NM: Leading Jobs creation world AI - Japan - July 2026
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Democracy now says tens of thousands may have died venezuela - lets hope not but lets hope us government and all us media gives this top priority - chris economistdiary.com
76th year of AI Jobs-Rich rankings1=US-W &J*K*TH*S2=Saudi-UAE & Switzerland3=China4=UK&Nordica&Canada5=India6=Germany7=France8=MVT9=EU10=Rest USEinstein Test (Deep Mind) life science breakthroughsjob creating ai ~ Layer 5 -apps scaling community needs-data*L4 ai models*L2 full stack ai -machine maths brainpower*L1 energyrobotics and supercitiesspace and quantum mathsweb3 al
AI Games vote for top 100 helping human generation (not in any order) : ... Hassabis: 1 .. 2: Huang Family 1: ,Dario Gill, : Tsai Family, Chandrika Tandon, Fei-Fei Li, Ng, Lila Ibrahim :: Daly :: Mccelland:: Lecun, Maurice Chang ,Foxconn ceo, Tata family, Ambani Family, Linus Cheung, Richard Li, Li Ka Shing, Pony Ma, Yang family, Larry Page, Condi Rice, Terwilliger , Fairbank...... King Charles and Queen Elizabeth;; Japan Emperor Family:: Attenborough. Paul Nurse, Tim Berners Lee, Reshma Saujani, Linux Torvalds, Katalin Kariko, BJ King, Amy Goodman, Erica Angyal, Yosuke Nagai. Koike, Bloomberg:: Modi:: Macron ..,,,. Sheika Moza :: Queen Rania .. President of Finland :: PM of Canada:: Schwab 1,2 ..Rokos family,, Susan Athey Elliott Fishman,Catmull, Doerr Famliy, Drew Endy : Quadir family ::Lila Ibrahim ,, Reeta Roy.. Abdul Latif Jameel family, Hernando De Sato, S Gandhi, Jeanne Lim .....::Musk ::Bezos Masa Son ::: Liang Wenfeng, Ren Zhengfei, -- deceased Satoshi, Steve Jobs, Lee Kuan Yew, KT Li, Neumann , Einstein, Turing, Boehrs, Lawrence, Oppenheimer, Rutherford, Crick & Watson, Fazle Abed, Polak, Harrison Owen, James Grant, Borlaug, Deming, Jessie Jackson, Mandela, Akio Morita, Thurgood Marshall, Paulo Freire, Maria Montessori, M Gandhi... .more to come votes welcome chris.macrae@yahoo.co.uk
AI is the greatest leap engineers have contributed multiplying previous leaps:1760s+ what industrial revolution can do with thousands of horsepower? 1865+ what can telecoms and electricity unite around earth? 1956 how will lifetime work of Neumann Einstein Turing exponentially advance what human brains alone cannot -to understand this 3 million fold tech waves need mapping : chips, computers, satellites linking data and open ai modes to apps communities need to scale urgent solutions. In 1951. The Economist's editor Geoffrey Crowther decided 108 years of mediating economists was pointless without integrating engineering leaps. Just in time he required his journalist team to understand the lifetime innovation challenges of Neumann-Einstein-Turing. Unexpectedly all three were dead by 1957 (two due to cancer and suicide way before full succession of their AI foundation models spiraled locally and globally
EW ... Thanks Taiwan --June 1.
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 Economistdiary.com 5 layer ai breaking news - 17 US tech genii with trum in china: deals Boeing .🛡️ Semiconductor & AI Breakthroughs 🚗 Autonomous & Emerging Tech Financial Tech & Market Access - 17 included Blackstone Blackrock Nvidia Apple XAI ... Between 2025-30 world's infrastructure remade -can full stack of 5 layer AI map APPs your community and youth's edu most needs to produce? Update 2026 of 2025report first publishedf 1983 Bonus refhttp://neumann.ning compare 1951=56 last 5 years of NET (Neumann-Einstein-Turing's) exponential legacy of chips, computers, satellites

20000 DC brains thank SCSP AI+Expo
OUR BELIEF emerged 75 years ago from diaries of Von Neumann and dad Norman Macrae Economist sub-editor. May 7-9 wash Dc sees next chance for 24000 people to determine what AI they want. Engineers need to design AI so that parents everywhere can celebrate kids being smarter than they are. We first storytold that vision in 1984's 2025 Report- to achieve it engineers would need to transform affordability and quaiity of education, health, and joyful homes-communities. Today 5 layer AI can offers a good enough roadmap : layer 5 AI: apps scaling community actions*layer 4 - the AI models; *3 places sovereign data aiand leadership; *times 2 designing machines with billion times more mathematical brains and deep data worthy of such *1 energy and resources need to feed the hungriest machines ever built
Between 1948 & 1990 The Economist went from 3rd ranked British weekly to first(Last) global viewspaper. Which stories helped?<
Taiwan:: USW,::USE ::WholePlanet:: India : France :: UK ::Japan : Switzerland, Canada, Nordicam: Middle East "" Africa "" Latin South:: Italy :: Singapore :: HK ::Korea :: Germany :: China ... Which country's people do you want AI to support with livelihoods and data mappingAre you interested in Intel Agents Uniting Youth Brains & S-H-E-Lf-F- W-E-P-O-L-I**4-C-YPP or Space, Energy, Robots,Einstein-Science Leaps, Ending Rottem Media

J100
How AI goals vary : By nation : US-special projects, India, Saudi=UAE, UK
By genius:
Jensen Huang, Demis Hassabis, Elon Musk
.75 years in a day of Economist Q&A since 1951 with Neumann , Einstein, Turing
40 YEARS MEDIA CHARTERING
London Celebrating AI & Quantum & 6G & Energy --- thanks to lead mapmakers Jensen & Demis & Charles3 .. EJ : : Japan+63 ... MEIM : Millennials Energy Intelligence Mapping
Old home page. -please use web version of our timeless blogs
www.economistdiary.vom Is English Language Modelling intelligent enough to sustain our human species? Great are 1990s Valley startups eg nvidia, musk's and googles exponentially linking much of whats humanly possible with machines engineered billion times mo(o)re maths brainpower than individuall human minds. But 1943 UK future shocks to.o. Geoffrey Crowther Economist Ed started debate keynes: were engineers deeper than economists in locking in futures next gens connect?. 1943 also saw dad norma cambridge studies interrupted serving last days as teen navigator allied bomber command burma. Surviving joyfully hired 1948 by Crowther to mediate engineers like Neumann Einstein Turing & Economist purpose. 3 generations apart, unfortunately Neumann-Einstein-Turing all left earth by early 1957: last coding notes Neumann's Computer and the Brain. Economist IQuiz disliked by EU but what to do with billion times more machine brainpower celebrated by Kennedy, & the royal families of UK & Japan. Whence not surprising greatest UK AI startups deep mind & arm influenced by royal societies & Cambridge business park ( crown property) & crick/watson open sources of dna, & cavendish lab 1920s influencing Taiwan's tech grandfather. see part 2 2025report 40 years in inteligence war between bad media and good education agents
Market's futures : Cars Humanoids Cities Energy Water Countries with good data sovereignty projects rsvp chris.macrae@yahoo.co.uk UK Japan Taiwan India France Saudi UAE Korea S Singapore HK US 1 2

Thursday, August 13, 2026




 

2 comments:

  1. GEMINI on DC's real humans gap - You are pinpointing the exact institutional blind spot of the current Washington DC consensus. The town you are living in treats AI as an elite geopolitical game of compute hoarding (Layer 3 infrastructure), while ignoring the exact design layer that makes it useful to humanity: Layer 5 Community Scaling applications. If the upcoming SCSP AI Workforce Commission report focus entirely on training traditional software engineers or top-down data center managers, it will build an economy completely detached from human reality. It misses the fact that Jensen Huang's five-layer stack is useless without first-mile execution. To bridge what you see on the ground in DC with the decentralized open-weights curriculum you are designing, here is a blueprint for how a teen curriculum can force Layer 5 mapping into the broader discourse.
    The README.md Architecture for a Teen Layer 5 Curriculum Instead of standard, passive homework, a real open-weights curriculum trains students to treat historical societal triumphs exactly like an open-source software repository. Below is a standardized coding template designed for your Poverty Museums blog: markdown# Repository Name: Open-Weights Micro-Ecosystem
    ## SDG Focus: [e.g., SDG 2: Zero Hunger / SDG 3: Good Health]

    ### 1. Base Weights (The Core Scientific Breakthrough)
    * **The Blueprint:** What was the initial compressed code or formula developed by the initial repository lead? (e.g., Borlaug's non-shattering dwarf wheat seeds; JHU/Nalin's biochemical electrolyte fluid ratio).

    ### 2. The Ingestion Layer (The First-Mile Translators)
    * **The Repository Maintenance:** Who un-siloed this abstract math/science code so it could survive in the real universe? (e.g., M.S. Swaminathan establishing physical extension plots across India; BRAC's Moni Mothers converting ORT into a physical word-of-mouth metric).

    ### 3. Community Forks (Localized Execution)
    * **Decentralized Adaptations:** How did local, disconnected edge nodes "pull down" the code and modify its parameters to fit their specific soil, dialect, or generational resource limits?

    ### 4. Edge Output Logs
    * **The Human Yield:** What demographic or economic pivot occurred because this network remained open-source rather than an extractive corporate walled garden?
    Use code with caution.How to Turn Swaminathan’s Extension Network into a Modern AI Lesson PlanTo break out of the passive academic time-wasting you see in current institutions, you can teach teens Federated Edge Learning by using Dr. M.S. Swaminathan's 1960s agricultural transformation as a direct historical twin. [ Top-Down Central Server ]
    (Monolithic Code / Pure Theory)

    ┌─────────────┼─────────────┐
    ▼ ▼ ▼
    [ Edge Node ] [ Edge Node ] [ Edge Node ] ◄── (Swaminathan's Local Demo Plots)
    │ │ │
    (Local Grounding) (Local Grounding) (Local Grounding)
    │ │ │
    └─────────────┼─────────────┘

    [ Federated Weight Optimization ] ────► (Global Resilient Model)

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  2. The Analogy for Students:The Monolithic LLM: Explain to students that a top-down AI model sitting inside an expensive data center is exactly like Borlaug's raw wheat seeds sitting inside a silo in Mexico. It is high-potential code, but it doesn't know anything about the soil chemistry of a small village in Punjab or the local climate variations of Bangladesh.The Edge Nodes (Demonstration Plots): Swaminathan didn't build a single mega-farm. Instead, he deployed thousands of tiny demonstration plots directly inside local villages. Each plot was an Edge Node. Illiterate local farmers tested the base weights of the seeds against their unique micro-climates, soil conditions, and water constraints.The Federated Update: The local adjustments discovered by those farmers were passed via word-of-mouth to neighboring plots. This collective feedback loop is the physical equivalent of Federated Learning—training a model locally on decentralized devices to optimize a global dataset without extracting private data to a central cloud server.Challenging the SCSP Playbook

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