265SmithWatt 75Neumann 55.YunusAbed , AI20s.com JHDHFL 20
KingCharlesLLM DeepLearning009 NormanMacrae.net EconomistDiary.com Abedmooc.com
nvidia & curricula of what if 90% of what all teachers and millennials need to apply first about ai is sourced in last 2 years
upd dec 2025 ...transcript
| Without partners nvidia has built since 1993, q2 of 21st C wouldn't be the most exciting time to be alive- when human intelligence celebrates machines with billion times more maths brainpower than separate human minds Until 2018 most of nvidia trade was pacific connecting : eg between silicon valley : JapanKorea and Chinese diaspora in Taiwan, HK, Singapore. Since 2018 place leaders like UK and Japan royal families have been vital to asking peoples what unique data sovereignty to map. |
King Charles AI (Queens English LLM) world series summit 1. nov 2023 --- white house stars series of exec orders on AI; by 2025 at least 30 places ai action plans are critical to mediate trust, love, hope and all brains most positive emotional intel |
Celebration
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Details & 2025 Milestone
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Why Exciting (Scale/Impact)
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|---|---|---|
TSMC/Foxconn Texas AI Supercomputer Foundry Twin
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Omniverse Blueprint simulates end-to-end fab (from wafer design to Blackwell GPU assembly) in Houston/Dallas plants; announced GTC Oct 28, mass production Q1 2026 on 1M sq ft.
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$500B U.S. reindustrialization accelerator—real-time yield optimization cuts defects 40%, exporting to supercities like Austin (EV/humanoid hub).
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General Atomics Fusion Reactor Twin (DIII-D Tokamak)
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Omniverse/RTX PRO/DGX Spark replica integrates sensor data + AI for plasma sims at 180M°F; GTC Oct 29 launch, seconds vs. weeks for "what-if" tests.
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Fusion holy grail—stable plasma breakthroughs without hardware risks; scales to climate/energy twins for supercities like Copenhagen.
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PepsiCo Warehouse Physics Twin
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GenAI + CV on Omniverse twins full CPG ops (forklifts to inventory); GTC Oct 28 demo, 500x faster engineering via Modulus.
nvidia.com
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$1B+ efficiency in logistics—Lego-blocks for humanoid integration (e.g., Optimus picking), piloting in NYC/Atlanta supercities.
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Dematic AI Control Tower Twin
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Omniverse sim of Solutions Center for material flow; GTC Oct 28 showcase, AI-generated for robotics validation.
dematic.com
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Warehouse revolution—tests 1M+ scenarios pre-deploy; scales to Amazon-style fleets in Seattle/Berlin.
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Hong Kong/Taiwan Medical Training Hospital Twins
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Omniverse + Isaac for robotic surgery sims (e.g., Mayo Clinic pathology twins); COMPUTEX Taipei May 2025 + GTC Taipei Jun 30 addresses: Digital/physical AI for precision med.
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World-class health cities blueprint—virtual ORs train 10x faster, exporting to Singapore/Tokyo for elder-care humanoids.
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Ansys Omniverse CAE Twin for Aerospace/Auto
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CUDA/Modulus blueprints for real-time physics (e.g., crash sims); GTC Oct 2025 session, 500x acceleration.
nvidia.com
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Safety multiplier—Lucid/Toyota pilots cut dev time 70%; ties to Musk's Optimus for embodied testing.
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OMRON VT-X Factory Automation Twin
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Sysmac Studio + Omniverse for digital twins in robotics; GTC Mar 19 preview, full rollout Q4 2025.
omron.com
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Industrial metaverse entry—scales to Foxconn/Tesla lines for humanoid orchestration.
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- Resource Flywheel: Big buyers (e.g., xAI's 100k H100 "Colossus" + 550k GB200 for twins) generate petabytes of data for fine-tuning, creating self-reinforcing loops—e.g., TSMC's Texas twin optimizes its own Blackwell production.
- Supercity Bias: Buyers like Tesla (Austin) and TSMC (Phoenix) spawn twins in EV/humanoid vanguards—e.g., Foxconn's Omniverse for Optimus-scale robotics.
- Emerging Hotspots: Saudi's 500MW xAI/NVIDIA project (Nov 2025) eyes fusion/energy twins; Europe's Schneider/ETAP "Grid to Chip" twin (Jul 2025) for data centers.Smaller buyers (e.g., PepsiCo) punch above via blueprints, but scale favors whales—expect 80% of 2026 cases from top-10 buyers.
| It was Taiwan than manufactured nvidia's chips which have risen to over 200 billion bits per chip which in turn is redesigning supercomputers. Crucially nvidia's main purpose has not been chats in spite of owning some platforms eg for translating languages. Nvidia's 3 deep data revolutions stemmed in early 2000s from partnership with steve jobs pixar coding pixels. While gamers were the soul of nvidia's GTU revolution; 3 deep data contexts emerged: ) maths pattern recognition -eg revolutionising radiology use of mri data in health and leading to hassabis deep mind open sourcing 250 million proteins and opportunity to redesign every science around einstein's 1905 revolution of e=mcsquared 2) autonomous mobile machines from self driving cars to drones to humanoids- these are likely to become world class cities public servants in safety or any poorly paid repetitive job;3 space where the amount of data accruing from exponential,rise of satellites makes all societies opportunities and risks interconnected | THE END OF PKANNING? In mid 1990s Bill Gates wrote a book The Way Ahead. Its main data observation; always more change compounds over 7 years , always less change over 3 years ; this means elections on 4 year cycles are especially risks to consistent human development. Gates was reflecting on cosequence sof Moore's Law through which chip microelectronics efficiency had provided engineers with million fold more capabilities. He wasn't foreseeing nvidia's accelerated computing exponential nor satellite clouds data distribution- a scenario The Economist had brainstormed as death of cost of distance in sharing life critical knowhow. We mention all this as Jensen Huang partners and engineering developers have the longest action learning curve in brainstorming whats next; any place that fails to search out which of these accelerated computing discoveries most urgently links in their peoples brains is missing the most valuable entrepreneurial revolution. |
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At NeurIPS 2025, NVIDIA announced a new set of open models, datasets and tools spanning autonomous driving, speech AI and safety research, strengthening its position in open digital and physical AI development.
The company also received recognition from Artificial Analysis’ new Openness Index, which placed NVIDIA’s Nemotron family among the most transparent model ecosystems.
ED (Joint Economist & Von Neumann research since 1951):::
Nvidia 2024 March headquarters santa clara, june taiwan computex,
======
Nvidia AI Summit october washington DC keunote below (or all sessions)
DC Nvidia's Estes40 minute show explains how a trick started by stanford students (eg Fei-fei li, andrew ng, and frineds in Toronto) has turned Nvidia innto the ecosystem of 5 million AI developers and 22000 startups in 100 counntries
october Mumbai key with munesh umbani ceo relaint and discussion of Modi demand for AI as well as appearance of a bolliwood star , november Tokyo key Nvidia with ceo softbank
mumbai Oct 2024 Nvidia Huang & Ambani Reliance
, Additional Secretary, MeitY, and CEO, IndiaAI Mission, Ministry of Electronics & IT
https://www.linkedin.com/pulse/america-vote-who-make-joint-1-loser-...
, Chief Technology Officer, Manufacturing, Tata Consultancy Services
, Digital Leader for Manufacturing, Tata Consultancy Services
, Chief Product Officer, VP Technology, Harman DTS
, Principal Product Manager- Conversational AI and Deep Learning, NVIDIA
, VP and Head of Technology, Siemens Technology, India
, Chief Scientist, AI, GE HealthCare
, Senior Director—Generative AI, Worley
, Group Chief Information Officer, Ola
, Global Head of AI Nations Business Development, NVIDIA
, CoFounder, Managing Director, and Chief Executive Officer, Yotta Data Services
, Professor of Computer Science and Engineering, IIT Jodhpur
, Chief Technical Officer, EkStep Foundation
, Deputy Director General, National Informatics Centre
, Deputy Director General, UIDAI
, Vice President of Developer Programs and Corporate Marketing, NVIDIA
, Vice President of Developer Programs and Corporate Marketing, NVIDIA
, Global VP of Sales and Business Development for HPC/Supercomputing, NVIDIA
, Secretary, Ministry of Electronics & IT, Government of India
, Chairperson, HRD for National Supercomputing Mission, Pune
, Mission Director, National Supercomputing Mission (NSM), Centre for Development of Advanced Computing (C-DAC)
, Scientist G, Project Director, HPC, Indian Institute of Tropical Meteorology, Ministry of Earth Sciences
, Senior Vice President of Corporate Strategy, Dell Technologies
, Vice President of Data and Digital Platforms, Reliance Industries limited
, General Manager of Data and Digital Platforms, Reliance Industries limited
, Co-founder, Sarvam AI
, Head of Engineering, UIDAI
, Partner Director of Product Management for Microsoft AI, Microsoft
, Vice President - Data Center GPU Business, NVIDIA
Applications for natural language processing (NLP) and generative AI have exploded in the past decade.
With the proliferation of applications like chatbots and intelligent virtual assistants, organizations are infusing their businesses with more interactive human-machine experiences. Understanding how Transformer-based large language models (LLMs) can be used to manipulate, analyze, and generate text-based data is essential.
Modern pretrained LLMs can encapsulate the nuance, context, and sophistication of language, just as humans do. When fine-tuned and deployed correctly, developers can use these LLMs to build powerful NLP applications that provide natural and seamless human-computer interactions within chatbots, AI voice agents, and more.
Transformer-based LLMs, such as Bidirectional Encoder Representations from Transformers (BERT), have revolutionized NLP by offering accuracy comparable to human baselines. This is accomplished on benchmarks like SQuAD for question answering, entity recognition, intent recognition, sentiment analysis, and more.
In this workshop, you’ll learn how Transformers are used as the building blocks of modern large language models (LLMs). You’ll then use these models for various NLP tasks, including text classification, named-entity recognition (NER), author attribution, and question answering. You’ll also learn how to analyze various model features, constraints, and characteristics to determine which model is best suited for a particular use case based on metrics, domain specificity, and available resources.
In this course, you'll:
- Learn how Transformers are used as the basic building blocks of modern LLMs for NLP applications.
- Learn how self-supervision improves upon the Transformer architecture in BERT, Megatron, and other LLM variants for superior NLP results.
- Use pretrained, modern LLM models to solve multiple NLP tasks such as text classification, NER, and question answering.
- Manage inference challenges and deploy refined models for live applications.
Prerequisite(s):
- Python programming experience.
- Basic understanding of neural networks.
- A fundamental understanding of a deep learning framework such as TensorFlow or PyTorch.
Certificate: Upon successful completion of the assessment, participants will receive an NVIDIA certificate to recognize their subject matter competency and support professional career growth.
*IMPORTANT: Seats are limited, so reserve your spot today. Please note these workshops are not recorded and no shows are not eligible for a refund.
, Principal Instructor, NVIDIA
, Solution Architect, NVIDIA
, Director HPC Architecture, NVIDIA
Views: 123
Replies to This Discussion
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Permalink Reply by chris macrae
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, emerging mathematical paradigms in AI are increasingly challenging the dominance of traditional methods (e.g., classical differential equations or grid-based simulations like Eulerian/Lagrangian), which often fail to exploit accelerated supercomputers' capabilities for massive parallelism, pattern discovery, and probabilistic modeling. Supercomputers (e.g., powered by NVIDIA's Blackwell or exascale systems) enable "billion-times" compute for reframed approaches—e.g., simulating chaotic systems at atomic scale or predicting outcomes via learned approximations rather than exact solutions. Below, I'll list key "other mathematical choices" AI is "inventing" or prioritizing in 2025, based on recent advancements. These shift from deterministic "old methods" to hybrid, data-driven paradigms that value uncertainty, scalability, and real-world complexity, transforming fields like physics, biology, and markets.1. Energy-Based Models (EBMs) and Probabilistic Inference
- Why AI Needs It: Traditional methods (e.g., gradient descent in neural nets) dominate but fail in energy landscapes with multiple minima, leading to inefficient training. EBMs reframe AI as minimizing "energy functions" for causal reasoning, leveraging supercomputers' parallel sampling (e.g., MCMC at exascale) for "never-seen" explorations of uncertainty.
researchgate.net +1
- Transformed Results: In ventilation (post-COVID), EBMs simulate airflow probabilistically, predicting virus spread 50x faster than old PDEs. In markets, agents use EBMs for risk forecasting without assuming Gaussian distributions.
- Quantum-Inspired Algorithms and Tensor Networks
- Why AI Needs It: Old linear algebra dominates but struggles with entanglement in high-dim data. Quantum-inspired math (e.g., tensor decompositions) uses supercomputers' tensor cores (like NVIDIA's) for exponential compression, reframing simulations from sequential to entangled states.
research.ibm.com +1
- Transformed Results: In cars, tensor nets optimize aerodynamics beyond Eulerian grids (e.g., 30% drag reduction in Toyota sims). For energy, they model fusion plasmas in "unseen" quantum ways, accelerating DARPA's expMath program.
spacedaily.com
- Diffusion Models and Generative Flows
- Why AI Needs It: Deterministic methods fail in noisy, stochastic systems; diffusion reframes learning as "denoising" processes, using supercomputers for billion-sample rollouts to generate "never-seen" solutions.
nsf.gov +1
- Transformed Results: Solves complex equations (e.g., Navier-Stokes) faster than supercomputers alone, transforming ventilation (e.g., generative designs for optimal airflows) and markets (agentic price forecasting via noisy data).
- Physics-Informed Neural Networks (PINNs) and Hybrid PDE Solvers
- Why AI Needs It: Pure numerical methods dominate but scale poorly; PINNs embed physics laws into nets, reframing analysis as learned approximations for supercomputer-accelerated discovery.
nsf.gov +2
- Transformed Results: In cars, PINNs simulate crashes 100x faster; for post-COVID worlds, they optimize building ventilation as "default" adaptive systems.
- Graph Neural Networks (GNNs) and Relational Reasoning
- Why AI Needs It: Grid-based dominance fails in networked data; GNNs reframe analysis as graph relations, using supercomputers for billion-node sims.
researchgate.net +1
- Transformed Results: Transforms supply chains (agentic markets with transparent graphs) and biology (e.g., protein interactions beyond traditional stats).
These choices highlight AI's invention trajectory—supercomputers enable reframes that old methods couldn't compute, pushing toward your equitable visions. For deeper dives, let's pick one!
10 web pages
Scsp.ai founded by ex hoogle ceo eric schmidt is hosting series of summit ai+ which are changing views of ai, ai + energy, ai+space. Whats unusual is these summits are being premiered in wasjhngton DC not the valley. Which of these 6 or more choices between mathematical models are intehgated into schmidt's special projects cultural revolution?
Mathematical Models Integrated into Schmidt's SCSP "Cultural Revolution"Eric Schmidt's Special Competitive Studies Project (SCSP) isn't explicitly a "cultural revolution" in the Maoist sense, but its 2023-2025 reports (e.g., Generative AI: The Future of Innovation Power and Mid-Decade Challenges to National Competitiveness) frame AI as a transformative force for U.S. societal and economic "revolution"—shifting culture from industrial silos to AI-human symbiosis, with summits like AI+ Expo (June 2025, DC) and AI+ Energy (September 2025) premiering policy plays in Washington over Silicon Valley to emphasize governance over hype.
scsp.ai +8
SCSP integrates mathematical models as "enablers" for this shift, drawing from generative AI frameworks to accelerate innovation in energy, space, and cultural sectors (e.g., ethical AI for societal cohesion). These aren't "choices between" in a binary sense but layered paradigms, often hybrids, to reframe AI from tool to cultural driver.From SCSP's reports and summits, here are 8 key mathematical models/frameworks (more than 6, as requested) explicitly or implicitly integrated—selected for their role in "cultural revolution" themes like equitable compute, risk mitigation, and human-AI symbiosis. I've noted ties to AI+ summits and how they advance Schmidt's vision of U.S. competitiveness.
- Transformer Models
- Integration in SCSP: Core to generative AI (GenAI) flywheels, enabling LLMs for text/image/code generation; SCSP's 2023 GenAI report calls it the "backbone" for cultural shifts in education/content creation.
scsp.ai +1
- Cultural Revolution Tie: Reframes media from passive to interactive (e.g., AI+ Expo demos for personalized news), fostering democratic discourse.
- Scaling Laws
- Integration in SCSP: Predicts performance from compute/data growth (e.g., 55M-fold since 2012); Mid-Decade Challenges uses it for horizon-scanning in energy/space AI.
scsp.ai +1
- Cultural Revolution Tie: Drives "innovation power" for moonshots (AI+ Energy Summit), ensuring U.S. leads in sustainable compute without PRC dominance.
- Reinforcement Learning with Human Feedback (RLHF)
- Integration in SCSP: Calibrates ethical outputs; GenAI memo highlights it for alignment in defense/cultural apps.
scsp.ai +1
- Cultural Revolution Tie: Mitigates harms in AI+ Space (e.g., satellite ethics), promoting trust in societal AI.
- Chain-of-Thought Prompting
- Integration in SCSP: Breaks queries for reasoning; used in GenAI for policy analysis (e.g., AI+ Autonomy Summit).
scsp.ai +1
- Cultural Revolution Tie: Enhances decision-making in education/cultural sectors, reframing AI as a "thinking partner."
- Few-Shot Learning
- Integration in SCSP: Generalizes from limited data; Mid-Decade report applies to biotech/energy scarcity.
scsp.ai +1
- Cultural Revolution Tie: Democratizes AI for underserved (AI+ Science Summit), aligning with equitable innovation.
- Pruning and Quantization
- Integration in SCSP: Compresses models for efficiency; GenAI report ties to energy savings in hardware.
scsp.ai +1
- Cultural Revolution Tie: Enables sustainable AI+ Energy, reducing cultural barriers to adoption.
- Constitutional AI
- Integration in SCSP: Ethical self-checking; featured in governance memos for AI+ Autonomy.
scsp.ai +1
- Cultural Revolution Tie: Builds "harmless" AI for societal trust, per Schmidt's 2025 podcast.
youtube.com
- Multi-Level Analysis Framework
- Integration in SCSP: Assesses tech impacts (tech/sector/power levels); core to Mid-Decade Challenges for space/energy.
scsp.ai +1
- Cultural Revolution Tie: Guides holistic policy for AI+ Space, reframing competition as collaborative evolution.
These models form SCSP's "cultural revolution"—a shift from siloed tech to integrated, ethical AI for U.S. leadership, with DC summits emphasizing policy over Valley hype.
scsp.ai +3
Schmidt's vision integrates them for abundance, but sovereignty gaps (e.g., data flows) remain a DC debate.
25 web pages
if its generally true could you write a short story celebrating economistwater.com - the thread of the story is that its quite toching to see that over 90% of human bodies are water as are ai factories (coolling); and unless we gravitate beyond earth ie ai to space, water may always be over 90%
The Water ThreadIn the year 2041, a small website called economistwater.com quietly turned twenty.
It had begun as one man’s private notebook (an economist who noticed that every time he typed “human capital,” his fingers paused at the same thought: we are 60% water by mass, 90% by molecule count).
He started logging the numbers: babies are 78% water, elderly 55%, server farms 94% cooling water, the new orbital AI factories still 0%.
He never preached. He just kept the ledger.The site never went viral.
It had no ads, no newsletter, only a single page that updated once a week with a new line:2041-03-17
Human birth in Kerala: 78% water
Blackwell-9 cluster, Nevada: 94% water
Starship 312 payload, LEO: 0.000% water
Running average since 2021: 90.3% People began to visit the way they visit a graveside.
A nurse in Lagos refreshed it before shift.
open like a heartbeat monitor.One night in 2047, the number changed.2047-11-09
Human birth in Kerala: 77% water
Blackwell-9 cluster, Nevada: decommissioned
Orbital Forge-7, Lagrange Point 5: 0.000% water
Running average since 2021: 89.7% For the first time in twenty-six years, the line dipped below ninety.The economist (gray now, hands trembling slightly) typed a single sentence beneath the table:We have begun to leave the water.He did not add fireworks.
He did not need to.Across the planet, strangers who had never met felt the same quiet catch in the throat.
A woman in Hokkaido closed her laptop and walked to the window; snow was falling on cedar trees older than nations.
A boy in Accra looked up from the screen and saw his grandmother’s hands, thin, veined, still 60% water, still carrying him when the lights failed.
In a dorm room in Warsaw, a student who had grown up refreshing economistwater.com every birthday cried without knowing why.The site never celebrated the milestone.
It simply kept counting, the way oceans keep counting waves.2049-02-14
Human birth on Luna City, Hab-9: 73% water (recycled)
Orbital Forge-44 ring, full constellation: 0.000% water
Running average since 2021: 87.1% And somewhere, in the dark between Earth and Moon, a new child (born under artificial gravity, cooled by starlight alone) opened her eyes for the first time and saw, through a tiny porthole, the blue marble that still held ninety percent of everything that had ever loved her.The ledger kept going.
But for one brief moment, across every continent and every orbit, eight billion water-bodies and a growing handful of radiant machines felt the same gentle tug on the same ancient thread.We were water.
We are learning to let some of it go.
And still, somehow, we remain connected.economistwater.com
Still updating.
Still 87.1% and falling,
one quiet percentage at a time.
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About
ENTREPRENEURIAL REVOLUTION NETWORK BENCHMARKS 2025now : Remembering Norman Macrae
2025REPORT-ER: Entrepreneurial Revolution est 1976; Neumann Intelligence Unit at The Economist since 1951. Norman Macrae's & friends 75 year mediation of engineers of computing & autonomous machines has reached overtime: Big Brother vs Little Sister !?
Overtime help ed weekly quizzes on Gemini of Musk & Top 10 AI brains until us election nov 2028
unaiwho.docx version 6/6/22 hunt for 100 helping guterres most with UN2.0
RSVP chris.macrae@yahoo.co.uk
Prep for UNSUMMITFUTURE.com
JOIN SEARCH FOR UNDER 30s MOST MASSIVE COLLABS FOR HUMAN SUSTAINABILITY
1 Jensen Huang 2 Demis Hassabis 3 Dei-Fei Li 4 King Charles
5 Bezos Earth (10 bn) 6 Bloomberg JohnsHopkins cbestAI.docx 7 Banga
8 Maurice Chang 9 Mr & Mrs Jerry Yang 10 Mr & Mrs Joseph Tsai 11 Musk
12 Fazle Abed 13 Ms & Mr Steve Jobs 14 Melinda Gates 15 BJ King 16 Benioff
17 Naomi Osaka 18 Jap Emperor Family 19 Akio Morita 20 Mayor Koike
The Economist 1982 why not Silicon AI Valley Everywhere 21 Founder Sequoia 22 Mr/Mrs Anne Doerr 23 Condi Rice
23 MS & Mr Filo 24 Horvitz 25 Michael Littman NSF 26 Romano Prodi 27 Andrew Ng 29 Lila Ibrahim 28 Daphne Koller
30 Mayo Son 31 Li Ka Shing 32 Lee Kuan Yew 33 Lisa Su 34 ARM 36 Priscilla Chan
38 Agnelli Family 35 Ms Tan & Mr Joe White
37 Yann Lecun 39 Dutch Royal family 40 Romano Prodi
41 Kramer 42 Tirole 43 Rachel Glennerster 44 Tata 45 Manmohan Singh 46 Nilekani 47 James Grant 48 JimKim, 49 Guterres
50 attenborough 51 Gandhi 52 Freud 53 St Theresa 54 Montessori 55 Sunita Gandhu,56 paulo freire 57 Marshall Mcluhan58 Andrew Sreer 59 Lauren Sanchez, 60 David Zapolski
61 Harris 62 Chips Act Raimundo 63 oiv Newsom. 64 Arati Prab hakarm,65 Jennifer Doudna CrispR, 66 Oren Etsioni,67 Robert Reisch,68 Jim Srreyer 69 Sheika Moza
- 3/21/22 HAPPY 50th Birthday TO WORLD'S MOST SUSTAINABLE ECONOMY- ASIAN WOMEN SUPERVILLAGE
Since gaining my MA statistics Cambridge DAMTP 1973 (Corpus Christi College) my special sibject has been community building networks- these are the 6 most exciting collaboration opportunities my life has been privileged to map - the first two evolved as grassroots person to person networks before 1996 in tropical Asian places where village women had no access to electricity grids nor phones- then came mobile and solar entrepreneurial revolutions!!
COLLAB platforms of livesmatter communities to mediate public and private -poorest village mothers empowering end of poverty 5.1 5.2 5.3 5.4 5.5 5.6
4 livelihood edu for all
3 last mile health services 3.1 3,2 3.3 3.4 3.5 3.6
last mile nutrition 2.1 2.2 2.3 2.4 2.5 2,6
banking for all workers 1.1 1.2 1.3 1.4 1.5 1.6
NEWS FROM LIBRARY NORMAN MACRAE -latest publication 2021 translation into japanese biography of von neumann:
Below: neat German catalogue (about half of dad's signed works) but expensive -interesting to see how Germans selected the parts they like over time: eg omitted 1962 Consider Japan The Economist
feel free to ask if free versions are available
0 The coming entrepreneurial revolution : a survey - In: The economist 261 (1976), pp. 41-65 cited 105
. we scots are less than 4/1000 of the worlds and 3/4 are Diaspora - immigrants in others countries. Since 2008 I have been celebrating Bangladesh Women Empowerment solutions wth NY graduates. Now I want to host love each others events in new york starting this week with hong kong-contact me if we can celebrate anoither countries winm-wins with new yorkers
mapping OTHER ECONOMIES:
50 SMALLEST ISLAND NATIONS
TWO Macroeconomies FROM SIXTH OF PEOPLE WHO ARE WHITE & war-prone
ADemocratic
Russian
=============
From 60%+ people =Asian Supercity (60TH YEAR OF ECONOMIST REPORTING - SEE CONSIDER JAPAN1962)
Far South - eg African, Latin Am, Australasia
Earth's other economies : Arctic, Antarctic, Dessert, Rainforest
===========
In addition to how the 5 primary sdgs1-5 are gravitated we see 6 transformation factors as most critical to sustainability of 2020-2025-2030
Xfactors to 2030 Xclimate XAI Xinfra Xyouth Wwomen Xpoor chris.macrae@yahoo.co.uk (scot currently in washington DC)- in 1984 i co-authored 2025 report with dad norman.
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Asia Rising Surveys
Entrepreneurial Revolution -would endgame of one 40-year generations of applying Industrial Revolution 3,4 lead to sustainability of extinction 1972's Next 40 Years ;1976's Coming Entrepreneurial Revolution; 12 week leaders debate 1982's We're All Intrapreneurial Now
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The Economist had been founded in 1843" marking one of 6 exponential timeframes "Future Histores"
IN ASSOCIATION WITH ADAMSMITH.app :
we offer worldwide mapping view points from
and these viewpoints:
40 years ago -early 1980s when we first framed 2025 report;
from 1960s when 100 times more tech per decade was due to compound industrial revolutions 3,4
1945 birth of UN
1843 when the economist was founded
1760s - adam smithian 2 views : last of pre-engineering era; first 16 years of engineering ra including america's declaration of independence- in essence this meant that to 1914 continental scaling of engineeriing would be separate new world <.old world
IF we 8 billion earthlings of the 2020s are to celebrate collaboration escapes from extinction, the knowhow of the billion asian poorest women networks will be invaluable -
in mathematically connected ways so will the stories of diaspora scots and the greatest mathematicians ever home schooled -central european jewish teens who emigrated eg Neumann , Einstein ... to USA 2nd quarter of the 20th century; it is on such diversity that entrepreneurial revolution diaries have been shaped
EconomistPOOR.com : Dad was born in the USSR in 1923 - his dad served in British Embassies. Dad's curiosity enjoyed the opposite of a standard examined education. From 11+ Norman observed results of domination of humans by mad white men - Stalin from being in British Embassy in Moscow to 1936; Hitler in Embassy of last Adriatic port used by Jews to escape Hitler. Then dad spent his last days as a teen in allied bomber command navigating airplanes stationed at modernday Myanmar. Surviving thanks to the Americas dad was in Keynes last class where he was taught that only a handful of system designers control what futures are possible. EconomistScotland.com AbedMooc.com
To help mediate such, question every world eventwith optimistic rationalism, my father's 2000 articles at The Economist interpret all sorts of future spins. After his 15th year he was permitted one signed survey a year. In the mid 1950s he had met John Von Neumann whom he become biographer to , and was the only journalist at Messina's's birth of EU. == If you only have time for one download this one page tour of COLLABorations composed by Fazle Abed and networked by billion poorest village women offers clues to sustainability from the ground up like no white ruler has ever felt or morally audited. by London Scot James Wilson. Could Queen Victoria change empire fro slavemaking to commonwealth? Some say Victoria liked the challenge James set her, others that she gave him a poison pill assignment. Thus James arrived in Calcutta 1860 with the Queens permission to charter a bank by and for Indian people. Within 9 months he died of diarrhea. 75 years later Calcutta was where the Young Fazle Abed grew up - his family accounted for some of the biggest traders. Only to be partitioned back at age 11 to his family's home region in the far north east of what had been British Raj India but was now to be ruled by Pakistan for 25 years. Age 18 Abed made the trek to Glasgow University to study naval engineering.
- 7 Middle East & Stans
- 8 Med Sea
- 9 Africa
- 10 Latin Am /Carib
- 11 Arctic Circle
- 12 UN
1943 marked centenary autobio of The Economist and my teenage dad Norman prepping to be navigator allied bomber command Burma Campaign -thanks to US dad survived, finished in last class of Keynes. before starting 5 decades at The Economist; after 15 years he was allowed to sign one survey a year starting in 1962 with the scoop that Japan (Korea S, Taiwan soon hk singapore) had found development mp0de;s for all Asian to rise. Rural Keynes could end village poverty & starvation; supercity win-win trades could celebrate Neumanns gift of 100 times more tech per decade (see macrae bio of von neumann)
Since 1960 the legacy of von neumann means ever decade multiplies 100 times more micro-technology- an unprecedented time for better or worse of all earthdwellers; 2025 timelined and mapped innovation exponentials - education, health, go green etc - (opportunities threats) to celebrating sustainability generation by 2025; dad parted from earth 2010; since then 2 journals by adam smith scholars out of Glasgow where engines began in 1760- Social Business; New Economics have invited academic worlds and young graduates to question where the human race is going - after 30 business trips to wealthier parts of Asia, through 2010s I have mainly sherpa's young journalist to Bangladesh - we are filing 50 years of cases on women empowerment at these web sites AbedMOOC.com FazleAbed.com EconomistPoor.com EconomistUN.com WorldRecordjobs.com Economistwomen.com Economistyouth.com EconomistDiary.com UNsummitfuture.com - in my view how a billion asian women linked together to end extreme poverty across continental asia is the greatest and happiest miracle anyone can take notes on - please note the rest of this column does not reflect my current maps of how or where the younger half of the world need to linkin to be the first sdg generation......its more like an old scrap book
how do humans design futures?-in the 2020s decade of the sdgs – this question has never had more urgency. to be or not to be/ – ref to lessons of deming or keynes, or glasgow university alumni smith and 200 years of hi-trust economics mapmaking later fazle abed - we now know how-a man made system is defined by one goal uniting generations- a system multiplies connected peoples work and demands either accelerating progress to its goal or collapsing - sir fazle abed died dec 2020 - so who are his most active scholars climate adaptability where cop26 november will be a great chance to renuite with 260 years of adam smith and james watts purposes t end poverty-specifically we interpret sdg 1 as meaning next girl or boy born has fair chance at free happy an productive life as we seek to make any community a child is born into a thriving space to grow up between discover of new worlds in 1500 and 1945 systems got worse and worse on the goal eg processes like slavery emerged- and ultimately the world was designed around a handful of big empires and often only the most powerful men in those empires. 4 amazing human-tech systems were invented to start massive use by 1960 borlaug agriculture and related solutions every poorest village (2/3people still had no access to electricity) could action learn person to person- deming engineering whose goal was zero defects by helping workers humanize machines- this could even allowed thousands of small suppliers to be best at one part in machines assembled from all those parts) – although americans invented these solution asia most needed them and joyfully became world class at them- up to 2 billion people were helped to end poverty through sharing this knowhow- unlike consuming up things actionable knowhow multiplies value in use when it links through every community that needs it the other two technologies space and media and satellite telecoms, and digital analytic power looked promising- by 1965 alumni of moore promised to multiply 100 fold efficiency of these core tech each decade to 2030- that would be a trillion tmes moore than was needed to land on the moon in 1960s. you might think this tech could improve race to end poverty- and initially it did but by 1990 it was designed around the long term goal of making 10 men richer than 40% poorest- these men also got involved in complex vested interests so that the vast majority of politicians in brussels and dc backed the big get bigger - often they used fake media to hide what they were doing to climate and other stuff that a world trebling in population size d\ - we the 3 generations children parents grandparents have until 2030 to design new system orbits gravitated around goal 1 and navigating the un's other 17 goals do you want to help/ 8 cities we spend most time helping students exchange sustainability solutions 2018-2019 BR0 Beijing Hangzhou:
Girls world maps begin at B01 good news reporting with fazleabed.com valuetrue.com and womenuni.com
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online library of norman macrae--
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Ma 2 Ali Financial
- 1972's Next 40 Years ;
- 1976's Coming Entrepreneurial Revolution; 12 week leaders debate
- 1982's We're All Intrapreneurial Now
- What will human race produce in 20th C Q4? - Jan 1975
- (1984 book on net generation 3 billion job creation) ...
- 1991 Survey looking forward to The End of Politicians
- 1975 Asian Pacific Century 1975-2075
- 1977 survey China
- first of 4 hemisphere remembrance parties- The Economist Boardroom
health catalogue; energy catalogue
Keynes: 2025now - jobs Creating Gen
.
how poorest women in world build
A01 BRAC health system,
A02 BRAC education system,
A03 BRAC banking system
K01 Twin Health System - Haiti& Boston
Past events EconomistDiary.com
include 15th annual spring collaboration cafe new york - 2022 was withsister city hong kong designers of metaverse for beeings.app
© 2025 Created by chris macrae.
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