2009, Londoner Demis Hassabis met Dr Fei-Fei li – a female mathematician who
emulates any male maths wizard. She had just moved to Stanford. Both
completed doctorates in neural networks and neuroscience AI (the subject of V
Neumann’s last lectures Computer & Brain before his death 1957).
Research area
had been relatively forgotten - nothing could be more different than programming
in Microsoft. Demis and Fei-Fei had idea that unless you were prepared to put
years of training into computer visioning, you’d never maximise the human apps
of brain tools and deep data science for good. Demis PhD had shown London taxi
drivers have larger hippocampuses because of spatial skill livelihoods. Stanford
had welcomed the idea of ImageNet that Li would run annual events connecting
huge amounts of mainly open source data exchanges on computer visioning.
Academic research is not used to a 29-year-old woman leading 8 years of ever
deeper data analysis including subcontracting 50000 Asians Amazon had already
used to do routine coding.
By 2017 West Coast was ready to make www dreams
great again but..Anyhow www.Aigames.solar likes to map whose intelligence
multiplied around these 2 maths superstars for good.
NB I dont have full details
having only enjoyed one day visit to Stanford before I’d heard of FFL. So here
only list people www.bard.solar and I can verify definitely helped scale critical
leaps forward.
Please tell us whom we’ve not yet seen
Fei-Fei Li
Hassabis; deep mind co-founders London
Andrew Ng google Page
Brin/Pichai
Stanford-alumn x
…..Lila Ibrahim from Valley to Hassabis in London
Jerry Yang
various biotech people who open source deep mind gift
200,000 protein database
alphafold2 champion science AI
Jennifer Doudno London’s royal feee and Moorefield eye hospitals
Antonio Guterres
Melinda Gates ..
Nvidia CEO ..
Hoffman/Yee ..
Condoleezza Rice..
Priscilla Chan
Humans Ai triple win– over 50 multidisciplines -
now connect Stanford, Mountain View, Santa Clara – see who builds labs at Stanford campus;
i assume they connect through Fei-Fei Li but when
eg their expertise matches Hassabis she passes them through-
see radical lab sponsors :
Brooklyn Mrs Tsai –
neuroscience schools at Stanford and Yale;
Hong Long Li La Shing ..
Bill Gates Allen institute
ChanZI…
G1/20 -v/o
UNGA23
AIGames.solar
Friends20.com
EconomistAfrica.com
EconomistEnglish.net
Humans
AI AIVERYGOOD WorldClassLLM
2020s may be first and last time tech exists to solve any deep community
challenge including those to span UN Sdgs at every GPS where families grow.
Over the last 20 years, there are many reasons why society's deepest needs have
lagged implementation in contrast to other intelligence applications.
These include
- chaos caused by war,
- financial bubbles,
- plague,
- population statistics that have omitted youth's intergenerational needs,
- short-term or fake media.
It’s also the case that data science that is both as deep as nature and as hi-trust as emotional intel gets requires much more community work than racing to be top 10 global data collector and then working out how to monetise it.
There are also various system design principles that von Neumann advised smart humans eg do NOT rely on economists as monopoly arbiters until or unless they value way above zero-sum games mapping.
In this regard, my family as biographers of von Neumann since 1951 including 40 years at The Economist have a lot of notes to fast forward to goodwill exponential auditors
Regarding 2020s HumansAI, leading vision “foundations” models are expensive (now at least 100 million dollar per version update) BUT they can be affordably scoped to plug in databases to focus on local ai, and or lessons experiencing new AI can be designed for different and with ages.
Infants AI data is currently collected at Stanford’s own playschool – nicknamed curiosity AI As early as 2017
Melinda Gates and the Nvidia CEO to create most wealth of next 5 year asked Fei-Fei Li to design 10 schools ai module including drawing and dance for kindergarten and nature trails and ethics for 11 year olds as well as maths modules on neural networks aimed at increasing high school girls becoming college engineers
see https://ai-4-all.org/resources/ FFL: Worlds-I-See
https://ai-4-all.org/resources/ FFL: Worlds-I-See
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