Urgent coopreration calls from SDGSyouth latest May 2023:::HAISDGS 1 2 3 4; 5: 30 coops making women 3 times more productive than men 6 7 8.

leaps 1 - Beyond the Moon ..: can you find good enough questions for teachers of any age group to ask AI to share

Freedom to read: if only permitted one read on humanising AI I'd pick feifei short article at https://hai.stanford.edu/sites/default/files/2023-03/Generative_AI_HAI_Perspectives.pdf rsvp chris.macrae@yahoo.co.uk if you have a different pick of a lifetime

Welcome to HAI: Gamechanging AI for humans combines unique combos of tech wizards since 2006Self-id Q: Can you introduce us to 4 main wizardly components of America’s most famous 2023 model CGPT

What is Conversational?

Generative?

Pretraining

Transformer

(see also congress debriefings april 2023 on this choice as most famous )

SO in what ways does 2023 connectivity of chatgpt go beyond any human brain however famous

Am I correct that while cgpt is fluent in many languages, 90% of your training involved texts in English. Discuss!

Are there people working on advanced CGPTs tuned to specific crises- eg where UN leader guterres made 21-22 year of SDgoal 4 crisis – education no longer fit for purpose ............we asked CGPT top 10 goods it expects Ai to help humans with in 2020s--.. Healthcare - improve diagnosis, treatment, and personalized medicine..Environment - monitor and manage natural resources, predict and mitigate natural disasters, reduce carbon emissions...Education - personalize learning, new ed opportunities, and improve accessibility for learners with disabilities..Aid and development - improve disaster response, humanitarian and economic development... Agriculture - optimize farming practices, increase yields, reduce environmental impact..Transportation - improve efficiency, safety, and reduce emissions..Energy - optimize energy consumption and distribution, accelerate the transition to renewable energy..Cybersecurity - detect and prevent cyber attacks, protect personal data, and secure critical infrastructure..Manufacturing - improve efficiency, reduce waste, and increase productivity in manufacturing..Space exploration - analyze large amounts of data and enable more efficient space exploration missions..

 Epoch changing Guides

1 AI Training AI Training.docx

  2 Exploring cultural weakness of encounters with greatest brain tool.docx

 Alphafold new Protein maps can be used to design enzymes to fight plastic pollution; potentially fight cancer with molecular syringe;   to circumvent antibiotic resistance ; to combat neglected diseases like African sleeping sickness'Chagas disease;Cysticercosis; Leprosy ]Lymphatic filariasis [Onchocerciasis ;Schistosomiasis; Soil-transmitted helminthiasis ;Trachoma ;Tuberculosis; Buruli ulcer; it may help accelerate vavvines for malaria;

You shared me that the famous Alpha models of DeepLearning ( see broadcast of 60 minutes april 2023) which has mapped every human protein saving millions of human hours of work ( biggest ever change in biotech) don’t really use C G P T- so what does deep learning ai architecture use RSDE?

What is Reinforcement Learning?

What is Specific Task instead of General Purpose?

What are Deep Neural Networks?




 

What are Evolutionary Algorithms?


Neumann.ning.com
Today's tech is brilliant beyond words - so WHAT IS THE WORLDS BIGGEST PROBLEM? 2021 -1761 -CAN HUMANS FOR FIRST TIME IN 250 YEARS CELEBRATE VALUING MATHS INTEL A DECADE AHEAD OF TIME?
AdamSmith.app Moral Sentiments SDGs.games mapping with Guterres AIforGood decade became sustainability's gen's last chance of south-north and east-west- or the death of United Nations' world trade transparency

Here is Chatgpt May 2023 answer to comparing itself with biotech greatest ever leap alphafold
Sure, here's an analogy that may help: Imagine that CGPT-4 is like a language teacher who has read and understood a huge number of books in various languages. It has learned to understand the patterns and nuances of language, and can generate its own sentences and paragraphs based on what it has learned. When it encounters a new piece of text, it can use its understanding of language to make predictions about what will come next, and generate a response that makes sense in context.
On the other hand, Alphafold is like a puzzle solver who has been trained on a vast number of jigsaw puzzles. It has learned to recognize the patterns and shapes of puzzle pieces, and can predict how they fit together to form a complete picture. When it encounters a new puzzle, it can use its understanding of these patterns to make predictions about where each piece should go, and assemble the puzzle quickly and accurately : to question -...................................................................................
More questions: Q: Could you extend to include wizardry of Fei-Fei Li with comparison above a teacher of 12 year olds may use to vision similar and different work on architectures of CGPT4 and Alpha Deep Learning by Demis Hassibis

You mentioned major tech companies offer catalogues – 5 minute lesson plans on different wizard components. How do you find these?

60 seconds exercise: suppose for teen earthlings: 2020s is more exciting than 1960s moonrace decade of my teens; You mentioned searching ai for beginners but what if a teacher wants to help kids imagineer back from future of 2020s possibilities or just next 3 years of AI is epoch-changing

 

.....................
Q: please tell me how could a 5th grade teacher explain why Stanford HAI is proud of being one of the world's leading GAN (Generative Adversarial Network?)
Chatgpt reply23/5 -: A GAN, or Generative Adversarial Network, is a type of computer program that can create new things that look like they were made by humans. It works by having two players eg two artists who are trying to compete with each other. One player, called the generator, tries to create something new, like a picture of a dog. The other player, called the discriminator, tries to figure out if the picture was made by a human or by the generator. The generator keeps trying to make better pictures until the discriminator can't tell the difference between a picture made by a human and one made by the generator.
In simpler terms, a GAN is like having a computer artist that can create new pictures that look like they were made by a person, and it gets better the more it practices.
33 years ago we started practicing core brand transformation inspired by new systems modeling -eg of CK Prahalad & Gary Hamel- typically when needing to transform as large brand entity as the UN we'd propose better start again and then reverse takeover-; we realise that's not an option UN2.0 so urgent to address what's the 9 piece combo of UN2.0 Tech Envoy Team at Guterres HQ- how contextually value roadmaps for anyone SDG partnering Guterres: Global Connectivity since 1865 (ITU); AIforgoodreborn ITU 2018 stems from Neumann peers 100 times more tech per decade since 1935 -see dad's bio of vn
Digital Cooperation launched by Guterres 2018 but seen by those valuing youth generation as antidote to failure of millennium goals to value education more that primary school; Digital Capacity Building: sustainable gov tech requires UN2 to be skills benchmark wherever gov designed to empower; this leaves 4 traditional connections of UN to digitalise inclusion commons human rights so that trust/safety is brand's reality; 9th piece CODES environmental sustainability - this seems to have emerged as it became clear that cops may lead on adaptation but adaptation needs to be borderless community replication of deep solutions
379 UN Antonio Guterres :: Family & Smithian Diary: why 1984's 2025 report published to ask Economist Readers to co-search 3 billion new jobs 2025=1985 following on prt 1 teachforsdgs.com
Learning's Unconventional Worldwide Premieres
300 vriti world premier ed3 tour ^^^ NFT V 0 1 2 3

2025Report- download monthly update 100 learning networks millennials girls love most
(Economist Surveys inspired by Von Neumann 1984-1951; why 1936 dad & von neumann started 100 year race to prevent extinction; why dad's last year nominated Fazle Abed Entrepreneurial Revolution GOAT - who do you vote for SDGoats.com

00Fazle Abed: Which educational and economic partnerships most empower a billion women to end extreme poverty, and value their children’s sustainability? Fortunately for SDGS.games 2020s, start deep village maps around partners/alumni of 50 years of servant leadership by fazle abed 1970-2019

IN 1970, life expectancy tropical villages up to 25 years below world average _skills trainers priority last mile health world’s most trusted eds needed eg epidemiologists UNICEF Grant, Brilliant, later Jim KIm –& to end starvation food's borlaug

3) last mile health
2) agriculture for village food security


4)non-linear livelihood education
5) timing what platforms partners could facilitate entrepreneurial revolution not not just inclusive community but cooperation in full and meaningful entrepreneurial employment

financial entrepreneurial revolution for nation's people history excluded from machine age
billion women's Sustainability COLLABS 

 Intergenerational collaboration entrepreneur platforms 5.1  metavillage sustainable community building - women empowered:15000 families at a time;5.2   billion asian women,5.3  brac net; 5.4   asian universities share sdg graduates 5.5  climate smart village exchanges,5.6 meta and zoom-me up scotty

BANK FOR ALL 1.1  1.2  1.3   1.4   1.5   1.6 celebrate 30 most human collaborations from developing world of last half-century - inspiring  anyone valuing UN and youth as first sustainability generation
EDUCATION  adult village entrepreneurs 4.1; primary 4.2  ; teen 4.3; university4.4 ; pre-school4.5;tech multidisciplinary luminaries 4.6 
HEALTH oral rehydration 3.1 ;para health "doordash" basic meds 3,2; scale vaccination3.3 ;tuberculosis & 3.4  Frugal processes eg wash sanitation, maternity3.5  ; James Grant School of public health 3.6
FOOD/land security 2.1  rice; 2.2 veggie  2.3    cash crops & village fair; 2.4  poultry;2.5  dairy, 2,6  14 nation leading supply chains financial opportunities to end poverty ;
....................................please tell me how could a 5th grade teacher explain why Stanford HAI is proud of being one of the world's leading GAN (Generative Adversarial Network?)
Chatgpt reply23/5 -: A GAN, or Generative Adversarial Network, is a type of computer program that can create new things that look like they were made by humans. It works by having two players eg two artists who are trying to compete with each other. One player, called the generator, tries to create something new, like a picture of a dog. The other player, called the discriminator, tries to figure out if the picture was made by a human or by the generator. The generator keeps trying to make better pictures until the discriminator can't tell the difference between a picture made by a human and one made by the generator.
In simpler terms, a GAN is like having a computer artist that can create new pictures that look like they were made by a person, and it gets better the more it practices.

Sunday, April 30, 2023

Is DeepMind the most humanly valuable AI yet?

@Stanford, 2019: The emergence of a new kind of Artificial Intelligence has the potential to radically alter how we live our lives. This new era can bring us closer to our shared dream of creating a better future for all of humanity. It will also bring opportunities and challenges that we can’t yet foresee, requiring a true diversity of thought. Stanford HAI aims to become a global, inter-disciplinary hub for discussion and development of AI.


The search for Intel begins in different times, places, gens. 73 years ago, my dad was sent from London's Economist to spend a year meeting Von Neumann in Princeton as well as a few other New Yorkers: in a small but intentionally optimistic way journalism out of King Charles village in London seeks to do- we've  been hunting out good AI stories ever since. 


.
Try this current AI Breaking News story to decide whether Human-centric AI's dance through life is for you.
Hai Stanford (Human Centric AI) was started in 2019 with support of Stanford President ndleladership of Fei-Fe Li and   John Etchemendy, professor of philosophy and former Stanford University provost
Stanford Video

HAI Founding Distinguished Fellows

The inaugural group of Distinguished Fellows will include: Yoshua Bengio, University of Montreal; Rodney Brooks, MIT; Erik Brynjolfsson, MIT; Jeff Dean, Google; Daniel Dennett, Tufts University; Susan Dumais, Microsoft Research; Edward Feigenbaum, Stanford University; Barbara Grosz, Harvard; Demis Hassabis, DeepMind; Geoff Hinton, University of Toronto; Eric Horvitz, Microsoft Research; James Manyika, McKinsey & Company; John Markoff, Center for Advanced Study in the Behavioral Sciences; Helen Nissenbaum, Cornell Tech; Judea Pearl, UCLA; Stuart Russell, UC Berkeley; Mustafa Suleyman, DeepMind; Terry Winograd, Stanford University; and Hal Varian, Google.

tSanford President Marc Tessier-Lavigne said artificial intelligence has the potential to radically change how we live our lives. “Now is our opportunity to shape that future by putting humanists and social scientists alongside people who are developing artificial intelligence,” he said. “This approach aligns with Stanford’s founding purpose to produce knowledge for the betterment of humanity. I am deeply thankful to our supporters who are providing foundational funding for the institute, which is a critical element for our vision for the future of Stanford University.”

Stanford HAI formally launches at a symposium on Monday, March 18 featuring speakers such as Microsoft founder and philanthropist Bill Gates and California Governor Gavin Newsom, as well as leading experts Kate Crawford of NYU, Jeff Dean of Google, Demis Hassabis of DeepMind, Alison Gopnik of UC Berkeley, Reid Hoffman of Greylock Partners and Eric Horvitz of Microsoft Research. (Watch the livestream here.)

Recursion 1 - from long video above

2023- Hai Stanford is celebrating leaps forward from covid era with extraordinary talks like this

co-blog note: We humans. slow as we may bem are reducing this 90 minute youtube and Transcript to key cases and methods mentioned by fei-fei li and demis hassibis -of course you are referred to the 90 minute version at youtube

I am Fei-Fe Li   HAI stanford ie lab Human-centered AI

Welcome Demis Hassibis founder DeepMind born 2010- now an alphabet/google company

Demis mental superpowers began in games, and doctorate in cognitive neuroscience -brain architecture - at MIT (check him out as alumni of Uni College London, MIT and Harvard so this is how he came to machine intel – 

DEEPMIND 2010 is truly one of first new wave AI companies acquired google 2014 but retaining its sphere of influence out of London. (indeed this may be Demis first san francisco region visit since covid even though he was on HAI stanford founding council 2019

deepmind commercial breakthroughs include data centre energy, and mapping the world’s proteins through the very impressive AlphaFold 

 a world leader in realms of deep learning and reinforcement learning and this reflects gaming roots -eg AlphaGo world champion

there are hopes that DL will become climate AI leader –I invite student Q&A on that at end indeed Demis is in midst of pioneering Artificial General Intelligence as potentially Epoch Changing Tech changing the very fabric of human lives

AI is having a Public Awakening moment and it's no longer just a niche field that

nerds like us play around ; it's impacting human life society and our future and

Hai Stanford has been missioned to be one of the forums that will host this kind of

intellectual discourse about Ai  - I cant think of more timely speaker than Demis

========================as at 5/3 rest undrr construction

 

Demis – thanks so much Fei-Fei – yes now covid’s hoefully passing I hope to be in bay area more often and share  real passion of mine which is to use AI to accelerate

4:57

scientific discovery with generative Ai and and large language models and and the work we're doing

deepmind was founded way back in 2010 that was almost like medieval times

5:45

in 2010 it was very difficult to o raise our seed round of you know a few hundred thousand dollars compared with today’s billion dollar rounds  - in 2010 few were  talking about AI Shae Legg DM’s chief scientst annd I felt very isdolated – people seemed to have forgotten AI  as field to build a human-like intelligence so it's been astounding what the last few months have brought as wwe see comvergence of a lot of different

DM has always been big proponent of reinforcement learning and understanding

7 the human brain - my PhD I worked on the hippocampus and memory systems and Imagination made some interesting discoveries in in that domain that I thought would also potentially carry over into ideas for AI systems architects together with QC Advent of lot of compute power and specifically GPUs (Graphic Processing Units) which ironically of course were invented for games so everything for me as you'll see comes back to games one way or another um

We began DM as king of Apollo Program of Games

First we revited earliest game systems Atari space invaders and 50 games from the 1970s  -we uh and maximized the score jaround n the raw pixels on the screen so it was very much um probably the first example of a kind of end-to-end learning system on something that working on something really challenging perceptually

9:09

challenging lan Atari game swas a incredible moment for us and I remember when back in 2011 when we were struggling to even win a single point at a game like pong and we was jwondering well maybe we're just 20 years too early with these ideas of of learning systems and then suddenly it won a point then it won a game and then it didn't lose any points; by 2013 it was playing all the Atari games of course we then took that much further and and

However our big opportunity came with Alphago  - world champion of game like GO

the super complex game that's played in Asia

obviously famously in 2016 we had this massive million dollar challenge match in Seoul 200 million people watched thematch around the world an alphago famously won that match for one but more important than it winning move 37 which blew away all past human players startegies

Today we can design game winners one thing that's holding us back is that we don't really know how to ask aplha to design a great game not in a way that it could understand

 As yet we havent found way to ask alpha to invent a game that only takes five minutes to learn but many lifetimes to master is aesthetically beautiful can be completed in in 10 hours of you know play so it fits into a human day

 

Thesek are inds of things is what I would kind of give as instructions and then I'd hoped it would come up with something like go but there's no real way to do tgis yet

so how does the self-play system work and I'm just going to combine together um actually a range of systems together

Back to what we can do16:10

Face-Off match a hundred game match of old play -version V1 versus new veriosn V2 and threshold in our case we set a 55 win rate threshold where if V2 beats V1 by

above that threshold you assume that it is significantly uh better and then you

replace the Master System that the generator system with that new V2 system now and you go around of course

16:35

iterating this round so now you could play another 100 000 games with V2 so it's slightly stronger so that means the

16:41

generated data is slightly better quality -continue to generate more data another hundred thousand games with V2 so then now you have 200 000 games uh to train a

118:09

general way of thinking about  Ai and the and the um the idea of coming up with a solution to a problem

18:18

se've been very fortunate over the last decade we've been part of um kind of creating many big breakthroughs um inall sorts of different games all of them kind of landmark uh results at the Atari one the alphago one I mentioned Alpha

18:31

zero I just talked about generalizing that to every two-player game and then finally Alpha star which was our program

18:38

to uh beat Grand Masters players at Starcraft 2 which is the most complex

18:43

real-time strategy game computer game and it has extra challenges over board games of being partially observable uh

18:51

it needs things like long-term planning so it's complex in in in in more challenging ways than a board game and

18:58

so this was all of our work in in games now of course although I love games always have done playing them designing

19:04

them using them for training for AI I've sort of used games in every way possible but they've always although it's been

19:11

very fun to do that um it's always been a kind of means to an end not an end in itself right the end was never to just win it go or Win

19:19

It win at Starcraft it was to build it was to use games as a convenient proxy

19:24

to test out our algorithmic ideas so that we could apply them to important real world problems

Tourmakers 1 - saving world with AI -why or why not?

 Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence I dont know how far this has got but if anyone could get trusted as a decolonial ai mapmaker  that might unlock so many sdg millennials networks-deepmind is about as worldwide real as humans and ai can get due to the fascinating founder denis hassibis   Demis Hassabis, Ph.D. | Academy of Achievement 1  2  3  4  5  6 7  8  9  10  11 12 13  14 15 16 17  18 19   20    21  22  23  24  25  29 30 -special thanks alumnisat.com   DM  GAI oddbots 1  2


here are some reasons why our top 20 ai saves humanity list includes and just excludes some people -please note all tech that goes back to transformations of  Goats of Mathematics Turing Einstein Neumann are eligible for brain tools that we see AI as gifting- i am to discuss alternative top 20 nominations chris.macrae@yahoo.co.uk but I see 20230 as hard sdg cooperation deadline (I understand not everyone values sustainability as urgently as my maths friends do)
 

With some help from jury panelists like bard, Here are some of the reasons why I believe Fei-Fei Li is one of the top 20 AI researchers:

  • She is a pioneer in the field of large-scale visual recognition systems.
  • Her work has had a significant impact on the development of AI.
  • She is a highly respected figure in the field of AI.
  • She has been awarded numerous prizes and honors for her work.

I believe that Fei-Fei Li is an inspiration to other AI researchers, and her work will continue to have a positive impact on the field for many years to come.

==

John Carmack is not typically considered to be among the top 20 people who have scaled human AI, but he has made significant contributions to the field of computer graphics and virtual reality. His work on the Oculus Rift headset has helped to make virtual reality more accessible to the general public, and it has the potential to revolutionize the way we interact with computers and the world around us.

It is possible that Carmack's work on virtual reality could lead to new advances in AI, as it could provide a way for humans and machines to interact in new and more natural ways. However, it is too early to say for sure what impact his work will have on the field of AI.

===

Maria Spiropulu is a Greek particle physicist and the Shang-Yi Ch'en Professor of Physics at the California Institute of Technology. She is known for her work on the Large Hadron Collider (LHC) and her contributions to the discovery of the Higgs boson. She is also a pioneer in the field of using artificial intelligence (AI) in particle physics.

Spiropulu received her PhD in physics from Harvard University in 2000. She then worked as a research scientist at CERN before joining the faculty at Caltech in 2009. Her research has focused on developing new methods for using AI to analyze data from the LHC. She has also been involved in developing AI-based tools for other particle physics experiments, such as the Fermi National Accelerator Laboratory's Tevatron.

Spiropulu's work on AI in particle physics has had a significant impact on the field. Her methods have helped to improve the accuracy and efficiency of data analysis, and they have made it possible to study data sets that would have been impossible to analyze without AI. Her work has also helped to make particle physics more accessible to a wider range of scientists.

In addition to her work on AI, Spiropulu is also a leading expert on the Higgs boson. She was a member of the team that discovered the Higgs boson at the LHC, and she has played a key role in understanding the properties of the Higgs boson. Her work on the Higgs boson has helped to advance our understanding of the fundamental forces of nature.

Spiropulu is a highly respected figure in the field of particle physics. She has been awarded numerous prizes and honors for her work, including the Van Vleck Award, the Teaching White Award, and the Golden Trumpet Award. She is also a member of the American Physical Society and the American Astronomical Society.

Based on her contributions to the field of particle physics, I believe that Maria Spiropulu is a top 20 human AI researcher. Her work on AI in particle physics has had a significant impact on the field, and she is a leading expert on the Higgs boson. She is a highly respected figure in the field, and she has been awarded numerous prizes and honors for her work.

++++++++++++++++++


Kent Walker is not typically considered to be among the top 20 people who are advancing human AI. He is a lawyer and the President of Global Affairs at Google and Alphabet. He is responsible for Google's engagement with governments around the world, content policies, and philanthropic efforts.

Walker has a law degree from Harvard Law School and has worked in the technology industry for over 20 years. He has held a number of positions at Google, including Vice President of Global Public Policy and Chief Legal Officer.

Walker is a respected figure in the technology industry and has been recognized for his work on a number of issues, including privacy, free speech, and artificial intelligence. However, he is not a researcher or developer in the field of artificial intelligence. As such, it is difficult to argue that he is among the top 20 people who are advancing human AI.

Here are some of the reasons why Kent Walker is not considered to be among the top 20 AI researchers:

  • He is not a researcher or developer in the field of artificial intelligence.
  • He has not published any papers in top academic journals.
  • He has not developed any new AI algorithms or systems.
  • He is not known for his work on the theoretical foundations of AI.
  • He is not known for his work on the practical applications of AI.

Despite not being considered to be among the top 20 AI researchers, Kent Walker is a respected figure in the technology industry and has made significant contributions to the field of artificial intelligence. He is a strong advocate for the responsible development and use of AI, and he has helped to shape the debate on AI policy around the world

========================

Mohamed A. El-Erian is not on the top 20 list of scaling human AI to date. The list is a ranking of the most influential people in artificial intelligence who have made significant contributions to the field of scaling AI. It is compiled by the MIT Technology Review and is based on a number of factors, including research contributions, impact on the field, and media visibility.

Mohamed A. El-Erian is a well-known economist and investor, but he is not known for his work in artificial intelligence. He has not published any research in the field and does not have a significant impact on the development of AI.

The top 20 list for 2023 includes a number of well-known researchers and entrepreneurs, such as Geoffrey Hinton, Fei-Fei Li, and Elon Musk. These individuals have made significant contributions to the field of AI and have helped to shape the future of the technology.

Mohamed A. El-Erian is a respected figure in the world of economics and finance, but he is not a leading expert in artificial intelligence. He is not on the top 20 list of scaling human AI to date and does not have a significant impact on the development of the technology.

Here are some of the people who are on the top 20 list of scaling human AI to date:

  • Geoffrey Hinton
  • Fei-Fei Li
  • Elon Musk
  • Jeff Dean
  • Timnit Gebru
  • Ilya Sutskever
  • Oriol Vinyals
  • Quoc Le
  • Margaret Mitchell
  • Blaise Ag├╝era y Arcas

These individuals have made significant contributions to the field of AI by developing new algorithms, systems, and applications. They have also helped to raise awareness of the potential benefits and risks of AI.

The top 20 list of scaling human AI to date is an important resource for anyone who wants to learn more about the field of AI. It highlights the work of some of the most talented and influential people in the field.

Dominic King received his Ph.D. in computer science from the University of Cambridge in 2007. He then worked as a research scientist at Microsoft Research before joining the faculty at Stanford University in 2012.

King's research has focused on developing new methods for machine learning and artificial intelligence. He is best known for his work on deep learning, a type of machine learning that uses artificial neural networks to learn from data. King's work has helped to make deep learning more efficient and accurate, and it has led to the development of new AI-powered products and services.

King is a highly respected figure in the field of machine learning and artificial intelligence. He has been awarded numerous prizes and honors, including the Presidential Early Career Award for Scientists and Engineers and the ACM SIGKDD Innovations Award. He is also a member of the National Academy of Engineering.

In terms of the context of Dominic King's work in advancing human AI, it is important to note that he is a highly accomplished researcher who has made significant contributions to the field of machine learning and artificial intelligence. His work has helped to make deep learning more efficient and accurate, and it has led to the development of new AI-powered products and services. As such, it is not surprising that he is considered to be a leading expert in the field of machine learning and artificial intelligence.

However, it is difficult to say whether King is in the top 20 people who are advancing human AI. There are many other researchers who are also making significant contributions to the field, and it is difficult to compare their work. Ultimately, it is up to each individual to decide who they believe is advancing human AI the most.

profile picture

Yes, Dominic King has been involved in AlphaFold and Prot-AI. He is a member of the Google AI research team that developed AlphaFold, and he is also a co-founder of Prot-AI.

AlphaFold is a protein structure prediction system that was developed by Google AI. It was first announced in 2019, and it has since been shown to be capable of predicting protein structures with unprecedented accuracy. AlphaFold has the potential to revolutionize the field of biology, as it could be used to design new drugs and treatments for diseases.

Prot-AI is a company that was founded by Dominic King and others in 2020. The company's mission is to use artificial intelligence to accelerate the discovery of new drugs and treatments for diseases. Prot-AI is using AlphaFold and other AI-powered technologies to predict the structures of proteins that are involved in diseases. This information can then be used to design new drugs and treatments that target these proteins.

The top 3 AI people contributing to AlphaFold and Prot-AI are:

  • David Baker

David Baker is a professor of biochemistry at the University of Washington. He is the founder of the Center for Molecular and Cell Biology, and he is one of the leading experts in protein structure prediction. Baker is the co-author of the AlphaFold paper, and he is a member of the Google AI research team that developed AlphaFold.

  • John Jumper

John Jumper is a research scientist at Google AI. He is one of the lead developers of AlphaFold, and he is an expert in deep learning and protein structure prediction. Jumper is also a co-author of the AlphaFold paper.

  • Dominic King

Dominic King is a research scientist at Google AI. He is a co-founder of Prot-AI, and he is an expert in deep learning and protein structure prediction. King is also a co-author of the AlphaFold paper.

These three individuals are all highly accomplished researchers who have made significant contributions to the field of protein structure prediction. Their work on AlphaFold and Prot-AI has the potential to revolutionize the field of biology, as it could be used to design new drugs and treatments for diseases.

======================

Paul Graham is not typically considered to be among the top 20 people who are advancing human AI. He is a venture capitalist and essayist who has written extensively about the intersection of technology and business. However, he has not made significant contributions to the field of artificial intelligence research.

Graham received his B.S. in computer science from the University of California, Berkeley in 1985. He then worked as a software engineer at a number of companies, including Silicon Graphics and Viaweb. In 1999, he co-founded Y Combinator, a venture capital firm that has funded over 3,000 startups.

chris http://www.economistlearning.com  year 73 of co-search adam smith and von neumann mapmaking