AI Story 1 - what to do with billion times smarter mathematician than separate human brains

DID WESTERN UNIVERSITY 4 YEAR DEGREES DELAY MILLENNIALS AGENTIC AI  & AGI WORLDs (1983 2025report.com with The Economist, following 33 years future history dialogues first inspired Von Neumann 1951)

Welcome to Neumann Hall of Fame Dialogues year 75 and 2025/6 as first college-age year of Agency including that linked to Billion Times Smarter Mathematical Brainpower 

As a Cambridge grad diploma maths lab DAMTP 1970s, i am biassed towards wanting to understand what deep data maps celebrating human's most urgent intelligence cooperations are made first with billion times deeper AI maths brains assisting thanks to accelerated computer architect Jensen Huang and Hassabis inspired DeepMind maths connected to Einstein 1905 revolution e-mcsquared and first demonstrated by alphafold3

Alphafold3 - 250 million proteins being UK deep mind answer (Demis Hassabis, pride of UK Royal Societies, google computing power ... continuation of turing and gatsby neuroscience and Crick institute ...)

we asked grok3 for other examples friends of Huang or Hassabis appear to be celebrating first with billion times smarter maths brains. 

usa doudna berkeley with nvidia and dell "significantly advance research in areas like fusion energy, materials science, biomolecular design, quantum computing (some say smart grid data can be so big it will need quantum), 

 and colossus Memphis  1  grok4

Taiwan supercomputer partnership announced computex 2025 _earth 2.0 with nvidia, IBM weather company, National instuites

French supercomputer announced europe ai week june 2025 alongside UK supercomputer - it looks as if biotech leadership with alphafold3 will also need to be joined by vaccine eg mrna research europe-uk (since kennedy/trump have pulled out of mrna research, halted cdc data mapping and appear to be rescoping NIH. Health AI leadership has become very uncertain and probably needs to be included in top 5 regions (or languager combos) valuing data sovereignty. A peculiarity of Trumps tarifs by nations is  does not always match strategic sectors 5-year development as exponentially efficiently as a billion times maths brain of tech supply chains can. This will probably multiply trust of Pacific millennials relatively abundant engineering brainpower. 

India supercomputer - modi, ambani, nvidia

Japan - before covid softbank uk arm and nvidia were of one vision- also beyond China , Japan is a lead case of an economy with so little of its own carbon fuel (eg 15% of past needs) that most island nations need green economy maps

UAE supercomputer

One clue is to look where these first 25X energy most efficient supercomputers are being built by whom (typically awareness of value of energy goes together with what moon shots on earth do all 8 billions humans want to see supermaths and agents for youth solve first )

rsvp chirs.macrae@yahoo.co.uk

....

Media story 1a :  in 1983's 2025 report we hypothesised that just before social media became a thing , the world's public broadcasters could unite on a millennials solutions "Olympics" which both attracted mass broadcast audience and kicked off chatting spaces. Having missed that opportunity to make tech wizards as celebrated as sportstars or pop starts we asked grok how to stage ai agent olympics at this unique time

-some of grok3's ideas for starters:

Here are 10 examples (we can expand to 30 with your input):

1. Energy Mapping: AI designs optimal energy maps for sustainable supercomputer deployment.
2. Water Efficiency: AI optimizes data center cooling to minimize water use.
3. Healthcare Access: AI delivers telemedicine diagnostics for rural communities.
4. Education Personalization: AI tailors learning for underserved students.
5. Microfinance Equity: AI predicts and distributes microloans for wealth creation.
6. Climate Modeling: AI forecasts climate impacts for local adaptation.
7. Food Security: AI optimizes agricultural yields in resource-scarce regions.
8. Digital Twin Innovation: AI builds virtual models for urban planning.
9. Language Preservation: AI protects indigenous languages via translation.
10. Disaster Response: AI coordinates real-time relief efforts globally.

Event Structure

1. Competition Phases:
   • Qualifiers (6 Months): Global teams (millennials, students, teachers) submit AI solutions via open-source platforms (e.g., GitHub). AI judges (e.g., Grok) score entries for feasibility, impact, and equity.
   • Finals (1 Week): Top 100 teams per context compete live, streamed globally. AI systems (e.g., NVIDIA’s Omniverse, DeepMind’s algorithms) solve real-time challenges (e.g., optimize a city’s energy grid).
   • Gold Medal Awards: 30 winners, one per context, judged by impact metrics (e.g., lives improved, CO2 reduced).
2. Participants:
   • AI Athletes: Open-source AI models (e.g., Llama, Grok) and proprietary systems (e.g., NVIDIA’s DGX, DeepMind’s AlphaCode) compete, showcasing diverse approaches.
   • Human Teams: Millennials, teachers, and students form teams to train/tune AI or provide local data, ensuring inclusivity.
   • Judges: Global experts (e.g., H&H), community leaders, and public voters via X.
3. Viral Popularity Tactics:
   • X Campaigns: Hashtags like #AIGIG2026 trend solutions (e.g., “AI saves 1M lives!”), inspired by 2024’s Nigerian malaria mapping campaign.
   • YouTube/TikTok: Short videos of AI solving problems (e.g., 60-second clips of AI optimizing water use) go viral, targeting 1 billion views.
   • Gamification: Public votes via X or apps award “People’s Choice” medals, mimicking Olympics fan engagement.
   • Teacher/Student Focus: Free workshops (using UNESCO’s AI education tools) train educators/students to participate, ensuring accessibility.
4. Overcoming the Catch-22:
   • Bypass Politics: Open-source AI and global participation sidestep nationalistic agendas, focusing on universal challenges.
   • Equity Focus: Prioritize solutions for the 96% (Reason 6), with contexts like healthcare and education for underserved regions.
   • Sustainability: Emphasize energy/water-efficient AI (Reason 5), with transparent XAI metrics to build trust..

Implementation Plan

• Timeline: Launch in 2026, aligning with India’s AI mission milestones (Reason 5). Prep starts now with X campaigns to crowdsource contexts.
• Budget: $50M (vs. Olympics’ $8B), funded by tech philanthropists (e.g., Musk, Gates), H&H’s companies, and crowdfunding. Low cost due to virtual format.
• Venues: Hybrid—virtual via X/YouTube, physical hubs in India (digital twin leader), Africa (solar potential), and Brazil (renewables).
• AI Tools: Use NVIDIA’s Omniverse for simulations, DeepMind’s algorithms for optimization, and Grok for real-time analysis of public feedback.
• Risk Mitigation:
  • Psychological Risks: Use XAI to ensure AI decisions don’t harm mental health (e.g., no manipulative chatbots).
  • Bias: Diverse teams and open-source models reduce Western-centric outputs.
  • Misinformation: Fact-check AI outputs via crowdsourced verification on X.

Expected Impact

• Scale: Reach 2 billion viewers (half the Olympics) via viral streaming, engaging 10 million teachers/students in workshops.
• Outcomes: 30 winning AI solutions deployed globally, impacting 1 billion lives (e.g., 100M healthier via AI diagnostics, 500M wealthier via microfinance).
• Millennial Role: Debt-free millennials lead teams, using H&H’s free resources (e.g., DLI courses, open papers) to innovate, proving university isn’t needed.

PS different nationalities might want to share how they map emerging tech markets- this is a view of china ny Kyle Chan -at the very least its interesting to see one way of visualising 10 dimensional venn diagram!

Moonshot Yang Zhiling china's 4 newai tigers 

Baichuan, Zhipu AI, Moonshot AI and MiniMax.