Journalism of 10**18 More Tech. Norman Macrae became Economist diarist of Neumann (Einstein Turing) in 1951. All three of the NET died suddenly (last notes Neumann - Computer & Brain , Bethesda 1956) but not before training economic jounalists of Neural Network maths and coding aim to map win-wins of their legacy of 10**18 more tech by 2025, JF Kennedy and Royal families of UK and Japan were first to debate what this might look like from 1962 - in 2025 the most exciting AI & BioI (learning) games millennials can play are rooted to exponential mapping
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help survey which places likely lead which community AI Forrestry & Photosynthesis AI Finland, Japan, perhaps oregon
nutrition ai japan, korea, taiwan edge aps and affordable insurance - india, literacy ai rural womens finance india india infrastructure ai - imec arabia to 3 seas young womens media - japan manga, korea kpop;reusable fashion uniqlo teaching hospital digital twin - hk , singapore, taiwan
Bloomberg 45 Cities- Civil Eng Road of Things SAIS 70 nations youth ambassadors of win-win science Deep learning billion year leaps in Einstein 1905 maths e=mcsquared starting with biotech's 250 million proteins.
Emperor Naruhito King Charles Narendra Modi.
Tuesday, December 28, 2004
Women Empowerment & AI's greatest fan in India, Mrs Ambani
2025 - help survey GROk view - **India** - **Action Plan**: Huang stressed India’s need for sovereign AI factories to harness its vast data and tech talent. He’s working with Indian cloud providers to deploy infrastructure for agriculture, healthcare, and more, emphasizing agentic AI. - **Unique Aspect**: He encouraged India to codify its diverse languages and cultures into AI models, democratizing access through open franchises chris.macrae@yahoo.co.uk
Monday, December 27, 2004
India is prioritizing the use of Nvidia chips to build "sovereign AI" infrastructure to process data within its borders for various applications, particularly those involving India's diverse languages and public services. The universal population data itself is not explicitly mentioned as one of thefirstdatasets to be "coded," but government and private initiatives will leverage non-personal datasets from various sectors to build foundational AI models.
Key areas of focus for initial data processing and AI model development include:
Indian Languages: A primary objective is to develop large language models (LLMs) and small language models (SLMs) trained on India's 300+ distinct languages and dialects to serve the large population. Tech Mahindra is using Nvidia's Hindi-language AI model to develop a custom model called "Indus 2.0," focused on Hindi and its dialects.
Government Services (AI4Bharat): The AI systems are intended to enhance governance and public service access through initiatives like "2047: Citizen Connect" and "AI4Pragati".
Sector-Specific Data: Core datasets for a national AI platform (AIKosha) are being contributed by ministries related to agriculture, weather forecasting, and Bhashini (the national language technology mission).
Healthcare and Legal Tech: Generative AI is expected to have a profound impact on industries like healthcare for personalized medicine and legal tech for document analysis.
Enterprise and Research: The new AI factories are intended to support large businesses, startups, and research centers running AI workloads in the cloud and on-premises for applications like digital content creation and financial services.
The emphasis on data sovereignty is to ensure that AI models are trained on local data under Indian rules, preventing foreign entities from exploiting Indian datasets and keeping the value within the country. While processing of public data is part of the long-term plan for governance, the initial immediate focus is on developing foundational language models and sector-specific applications using non-personal data where available.
