AhbarjietMalta

Chapter 19: Use Cases Financial Industry

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Chapter 19: Use Cases Financial Industry

Introduction

According to MarketsandMarkets, how the AI market is expanded all over the industries and how the CAGR and market share has been expanded is being illustrated on the image 19. The market span and other statistical information has been already shared extensively and these chapters will be more focused on particular industries.

Figure 19.1: Market overview of industry specific hold of AI and it’s CAGR (data of 17-18)

Points to Remember

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Points to Remember

Qualitative problem-solving is an approach that focuses on understanding the underlying principles and concepts behind a problem before attempting to solve it.

ChatGPT, being a generative AI tool, can actually progress on solving primitive logics to get a foundational output.

Though it’s not well adapted with human-level qualitative analysis and its opinion is just collected as part of its learning data, yet it can grasp concepts and build on the top of it with immediate effect.

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ChatGPT’s Role in Qualitative Problem Solving

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ChatGPT’s Role in Qualitative Problem Solving

This qualitative approach can unleash a way of different perspectives to examine a particular problem and might help in approaching or developing many theoretical concepts. ChatGPT, being a generative AI tool, can actually progress on solving primitive logics to get a foundational output. Though it’s not well adapted with human-level qualitative analysis and its opinion is just collected as part of its learning data, yet it can grasp concepts and build on the top of it with immediate effect. Only in problem solving, it also helps in processing the problem, approaching ideas with focused vision and more clarified objectives. This can also help any research community or management community to manage their research or corporate projects in a very skillful manner.

These 3 following conversations with ChatGPT sum up the utilization process of ChatGPT in solving problems in a qualitative manner. In example 1, it was able to solve a logical reasoning flow in rapid action:

Example 1

Figure 18.1: A qualitative logic problem solved by chatGPT

In example 2, it was able to provide a research outline catering to a specific problem:

Example 2

Figure 18.2: A ChatGPT generated project outline to tackle sentiment analysis review

In example 3, it was able to provide a different explanation to a philosophical principle:

Example 3

Figure 18.3: A ChatGPT generated 4 different interpretations of Aristotle’s philosophy

Chapter 18: Problem Solving Abilities (Qualitative)

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Chapter 18: Problem Solving Abilities (Qualitative)

Introduction

Qualitative problem-solving is an approach that focuses on understanding the underlying principles and concepts behind a problem before attempting to solve it. This approach is often used in fields such as science, engineering, and business, where complex problems require a deeper understanding of the underlying mechanisms and relationships between variables. Qualitative problem-solving involves breaking down a problem into its fundamental components and analyzing them from multiple perspectives to gain a holistic understanding of the problem. This approach often involves using qualitative data such as observations, interviews, and case studies to identify patterns and relationships between variables. One of the key advantages of qualitative problem-solving is that it allows individuals to identify and address the root causes of a problem rather than simply treating its symptoms. This approach is particularly useful in complex problem-solving scenarios where the underlying causes of a problem may not be immediately apparent.

Points to Remember

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Points to Remember

As a language model trained by OpenAI, ChatGPT is equipped with a sophisticated natural language processing system that enables it to perform various mathematical operations with a decent and a basic degree of accuracy and efficiency.

Its proficiency in these areas allows it to handle mathematical problems that require a less deeper understanding of mathematics and analytical thinking, and its expertise extends beyond the basic and intermediate levels of mathematics as it can handle complex mathematical problems that are already open source in the market.

Quantitative logic and aptitude-based reasoning are two critical skills that are often overlooked in modern-day problem-solving.

This underrated section encompasses a range of topics, including mathematical puzzles, logical reasoning, mathematical series, logical series, numerical patterns, and visual reasoning.

By developing proficiency in quantitative logic and aptitude-based reasoning, individuals can enhance their critical thinking and problem-solving abilities.

Though ChatGPT is not fully well trained for these purposes, it is again capable of solving basic fuzzy logics, math puzzles, less qualitative and without visual pattern aptitude problems.

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Basic Logic and Reasoning

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Basic Logic and Reasoning

Quantitative logic and aptitude-based reasoning are two critical skills that are often overlooked in modern-day problem-solving. This underrated section encompasses a range of topics, including mathematical puzzles, logical reasoning, mathematical series, logical series, numerical patterns, and visual reasoning. Mathematical puzzles require the use of mathematical concepts to solve problems, while logical reasoning involves the use of deductive or inductive reasoning to arrive at a conclusion. Mathematical and logical series involve identifying patterns and relationships between elements in a sequence, while numerical patterns involve understanding the underlying formula or rule that generates a sequence of numbers. Visual reasoning requires the ability to interpret visual cues, such as diagrams or graphs, to solve problems. By developing proficiency in quantitative logic and aptitude-based reasoning, individuals can enhance their critical thinking and problem-solving abilities. This can be particularly beneficial in fields such as mathematics, computer science, engineering, and finance, where complex problems often require a deeper understanding of mathematics and logical thinking. Though ChatGPT is not fully well trained for these purposes, it is again capable of solving basic fuzzy logics, math puzzles, less qualitative and without visual pattern aptitude problems.

Figure 17.3: A mathematical puzzle problem with sequential logic by chatGPT

Basic Math and Statistics

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Basic Math and Statistics

As a language model trained by OpenAI, ChatGPT is equipped with a sophisticated natural language processing system that enables it to perform various mathematical operations with a decent and a basic degree of accuracy and efficiency. Specifically, ChatGPT is proficient in performing the four primary operations of mathematics, namely subtraction, addition, multiplication, and division. Furthermore, ChatGPT possesses the ability to perform advanced mathematical operations such as integrations, derivatives, series expansion, and other traditional upper-level operations. Its proficiency in these areas allows it to handle mathematical problems that require a less deeper understanding of mathematics and analytical thinking, and its expertise extends beyond the basic and intermediate levels of mathematics as it can handle complex mathematical problems that are already open source in the market.

Figure 17.1: An integration problem dealt with sequential logic by chatGPT

Similar impressions can be captured from its expertise on statistics as well. It shows brilliant efficiency in performing decent statistical measurement and analytical interference like getting the logical probability, standard deviation calculation, variation calculation, distribution etc. These basic math and stats are very much helpful in academic learning as well as in competitive examination setup, hiring interviews and daily practice purposes. Also these are used as the elementary layers of many complex problems, so using the feedback generation system of ChatGPT, one can eventually lead closer to the solution of many complex problems gradually.

Figure 17.2: A probability problem dealt with prompt sequential logic by chatGPT

The Growing Importance of Quantitative Problem-Solving

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The Growing Importance of Quantitative Problem-Solving

One of the main advantages of a quantitative approach to problem solving is that it enables a more objective and fact-based appraisal of issues. Quantitative issue solvers can spot patterns and trends utilizing data and statistical techniques that might not be immediately obvious through subjective observation. This may result in results that are more accurate and trustworthy, which will eventually improve decision-making. In addition, a quantitative problem solving approach can also help to identify and solve problems more efficiently. By breaking down complex problems into smaller, more manageable components and using mathematical models and algorithms, quantitative problem solvers can often find solutions more quickly and effectively.

Another area in quantitative approach, Decision science, which has become increasingly important in the modern world, as more and more businesses and organizations seek to make data-driven decisions. Decision science is an interdisciplinary field that combines elements of mathematics, statistics, economics, and psychology to help individuals and organizations make better decisions. It can help to identify and mitigate biases in decision making. By using rigorous analytical methods and considering a wide range of factors, decision scientists can help decision makers to make more objective and informed decisions.

As authors, we want to establish decision making and more quantitative science as it majorly covers all the basic elements of math and statistics. And at industry level, quantitative strategists are valued with top-tier compensation especially in trading firms, highly technical firms. Another larger area of decision science is Data Science, which caters to a larger area of AI and machine learning, more complex and strategic algorithms, visualization, and interpretations of Data, and probably the most highly valued and probably the most trending career path in the market.

ChatGPT, while not yet fully capable of solving hard-core, complex quantitative problems, possesses the fundamental training required to effectively address smaller to medium-level problems. Its skillset is well-suited to efficiently handle a variety of problem-solving tasks, providing valuable support to users seeking assistance with quantitative analysis.

Chapter 17: Problem Solving Abilities (Quantitative)

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Chapter 17: Problem Solving Abilities (Quantitative)

Introduction

In the present world, tackling quantitative problems is becoming more and more crucial. The ability to properly assess and solve difficult issues using quantitative approaches has become an essential talent for many occupations due to the amount of data and the rapid growth of technology. Nowadays, many industries, including business, research, and healthcare, largely rely on data-driven decision-making and problem-solving.

Points to Remember

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Points to Remember

Together, coding and programming have transformed the way we live and work, powering everything from smartphones and websites to self-driving cars and medical devices.

They offer an exciting and rewarding career path for individuals with a passion for technology and innovation, providing opportunities to work on cutting-edge projects and solve complex problems.

In recent years, coding and programming have become increasingly in-demand skills, with many organizations seeking individuals with expertise in these areas to help drive innovation and digital transformation.

The global coding bootcamp market size was valued at $602.3 million in 2020 and is projected to reach $1,365.6 million by 2028, growing at a CAGR of 10.2% from 2021 to 2028.

Though the market data seems quite eye-catching, according to the data from Statista, the median age range for learning the coding and programming language is between 5 to 9 years.

The domain of code generation is one of ChatGPT’s most important contributions to the coding industry.

ChatGPT is an excellent resource for individuals looking to delve into the world of coding and programming languages.

Whether you’re a complete beginner or someone looking to advance their existing coding skills, ChatGPT can help you to plan out your learning path in an expert way.

With its ability to understand your goals and preferences, it can suggest personalized strategies for learning coding and programming languages.

It can also help you to create a realistic timeline and set achievable goals for your coding journey.

A high degree of accuracy can be achieved by ChatGPT, and rapid code creation can be performed.

ChatGPT can quickly fix any coding issues and any bugs within the code snippet.

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