Generative AI technology

Why is in news? Generative artificial intelligence has become a buzzword this year, capturing the public’s fancy and sparking a rush among Microsoft and Alphabet to launch products with the technology they believe will change the nature of work.

What is generative AI?

Like other forms of artificial intelligence, generative AI learns how to take actions from past data.

It creates brand new content , a text, an image, even computer codebased on that training, instead of simply categorizing or identifying data like other AI.

The most famous generative AI application is ChatGPT, a chatbot that Microsoft-backed OpenAI released late last year.

The AI powering it is known as a large language model because it takes in a text prompt and from that writes a human-like response.

GPT-4, a newer model that OpenAI announced this week, is “multimodal” because it can perceive not only text but images as well.

Significance of Generative AI

Evolution of Generative AI

The technology is helpful for creating a first draft of marketing copy, for instance, though it may require cleanup because it isn’t perfect.

One example is from CarMax Inc, which has used a version of OpenAI’s technology to summarize thousands of customer reviews and help shoppers decide what used car to buy.

Generative AI likewise can take notes during a virtual meeting. It can draft and personalize emails, and it can create slide presentations.

Microsoft Corp and Alphabet Inc’s Google each demonstrated these features in product announcements this week.

Concerns with Generative AI

School systems have fretted about students turning in AI-drafted essays, undermining the hard work required for them to learn.

Cybersecurity researchers have also expressed concern that generative AI could allow bad actors, even governments, to produce far more disinformation than before.

At the same time, the technology itself is prone to making mistakes.

Factual inaccuracies touted confidently by AI, called “hallucinations,” and responses that seem erratic like professing love to a user are all reasons why companies have aimed to test the technology before making it widely available.