AI Transcended : When people talk about Artificial Intelligence (AI), Machine Learning (ML), Deep learning (DL), and Artificial Neural Networks or Neural Networks, they use the words in different ways but most of the time interchangeably. However, each term actually has its own definition, meaning, purpose, and connection to the others.

Artificial Intelligence – Outlook

AI means that computers can do things that normally only people can do, like learning, understanding, and solving numerical/logical etc kind of problems. The goal is to make robots act like humans in many different areas. This means making computer programs that help machines understand things, learn new things, think logically, and make choices.

AI Transcended

The main goal is to make things that can do things like people, and to make them better at different things. AI programs can help doctors find new ways of treating patients, control driverless cars, and help people learn in schools. Before we go deeper, it’s really important to understand the basic idea of AI, which is explained below.

Artificial intelligence is like a popular kid in computer science, and it wants to make machines as smart as humans. AI is a widely known and researched concept that is used in modern businesses and in various areas of our daily lives. When people use artificial intelligence, the science of how things move, and taking pictures together, they can make better pictures, come up with new ways of taking them, and make the process of taking pictures overall better.

The collaboration between these areas helps to improve how pictures are processed, how computers see things, how lenses work, and all Photography technology. Machines that are very clever and have been taught well can do things that people usually do with their minds, like understanding things, thinking logically, learning new things, and deciding what to do. AI helps machines become really smart by using tools and strategies. This tells us everything we need to make smart systems, both in theory and practice.

AI and Theoretical Physics, have a lot in common in things like creating simulations, looking at data, finding ways to improve processes, using quantum computers, and exploring how new patterns and behaviors emerge. AI and theoretical physics can work together to improve both areas and help us learn more about how the universe works.

For AI, Data is Everything

The correct answer to the question “For AI, data is everything”, is “NO”. For Machine learning, the answer may be true, though. In the industry usually, data mean “numbers and stats”. However, the text is also data. AI offers huge space to innovate, re-innovate, and create a creative mess for improving customer experiences. Applications of AI and its related techniques like machine learning and deep learning are improving day by day, though.

The right vision and determined mindset will create the best intelligent customer interface that can thrust businesses on an accelerated maturity path to help the digital transformation of the organization with purpose and customer-centricity. As of date, AI has made some breakthroughs at the base level and is able to perform below-average activities.

  • FinTech: Predicting customer rating, defaulting in repayment etc. Credit scoring or direct lenders are using AI for credit scoring and lending applications.
  • Insurance: Predicting the rate of death or likely date of death for funeral insurance business.
  • Finance: This category rely on AI chatbots, mobile app assistant applications in order to monitor personal finances and predicting fraudulent activity on a credit card
  • E-commerce: Predicting customer churn
  • Healthcare: Predicting patient diagnostics
  • Social Network: Predicting certain match preferences on a dating website
  • Biology: Finding patterns in gene mutations that could represent cancer

Major reasons for this paradigm shift and the increasing adoption of artificial intelligence chatbots (AI-driven bots are the best example) for use as virtual agents or assistants are changing customer expectations, falling customer satisfaction, and the promise of lower operating costs. Banking, financial services, FinTech services, and insurance services are major gainers of AI and are clearly taking the lead here. All these players are using AI to monitor regulatory framework adherence, compliance, and Fraud Detection

Facial recognition technology is better at recognizing people than humans. It is around 10 to 15 times more accurate. New ideas like robots and fake thinking are growing quickly because of better computers and faster internet connections.

AI Beyond Data or Past Data Trends

AI is a bundled technology here which is powering every single business. Artificial intelligence is a broad and active area of research, but it’s no longer the sole province of academics; increasingly, companies are incorporating AI into their products. AI means computers can do things like learn, understand, and solve problems, just like people do. It’s not difficult to make things smart or intelligent, but it’s more important to have the right mindset, goals, personality, and emotions to achieve smartness or intelligence.

Artificial intelligence is being used in many different areas, like healthcare, banking, transportation, and entertainment, to make big changes. AI is usually connected to ways of processing information that rely on past patterns in data to teach computers how to make predictions. AI has the ability to do more than just analyze data and patterns from the past, creating new opportunities and challenges.

While data is undeniably the lifeblood of AI, it is critical to note that AI’s capabilities go beyond just examining previous trends. AI algorithms can reason, learn, and adapt in real time, allowing them to make judgments and solve complicated issues in changing situations. This feature enables AI to move beyond the constraints of historical data and into the domain of real-time data processing and decision-making.

Anomaly detection is one area where AI outperforms traditional data trends. Anomalies that depart from known patterns are frequently missed by traditional data-driven techniques. AI systems using powerful machine learning techniques, on the other hand, can detect abnormalities and outliers based on real-time data inputs and contextual information. This skill is especially useful in fraud detection, cybersecurity, and anomaly-based predictive maintenance, where identifying unique patterns is critical.

Another area where AI outperforms previous data trends is in its capacity to manage unstructured data. While structured data, such as numerical values in databases, has typically been the focus of data-driven AI models, unstructured data, which includes text, photos, audio, and video, has an abundance of untapped knowledge.

Natural language processing (NLP), computer vision, and speech recognition are examples of AI techniques that enable computers to interpret and extract insights from unstructured data, opening up new prospects for sentiment analysis, picture identification, content development, and other applications.

AI Transcended – Limitless

AI can help people make better decisions by using both data and human knowledge. AI can help people make better decisions by giving them useful information and suggestions based on data. Collaborative approach called augmented intelligence accepts that AI is not meant to take over human intelligence but rather improve it. By using AI’s brain power and human creativity, companies and experts can get more useful information from data and make better decisions.

“Moreover, AI is now used more often to generate new things or simulate situations, rather than just looking at old information. ” Some computer programs, like GANs and deep reinforcement learning, can create new pictures, songs, and writing that look and sound real even though they have never been made before. AI can help in creating new and innovative things in art, design, and entertainment. This can be very interesting and can lead to new ideas beyond what humans can think of.

AI uses data and past patterns, but it can do more than just that. Artificial Intelligence has the power to quickly think, understand messy information, work with human experts, and make new things. This makes it very powerful. As technology gets better, it will be more important to think about what could happen instead of just looking at what has already happened. By using AI to its fullest, we can discover new ideas, create new things, and find answers that will make the future better.

Feedback & Further Question

All credits if any remains on the original contributor only. Do you need more details or have any questions on topics such as technology (including conventional architecture, machine learning, and deep learning), advanced data analysis (such as data science or big data), blockchain, theoretical physics, or photography? Please feel free to ask your question either by leaving a comment or by sending us an  via email. I will do my utmost to offer a response that meets your needs and expectations.

Books & Other Material Referred

  • Open Internet & Live conferences feedback and interactions.
  • AILabPage (group of self-taught engineers) members hands-on lab work.

Feedback & Further Question

Do you have any questions about Deep Learning or Machine Learning? Leave a comment or ask your question via email. Will try my best to answer it.


Conclusion – Making things smart or intelligent is easy, but it’s important to consider your attitude, intentions, personality, and feelings when using them. In the next few years, machines will get much better at learning and keeping us safe online when we use computers to do things like pay for things or keep our information secure. Instead, a business will naturally move towards tasks that affect how well they do, without even realizing it. The classic example in AI that helps make customers happier is really important.

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Posted by V Sharma

A Technology Specialist boasting 22+ years of exposure to Fintech, Insuretech, and Investtech with proficiency in Data Science, Advanced Analytics, AI (Machine Learning, Neural Networks, Deep Learning), and Blockchain (Trust Assessment, Tokenization, Digital Assets). Demonstrated effectiveness in Mobile Financial Services (Cross Border Remittances, Mobile Money, Mobile Banking, Payments), IT Service Management, Software Engineering, and Mobile Telecom (Mobile Data, Billing, Prepaid Charging Services). Proven success in launching start-ups and new business units - domestically and internationally - with hands-on exposure to engineering and business strategy. "A fervent Physics enthusiast with a self-proclaimed avocation for photography" in my spare time.

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