Achi news desk-
In an era defined by rapid technological advancement, artificial intelligence (AI) has emerged as a transformative force revolutionizing industries worldwide.
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The term “Generative AI” popularly known as “Gen AI”, has been the talk of the town ever since AI startup OpenAI launched its flagship AI chatbot – ‘ChatGPT’ for public use. Since then, the spectrum of Gen AI has only expanded, with every global corporation investing in the technology.
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This created a fertile ground for next-gen AI models to flourish, spawning new and advanced AI models with capabilities ranging from text to image generation, and in some enterprise-level models, even advanced code generation. But what made Gen AI the breakthrough technology of the 21st century? In this article we will try to understand the same from the point of view of process improvement.
What is AI?
Before we understand what Gen AI is, we need to understand what AI is. just put, “AI is computer software that allows a system to learn new things through trial runs, remember the results, and use critical analysis to provide predictable results when executed in a new space.‘ A simple example of an AI system is Recommendations page of your social media platforms. It takes data like watch time for specific media content, the reaction it generated (liked or disliked, heart or report, etc.), and other complex data points like search history and preferences to create a personalized experience in the app.
Unbeknownst to the general public, artificial intelligence is a mainstay of today’s personalized app experience algorithms. Whether it’s from job postings on LinkedIn to new music on Spotify, from suggested videos on YouTube to recommended purchases on Amazon, AI is a critical part of our technology ecosystem today, and the use cases for AI are growing every day. However, AI is not a one-size-fits-all solution, and over the decades it has branched out into a number of specializations, and over time, these specializations are expected to expand even further.
(Image Source: AI Mind Map | By Samrat Kar | Machine Learning and Artificial Intelligence Study Group | Medium)
Such a branch of AI is known as natural language processing (NLP).
NLP models are trained on extensive language-related data using Complex machine learning the so-called paradigm neural networks.
Neural networks mimic the complexity of the neural network of the human brain and are thus able to recognize complex patterns in inputs, memorize these patterns and provide human-like responses when using a new environment.
Due to their complex nature, NLP has traditionally been used in plagiarism and fraud software, but more recently, their capabilities have been harnessed to create Generative AI models, the backbone of all Generative AI tools.
What is generative AI?
As presented, Generative AI is an AI model developed over the complex NLP architecture. Initially developed as an improvement to the classic Large Language Model (LLM), Generative AI stands out for its extensive training and creative capabilities.
Just like a child, an AI model is not created with all knowledge pre-loaded. He must be trained, taught, tested and retrained. In this process, the Generative AI LLM models are trained data available online.
This gives him access to massive data sets, which creates countless complex patterns.
These patterns, along with the classic NLP architecture, made Generative AI what it is—a solution that can take conversation tapes, process them in real-time, and generate new responses based on its stored memory and contextual references to the input.
The benefits of Generative AI
Generative AI is the future of multimodal content creation. Whether it’s new text, images, videos or even complex code, Gen AI can generate credible content in seconds. The main advantages of Generative AI are as follows:
1. Low idea times: Generative AI takes little to no time to think about content. After running a prompt, AI Generative’s extensive GPT model retrieves data from its memory, analyzes the context of the query, and accordingly, generates output.
2. No performance degradation: Unlike humans, who are drained after a hard day of mental or physical work, the Gen AI never gets tired. It may experience response lag due to network fluctuations or a lack of content in its memory, but once it starts producing, it can do the same job over and over again, without complaining, questioning or degrading the quality of the output.
3. The ability to make connections between responses: Generative AI models can contextualize nonsensical data points, such as the broadcaster’s emotional state, age, and demands, to create a personalized response. Therefore, if the prompt changes, but the topic remains the same, it is very likely that the responses will match.
Limitations of generative AI
Although Generative AI is the future of technology, it is not without limitations. Generative AI, under the guise of its accessibility and availability, is a highly sophisticated piece of technology, and it has its own set of drawbacks.
1. hallucinations: Because Generative AI ‘generates’ new content, if the conditions are right, it is likely to generate entirely new, and usually bogus, ideas to fill in places where factual data is limited. This can compromise the quality and credibility of one’s content.
2. Pre-trained biases: Since Generative AI was trained on historical data available online, it is likely that biases available in this data set have crept into the model. Therefore, it is recommended to run several iterations and iron out biased responses.
3. The quality of the message affects the response: Unlike current search engines, Generative AI is not a search tool. This is a conversational system, so the input provided is just as important as the response. Therefore, it is recommended to have a basic understanding of instructional science before using Generative AI professionally
The future of process improvements: generative AI
With the foundation established, we find ourselves in the present, in a reality where Gen AI is everywhere.
But there is this fear, the uncertainty of AI replacing human work.
However, as someone who is in constant touch with technology, I can positively state that these fears are just rumours.
Gen AI is not a competitor, but rather a tool that can be used to improve their productivity, generate new ideas, and ensure that we spend less time doing mundane tasks and more time creating and ideating.
Ideas have never been more rewarding, and with Gen AI leading the pack for improvements, there won’t be a use case left that Gen AI can’t improve.
Let’s take an example of how Gen AI makes our life easier.
Example 1: Summary
In our hectic lives, it is imperative that we don’t have enough time to read long documents and summarize them for easy use in our workplaces.
Generative AI is proving to be an excellent tool for summarizing long documents into easy-to-understand summaries that can be used later in our workplaces.
A fitting conclusion to this article would be to use an artificial intelligence (Gen AI) tool to summarize the same, providing a holistic view of the content to the readers, and demonstrating its capabilities as an enhancement tool.
immediate: Imagine you are the editor of a reputed newspaper in India. An article was submitted by an aspiring tech columnist, but he missed adding a conclusion. Summarize {content} in less than 200 words, and provide a short 50-word conclusion for it, which can be added. Adjust the tone and flow of the content.
We will replace {content} in this article with the Gen AI tool. Come see the magic happen!
Answer: (use ChatGPT 3.5)
In the crowded landscape of technology, the emergence of Generative AI, or Gen AI, has revolutionized process improvement.
Stemming from OpenAI’s ChatGPT, Gen AI has evolved into a versatile tool adopted by global corporations.
Its prowess spans the creation of text, image and code, making it a cornerstone of 21st century innovation.
At its core, Generative AI builds on the foundation of natural language processing (NLP) models, leveraging vast datasets to create complex patterns and responses similar to human cognition.
Its advantages are many: quick ideas, unquestionable performance and a personal relationship.
However, like any innovation, Generative AI is not without its limitations, including the risk of pre-trained hallucinations and biases.
Despite these challenges, the future of process improvement lies in Generative AI.
It is not a threat to human work but a catalyst for creativity and efficiency. Embracing Gen AI empowers us to transcend mundane tasks, fostering a realm where ideas flourish and innovation thrives.
As we navigate this technological landscape, let us harness the potential of Gen AI to propel us toward a future where the possibilities are limitless.
A fitting end to the article, don’t you think?
(The writer is a B.Tech graduate from Tazpur University and currently working as a Systems Engineer at TCS, Delhi. All views and opinions expressed in the article are those of the author).
