265SmithWatt 75Neumann 55.YunusAbed , AI20s.com JHDHFL 20
KingCharlesLLM DeepLearning009 NormanMacrae.net EconomistDiary.com Abedmooc.com
Nvidia 5 ai summits in 2024 together with King Charles 3 AI world series summits from us exec order 31 oct 2023
| 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 |
| 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. |
;
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
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Replies to This Discussion
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Permalink Reply by chris macrae
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celebrate scaling intelligences most productive world series of nation brand (data soc) speeches
nov orea apec
october washington dc https://www.youtube.com/watch?v=SPGn9MZb1a05 ways nvidia ai partners most helped us in 2025; celebrated tsmc and foxconn bring ai foundry to texas; celebrating 17 quantum startups support of eg defenceand space ai; 6g telecoms usa with noki; worldiwide partnership with uber intel self driving cars; rebuilding half of usa doe top supercomputers -nvidia's 20X computational effiency also 20 x energy efficiency
summer paris https://www.youtube.com/live/p6hX206xszI?si=bOqQBwcAZlKaOwxw&t=... https://www.nvidia.com/en-us/on-demand/playlist/playList-0dc0b10a-e...
and london
may taiwan
march stanta clara
dec 2024 honh kong
nov 2024 japan
oct 2025 india
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Dr John Hamre Chair CSIS 1.40
John Hamre I''ve been looking at your website and you do talk about uh Nvidia's being a platform. What does
that mean? A platform?
Jensen Huang: A platform is something that you build other things
upon. Nvidia is the largest pure play technology company the United States has
ever seen. In fact, we're the largest pure play technology company the world's ever known. We create technology out of nothing. Our final product is pure technology and in order to use it, you have to create software and applications for various industries above it.
You know, if you look at most of the technology companies today, some of it could be in social media, some of it could be in e-commerce, some of it it could be in information search and and these are all amazing technology companies whose business models are something else. BUT our business model is purely technology.
Now the way that that AI works and our technology works is that in the final analysis the technology platform
is built in layers and that's one of the reasons why we think of it as a platform. You're standing on top of it.
2:53 5 Layer Platform Energy*Chips
An application or an industry stands on top of that platform. That platform starts with energy on the bottom. One of the reasons why why uh this administration uh has made such a huge difference right away if it's is this pro- energy growth initiative its attitude about energy is that if we don't have energy we can't enable this new industry to thrive it is absolutely true so layer one is energy
layer two are essentially the chips and systems but the chips that's where Nvidia comes in
layer three is a whole bunch of software and we build a whole bunch of software on top of our chips. And we're well known for this piece of software called CUDA, but there's hundreds of different pieces of software that we create that enables people to do AI for different fields of science or language or images or whatever it happens to be, robotics or manufacturing and such. But that third layer is best called infrastructure. Basically software.
Now people historically have thought of infrastructure really as cloud. But increasingly it's really important to realize that infrastructure includes land, power, shell because these are and I'll speak about this in a second that this industry spawn another industry altogether and I'll come back to that. But the third layer is basically infrastructure and that infrastructure includes financial services because it takes an enormous amount of capital to do what we do and historically all of that software.
AI= The 4th layer: above infrastructure and this is where people largely focus on when they talk about AI which is the AI models. This is the revolutionary of course Chad GPT uh incredible work that anthropic does with
cloud and uh Google does with Gemini and what XAI does with Grock. But the
important thing to realize those are four of the one and a half million AI models
in the world. AI is not just intelligence that understands English or language, but it's AI that understands
genes, proteins, chemicals, the laws of physics, AI that understands quantum. AI
that understands physical articulation, otherwise known as robotics. AI that understands patterns across long sequence of time, financial services, AI that understand longitudinally across multiple modalities, healthcare. And so AI has all of these different reaches and domains. We talk about this one area. We just have to be very careful to understand that AI AC spans basically every form of information across every field of science across every single industry. One and a half million AIs around the world.
Apps are Layer 5: On top of AI Layer 4 are all the applications and we never should forget that in the final analysis these AI models are technologies but technologies are about enabling application and use whether you're in health care you know you could be in entertainment manufacturing self-driving cars
transportation each one of these industries have AIs that deeply affect them and these are the five layer stack
6:18
Nvidia is at the lower level, the platform level. The reason why we say that, you know, we're AI company that works with every single AI company in the world is because we're the platform
by which we are able to work with all of these technology companies and all these application companies across all these industries. And so that is a platform that we created. the mode that people
describe, not so much a mode, but basically the the language by which all
of these different applications and these different technologies speak to us is an architecture we invented 25 years ago called CUDA. And on top of that CUDA libraries, a whole bunch of algorithms
that we invented over the years and that is basically Nvidia's platform. In the
end, we don't build self-driving cars, but we work with every single self-driving car company in the world.
In the end, we don't discover drugs, but we just have we work with every single drug discovery company in the world. We're the platform by which they build their things. We're a platform company.
Dr John Hamre I I think half of I had a half a dozen
young kids come up to me today say Nvidia gave them a better gaming experience. I mean you're all here.
Jensen Huang Before we invented the AI industry, the first industry we created is the
modern gaming industry. Absolutely. Yeah. You may not know this. I'm very proud to say. Nvidia is the world's
largest gaming platform.
Dr John Hamre: Okay. So, let me ask you. You said something recently that was quite
provocative. You you said that China was winning the AI race, the AI competition. I know that you've got a powerful competitor in Huawei and Huawei has a lot of advantages you don't
have. Can you clarify this competition? Are we really losing?
Jensen Huang: It was a very good headline. It was a great headline. Yeah. And and u apparently caught up a lot of attention. and as you know with headlines: the disclaimer part ie the foundation part was left out of the headline but but the the way to think about that is that let me just handicap it right now if you look at AI and go back to the first thing that we said AI is a five layer cake (energy*chips*infrastructure*AI models*applications let's just always simplify it's not it's not quite this simplistic
at the lowest level energy. China has twice the amount of energy we have as a nation. I want to ask about that twice as mu ch energy as we have as a nation and there our economy is larger than theirs. Makes no sense to me. We also know that one of the most one of the most important initiatives, one of the most important policies of this administration and it was the first thing that President Trump said to me when we met is listen we need to reindustrialize America. We need to inshore manufacturing again. We need to make we need to help America make things again. It's going to create jobs. that part of the economy has been outshored
and completely gutted the United States. We need to bring that back and he needs my help to
do so. And so so that entire sector of the economy is missing and however
without energy how do we build chip plants, computer system plants and these AI data
centers we call them AI factories. We're building simultaneously three different types of factories in the United States. Chip factories, supercomputer factories, and AI factories. They all require energy. Every single one of them. And so, on the one hand, we want to re-industrialize the United States. How
do you do that without energy? And so the fact that we vilified energy for so
long, President Trump sticking his neck out and making taking it on the chin and
helping this helping the country realize that energy is necessary for our growth
is one of the the really one of the greatest things he's done right off the bat. And so now at the energy level,
back to that stack, we're, you know, 50%. And they're growing straight up. We're
kind of flat right now. And so number one, uh, energy.
Number two, chips. We're generations ahead. We are generations ahead on chips. And I
think everybody recognizes that.
Number three, infrastructure. If you want tp build a data center here in the United States, from breaking ground to standing up a AI supercomputer is probably about three years. They can build a hospital in a weekend.
That's a real challenge. And so at the infrastructure le layer, their velocity
of building things because they are builders is extraordinarily high. Now,
So in spite of our leadon chips don't be complacent. Remember, semiconductors is a manufacturing process. Anybody who thinks China can't manufacture is missing a big idea.
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
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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--
==========
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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