who's 100 times moore tech/humanity would world uniquely miss

[chris macrae]

Neumann year 68 of LLMs can help prevent humans from extinguishing each other

Architect Intelligence game 1 spans 1951-2025   booknet5.docx comments welcome [e-mail] if poss mention 2025 report in subject line

- which game play do you want to linkin -

α chronologically;

γ  leading edge ai for good- back from future's final exam 7 years to 2030

β tracking any continuously good for development intelligence- where/when it started, how it spread exponentially good impact often as much through deep human trust networking until hi-trust cooperation tech came along to leapfrog with it; always be clear did the movement start without access to electricity which requires deepest intergenerational mapping, or what was system missing before exponential human advancement across a place's community occurred ; note too that over 70% of nations (although minority of people) don't have mineral resources; rich nations macroeconomists are doubly wronging such peoples; they are not in the strategic competition markets these policy makers shout about; and only having natural assets they doubly lose every time green development takes a back seat 

It began with NET asking Economist journalists this question - what would you miss without α v Neumann , Crowther Einstein  Turing Courant mathsdao1.docx JFK & Korolev satellites Moore&Royce chips macarthy&Stanford Soros&Rand -soros first maths billionnaire and top "pure" phianthropist  mathsdaobillionaire.docx Prince Charles & Hitohito 1964 Z(inter-gene reconciliastion) Tokyo Olympics and japan calciulator company requires intel to invent programmable chip

OR in the middle between 1984 and 2001 what would humans miss without Steve Jobs and Fazle Abed β jobs whose 1st netwrking revolution started with PC mack and whose 2nd revolution started hosting abed 65th birtday party in silicon valley before deciding how to design iphone to mobilise what pcs hadn't deeply made community reality abed who for 25 years specialised in eg solutions like food's borlaug and chandler & yuan longpin health's James Grant needed in communities with no electricity; it united womens world health greatest ID says (eg JYKim, farmer, Brilliant) ed's paulo freire & Gandhi family Lucknow; later in india Kalam & Nilekani english media's attenborough & palin ;loval voices for green eg wangaarit maathai east to us: connectors eg chen family and ezra vogel lee kuan yew rise of asian superisles and cooeration regions eg asean and from 1995 help turn bangladesh into digital dev lab (n=both solar and mobile ) see eg quadirs nevile wilaims, reeta roy, abdul latif 2nd half 20th C culture? or great artists and green architects eg John Lennon IM Pei Buckminster Fulller global vilage system transformatiioin mapping gifford pinchoit, ackoff, harrison owen

\or back from future what would we miss today without γ Fei-Fei Li Stanford since 2009, HAI since 2019) and Hassabis 1  2(deep mind 2010 - first billionaire of regenerative ai to fund Stanford, alphafold2 has donated 200000 protein database; campuses connect london ; new york courant mountain views google brain ...) Jerry Yang's Asia-Stanford network including masa Son Li Ka Shing, overlaps with Schwarzman scholars & Hong Kong Guterres hulin zhao, melinda gates Mr & Ms Jin Page & Brin  Asian ceo leadership at5 Google Nvidia Microsoft wildcards satishi & musk Allen Insiitute Sheikha Moza & Charles Yidan - new education summits; Michael Crow

[chris macrae]

α

Source checked with Bard LLM (except where quoted) - Kennedy  vision seems to be  last American leader who didn't just promise youth "yes you can" but celebrated setting in motion inter-decade innovations (satellite, peace corps, mapping win-win interdependec0 that planted (positive exponentials rising from  1960s)-

please note this is not a left versus right political remark (and his assassination in 1963 means the world never saw all the value multipliers' impact play out); notably the french origin of entrepreneurial(JB Say) was about societal empowerment of advancing all the peoples not a monetary ideology per se ;

London Scot James Wilson who founded The Economist in 1843 had inherited a scottish SMEof hatmaking but found london was thinning scots population and over-taxing the colony of scotland; he came to london to become an MP to throw out vested interest MPs; started a royal society newsletter; inspired 20 something queen victoria to change from ruling empire to commonwealth mapping 2 overall goals end poverty and end starvation ;

ED: Crowther The Economist's editor before and after world war2 had continued the 2 goals as editorial lenses as how journalists valued  stories they covered but his biggest move of all was to send jouranaist in 1951 to be trained by Von Njeumann in tech's coming exponential change

Kennedy & 1 The Economist share human advancement promising news; 2 interdependence; 3 Satellite  e/moon race; 4 peace corps

1 quote by Kennedy in which he mentions The Economist (which decades did it live up to Neumann's survey - what goods can peo0ples unite when given 100+ times more tech every decade0. In a speech to the American Newspaper Publishers Association in 1961, Kennedy said:

"The Economist is one of the most respected journals in the world. It is read by men and women of affairs in every country. It is a journal of ideas, and it is a journal of facts. It is a journal that is not afraid to speak its mind, even when its views are unpopular."

 

x

NET stories

Without Neumann-Einstein-Turing probably Hitler would have won; the chances of any digital good let alone human good would have been near zero. Sadly, as far as we can see the NET only worked in the same space Princeton for 18 months just before world war 2; Neumann most wanted Turing to stay but couldn’t get him a visa. One of the things that united the NET- they wished that no human beings time ever be wasted. They had got most of their lives spent on the sad nuclear arms race (necessary to beat hitler but what might net have advanced for digital good).  When war ended Neumann worked night and day on digital good; Einstein was tool old to do more breakthrough maths but he clarified hopes and fears with extraordinary chats: see Einstein & Gandhi; or Einstein & Freud: or Einstein & Black Undergraduates

 From 1951 to his death by cancer in 1957 it was essentially V Neumann who was left to train economist and other visitors on what good legacies the “Goats” of maths (without brain tools beyond slide ruler) hoped humans would see- von neumann’s last lecture notes delivered at yale by hos wife “ computer and the brain” seem to have been ignored by the great engineering designers of digital for 50 years; the Fei-Fei Li and Hassabis made huge leaps- if  lots of time training/generating computers’  vision, then  no mission is impossible (for better for worse); as it turns out landing on the moon back in 1968 was far simpler than landing Aiforgood on earth; but 2020s may be most smartly valued as humans last moonshot – that’s if you want younger half of world to have a chance to prevent risks of plague, climate, nuclear war or indeed anything where man now completes “connectivity maps” on natures worldwide scale

=====================

[chris macrae]

α

goal 2 food - at least a billion people from 1945 would have starved without alumni networks began by borlaug; in asia where about 65% of people live, rice is the dominant staple crop and at least 10 times more local production is possible with best seed for conditions; after world war 2 japan made such a leap with borlaug's tech that 1) tacitly it may already have been applying some of his knowhow; anywhere that saw what japan could do exchnaged knowhow stating with south korea and taiwan; overall american chandler coordination of rice association IRRI (philippines) and veggie institute (taiwan) also wordl vegetable      may have multipliied east asia knowhow    -in china  yuan longpin is recognied- when he died recently china had 800000 rice variety specs accessible from local libraries; overall borlaug's revolutions arrved in south asia bangladesh with fazle abed partners  from 1972 - see also martha chen's recount published as quiet revootion (women empowerment's birth in asia) - she was abed family's first employee ; she is one of 2 people at harvard whose case studies on asian empowerment end poverty match my 60 trips to Asia and dad's 40 - the other is late great ezra vogel- I cant wait for an asian llm to re-verify asian development miracles since 1945 as bill gates has said harvard may be great but deep global viilage cases end poverty- nope that not what law or mastering business admin encounters  35:53NOW PLAYINGBill Gates Harvard Commencement Address 2007

Borlaug's labs had been in Mexico but as far as Africa sharing in the green revolution. sadky the EU's common agricultural policy from 1962 largely blocked Africa from win-wins of staple foods

EXERCISE ASK WHETHER THE WIDER REPRECUSSIONS OF NOT FULLY VALUING INTEL SUPPORTING PLACES CORRESPONDENCE WITH NATURES MARKETS

because there are many small island nations , less than 25% of nations have ever competed in the strategic "industrial era"  markets amerrica  values most - these countries literally have no significant mineral resources; thus food/agriculture and natural security comes first in a majority of nations -

we can therefore see the failure by the big west countries to go green is a double blow not only with climate crisis volatility but as yet curricula of local food and local diversity are either not taught in american universities or their professors would fail if examined by what asian rural women need to build intelligence around - this was amazing finding of steve jobs hosting 65th birthday party fazle abed  2001 - after 16 visits to bangladesh we can confirm that 1 billion women at bottom of pyramid see these 30 intelligence cooperations as fundamental www.abedmooc.ocm - this is what the new university7 movement from 2001 has been connecting to gather with abed and jobs partners - probably arizona state led by CROW (previously co-founder of Earth Institute) is best placed us university for this practice knowledge ; the question then becomes will gps data science databases be built to value this real human development knowhow; it is key  that this question is integral to the commitments made to UN and SDGs - see Guterres

[chris macrae]

lets sample a journey from γ Fei-Fei Li more EconomistLearning

2017 Here is the first speech fei-fei li gave at UN https://www.youtube.com/watch?v=N86BgtAqQPY - this helped launch ITU AIforgood in 2017 - now the pivotal transformation piece of guterres Un2 tech roadmapping and always online at the ITU- previously ITU summits had focused on web2 knowhow called WSIS - in 2022-23 fei-fei li has helped concluded first year of US www.ai.gov training and in june 2023 she and hassabis gave the white house public podcast on innovation in 2023...

Fei-Fei Li transcript youtube launch ITU aiforgood summit 2017, with the time numbers and line spaces removed:

Fei-Fei Li: It's quite an honor to be here and first time in Geneva, what a beautiful city. So um, I'm going to share with you a little bit of what I've been doing in the past almost 20 years of my ai career and it's mostly focusing on computer vision and machine learning.

Vision:

The visual system is one of the oldest and most important uh sensory system for animals in fact, more than half of our brain is involved in visual processing. It's been 540 million years of evolution until today, vision is one of the most important components of human intelligence, responsible for many activities that are important for us such as navigation, manipulation, communication, entertainment, work and and so food seeking and all this. So animals from simple ones all the way to complex ones almost ubiquitously have a visual system. In fact, a fun facting evolution that uh vision was said to be responsible for one of the most important evolutionary events in in in the history of animal kingdom which is the cambria explosion 540 million years ago during which time that the number of animals quickly exploded from just a few handful of different species all the way to many many more. So um it really underscores the importance of visual intelligence as part of the overall intelligence system.

Evolution of Vision:

In the same time, the evolution of visual machines has a much shorter period of time. Just like ai as a field is about 60 years old, computer vision as an important area of ai is about 60 years old or a little less. So even though we've been progressing rapidly, the technology of vision is still just at the very brink of making important contributions to our society. We still have not yet given sight to most of our visually impaired fellow people. We have lots and lots of cameras from the space all the way through the airplanes and drones overseeing our our home the earth yet we don't have a comprehensive technology to map out everything we're seeing or in swimming pool scenario that today we still don't have a very robust system that can detect drowning swimmers. Or in healthcare, there is increasing demand in terms of visual visual processing for diagnosis. So many areas of human life and society today demand computer vision technology. And the goal i think as a computer vision scientist is really to develop algorithms that can shine shine light onto this digital world.

Guardian Angel System:

So with that in mind, today I'm going to share with you um two research talk actually. In terms of the the progress of computer vision, we have come a long way. Just as thomas has introduced earlier, imagenet has become a benchmark for the progress of computer vision and contributed to the progress of machine learning and deep learning. And if you just look at the image classification task from the first year that imagenet challenge was rolled out which is 2010 all the way to about two years ago, the error rate has been steadily decreasing especially thanks to the breakthrough technology of deep learning to the point that it's hard to distinguish the performance of a human versus the performance of machines. In fact, in the field of computer vision, we have many areas of research not only object classification but also object segmentation, object detection, human pose estimation, 3d object recognition, scene parsing and so on. So this is a very lively and thriving field working on the basic technology of visual intelligence.

Well today with this audience, I would like to share with you actually two application area that we're applying computer vision technology to. One is in ai assisted health care, another one is for visual senses. And then to conclude, I'll also discuss a topic that is very dear to my heart which is about education and diversity.

So let me start with the first topic which is what we call the guardian angel system.

AI Assisted Healthcare:

One of the most here is the guardian angel hypothesis. Ai technology can help better the workflow of healthcare. We hear a lot about diagnosis using ai technology, especially radiology, pathology and so on. But there is another huge area of healthcare that's really important which is workflow. Workflow happens everywhere from emergency room to operation room from icus to primary care to uh to a pharma pharmacy or home care. So a workflow is an area where patients we care about the quality of treatment, the safety of patients as well as innovating technology to cut down the cost. Here as an example, we worked on one really important problem.

Hand Hygiene Tracking:

It's actually a really prevalent problem in all healthcare systems in america. One in 25 patients get infected by hospital acquired infection which might have actually fatal consequences to patients, costing america about 35 to 45 billion dollars per year. And one of the most important factors for hospital acquired infection is hand hygiene. That's a leading driver.

So the lack of good hand hygiene practice by medical personnel from nurses to doctors is one of the biggest drivers for this issue. So it's a really hard problem to solve.

In the past, what happens is for decades and decades, we use the hospital system use in-person audit. We have secret shoppers that tries to assess the quality of this. Recently RFID technology is used to try to replace human audits but RFID is very coarse and it's has a lot of signal to noise ratio problem and disrupts workflow.

With the recent advancement of computer vision technology, especially sensors that provides privacy, which are depth sensors, we have proposed a computer vision system that can track the movement of clinicians in the hospital without intruding in their privacy. So we don't have to reveal who they are but be able to track their hand hygiene movements.

This is non-invasive, it's continuous, it's unbiased, very very cheap and powered by AI algorithm. And this is a collaboration with Stanford's children's hospital where in a particular hospital unit, we put these sensors close to the hallway close to the hand hygiene dispenser and we can monitor the movements of the clinicians.

Long story short, we used a deep human tracking and then deep learning recognition system behind our technology and our performance of these hand hygiene activity recognition is actually really high and better than many of the state-of-the-art systems.

Visual Census

Census is what government uses to get an understanding of what our society is. Government spends billions of dollars every decade or so to do a census. United States just did a census in 2010, spending about a billion dollars per year. And this is where we get basic information of demography, income, education, race and all this.

A few years ago, my student and I started thinking about the really crazy thought: Can we do census for free using data big data available around the world or in the country in America? And we thought about Google Maps. Google Maps not only have GPS information, it has pictures. It has millions and millions of pictures of our streets on Google Street View. And there is one object that is prevalent in every city, every neighborhood in America, and that object is a car. A car really has a lot of information. Every time you know a car, you can look at its make, model, year and get a lot of information from that.

So we thought of this crazy project that we're going to go to the 200 most populated city in America and download street view pictures from Google Maps. We downloaded 50 million images from the 200 cities in America. And then we're going to detect every single car on the street and use a computer vision system to recognize all the details, the make, model, year of the car and we're going to use that to infer the social makeup of American cities.

This is the project we did. We call it visual census. Demographic prediction using 50 million Google Street View images and the cars in them. I'm going to skip what exactly we did in terms of car recognition. It suffices to say that we use a deep learning system to first detect a car, the presence of car and put a bounding box on it. And then use another deep learning system to recognize 202,657 types of car ever manufactured by human society in after 1990. And the recognition accuracy is really high.

And with that, we can get a lot of information about cars. And then we can ask questions like, can cars predict house neighborhood or or city income? And I'm going to just skip this and say we use a lot of features of the car. But the long story short is on your left, the actual zip code and income, house average household income is the data collected by household by US Census. On your right hand side is the predicted average household income by using the car information we get from the Google Street View. High correlation.

Here's another example. We even use car to predict voting results in the 2008 presidential election, Obama versus Vic McCain. And we can go down to zip code, precinct level.

Opens in a new windowThe New York Times

On the left is the actual result. On the right is the predicted result with the car information

n summary,

• Sedans predict Obama voters.
• Environmentally friendly cars predict Obama voters.
• Trucks and SUVs predict Republican voters.
• We can use car information to predict cities' environmental friendliness, crime rates, segregation, and racial diversity.

AI for All

• AI is a rapidly growing field, and we need to include more people from diverse backgrounds in the field.
• Studies have shown that diverse teams are more innovative and creative.
• AI for All is a non-profit organization that educates the next generation of AI technologists, thinkers, and leaders.
• The organization's mission is to bring diverse voices to AI and ensure that the next generation of technologists reflects the composition of our general population.
• AI for All partners with universities to hold K-12 programs that focus on AI education and humanistic centric AI teaching.
• The organization hopes to create an ecosystem between students, current technologies in industries, as well as the public and policy makers.
• The inaugural universities that are participating in the programs include Stanford, Princeton, Berkeley, and Carnegie Mellon.
• Some of the founders and advisors of AI for All come from a diverse background of entrepreneurs, Silicon Valley CEOs, educators, and policy makers.
• Melinda Gates and Jensen Huang are the seed funders of AI for All.

Conclusion

• AI is a very exciting field, and it's just the beginning.
• There are many opportunities for people from diverse backgrounds to get involved in AI.
• I'm happy to talk more offline.

Thank you."

[chris macrae]

sample γ Demis Hassabis more EconomistLearning.com

2019amazon podcast

https://theworldin.economist.com/edition/2020/article/17385/demis-h...

xI have devoted my life to building AI because I believe it is going to be the most important technology ever invented. By deepening our capacity to ask how and why, AI will advance the frontiers of knowledge and unlock whole new avenues of scientific discovery, improving the lives of billions of people.

Powered by curiosity 

The marvel of the human brain is proof that general intelligence is possible; creating AI is as much a journey of discovery into the inner workings of our own minds as it is an invention. The evolution of a larger cortex equipped humans with greater intelligence, enabling us to build more complex and co-operative social structures, which eventually gave rise to all of modern civilisation. Similarly, AI can help us build radically new and improved ways of life. The very curiosity that led to the scientific method may well be the key—not only to solving society’s greatest challenges today, but to understanding ourselves and making sense of the universe around us.

This article appeared in the 2020 visions section of the print edition under the headline “A supercharger for science”

==============================================

2023 Summer lecture EPFL Switzerland EPFL Facebook Twitter EPFL on LinkedIn EPFL on Coursera

here are some questions posed to Demis at this talk https://www.youtube.com/watch?v=Ds132TzmLRQ

59:11
for science but also for Humanity in general, how far Humans AI go?
59:16
I I think I've always imagined there's almost no limits in some way to AI because if you look around us in modern civilization how did we amazing things we see around us - it was with intelligence so
I think if you think back/ and you do thought experiments like you imagine going back to
pre-agricultural era and you you talk to a tribes person then about you know one
day we'll build Manhattan in New York and fly over in a 747 in 10 hours you
know it would sound Unthinkable and I think human intelligence has done that and I think
that there'll be almost as big another Revolution with these tools and and helping us solve all incredible problems that we think are quite intractable today eg energy sources material
design I'm thinking as well as biology and Drug design curing hundreds of diseases
-- I think that's all within reach and then I hope we would have a much more...
you can call it radical abundance and also much more equality in the world and lots of these huge
problems some of which we've created for ourselves as a society like climate, we'll have really great
solutions with AI helping the best experts in the world to solve these problems

1:00:40
I'm Leon from open knowledge Association and I have a question linked to the use case of infrastructure do you
intend to to use infrastructure AI  eg for Waste Management or or for simulation of city architecture or stuff like that?
1:01:05
great questionL  I'd love to do that, I think there's huge potential in using AI to optimize existing infrastructure ,
transport and power grids and so on I think to get 30% more out of them, that's what we found with the data centers where we optimized  massive data centers that Google uses to Power  search YouTube and so on
-we saved  30% of the energy from the cooling systems by using AI to control them and they already were quite
optimized systems  ..but you can even imagine things like shipping, shipping lanes I mean there's a huge amount of pollution is caused by that and just being more optimal on Logistics as well as inventing new Solutions like the plasti- heating enzymes I mentioned, or designing ways to deal with waste 
recycling I think all of that AI could help that you know that entire uh industry actually if we if we embed it in that

how do you see the role of Open Source in AI over the next decades and what do you see to

be the most the best approach to AI in terms of balancing  risks since its harder to maintain safety when everything is open but at the same time letting everyone contribute and using all of the brains in the world for this amazing development ?

:02:31

good question, and a complicated one right as you might expect you've actually said that you know you've explained that in your question so up till now know like deepmind's pretty much published everything we've done uh uh all our nature science papers

• AlphaGo: Mastering the Game of Go Without Human Knowledge (Nature, 2016)
• AlphaFold: A Solution to a 50-year-old Problem in Protein Structure Prediction (Nature, 2020)
• Pathways to Language from Self-Play (Science, 2022)
• MuZero: A General Reinforcement Learning Algorithm (Nature, 2022)
• Scaling Laws for Neural Language Models (Nature, 2022)
• LaMDA: Language Models for Dialogue Applications (arXiv, 2022)
• ViZDoom: A Video Game Platform for Reinforcement Learning (arXiv, 2017)
• Human-level control through deep reinforcement learning (Nature, 2015)
• Playing atari with deep reinforcement learning (Nature, 2013)

 a more complete list on their website: https://deepmind.com/research/publications/

and we have open sourced Alphafold2 and other things I think it's got to be on a case-by-case basis as the systems get more and more powerful and being open may attract bad actors...

obviously one would like to do open science and things  to progress much more quickly like that and it's good to get external review of your systems um but don't really have a full  solution

-and it is already a big debate

1:03:53

ideal case : I would encourage any of you in Academia to be working on this is more interpretability analysis of the current systems and we're not doing enough of that research on that work I would say relative to capability development so that we could develop evaluation tests for these systems so we can really rigorously know before we release them open source and other things that they're safe in certain ways what the properties they have  so they can be perhaps have some guardrails around them - that would be the best right and then you can put them out into the world for people to experiment

Here is bard summary of the talk part of above youtube

"Using AI to accelerate scientific discovery

• I'm honored to receive the honorary doctorate from EPFL. I've always admired EPFL and we have many collaborations with the fusion lab here.
• DeepMind was founded in 2010 when nobody (other than Fei-Fei LI) was really thinking about working in AI. We felt that a lot of progress could be made if we brought together hardware advancements, algorithm advancements, and some knowledge about how the brain worked.
• Our mission statement was to try and solve intelligence and then use it to advance science and benefit humanity. By solving intelligence, we meant trying to understand the nature of intelligence and then recreate that in an artificial construct.
• Our first big result was with classic Atari games. Our first system called DQN Atari was able to demonstrate the power of learning systems. It was the first really big system that was an end-to-end learn system.
• DQN Atari didn't give the rules of the game or the criteria of how to get points to the system. All we gave it was the raw pixels on the screen and it had to figure out everything else from first principles.
• This was pretty astounding because no one had ever done something at this kind of scale. The inputs were 20,000 pixel frames and that was pretty huge for any kind of neural net or learning system.
• After Atari, we moved on to Go, which was considered to be much harder than chess. AlphaGo was able to beat a human professional Go player in a five-game match in 2016.
• AlphaGo was a major breakthrough and it showed that AI could now tackle even the most challenging problems.
• After Go, we turned our attention to protein folding. Protein folding is a fundamental problem in biology and it's essential for understanding how proteins work.
• AlphaFold was able to make major advances in protein folding and it was able to achieve state-of-the-art results on a number of benchmarks.
• AlphaFold is a significant step forward and it has the potential to revolutionize our understanding of biology.
• I believe that AI has the potential to accelerate scientific discovery in a number of ways.
• AI can be used to automate tasks that are currently done by humans, freeing up scientists to focus on more creative and strategic work.
• AI can be used to analyze large datasets that would be too time-consuming or difficult for humans to process.(It is estimated that the 200000 protein database that we have open sourced = million of years of graduate work)
• AI can be used to generate new hypotheses and insights that would never have been possible without machine intelligence.
• I believe that AI is a powerful tool that can be used to make a real difference in the world.
• I'm excited to see how AI will be used to accelerate scientific discovery in the years to come.**

=============ed note we feel few people re better placed to advance ai op abd reduce risk -though exponential risk has been a concern of people i trust for at lwast 30 years- here is one elementary tour from our viewpoint riskai1.docx

[chris macrae]

α

ED: was it possible (in the Queens English) to architect global media for good- could we imagine a world where innovation is designed so that each next girl born has better and better chnaces at life as well as everyone else EW 1bng  Abedmooc.com

Geoffrey Crowther (see footnote publications = arguably greatest futures editor you have never heard of - his editing of the economist spanned world war 2 and decades before and after :- these 2 comments of president kennedy's offer a timely assessment of what was effectively Crowther's legacy as win-win mediatir seeking (like scot's ethical source adam smith) to unite human beings endeavors everywhere

 

https://www.raabcollection.com/presidential-autographs/kennedy-japan

1943 was the centenary of The Economist - the autobiography of 100 years of the Economist as Royal family's assistant (Wilson from Ireland repeal corn laws to India Charter bank, Bagehot English Constitution ... in changing to commonwealth is amazing; it bridges history and future of 100 extraordinary yeras; however crowther saw that what the net (Neumann Einstein Turing) were designing was going to accelerate innovation changing sustaiinability of 99% of human relationships; hence he dispatced sub-editor norman macrae to be pretrained at proinceton/NY for year of 1951 ( also dispatched to birth of EU messina 1955,  1962 reintroduction of Japan and Superports S (gateway to 65% of humans who are Asian) as one of world win-win innovators of Neumann's 100 times more tech /decade ) 

Know about the World Trade of Tea

stories of the 3 royals who most imoacted asian trade histories fascinate me - Uk, Japan , Netherland- back in 1776 when the English were thrown out of Boston and USA, Britannia redoubled her oriental world tade routes; the dutch had already become partners(swapping new york for peaceful development of nutmeg trade); the portuguese, the original coloniosers had amrried into England's Royal family

67 years after america's Independence, Economist Founded to assiatant 20 something Victoria to transform trading maps from Empire to Commonwealth?

The Economist is the dairy from the UK side since 1843\ - (for fun i asked  bard for a favorite story of 1950s UK Royal Intelligence - eg why did Queen Elizabeth christen his first child german for freeman/? -bard adds That is a very interesting and thought-provoking story. It is amazing to think that the story of James Wilson and the Economist has come full circle with the coronation of King Charles. It is also interesting to think about the role that artificial intelligence (AI) can play in helping us to achieve the UN Sustainable Development Goals (SDGs).

and The Economist has tried since 1962 to equally  celebrate Japan'sideas for advancing humanity -eg it was japans calculator company whose huge order caused intel to desih=gn programable chips 1964; from 1977 it discussed optimal maps for half of people living east of iran

 =====================

books that Geoffrey Crowther published:

• Economic Forecasting: An Introduction (1937)
  Opens in a new windowWikipedia

  Book Economic Forecasting: An Introduction by Geoffrey Crowther
• The Economic Ideal (1939)
  Opens in a new windowWikipedia

  Book The Economic Ideal by Geoffrey Crowther
• The Great Depression: How It Came, What It Did, and What It Left Behind (1939)
  Opens in a new windowWikipedia

  Book The Great Depression by Geoffrey Crowther
• The Rise of the American Economic System (1941)
  Opens in a new windowLSE Blogs

  Book The Rise of the American Economic System by Geoffrey Crowther
• The Years of Recovery: British Economic Policy, 1945-51 (1952)
  Opens in a new windowWikipedia

  Book The Years of Recovery by Geoffrey Crowther
• The Economic Revolution in Britain (1955)
  Opens in a new windowWikipedia

  Book The Economic Revolution in Britain by Geoffrey Crowther
• Economic Forecasting in Western Europe (1960)
  Opens in a new windowWikipedia

  Book Economic Forecasting in Western Europe by Geoffrey Crowther
• The Art of Decision (1961)
  Opens in a new windowNew York Magazine

  Book The Art of Decision by Geoffrey Crowther

  ===================================================

  references - whick are your fav books on goodwill multipliers of asia since 1962

  -ww fing ezra vogels work out of harvard essential to all far east growth; absent of abed's diary, we'd suggest harvard's martha chen for women builing s asia nation rural communities;;; an interesting but less academically deep genre was asia rising by rohwer but sadly he died young in a boating accident just when asia's jigsaw was expoentially raining world trade

=======================================

Crowther also had academic partnerships with a number of institutions, including:

• Claremont McKenna College in Claremont, California, where he gave a lecture in 1958 that was later published as the book The Economic Revolution in Britain.
• The London School of Economics, where he was a visiting professor in 1960.
• The University of Oxford, where he was a member of the Oxford University Institute of Economics and Statistics.

Crowther was a respected economist and journalist, and his work had a significant impact on the way that economics was taught and understood. His books are still widely read today, and they provide a valuable insights into the history of economics and the development of economic thought.

[chris macrae]

β

magic isnt easy to write up unless you have seen who needed it, and spent decades across generations mediating intelligence architecture, and it may help to be not a mathematical great but one who sees maths as about helping people faced with very last chances

elp code 500 un ai solutions -GWHYNETSPJ

Gov2 Womenempwered HumanAI Youthtoo Neumann Einstein Turing

S= goals 1-5 & 17 She-tooHealthEdLeadFoodFinance abedmooc.com

P=PolicER J=TobsSolarWarer

https://www.itu.int/dms_pub/itu-s/opb/gen/S-GEN-UNACT-2022-PDF-E.pdf

1UNITAR 1: NVIDIA GPHJ •P216 The United Nations Satellite Centre (UNOSAT) collaboration NVIDIA on training and research activities AI for Earth Observation SDG with an initial emphasis on disaster management. UNOSAT and NVIDIA to benefit from their respective facilities, resources, and domain experience. 2 initial priorities: 1) integration of NVIDIA’s accelerated computing platform within UNOSAT’s infrastructure to fast‐track research and development

AIgood REHEARSAL: the miracle of 1 billion asian women (family building love stories) empowering end to extreme poverty (from villages without electricity in 20th C to leapfrog models when partners brought solar and mobile)

you might think economics would celebrate the intelligences that helped support this miracle- -there's a problem known as PAULO FREIRE"S PEDAGOGY- the idea that one man could encourage 100000 educators to go live in villages without electricity to help train illiterate village women build the 8th most populous nation doesnt fit western-northern world's view unless your family tree includes asian missionaries and understanding multiple ways in which tropical regions needed unique solutions for infants to survive; when you have no electricity, you are in huge humidity every day and there is no trade between yiur rural region and cities , you become the forgotten bottom pyramid of earth

at abedmooc. mainly 3 young female (Asian and latin0 jouunalists and I logged up  are some puzzles inoted around 20 meetings with Fazle Abed 16 in bangladesh - maybe you can find some other puzzles because his whole intelligence weaves together so many innovations of SHELF (goals %*#*$*@*!*17( that its hard to believe that someone could continue over 50 yeras aged 33 to 83 mapping them - lets start at what happened as a result his 80th birthday party spring 20216- basically his 5 truest believers stared a mutiny at the UN - no there is not a bats chancein hell of educatirs achieving goal 4 on education unless they blend with technolgists and every practice expertise in un - eg food heal water blends too; these were dring peo[ple the then head of teh world bank the female pm of norway the female mayir of tokyo and probably the greatest tecaher to speak 3 languages english, chiense and code; fortunately the new Un leader guterres coming from serving refugggees agree the need ; we are now into yera 8 of digital cooperation roadmapping un2 and celebrating aiforgood as the only chnace that etachers teach and ever last mile practice of sdgs can uite 8 billion beings 

unlike gandhi, abed traneled from s asia to study engineering at glasgow, not law at bar of londonhe did this about 8 years after Britain had partitioned his homeland to be a colony of west pakistan; this was probably the greatest accidental tragedy of britain returning freedoms to peoples; west pakitan is about 1000 miles from east pakistan; it had no interested in shared development; india was in between but had been given the bay of bengals great port calcutta. so themuslim  peoples of the bay of bengal had ebe=very barier against them; fazle soon devided that naval engineering wasnt something of use to his peoples practicall so he converted to studying chartered accounting but had the engineerung mindset of blueprinting systems; and so by around 1968 he was extremely successful- hored by royal dutch shell to be regional ceo of hius himeland; then a tragedy struck half a million people all around teh shell campus were kiled by a cyclone; for about e12 weeks the vcampus became the epicentre of disater relid- abed met all sorts of missionaries; then he was told be shell- right now you need to support west pakstan re-estanlish order; that was where abed resigned form shell; finished his lond ocontract - sold his putney flat and with about 70000 dolars was ready to rebuild 15000 vilage homes (100000 people community) that had been flattened during teh war of idnependence; no sooner than the homes wer rebuilt than abed saw tens of women deying if starvation wekly; scores of infants dying of dehydration; he had to find sdmall bsuienss solutions they could replicate hunderds or thosusands of times but both making positive cash flow however small and serving life saving needs; nowehgre else in the workd has such a populosu place (90% rural only 10% in cities in 1972) been supported by a bottom-up public servant ; we can divide 30 intelligence cooperation solutions that 1 billion bottom of puyrmaid girls needed into 4 parts; 10 yrears solutions mainly sevring 3 by 100000 person communities which i call metaviages; finding a solution that unicef wanted niot only to be shared nationwide about across all of tropical asia; by 1996 afrer 25 yers of person to person networking vabed found partners who broight siokar and mobile to enetrepreneur with; then in 2001 steve jobs hoists 65th birthday party of abed in siliocon valley- what might happen if intelliugences were blended between arguably the 2 greatest personal networkers (real newtirks of abeds vilage women community buildes ,and virtual steve jobs 2.0 ; we call the mack personal computer jobs1.0, we call university in mobile phone joibs 2.0- could tehse 2 pople linkin colaborations to both theiur intelliugences and would the 4g era be a cahnce for the computer visons of the original net to be born again)

[chris macrae]

α20 Drucker  Schwab Guterres  Abe  -and back Ackoff Simon Owen Neumann Orwell

(tour alpha 20 is unusual we go chronologically forward; here  from Drucker 1967 to currency of Abe/Guterres and return through practical foresight back to V Neumann first designs of games digital humans play

When it comes to jargon of local-to-global transformation it would help to agree in one language (probably english as business lingua) before large language mediating to eg 1000human  languages through maths code

back in the 1960s drucker populariused serail post-indsutrail age (brad recommend 1967's discontinuity)- he didnt number this vuis a vus schwab's 4th industrial revolution or Japan's Society 5.0; simpler UN ,leade Guterres is spending hsi 10 years since 2017 asking:  can we even change government once since demongraphic constitutions perfects to messaging by armed men on horseback;  practically i like summary paper by ackofffor intelligence to leap over inconvenient truths - one definition of a broken system is when the harder previous experts apply their rules (even those society gave them a do no harm monopoly to admin) the more chaos (see maths defn by Einstein et al or view the case of covid) is caused- if uyou are concerned to inovle communities of eg up to 3000 brains in real open spaces not just hackathons, harrison owen's spirited engagements accelerating coperation and emotiobal intel now have half a million replications around the world since 1984 www.openspaceworld.com (beware kids from 9 years up curiously adapt open space facilitation with more flow than elders; sadly most schooling systems ban open space because such joy of innovation interferes with examining mindsets)

Orwell only just creeps into AI Game version 1 where we choose to look at intellects that actively contributed 1850-2025 - of cours the game can be applied at any time in histry but our point is nothing brans can spend 21st c time is uncganged from 1950 unless you are a hermit.Orwell foretld at least 4 amazing contexts:

worldwide sustainabilirt - 1984

the porential tragedy of places like myanmar

the tragedy of world food - aniumal farm

-his local passion for catyalonia's entrepreurs- in supporting their case he contacted tb which robbed us from mire of this future-mapmakers (crusader against dumbing down by top-down media) quests in 1950 age 46

There is a heck of a lot needed in eg wikipedai form to follow how systems analys began from early in 29th and hoiw ai has (on digita se=teroids) become its 21st c trabsformation. IF you can contribute an insight on this map please chat with me [e-mail] . Only recently did bard update me on Herbert Simon whose name I'd heard but who's ledgacy i have only just begun to catch up with

Herbert Simon continued to make significant practical contributions to the field of systems analysis into the 1990s. In 1991, he published The Sciences of the Artificial (3rd ed.), which is a collection of his most important papers on the topic of artificial intelligence. This book was highly influential, and it helped to shape the way that we think about AI today.

Simon also continued to work on the development of computer-based decision-making tools. In 1996, he co-founded the Strategic Planning Institute, which is a non-profit organization that provides decision-making tools to businesses and government agencies.

Simon's work on artificial intelligence and decision-making had a profound impact on the field of systems analysis. He helped to develop new methods for understanding and managing complex systems, and his work is still used today by businesses, governments, and other organizations.

Here are some of Simon's other influential publications:

• Administrative Behavior (1947): This book is a classic work on the theory of organizations. Simon argues that organizations are complex systems that can be understood by using systems analysis techniques.
  Opens in a new windowwww.amazon.com

  Administrative Behavior book
• Models of Man (1957): This book is a collection of Simon's papers on the psychology of thinking and problem-solving. Simon argues that humans are limited in their ability to process information and make decisions, and he develops a number of models to explain how humans think and solve problems.
  Opens in a new windowwww.amazon.com

  Models of Man book
• The New Science of Management Decision (1960): This book is a classic work on the field of management science. Simon argues that managers need to use quantitative methods to make better decisions, and he provides a number of examples of how managers can use these methods.
  Opens in a new windowwww.amazon.com

  New Science of Management Decision book

Simon's work is still relevant today, and it continues to be used by businesses, governments, and other organizations. He was a pioneer in the field of systems analysis, and his work has had a profound impact on the way that we think about complex systems.

This might sound like a nerdy question but actually converging on a map for 8 billion beings to see each others most urgent needs matters if we arfe to be mother nature's fav species vis a vis her extinction protocls

which do you think is the most advanced system transformation calling 

un2 or gov2 =eg vision lead by UN guterers since 2017 (also known as digoital cooperation rodamapping -see )

web3 or ed3 -what we need tio change in 2020s if media and education is to stop wasdting youyth times with liues, hatered or stuff that irrelevant to youth being first sudtainability generation

schwab world economic forum's 4th industrial revolution  

late great japanese president abe soc 5.0

-actually if i understand correctly they are all trying to make the same giant leap apart from industrial revolution 4 

now of course you do need to double wheck as all of these dynamic maps as very fast changing but my understanding is that at japans g20 in 2019 abe called for one addition to industrial revolution 4 that is something he called osaha trach as he hoped everyone would agree to do it by the time of the osaka expo - it was sharing transnatioanlly deep data in ways relevant to poorest local communities in a global voilage world; when we talk of sharing we mean agreeing eg how to see any places greatest climate or  adaptation challenges we dont necessdarily mean globally taking action which needs locals to choose

in any event abe's plea caused the un2 framework to add a 9th transformation subsystems codes - it slso moved along some parts of cop26 - where nations were stuck on agreeing what they would all do together could we get on with adaptation knowhow that localities anyone need to make heir own productive deciosnson

it is quite amazing when you think of it that top down national govs for hundreds of years and even multilateral designs of 1945 have not been totally transsformed once compared with corporations which may have gone 3 revolutions

I must admit some of this langauge seems to get lost in translation - in some ways it was simpler in the late 1960s when both peter drucker and my father on behalf of yesrs 15-20 of neumann's survey used the term post-indusrtrial revolution - their point was value in advanced countries was no longer on making inanimste things but in service o even in knowhow products and this would require everyone in advanced economies to be users of brain tools - the coming of the internet, the coming of moibile just being 2 examples that 2wer quite hard to envision when the slide ruler was still the most advanced comutational tool

I find bard LLM extremely useful - if i carefulyl clarifey place and date it gets very helpful ; my father was homescjholed up to about 13 in british embassies in places like stalins mosccw as grandads job was britains main intel on the increasing evil of  bothstalin and hitler - a job grandad had started when his postgrad studies as a scot who had travelled to at heidelberg got interrupted by world wat=1 - i remember dad saying that at approximately age 12 he met peter drucker at tea in british embassy moscow - at that time druvcer had started his career in jouranlism- he was always going  to place about 12 yeras ahead of my father but my the late 1960s most of their innovation ideas and  how fast future was changing were closeesly aligned - here's bards help on seein this

bard says: 

Peter Drucker was first employed by the Frankfurter Zeitung, a German newspaper, as a journalist in 1931. He worked for the newspaper until 1933, when he was forced to flee Germany due to the rise of the Nazi Party.

After fleeing Germany, Drucker went to London, where he worked as a freelance journalist for a number of publications, including the Manchester Guardian and the New Statesman. In 1935, he moved to Moscow, where he worked as a correspondent for the Christian Science Monitor.

• In 1937, Drucker left Moscow and moved to London, where he worked as a freelance writer and editor.
• In 1939, he married Rose Huberman, a fellow German Jew who had also fled the Nazis.
• In 1940, Drucker moved to the United States, where he worked as a management consultant for a number of companies, including General Motors and General Electric.
• In 1943, he published his first book, The End of Economic Man, which was a critical analysis of the Nazi economic system.
• In 1949, he published his second book, The Future of Industrial Man, which was a more optimistic view of the future of capitalism.
• In 1954, he published his third book, The Practice of Management, which is considered to be one of the most influential books on management ever written.
• In 1956, he was recruited by Claremont University, where he taught management for the next 20 years.

Did drucker ever discuss the term artificial intelligence

Yes, Drucker did discuss the term artificial intelligence (AI) on a few occasions. In his 1969 book The Age of Discontinuity, he wrote that AI was "one of the most important developments of our time." He also wrote that AI had the potential to "transform the way we live and work."

====================== I hope this episode makes the case for  people to track back their \family tree as history is often far more diverse and even a tragedy of accidents  - my request is strengthened if you are disapoira or immigrant because our hyperconnecting world needs families to be twin histiorians of at least 2 places so that we can twin diversity and better yet we can keep track of llms as Large language Mediation attempt to help unite us by mediating the hopes and positive emeotional energies if 1000 different cultures

its the case that where peter and dad grew up is the very strange area south to nortn of what is now called the suez canal has been the region where world wars 1,2 and now putins war have spun - its amazing that over 110 years the combined intelligence of today's 8 billion beings still hasnt resolved this one region's complex needs to accecss world shopping lanes etc

there's another story that has bee clear for 70 yeasr snow - neither father nor drucker was saying that experientailly accelerated change was a choice they would make for humans but they were saying tere is no way to stop this acceleratuon so our last chances of preventing extinction must get ebough people mediating ahead of change - in that sense aiforgood is in my view the last chance solutions of all of the above experts way of framing the future- we most syop igorant mass interviews on ai risk- yes tehre are rsiks but these can be contextaully calrified; eg end all bad medai; eg make sure no bad actirs are playing with viruses or natyres dones whuhc mat=y be irreversible but if there is anyine telling you we have a bats chance in helll of not gesing destroyted by claimte without good ai - well ist your choice but i am of the belief that extinction would be tehgreatest matys errir ever - and in fact all ai is mathematiucs bef=fire it gets applied to anyhting - so this is why part of the game of architect of intelligence is asking who are the maths propel you trust most- i realise making gokd amtehmatucians world calss heroes is not something society has done much of - but as i say extunction would be the greaest naths error ever - and whilei am only a minor nathemtician Ima statscamg=brodge dampot comored with peers like conway or hwakings -it saddens me when i see ggos mathematucains being abused 

socity 5.0