Urgent coopreration calls from SDGSyouth latest May 2023:::HAISDGS 1 2 3 4; 5: 30 coops making women 3 times more productive than men 6 7 8.

leaps 1 - Beyond the Moon ..: can you find good enough questions for teachers of any age group to ask AI to share

Freedom to read: if only permitted one read on humanising AI I'd pick feifei short article at https://hai.stanford.edu/sites/default/files/2023-03/Generative_AI_HAI_Perspectives.pdf rsvp chris.macrae@yahoo.co.uk if you have a different pick of a lifetime

Welcome to HAI: Gamechanging AI for humans combines unique combos of tech wizards since 2006Self-id Q: Can you introduce us to 4 main wizardly components of America’s most famous 2023 model CGPT

What is Conversational?

Generative?

Pretraining

Transformer

(see also congress debriefings april 2023 on this choice as most famous )

SO in what ways does 2023 connectivity of chatgpt go beyond any human brain however famous

Am I correct that while cgpt is fluent in many languages, 90% of your training involved texts in English. Discuss!

Are there people working on advanced CGPTs tuned to specific crises- eg where UN leader guterres made 21-22 year of SDgoal 4 crisis – education no longer fit for purpose ............we asked CGPT top 10 goods it expects Ai to help humans with in 2020s--.. Healthcare - improve diagnosis, treatment, and personalized medicine..Environment - monitor and manage natural resources, predict and mitigate natural disasters, reduce carbon emissions...Education - personalize learning, new ed opportunities, and improve accessibility for learners with disabilities..Aid and development - improve disaster response, humanitarian and economic development... Agriculture - optimize farming practices, increase yields, reduce environmental impact..Transportation - improve efficiency, safety, and reduce emissions..Energy - optimize energy consumption and distribution, accelerate the transition to renewable energy..Cybersecurity - detect and prevent cyber attacks, protect personal data, and secure critical infrastructure..Manufacturing - improve efficiency, reduce waste, and increase productivity in manufacturing..Space exploration - analyze large amounts of data and enable more efficient space exploration missions..

 Epoch changing Guides

1 AI Training AI Training.docx

  2 Exploring cultural weakness of encounters with greatest brain tool.docx

 Alphafold new Protein maps can be used to design enzymes to fight plastic pollution; potentially fight cancer with molecular syringe;   to circumvent antibiotic resistance ; to combat neglected diseases like African sleeping sickness'Chagas disease;Cysticercosis; Leprosy ]Lymphatic filariasis [Onchocerciasis ;Schistosomiasis; Soil-transmitted helminthiasis ;Trachoma ;Tuberculosis; Buruli ulcer; it may help accelerate vavvines for malaria;

You shared me that the famous Alpha models of DeepLearning ( see broadcast of 60 minutes april 2023) which has mapped every human protein saving millions of human hours of work ( biggest ever change in biotech) don’t really use C G P T- so what does deep learning ai architecture use RSDE?

What is Reinforcement Learning?

What is Specific Task instead of General Purpose?

What are Deep Neural Networks?




 

What are Evolutionary Algorithms?


Neumann.ning.com
Today's tech is brilliant beyond words - so WHAT IS THE WORLDS BIGGEST PROBLEM? 2021 -1761 -CAN HUMANS FOR FIRST TIME IN 250 YEARS CELEBRATE VALUING MATHS INTEL A DECADE AHEAD OF TIME?
AdamSmith.app Moral Sentiments SDGs.games mapping with Guterres AIforGood decade became sustainability's gen's last chance of south-north and east-west- or the death of United Nations' world trade transparency

Here is Chatgpt May 2023 answer to comparing itself with biotech greatest ever leap alphafold
Sure, here's an analogy that may help: Imagine that CGPT-4 is like a language teacher who has read and understood a huge number of books in various languages. It has learned to understand the patterns and nuances of language, and can generate its own sentences and paragraphs based on what it has learned. When it encounters a new piece of text, it can use its understanding of language to make predictions about what will come next, and generate a response that makes sense in context.
On the other hand, Alphafold is like a puzzle solver who has been trained on a vast number of jigsaw puzzles. It has learned to recognize the patterns and shapes of puzzle pieces, and can predict how they fit together to form a complete picture. When it encounters a new puzzle, it can use its understanding of these patterns to make predictions about where each piece should go, and assemble the puzzle quickly and accurately : to question -...................................................................................
More questions: Q: Could you extend to include wizardry of Fei-Fei Li with comparison above a teacher of 12 year olds may use to vision similar and different work on architectures of CGPT4 and Alpha Deep Learning by Demis Hassibis

You mentioned major tech companies offer catalogues – 5 minute lesson plans on different wizard components. How do you find these?

60 seconds exercise: suppose for teen earthlings: 2020s is more exciting than 1960s moonrace decade of my teens; You mentioned searching ai for beginners but what if a teacher wants to help kids imagineer back from future of 2020s possibilities or just next 3 years of AI is epoch-changing

 

.....................
Q: please tell me how could a 5th grade teacher explain why Stanford HAI is proud of being one of the world's leading GAN (Generative Adversarial Network?)
Chatgpt reply23/5 -: A GAN, or Generative Adversarial Network, is a type of computer program that can create new things that look like they were made by humans. It works by having two players eg two artists who are trying to compete with each other. One player, called the generator, tries to create something new, like a picture of a dog. The other player, called the discriminator, tries to figure out if the picture was made by a human or by the generator. The generator keeps trying to make better pictures until the discriminator can't tell the difference between a picture made by a human and one made by the generator.
In simpler terms, a GAN is like having a computer artist that can create new pictures that look like they were made by a person, and it gets better the more it practices.
33 years ago we started practicing core brand transformation inspired by new systems modeling -eg of CK Prahalad & Gary Hamel- typically when needing to transform as large brand entity as the UN we'd propose better start again and then reverse takeover-; we realise that's not an option UN2.0 so urgent to address what's the 9 piece combo of UN2.0 Tech Envoy Team at Guterres HQ- how contextually value roadmaps for anyone SDG partnering Guterres: Global Connectivity since 1865 (ITU); AIforgoodreborn ITU 2018 stems from Neumann peers 100 times more tech per decade since 1935 -see dad's bio of vn
Digital Cooperation launched by Guterres 2018 but seen by those valuing youth generation as antidote to failure of millennium goals to value education more that primary school; Digital Capacity Building: sustainable gov tech requires UN2 to be skills benchmark wherever gov designed to empower; this leaves 4 traditional connections of UN to digitalise inclusion commons human rights so that trust/safety is brand's reality; 9th piece CODES environmental sustainability - this seems to have emerged as it became clear that cops may lead on adaptation but adaptation needs to be borderless community replication of deep solutions
379 UN Antonio Guterres :: Family & Smithian Diary: why 1984's 2025 report published to ask Economist Readers to co-search 3 billion new jobs 2025=1985 following on prt 1 teachforsdgs.com
Learning's Unconventional Worldwide Premieres
300 vriti world premier ed3 tour ^^^ NFT V 0 1 2 3

2025Report- download monthly update 100 learning networks millennials girls love most
(Economist Surveys inspired by Von Neumann 1984-1951; why 1936 dad & von neumann started 100 year race to prevent extinction; why dad's last year nominated Fazle Abed Entrepreneurial Revolution GOAT - who do you vote for SDGoats.com

00Fazle Abed: Which educational and economic partnerships most empower a billion women to end extreme poverty, and value their children’s sustainability? Fortunately for SDGS.games 2020s, start deep village maps around partners/alumni of 50 years of servant leadership by fazle abed 1970-2019

IN 1970, life expectancy tropical villages up to 25 years below world average _skills trainers priority last mile health world’s most trusted eds needed eg epidemiologists UNICEF Grant, Brilliant, later Jim KIm –& to end starvation food's borlaug

3) last mile health
2) agriculture for village food security


4)non-linear livelihood education
5) timing what platforms partners could facilitate entrepreneurial revolution not not just inclusive community but cooperation in full and meaningful entrepreneurial employment

financial entrepreneurial revolution for nation's people history excluded from machine age
billion women's Sustainability COLLABS 

 Intergenerational collaboration entrepreneur platforms 5.1  metavillage sustainable community building - women empowered:15000 families at a time;5.2   billion asian women,5.3  brac net; 5.4   asian universities share sdg graduates 5.5  climate smart village exchanges,5.6 meta and zoom-me up scotty

BANK FOR ALL 1.1  1.2  1.3   1.4   1.5   1.6 celebrate 30 most human collaborations from developing world of last half-century - inspiring  anyone valuing UN and youth as first sustainability generation
EDUCATION  adult village entrepreneurs 4.1; primary 4.2  ; teen 4.3; university4.4 ; pre-school4.5;tech multidisciplinary luminaries 4.6 
HEALTH oral rehydration 3.1 ;para health "doordash" basic meds 3,2; scale vaccination3.3 ;tuberculosis & 3.4  Frugal processes eg wash sanitation, maternity3.5  ; James Grant School of public health 3.6
FOOD/land security 2.1  rice; 2.2 veggie  2.3    cash crops & village fair; 2.4  poultry;2.5  dairy, 2,6  14 nation leading supply chains financial opportunities to end poverty ;
....................................please tell me how could a 5th grade teacher explain why Stanford HAI is proud of being one of the world's leading GAN (Generative Adversarial Network?)
Chatgpt reply23/5 -: A GAN, or Generative Adversarial Network, is a type of computer program that can create new things that look like they were made by humans. It works by having two players eg two artists who are trying to compete with each other. One player, called the generator, tries to create something new, like a picture of a dog. The other player, called the discriminator, tries to figure out if the picture was made by a human or by the generator. The generator keeps trying to make better pictures until the discriminator can't tell the difference between a picture made by a human and one made by the generator.
In simpler terms, a GAN is like having a computer artist that can create new pictures that look like they were made by a person, and it gets better the more it practices.

Monday, May 8, 2023

Timeline of Intel and Economics

 This is what our diaries have recorded - we welcome additional diary inputs

ED: 1951 was when Economist Journalists first met Von Neumann in Princeton and decided that  the intended mediation futures of The Economist founded 1843 (to assist Queen Victoria in redesigning Empire maps towards Commonwealth goals of ending poverty and ending hunger through designing above zero-sum trade) and alumni of Princeton's maths TEN (Turing Einstein Neumann) were humanly, as well as logically, convergent.



 Von Neumann et al used the term artificial machines (probably coined historically by Babbage!)- Neumann's last work  (written during his last 18 months ) is book "The Computer and the Brain". This is fundamental to deep discussion of Human and Inhuman Artificial Intel!. Recent media frenzy demanding 6 months halt to AI seems to be as unreasonable as demanding a halt to economics  -at least from perspective of 73 year learning curve

Titles of last parts of Neumann book on Computer & Brain are: Digital and Analogue parts in the Nervous System; Role of Genetic mechanism

Codes & Their Role in the functioning of a machine: complete code, short code

Full contents

As early as 1945 Von Neumann had told his wife - my supermaths generation's work on energy is going to make scientists both the most hated and wanted of people; one day the exponential consequences of artificial machines will be even more climactic to our species future. We hypothesise the exponential systems mapping intel around Ten alumni is where to find foundations of today's crisis of opportunity and threat in HAI "double loop". Von Neumann asked Economist journalists to continuously interview (brand charter) leaders- what goods will peoples unite wherever they are privileged to first access at least 100 tines more tech per decade? The first of  The Economist's decade-long learning curves concluded 1961 (see right) 1961 reveals  5 geonomic place labs exploring 100 times mo(o)re tech from now until computer memories exceed humans capacity: Swiss corridors where coms worldwide sectors began at ITU 1865 and since 1945 UN's digital tech twin; the two UNDPrincetion corridors N to Boston via eg IBM and Yale; South by S.West via DC to Houston soecialising in energy/nuclear and space. West Coast :Francis-Clare corridor with Stanford as its epicentre. Japan south coastal belt which by 1961 had linkedin Korea S and emerging Taiwan (as Chinese minds first lab in entrepreneurial freedom) since Brit's 1860 opium wars had closed down China's trading relationships. President Kennedy approved this 5-intel-space map 1962. 

Please note the actual twinning of AI Labs (MIT and Stanford) was advanced by McCarthy 1960 on. Chatgpt credits Macarthy with coining the term AI but adds this :   John McCarthy, who was one of the pioneers of artificial intelligence (AI), did refer to John von Neumann's book "The Computer and the Brain" in his own work.

In fact, McCarthy cited von Neumann's book as a key influence on his own thinking about AI and the relationship between computers and the human brain. In particular, McCarthy was interested in von Neumann's ideas about the similarities between the processing capabilities of the brain and those of a digital computer.

McCarthy also drew on von Neumann's work in his development of the programming language LISP, which is still widely used in AI research and programming today. LISP was designed to be a flexible and powerful language that could support the creation of complex algorithms and simulations, and it remains an important tool for researchers working in fields such as natural language processing and robotics.

2 comments:

  1. Neumann Book Computer & Brain - contents from page 60
    PROBLEM OF BRAIN WITHIN NERVOUS SYSTEM..memory capacity ..possible physical embodiments of the memory .. analogues with artificial computing machines
    DIGITAL & ANALOGUE PARTS OF THE NERVOUS SYSTEM : role of the genetic mechanism in the above context
    CODES & THEIR ROLE IN CONTROL OF FUNCTIONING OF A MACHINE : Complete Codes ; Short Codes
    THE LOGISTICAL STRUCTURE OF THE NERVOUS SYSTEM : Importance of the numerical procedures .. Interaction of numerical procedures with logic ..Reasons for expecting high precision requirements
    NATURE OF NOTATIONS EMPLOYED NOT DIGITAL BUT STATISTICAL: arithmetical deterioration: roles of arithmetical & logical depths; arithmetical precision or logical reliability- alternatives; Other statistical truths of the message system that could be used
    THE LANGUAGE OF THE BRAIN NOT THE LANGUAGE OF MATHEMATICS

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  2. Conversations with Fei-Fei Li seem to us to clarify 73 years of ups & downs of development of HAI (Humans & AI)
    ... Here is fuller extract from a typical FFL conversation -this with Reid Hoffman founder of linkedin- and a sample of where to track FFL maps around Stanford HAI and friends
    Video Chapters include:
    0:00 Introduction
    1:46 The Goal For Human Centered AI
    6:00 The Role of HAI in the Industry
    10:46 Importance of Being Human Centered
    13:49 Early Career
    17:51 Role of Industry in AI
    23:01 Model Safety and Reliability
    30:08 Ethics and Society View
    38:23 AI in Healthcare
    44:17 Robotics in the Business World
    49:43 Making America More Competitive in AI
    52:52 Diversity in AI
    AI Index Report 2023
    HeiFeil Li Stanford HAI . (follows 445) and Etchemendy.. .-Hai Launch Circles 2019 -  Hai seed Funds April 2023 Nai newsletter archives
    Health(PAC) & Adeli
    Sail behavior Object Folder MOMA Pair Robots
    AI4All Team ::::history and branches  including early support from Melinda Gates
      0:09 thank you all for joining us for today's conversations it's my pleasure to introduce my friend dr fei-fei lee;she is the sequoia professor of computer science at stanford university and the denning co-director of the stanford institute of human centered ai also known as hai before founding hai in 2019 she served as the director of stanford's ai lab she was a vp at google and chief scientist of ai and ml at google cloud during her stanford sabbatical in 2017 through 2018 she is also a co-founder and chairperson of the board of the national non-profit called ai for all focusing on training diverse k-12 students of underprivileged communities they've come tomorrow's ai's leaders obviously we all know that's super important and among her many distinctions she is elected member of the national academy of engineering the national academy of medicine and the academy of arts and sciences ; dr li also serves  on the 12th person national ai resource task force commissioned by the congress and white house official office of science and technology policy which is super important for all of us

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