nature of the domain.

Often, we’re attracted to niche domains because we believe they offer good paychecks, less competition, and the potential for elevated status within our social circles.

The issue with this approach is its lack of longevity. Niche technologies continually evolve, prompting the desire to switch to new domains. Frequent shifting prevents the development of expertise in any one area.

As I’ve matured and observed the world more closely, I’ve recognized that niche technology isn’t a prerequisite for success. Excelling in your chosen field is.

While this factor helped me transition to AIML, I wouldn’t recommend considering it as a core factor in decision-making.

Final Thoughts

I firmly believe that choosing a career path should be based on genuine passion and interest. Success is hard to achieve if you are solely motivated by money and status. In contrast, if you pursue what you truly love, financial reward and recognition will follow naturally. Though it may take time, it’s worth finding a field that aligns with your interests and strengths. For instance, it took me the first six years of my career to decide that I wanted to specialize in the field of AIML.

Although I enjoy sharing my experiences to help others going through similar phases of life, I primarily write about productivity and healthy lifestyles. If you’re interested in learning more about these topics, please follow and subscribe. If you find my content helpful, show your appreciation by giving me a clap. Your support encourages me to create more!

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Manish Kumar

Sharing wisdom on how to become best version of yourself. Topic includes physical/mental fitness and food habits. Reading, writing, meditating along the way!