Google CEO Sundar Pichai recently highlighted the growing role of Artificial Intelligence (AI) in India’s digital transformation during a roundtable interaction with Prime Minister Narendra Modi in New York. Pichai mentioned that Prime Minister Modi is dedicated to revolutionising India through his digital vision and is actively exploring how AI can benefit the nation across various sectors, such as healthcare and education.This meeting took place as part of PM Modi’s three-day visit to the United States, where he engaged with top technology leaders.
Following the discussion, Pichai explained that Prime Minister Modi is committed to pushing initiatives like “Make in India” and “Design in India.” This focus has led Google to manufacture its Pixel phones in the country, showcasing a strong commitment to contributing to India’s digital economy. Pichai emphasised that the Prime Minister is keen on ensuring that AI serves the people of India effectively. He also mentioned that PM Modi encouraged the technology industry to explore AI applications in fields such as healthcare, education, and agriculture.
Moreover, Pichai shared that the Prime Minister is not only considering the transformative impact of AI on these sectors but is also focused on developing the necessary infrastructure, such as data centres and energy solutions, to support this technological shift. Google is already collaborating with various Indian government bodies, including the Ministry of Electronics and Information Technology (MeiTy), as well as the Agriculture and Health ministries, to further explore AI opportunities in the country.
In light of this growing partnership and investment in AI, Google is also expanding its educational outreach by offering several AI courses. These courses are aimed at empowering individuals with the necessary skills to excel in the evolving technology landscape.
7 Popular AI Courses Offered by Google in 2024
For those looking to build a career in AI, Google provides a range of free online courses with certification. These courses are designed to cater to both beginners and professionals who want to enhance their expertise in AI.
Introduction to Generative AI
This course offers a foundational understanding of generative AI, covering its basic principles, how it works, and its potential applications across various fields. Learners will explore the different techniques used to generate creative content, such as images, music, and text.
Introduction to Large Language Models
Focusing on the basics of large language models (LLMs), this course explains how these models are trained and used to understand and generate human-like language. It also covers their applications in natural language processing and how they can be utilized to solve complex language-related problems.
Introduction to Responsible AI
This course delves into the ethical considerations and challenges associated with AI development and deployment. It emphasizes the importance of building AI systems that are fair, transparent, and inclusive, ensuring they benefit society while minimizing potential harms.
Introduction to Image Generation
Designed for those interested in computer vision, this course introduces the methods and technologies behind image generation using AI. Participants will learn how to create visual content using deep learning techniques and understand the algorithms that power these systems.
Encoder-Decoder Architecture
This course provides a detailed look at the encoder-decoder architecture, a key concept in modern machine learning. It explains how this architecture is used in various AI applications, such as language translation and image captioning, by converting inputs into desired outputs.
Attention Mechanism
Participants will gain insights into the attention mechanism, an advanced concept in deep learning that allows models to focus on specific parts of the input data. This course covers its role in improving the performance of neural networks, particularly in tasks like language modeling and machine translation.
Generative AI Fundamentals
This comprehensive course covers the core concepts of generative AI, including different types of generative models such as GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders). It provides a solid foundation for those looking to understand the mechanisms behind AI’s creative abilities.
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