GENERATIVE AI

• Generative AI is a rapidly growing branch of AI that focuses on generating new content (such as images, audio, text, etc.) based on patterns and rules learned from data.
• The rise of GAI can be attributed to the development of advanced generative models, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).
• These models are trained on large amounts of data and are able to generate new outputs that are similar to the training data. For example, a GAN trained on images of faces can generate new, synthetic images of faces that look realistic.
• The most famous generative AI application is ChatGPT, a chatbot that Microsoftbacked OpenAI released last year. The AI powering it is known as a large language model because it takes in a prompt and from that writes a human-like response.

3. Applications of Generative AI

• Create realistic images and animations. Text-to-image programs such as Midjourney, DALL-E, and Stable Diffusion have the potential to change how art, animation, gaming, movies, and architecture, among others, are being rendered.
• Generative AI can be used to compose music and create art.
• Create brand logo: E.g. many startups are exploring services like DALL.E2, Bing Image Create, Stable Diffusion, and MidJourney to create their brand logo.
• Generate text messages. ChatGPT to generate news articles, poetry, and even code. AI-assisted drug discovery.
• Generative AI can be used to design and control robotic systems.
• Automate things e.g. Microsoft-owned GitHub Copilot, which is based on OpenAI’s Codex model, suggests code and assists developers in autocompleting their programming tasks.
• 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.

4. Concerns about 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.
• It will have a profound effect on jobs as automation will replace humans, especially in the creative industry.
• Large parts of the creative workforce, including commercial artists working in entertainment, video games, advertising, and publishing, could lose their jobs because of generative AI models.
• Artists are worried that the internet will be flooded with artwork that is indistinguishable from their own, simply by telling the system to reproduce the artwork in a unique style.
• One of the problems with large language models is their ability to generate false and misleading content.
• Such capabilities can be misused to generate fake news and disinformation across platforms and ecosystems.

5. Role of Google and Microsoft in Generative AI

• Those two companies are at the forefront of research and investment in large language models, as well as the biggest to put generative AI into widely used software such as Gmail and Microsoft Word. But they are not alone.
• Large companies like salesforce Inc as well as smaller ones like Adept AI Labs are either creating their own competing AI or packaging technology from others to give users new powers through software.

6. Involvement of Elon Musk

• He was one of the co-founders of OpenAI along with Sam Altman. But the billionaire left the startup's board in 2018 to avoid a conflict of interest between openAI's work and the AI research being done by the Tesla Inc-the electric vehicle maker he leads.
• Musk has expressed concerns about the future of AI and batted for a regulatory authority to ensure the development of the technology serves the public interest.

7. Indian Initiatives

• National Strategy for Artificial Intelligence: The Government has published the National Strategy for Artificial Intelligence with the objective of developing an ecosystem for the research and adoption of Artificial Intelligence.
• National Mission on Interdisciplinary Cyber-Physical Systems: Under this Mission, Technology Innovation Hubs (TIH) has been established on Artificial Intelligence and Machine Learning at the Indian Institute of Technology (IIT) Kharagpur, which aims to provide state-of-the-art training and capacity building for the creation of next-generation scientists, engineers, technicians, and technocrats in the field of Artificial Intelligence. 

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