IN SEARCH OF INTELLIGENCE unites families advancing next generation's life on earth. December 2024, Wash DC, chris.macrae@yahoo.co.uk ; linkedin UNwomens::: 2025Reporter Club
That's our open syatem foundations observation. scaling over 75 years since John Von Neumann asked Economist journalists to mediate futures of brainworking through 3 million fold hi-tech waves :Moore's Silicon Valley,*Satellites 1G to 5G Death of Distance mobilising data round earth* Jensens platforms for DEEP LEARNING Data Science aligned to Einstein's 1905 nano-science-Earth revolution. NB Miraculous Transformations In tha last 5 quarters of human endeavor, may we commend projects emerging from 6 summits linkedin by Taiwanese-Americans gravitated by Jensen Huang (Nvidia) and 4 summits living up to King Charles wishes for humanity : Nov 2023 London Turing latest Deep Minds,, May 2024 Korea, Summer 2024 semi-private Japan State Visit to London (Charles 60th Anglo-Japan reunion as 1964 delegate to Tokyo Olympics), December 2024 India's Wadwani AI in DC (with next round of King Charles Series - Macron Paris Feb 2025).. Jensen's health AI meta-collab: Hong Kong Digital Twin 2020s supercity health centres :Tokyo Update Maso Son & Japan Royal LLM everywhere; India's sata socereignty od world largest population with Ambani & Modi; NVidia in DC with eg LOgkhttf Martin ; Taiwan RWins galore eg Fioxconnn extension to foundry for autonomous as well as mobile world; San Jose March 2-24 tenth annual upfate of most joyful parternship tech world has ever generated Over the past year, key international organizations, like the G7, OECD, and Global Partnership on Artificial Intelligence (GPAI), have shaped the global AI governance conversation and focused on foundational principles, critical risks, and responsible AI development. Looking ahead to 2025, how are G7 countries and corporations planning to implement AI governance frameworks and address challenges, such as the growing energy demand for AI technologies? Join the Wadhwani AI Center for the International AI Policy: Outlook for 2025 conference. This full-day event will be held at CSIS headquarters on December 9, 2024, from 9:00 AM to 6:00 PM ET and will convene leading policymakers, industry experts, and thought leaders to explore the latest international efforts in AI governance. Featuring keynote speeches from distinguished figures, including Ambassador Shigeo Yamada of Japan to the United States, Ambassador Laurent Bili of France to the United States, and Sara Cohen, Deputy Head of Mission at the Embassy of Canada, this conference will highlight key international perspectives in AI governance.

Monday, December 31, 1979

Here's Dibs on Humans Intelligence AI learning starters for kids and mentors:
-- under 7,
DANCE

 under 10
DRAWING

under 13
ETHICS
ENVIRONMENT

11 and plus -
NOFAKEFACES PLEASE - part 2 plus debate over fame vs privacy -eg EconomistSports.net

For those who want to change maths at whatever age you can -see 4 N's (Nets)
GA
NEUral
RecurrentNEU
ConvolutionalNEU

(gwiz and thought english was my mother tongue)

 

please help us update dibs on age-sensitive AIgood Bard tells me Neural Network was named as maths model for brain in 1943 (see footnote)

Fei-Fei Li coined the term "HAI" or Human-centric AI. in a mooc 2017 AI for Everyone: Succeeding in the Age .
She likely coined these terms - in her mooc deep learning" use of artificial neural networks to learn from data.
Elsewhere:
Transfer learning is a technique that allows a neural network trained on one task to be used for another task.
Zero-shot learning is a technique that allows a neural network to learn to classify images of objects that it has never seen before.

 From The Economist's change of decade70s/80s wishes

 - what the world needs now is for the greatest female

 mathematician's star to be born

Fast forward AIGames 2023 - see worlds of greatest

 female intelligence stars orbiting round fei-fei li at

www.economistwomen.com  & www.economistenglish.net/2023/08 

- rsvp if you feel we have missed ai20s.com female rockstars  of AIforgood

Recurrent name appeared in 1986, and convolutional 1989 Yann LeCun referring to when maths makes a third funntion from 2 functions
x the complete history of which mathematicians studied brains and which neuroscientists studied maths or computation can be very rewarding to valuing humanity but does not need to be immediately viewed to make sure you play good ai 2020s

for the record bard shares :

  • John von Neumann was a Hungarian-American mathematician and physicist who is considered to be one of the founders of computer science. He wrote a paper in 1958 titled "The Computer and the Brain" in which he discussed the similarities between computers and the human brain. In this paper, he proposed that neural networks could be used to create artificial intelligence.

  • Alan Turing was an English mathematician and computer scientist who is considered to be the father of theoretical computer science and artificial intelligence. He wrote a paper in 1950 titled "Computing Machinery and Intelligence" in which he proposed the Turing test, which is a test of a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human. In this paper, he also discussed the possibility of creating artificial neural networks.

However, it is important to note that neither von Neumann nor Turing actually built a neural network. The first neural network was built in 1958 by Frank Rosenblatt, who called his neural network the perceptron.

fast forwsrd to 2014- also year 5 of fei-fei li and stanfird sharing vision coding imagenet with the world --
  • Generative adversarial networks (GANs) are a type of neural network that can generate new data. GANs consist of two neural networks: a generator and a discriminator. The generator is responsible for generating new data, and the discriminator is responsible for distinguishing between real and fake data.

The name "generative adversarial" comes from the fact that the generator and discriminator are in a constant battle with each other. The generator is trying to create data that is so realistic that the discriminator cannot tell the difference between it and real data. The discriminator is trying to learn to distinguish between real and fake data.

The names for these three types of neural networks were chosen by different people. The name "convolutional neural network" was coined by Yann LeCun in 1989. The name "recurrent neural network" was coined by David Rumelhart and James McClelland in 1986. The name "generative adversarial network" was coined by Ian Goodfellow, Yoshua Bengio, and Aaron Courville in 2014.

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