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AI
The entire world is AI. It is gaining currency .AI is the technology for rapid changes in security, data, Growth and development of economy., Governance, innovations, and managing resources, education, Agriculture. Cybersecurity. Job creation and enhancing skills. (PM speech}
What was said when the Basic language of the computer introduced?
Coming to the contribution of Rajiv Gandhi in ushering IT revolution in India, he allowed a duty free import of computer for software development in India only if it will earn 250% of its cost by exporting softwares in 4 years. To call such small leeway a revolution especially when his predecessors were the ones who had kept such high import duty earlier is no different than thanking a murderer for merely attempting murder but not killing. Manufacturing of mainframes was still a monopoly of state owned ECIL. Computerization of ticket booking services in Indian Railway starting in 1984 can hardly be called anything more than a mundane administrative decision as Indian Railway was utilizing the services of IBM before as well for many purposes. The actual revolution in the IT sector occurred when PVN Rao abolished import duty on computers used for exporting software, making the software export income tax free for 10 years and paving the path for the entry of global tech giants in India. The result of such policies was reflected in more than ten-fold increase of the software export earning of Indian companies between 1991-92 and 1997-98.
Coming the saga of C-DOT and telephone network in India, Pitroda had promised that he will build a 10,000 line capacity automatic telephone exchange in India within three years but when it comes to delivering, he was merely able to deliver a 6,000 lines telephone exchange by 1990. The success of the telecommunication policy of Pitroda can be estimated by the fact that the telephone penetration in India in 1989 was around 0.8% while 10 years later in 1999, it was merely hovering around 2.8%. Pitroda was obsessed with C-DOT to the extent that he killed the development of cellular network in India which was going to be developed with the assistance of World Bank and Ericsson by terming cellular phones as 'luxury gadgets not needed for a developing country' and a year later, he hired US based company, Multi-Tech, owned by a group of professors of Stanford University for providing consultancy on development of cellular phone technology in India with consultancy fee of around $3 million producing nothing.
The actual revolution in the world of telecommunications and IT in India happened during the era of Atal Bihari Vajpayee when his government formulated National Telecom Policy in 1999. In the budget of 2000, the import duty on cellphones was reduced from 25% to 5%, long distance mobile communication was thrown open to the private sector and ended the monopoly of VSNL in international calls in 2002. The result of Vajpayee' success is revealed by the numbers. The telephone penetration rate in 1999 was a meagre 3% while in 2010, it had breached the 50% mark. The success of telecommunication and IT in India has been written by the entrepreneurs primarily and well supported by the Vajpayee and PVN Rao government, not the glorified Rajiv and Pitroda.
Computer technology renders the central themes like speed etc?
The technology of computer rendering directly enables and advances core themes like speed, realism, and complexity through continuous hardware and software innovation. Key developments in this field have led to instantaneous visuals in video games, cinematic special effects, and realistic architectural visualizations.
Hardware acceleration
Specialized hardware has dramatically increased the speed and complexity of computer-rendered images.
Graphical Processing Units (GPUs): Initially developed to speed up 3D graphics in video games, GPUs are built to perform many similar computations at once. They accelerate rendering algorithms like rasterization and ray tracing, making real-time graphics possible.
Parallel processing: Both GPUs and render farms use parallel processing, which divides complex rendering tasks into smaller jobs to be completed simultaneously by multiple processors or computers.
Real-time versus offline rendering
Render technology has evolved to meet different needs for speed and quality.
Real-time rendering: This process generates images instantly, often at 30 to 60 frames per second or higher, to create the illusion of smooth motion.
Technology: It typically uses optimized rasterization algorithms to convert 3D models into 2D pixel-based images at high speeds.
Application: Real-time rendering is critical for interactive applications like video games and virtual reality, where instant feedback is necessary.
Offline rendering: This process prioritizes visual quality over speed, generating frames over minutes, hours, or even days.
Technology: It uses more advanced and computationally expensive techniques, like path tracing, to simulate how light behaves in a realistic environment.
Application: Offline rendering is used for creating high-quality CGI in films, architectural visualizations, and animated movies.
Rendering techniques and algorithms
Advancements in rendering software enable greater realism and speed.
Ray tracing: This advanced technique simulates light by tracing the path of rays as they bounce off objects. It is highly effective at producing lifelike reflections, shadows, and lighting effects, and is now being integrated into real-time applications with hardware acceleration.
Differentiable rendering: A more recent development that integrates rendering with deep learning. This technique allows AI to "understand" the relationship between 3D scenes and their 2D projections, making it useful for tasks like reconstructing 3D models from images.
Shading algorithms: Renderers use complex algorithms, or "shaders," to compute the colors of pixels based on lighting, texture, and the material properties of objects. Modern GPUs have open architectures that allow programmers to write custom shading routines for maximum realism.
Technological convergence
Speed and power also depend on the integration of various technologies.
Cloud computing: Cloud rendering services leverage massive networks of high-performance servers, or "render farms," to process rendering jobs faster and more efficiently than a single local machine.
Software and hardware optimization: The full potential of high-end hardware, like a powerful CPU and GPU, can only be realized with well-optimized software. Developers must create efficient code and implement features that take advantage of specialized processors.
How Google etc differ from AI
The primary difference lies in their function: Google's traditional search engine retrieves and organizes existing information, while generative AI creates new, original content.
Here is a breakdown of the key differences:
Aspect a Traditional Google Search b Generative AI
A Primary function Serves as a digital librarian, directing users to relevant information on other websites. Acts as a personal assistant or creator, generating new text, images, or code in response to user prompts.
B Output A list of links (the Search Engine Results Page) with short snippets of text. Direct, concise, and conversational summaries or new creative content, synthesized from multiple sources.
A User interaction Primarily keyword-based queries, though it has evolved with some semantic understanding. Highly conversational, allowing users to ask complex, natural language questions and engage in follow-up dialogue.
B Content creation Retrieves existing content from its web index; it does not create new content on the fly. Creates new and original content, often adapting its responses based on the user's preferences and context.
Personalization Personalizes results based on search history and location, but can feel generic and sometimes overwhelming. Can provide tailored suggestions and responses based on real-time user engagement and preferences.
B Technology Relies on crawling and indexing the web, with algorithms that rank content based on factors like keywords and authority. Uses large language models (LLMs) and deep learning to understand user intent and generate responses.
How Google is adapting to AI
Google has recognized the shift toward conversational, AI-driven search and is integrating generative AI into its core search product.
AI Overviews: Provides an AI-generated snapshot summarizing key information for more complex queries.
AI Mode: Offers an advanced AI search experience with more in-depth responses and reasoning, which Google is rolling out to the public.
Query fan-out: Uses AI to break down complex questions into subtopics and search multiple data sources simultaneously for a more comprehensive response.
SO WHAT IS AI
AI is trying to act as if us in the presentation, verbatim text, arrangements, seminar style etc etc ; and speed is the basic point; I did taxation revenue in barcode with the computer as presentation; now AI can offer me powerpoint charts of different axis from which I can choose and within 5 minutes while travelling to office. YET ALL THE OUTPUT I MADE THROUGH THE MACHINES, SOFTWARE AND ALGORITHM ALL THESE YEARS ARE CONVERTED BY HUMAN AS FED-SOFTWARE WITH MARKETING ANALYSIS. THAT MEANS, MY INTELLIGENCE IS STILL THE BEST; BUT AI CAN REPRODUCE ONLY THE PAST FEEDINGS; BUT I MAY THINK INSTEAD OF AI ANOTHER AAI OR BI IN A DECADE. WHEN YOU TALK TO A BRILLIANT DOCTOR ABOUT YOUR HEART, HE BROADLY NARRATES, THE PROS AND CONS OF THE SURGERY AND CONDITIONS FOR ONE HOUR WITH CHARTS ETC, WHICH WHEN ADDED TO THE AI FEEDS BACK IN FEW SECONDS. IT IS INDEED A TOOL OF PROGRESS FASTER THAN OUR MIND MAY GRASP. PM SPEAKS THAT. IT HELPS ALL FIELDS. BUT IT CANNOT WRITE A NEW TREATISE ON RIG VEDAM AND FIND IN DEPTH MEANING AS A HUMAN BRAIN MAY DO IN 2028.
K RAJARAM IRS 111025