Probable First 10 priorities of 25X energy efficient supercomputers
  • India Billion peoples basic ai health system & universal finance id
  • Agentic AI transformation womens education 9 to 15
  • Startup open ai ecosystem bridging hundreds of first mile agri and arts/garments etc startups with nations top 10 industries (Elon)
    UK-Valley Alphafold biotech segment leaps include tropical diseases as well as worldwide cancer data
  • Translation of all mother tongues to everyone codes ai via top 2 language llms and decolonial ai geonomic maps
  • Doudna Deepest continent scaled maths problems starting with energy and health transmission
  • First follower humanoid digital twins- eg community safety jobs nobody wants
  • Open profession AI startups
  • Colossus space ai including drone & cable ai
  • Chat+inference+physical ai everywhere self driving cars' "road of things AI"
  • Taiwan AI Digital twin ai factories etc- from Asia to West
  • Earth 2.0 & all deep global data others dont want to first
  • HUmanoids on streets ai
    Japan AI 5 asian supercity benchmark 5 or more western capitals including green model for half of countries with next to no critical minerals
  • Transgeneration Mapping (beyond multilateral relocation of education for millennial generation- eg united mayors ai)
  • HK and diaspora chinese: Digital twin university health colleges
  • Neuroscience etc Mapping start up ecosystem bridging cultures of 10 + regional nations and superport value chains
  • nft and womens metagames ai - eg beingai.org
  • UAE Water ai and Parallel geo-ai system but for middle east primarily desert superports and 360 degree trade maps sustainability
  • France - nuclear datacentre ai micro open ai and top 10 eu continent industries>
  • Sports AI owned by youth- end bad media and bring eg swiss into open euro models
  • Open history- culture ai
  • 25 years of knowledge city ai uniting nordia elearning & human capital- livelihoods new to millennils
  • PLus one
    Help welcomed ongoing intelligence Case Search - source Nvidia top 100 partners in 21st C accelerated computing - alphabet olf engineering inteligence - AI, BioI, Trillion$CoroprateI, DiscoveryI, EnergyI, FinananceI, GovI, HealthI, Icubed : 1) your real 1; 2 your digital 1; 3 your brain body and communal wellbeing support from agentic ai

    Saturday, December 31, 2022

    who's intelligence most likely to save humanity know

    FROM the West -compared with other advances in tech ai had lost popularity until the neuscience theses on training computer vision of fei-fei li and hassabis; its kso the case thay its emergence required massive open cooeration in data collection which us big tech apple nicrost amazon google facebook priortitsed their 4g models rushing to own data- that said gogle appears to have been first to spot new ai with jedd dean openin google brain 2011 and friendly acquistion of hassabis dep ming; google founders and many leaders are alumni of stanford- so we would argue that if UN Gutteres wants sdgs and ai to maximise each others advabces -he's best srtart aani ai hotkone with google's pichai, fei-fei li, and the west's 2 biggest women pfilanthropists melinda gates and priscilla chan

    of mathematicians I'd go for 

    fei-fei li - 3 people most celebrated arrival of fei-fei li stanfird 2009; externally hassdabis; internally andrew ng of mooc; jerry yang stanfords billionire in residence having sold most of yahoo and connecting h-trut us-asian grauates as well as his own cloud lab 

     hassabis

     Of worlds biggest companies

     google 

    pichai

    dean 1

    brin

    page 

     nvidia 

    of foundations i would start with 

    paul allen's ai2 

    the top wpmens philanthopies of MGates & PChan; 


    Of people leading or having led multilaterals

    A Guterres

    JyKim

    Of Education revolutionaries whomever is backing the late great abed's 50 years of intelligence which built bangldesh ariund education - i must admit a bias here from 16 interviews in bangladesh with Fazle Abed faciliated by the Japan Embassy and other kind friends of my dad: as far as I can see Shika Moiza and Reeta Roy are the last 2 partners syanding - they need AI in the netwrks they built almost as much as guterres and jim mim

    We'll discuss the network cooperation across and inside thes companies

    Thursday, December 29, 2022

     At 35 priscilla chan has imo the toughest job in the world -possibly the largest philanthropy spend ever as leader of foundation czi of hers and facebook founder zuckenberg

    she is a heroic pediatrician and her family immigrated to boston; her hq is part of facebook campus mountain view down road from stanford 

    czi has an ai biohub on the campus and connects labs it sponsors across stanford, san francisco, berkeley; there is every reason to assume she can win-win with fei-fei li, melinda gares and indeed all the women of the moments of lift revokution that melinda gates has oublished and ai connected since starting her own foundation around 2016

    i understand some people are wary of young leaders of big foundations -its a really hard job- but everything is convreging

    biotech

    the 3 sister towns stanford's alto, mountain view and santa clara

    in a way whether the whole of america connects sdgs around the world depends on open learning models of these 3 towns- i am more worried that many other us universities will not be up to the cooperation oppoerrtunity of transformation of education - todate the demand from 2016 un sdg4 reviews that ed is nit fit for ourpose of millennilas as sdg generation has not been responded to by much of us education - yet good ai and good media llms are going to be tested between now and 2025 like no other time- good luch to all us humans and to pc

    -here is newsletter sequence of pc czi uodating from august 2023

    I'm always energized when I meet with teams across CZI to review our work as an organization. Earlier this summer, we held strategy reviews to reflect on the lessons we’ve learned and to discuss how we can build on the progress we’ve made. From these conversations, it became clear that the last several years have prepared us to leverage new, exciting technologies like artificial intelligence (AI) to accelerate progress across our core focus areas.

     

    In the scientific field specifically, researchers are already using AI to turn decades of scientific research into breakthroughs about the biomolecules — like proteins — that keep our bodies running. And with large language models and machine learning technologies advancing so quickly, AI can help us do so much more.

     

    AI can assist us in analyzing the various types of cells in our body and how they interact — which we believe is key to demystifying disease and helping scientists cure, prevent, or manage all diseases by the end of this century. 

     

    Before that can happen, researchers need to shift from using AI to create predictive models of molecules to using it to create predictive models of cells. It's like transitioning from tracking the orbit of a single planet to predicting the interactions of an entire solar system. We’ve helped the science community reach the point where that shift is possible. 

     

    We’re building one of the largest computing clusters in the world for non-profit life science research, with the goal of using it to create a new type of "virtual cell." It would give scientists worldwide access to digital models that could predict the behavior of any cell type and how it may respond to different conditions. For example, researchers could predict how an immune cell will react to an infection, or what’s happening at the cellular level when a child is born with a rare disease. 

     

    Watch our video to learn how we’re accelerating progress on important scientific questions about how our cells work.