The buzz and traction this generative AI is creating has been decoded

Launched in November, ChatGPT surpassed 1 million users in just five days.

Few 21^Yingshi Century Innovation has captured the minds of people like ChatGPT over the past month. Launched in November 2022, it crossed 1 million users in just five days.

A now-popular tweet puts the extent of ChatGPT’s success into context—it took Netflix 41 months, Facebook 10 months, and Instagram 2.5 months to reach 1 million users.

ChatGPT has over 1 million users in just 5 days.

In comparison, it took Netflix 41 months, FB 10 months, and Instagram 2.5 months.

But many have yet to reach their full potential.

Here are 10 exciting things you can do with it right now:

— Alexander Volodarsky 🇺🇦 (@volodarik) December 8, 2022

ChatGPT is a product of OpenAI, an AI research and deployment company founded in 2015 by Sam Altman and Elon Musk.

The tool has gained significant traction for its ability to answer follow-up questions, admit mistakes, challenge incorrect premises and reject inappropriate requests, according to the OpenAI website.

Noting its ability to produce human-like conversational responses to questions, futurists have touted ChatGPT as a potential tool for education and media.

ChatGPT is just one of many utilities of a larger technology – generative artificial intelligence, which is part of a larger family of artificial intelligences.

“Generative AI focuses on algorithmically creating new data or content with minimal human involvement, similar to existing data,” explained Dr. Debanga Raj Neog, Assistant Professor at IIT’s Guwahati Mehta Family School of Data Science and Artificial Intelligence.

Generative AI can harness the power of machine learning to generate images, videos, text, music, 3D models and websites, Dr Neog added.

For the uninitiated, machine learning (ML) is an application of artificial intelligence that helps machines learn better using data and algorithms; example: image recognition services.

With its applicability across multiple sectors of the economy, generative AI is poised to advance a data-driven economy. According to Arun Meena, founder and CEO of RHA Technologies, by 2025, generative AI will contribute 10% of all generated data.

According to a recent report by Acumen Research and Consulting, the global market for generative artificial intelligence will only be $7.9 billion in 2021 and is expected to grow to $110.8 billion by 2030.

Moreover, the generative artificial intelligence market is likely to grow at a compound annual growth rate (CAGR) of 34.3% from 2022 to 2030.

Jaideep Kewalramani, Head of Employment and Chief Operating Officer at TeamLease Edtech, believes that as AI algorithms mature, several industries will experience disruption, adding: “Generative AI will be able to produce unique works of art, literature, Write software code, create marketing content, provide fashion tips, develop recipes, have human conversations, provide consulting and more.”

Use cases for generative AI are still evolving and are expected to enter human domains as well, e.g. human resource management.

Generative AI can help managers create interview questions for candidates and provide features such as employee onboarding.

Generative AI can also help internal employee communications by automatically replying to emails, translating text, and changing the tone or wording of text. The technology promises to make life easier for executives by creating presentations based on prompts.

“GAI may make automation more human and make communication across layers more transparent. A more powerful but subtler (in terms of being seen) application is in the realm of understanding people,” said Asif Upadhye said consulting firm.

Mr Upadhye added that generative AI could also improve recruitment through the use of predictive video or emotion-based tracking.

However, the use of generative AI by companies raises a related question – what impact does the technology have on jobs and job creation?

This question has a more complicated answer.

Generative AI is a relatively new subset of the larger field of artificial intelligence. Therefore, numerical estimates of its impact on the job market remain a matter of speculation.

However, a larger AI market could spark a fourth industrial revolution. At least 63% of global CEOs interviewed by PwC in 2019 believe that the influence of artificial intelligence will exceed that of the Internet.

Another PwC report states that AI has the potential to increase global GDP by 26% by 2030 — an estimated $15.7 trillion.

An EU brief cites research from the McKinsey Global Institute that suggests that by 2030, around 70 percent of companies will have adopted at least one AI technology.

However, companies adopting AI could be disruptive to the workforce, especially in labor-intensive markets like India. According to a report by the World Economic Forum, AI could add 97 million new jobs by 2025, while phasing out 85 million jobs.

The prevailing view is that AI may cause job losses in labour-intensive sectors in the short term, but create jobs and increase productivity in the long run.

According to Mr Meena of RHA Technologies: “Countries with a larger workforce may face problems in the short term due to job losses for repetitive tasks and increased costs of retraining those who will be replaced by such technologies.”

Workers with knowledge of artificial intelligence, machine learning and robotics will be at an advantage in the fourth industrial revolution, he added.

To offset job losses from AI-driven automation, there is an increasing focus on upskilling and reskilling employees and job seekers. Example: Gartner research shows that 20% of programming professionals will be retrained due to disruption caused by generative AI.

Mr Kewalramani said: “Certain segments of the workforce will come under pressure. Industry and academia must come together to reskill the talent pool and incorporate new skills into the undergraduate curriculum.” Overnight is just a skeptic’s view .

In the frenzy surrounding generative AI, it’s easy for the average person to overlook its pitfalls.
Dr. Neog cautions that controlling or predicting the outcomes of AI models can be challenging because algorithms have had low explainability in the past.

“This can make it difficult to understand how these models make decisions. Also, if the data used to train the AI ​​is biased, the generated content may also be biased or flawed,” he said.

Given its widespread use (for now) in creating online content, issues of copyright infringement and misinformation may raise eyebrows.

Upadhye believes that over time, it will become difficult to understand what constitutes original content, and contributions to derivative works may be questioned, adding that intent to use will matter in the future.