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?
(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?
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
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.
6:05 pm - 6:15 pm
Presenting UChicago’s Market Shaping Accelerator & Innovation Challenge 2023
Rachel Glennerster, Associate Professor of Economics, University of Chicago; former Chief Economist at the Foreign Commonwealth & Development Office (FCDO) and the Department for International Development in the UK; former Executive Director of the Abdul Latif Jameel Poverty Action Lab (J-PAL)
Michael Kremer, University Professor in Economics, University of Chicago and Director of the Development Innovation Lab and 2019 Nobel Laureate
6:15 pm - 6:45 pm
Panel I: The Economics of Accelerating Innovation
Susan Athey, Economics of Technology Professor, Stanford Graduate School of Business; Senior Fellow at the Stanford Institute for Economic Policy Research; Chief Economist of the Antitrust Division at the U.S. Department of Justice (DOJ) (Panelist)
Michael Kremer, University of Chicago (Panelist)
Jean Tirole, Honorary Chairman of the Foundation JJ Laffont-Toulouse School of Economics (TSE) and of the Institute for Advanced Study in Toulouse (IAST); Scientific Director of TSE-Partnership; 2014 Nobel Laureate (Panelist)
Christopher Snyder, Joel Z. and Susan Hyatt Professor in Economics, Dartmouth College (Moderator)
6:45 pm - 7:00 pm
Panel I Q&A
7:00 pm - 7:30 pm
Panel II: Market Shaping to Solve Global Crises (Pandemics + Climate Change)
Catherine Bremner, Former Director of International Climate and Energy in the Department for Business, Energy and Industrial Strategy in the UK (Panelist)
Jane Flegal, Climate at Stripe; Former Senior Director for Industrial Emissions, White House Office of Domestic Climate Policy (Panelist)
Justina Gallegos, Climate Finance and Industrial Strategy, White House National Economic Council (Panelist)
Matthew Hepburn, Senior Advisor at the Office of Science and Technology Policy, leading the effort on implementing the American Pandemic Preparedness Plan (Panelist)
Rachel Glennerster, University of Chicago (Moderator)
7:30 pm - 7:40 pm
Panel II Q&A
7:40 pm - 8:00 pm
Rachel Glennerster, University of Chicago