HAPPY 2024: in this 74th year since The Economist started mediating futures of brainworking machines clued by the 3 maths greats NET (Neumann, Einstein, Turing) people seem to be chatting about 5 wholly different sorts of AI. 1BAD: The worst tech system designers don't deserve inclusion in human intel at all, and as Hoover's Condoleezza Rice . 2 reports their work is result of 10 compound techs of which Ai is but one. Those worst for world system designs may use media to lie or multiply hate or hack, and to perpetuate tribal wars and increase trade in arms. Sadly bad versions of tv media began in USA early 1960s when it turned out what had been the nation's first major export crop, tobacco, was a killer. Please note for a long time farmers did not know bac was bad: western HIStory is full of ignorances which lawyer-dominated societies then cover up once inconvenient system truths are seen. A second AI ecommerce type (now 25 years exponential development strong) ; this involves ever more powerful algorithms applied to a company's data platform that can be app'd to hollow out community making relatively few people richer and richer, or the reverse. You can test a nation's use of this ai by seeing if efinance has invested in the poorest or historically most disconnected - see eg bangladesh's bklash, one of the most populous digital cash systems . Digital money is far cheaper to distribute let alone to manually account for so power AI offers lots of lessons but whether its good or not depends in part on whether there are enough engineers in gov & public service to see ahead of what needs regulating. There are 2 very good ai's which have only scaled in recent years that certainly dont need regulating by non engineers and one curious ai which was presented to congress in 2018 but which was left to multiply at least 100 variants today the so-called chats or LLMs. Lets look at the 2 very good ai's first because frankly if your community is concerned about any extinction risks these AI may most likely save you, One I call science AI and frankly in the west one team is so far ahead that we should count ourselves lucky that its originator Hassabis has mixed wealth and societal growth. His deep mind merged with google to make wealth but open sourced the 200 million protein databank equivalent to a billion hours of doctorate time- so now's the time for biotech to save humanity if it ever does. Alongside this the second very good AI graviates around Fei-Fei Li) in developing 20 million imagenet database so that annual competitions training computers to see 20000 of the most everyday sights we humans view around the world including things and life-forms such as nature's plants and animals. Today, students no longer need to go back to 0.1 programming to ask computer about any of these objects; nor do robots or and autonomous vehicles - see fei-fei li's book worlds i see which is published in melinda gates Entrepreneurial Revolution of girl empowerment
ED , VN Hypothesis: in 21st C brainworking worlds how people's times & data are spent is foundational to place's community health, energy and so natural capacity to grow/destroy wealth -thus species will depend on whether 1000 mother tongue language model mediates intelligence/maths so all communities cooperatively celebrate lifetimes and diversity's deep data ) . Check out "Moore exponential patterns" at year 73 of celebrating Game : Architect Intelligence (Ai) - players welcome .. some jargon

Thursday, December 31, 2020

AIchartering.com

From Brand Chartering team 1990s valuing world's most trusted brand platforms for millennial sustainability generation to AIChartering 2020s
welcome AIC1 Google Deep Mind now uniting Google Brain 1 out of AI.google Ap2023  &  ..
Panchai menu 23/4

AIC1.1 AlphaGo

AlphaGo is a computer program that was developed by Google DeepMind to play the game of Go. In 2016, AlphaGo defeated a professional Go player, Lee Sedol, in a series of matches. This was a major breakthrough for AI, as Go is a very complex game that was previously thought to be too difficult for computers to master.

AIC1.2 AlphaFold

AlphaFold is a protein folding prediction program that was developed by Google DeepMind. It is able to predict the structure of proteins with unprecedented accuracy. This could have a major impact on the fields of medicine and biology, as it could help scientists to better understand how proteins work and how they can be used to treat diseases.

AIC1Z1 Transformers big takeovers (previous community models)

Transformers are a type of neural network that are used for natural language processing tasks. They are particularly good at tasks such as machine translation, text summarization, and question answering. By big takeovers, transformer designers are referring to the increasing use of transformer models in a variety of tasks. Transformer models are a type of neural network that are particularly good at natural language processing tasks, such as machine translation, text summarization, and question answering. They have been shown to outperform other types of neural networks on these tasks, and they are becoming increasingly popular.

The use of transformer models is having a major impact on a variety of industries. For example, transformer models are being used to improve the accuracy of machine translation systems, which is making it easier for people to communicate across languages. Transformer models are also being used to improve the performance of text summarization systems, which is making it easier for people to find the information they need in large documents. And transformer models are being used to improve the accuracy of question answering systems, which is making it easier for people to get the information they need from the internet.

The increasing use of transformer models is having a major impact on the way we interact with the world. Transformer models are making it easier for us to communicate, to learn, and to get the information we need. And as transformer models continue to improve, they will have an even greater impact on our lives.

Here are some specific examples of how transformer models are being used to "take over" different tasks:

  • Machine translation: Transformer models have been shown to outperform other types of neural networks on machine translation tasks. For example, the transformer model T5 was able to achieve state-of-the-art results on the WMT 2019 machine translation benchmark.
  • Text summarization: Transformer models have also been shown to outperform other types of neural networks on text summarization tasks. For example, the transformer model BART was able to achieve state-of-the-art results on the CNN/Daily Mail summarization benchmark.
  • Question answering: Transformer models have also been shown to outperform other types of neural networks on question answering tasks. For example, the transformer model GPT-3 was able to achieve state-of-the-art results on the SQuAD question answering benchmark.

AIC1Z2 Word2vec

Word2vec is a method for learning the vector representations of words. These vector representations can be used for a variety of tasks, such as text classification, sentiment analysis, and natural language generation.

AIC1Z3 WaveNet

WaveNet is a neural network that can be used to generate realistic speech. It is used in Google Assistant and other voice-activated products.

AIC1Z4 Sequence to sequence models

Sequence to sequence models are a type of neural network that can be used to translate text from one language to another. They are also used for tasks such as machine translation, text summarization, and question answering.

AIC1Z5 Distillation

Distillation is a technique that can be used to improve the performance of a machine learning model. It works by transferring the knowledge from a large, complex model to a smaller, simpler model.

AIC1Z6 Deep reinforcement learning

Deep reinforcement learning is a type of machine learning that can be used to train agents to learn how to behave in complex environments. It is used in a variety of applications, such as robotics, game playing, and finance.

AIC1Z7 Distributed systems and software frameworks

Distributed systems and software frameworks are used to develop and deploy large-scale machine learning models. They provide a way to manage the resources required to train and run these models, and they make it easier to develop and deploy models across multiple machines.

TensorFlow : JAX

There are many ways that teachers can use these technologies in the classroom. For example, they can use AlphaGo to teach students about the game of Go, or they can use Transformers to help students learn about natural language processing. They can also use Word2vec to help students learn about the vector representations of words, or they can use WaveNet to help students learn about how to generate realistic speech.

---- further Q&A qirh bard

I understand that if you are in biotechnolgy now that alphafold has gifted you a huge leap forward - 200000 protein database -which Hassibis estmates might have taken a billion years if humans without ai had needed to do this. While I dont immediately expect any of the other innovations will be that big! can you indicate which sorts of practioner apart from bitechnolgists should be following which type of ai model that google deep mind is now in centre of?

Sure, here are some of the practitioners who could benefit from following the latest AI models from Google DeepMind:

  • Biotechnologists

As you mentioned, AlphaFold has the potential to revolutionize biotechnology. It could help scientists to better understand how proteins work and how they can be used to treat diseases.

  • Pharmacologists

Pharmacologists could use AI to design new drugs and to better understand how existing drugs work.

  • Chemical engineers

Chemical engineers could use AI to design new materials and to improve the efficiency of chemical processes.

  • Materials scientists

Materials scientists could use AI to design new materials with specific properties, such as strength, lightness, or conductivity.

  • Engineers

Engineers could use AI to design new machines and to improve the efficiency of existing machines.

  • Scientists

Scientists in a variety of fields could use AI to help them to collect and analyze data, to make predictions, and to develop new theories.

  • Businesses

Businesses could use AI to improve their operations, to make better decisions, and to develop new products and services.

  • Governments

Governments could use AI to improve their services, to make better decisions, and to protect their citizens.

These are just a few of the many practitioners who could benefit from following the latest AI models from Google DeepMind. AI is a rapidly developing field, and it is important for practitioners in all fields to stay up-to-date on the latest developments.


The only silver lining of the plague in our midst -

 

hopefully everyone will want to map intelligence AI or human geared to see this world vision -we hired teachfo.net web for a hear



BREAKING NEWS ONLY MILLENNIALS GRADUATE TEACHERS COLLABS CAN SAVE US FROM EXTINCTION

3.1 * (  5.1  5.2  5.3  5.4  5.5  5.6;) * 4.3 ... tour world wk's happiest teachers 1 2 3 4

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Its fascinating comparing stories of Fazle Abed (TeachFor.net stories) who got the opportunity to build most of a new nation's education system and Wendy Kopp who has linked together over 60 nations where graduate teachers are asking what purpose can education serve if there is to be a sustainability generation

TeachFor.net Story SDG0: Do you know the story of the marketer of the world's number 1 life saving cure? You might expect him to be the world's richest man. #Shetoo Instead he became sustainable womankind's number 1 Collaborations champion. This most exciting of all human interest stories gravitates inconvenient truths (see why churchill coined this phrase, gore adopted it to mobilise client crisis movements but missed its meaning to health servants) -there's no sustainable purpose in being a nobel judge, no whole truth in claim to be a world leader of human rights, mental health problems in being a millennials superstar, no evidence of being an economist worth trusting, waste of your life as a teacher if you cannot do mappng searches of the difference between family networks knowing and collaboratively connecting this cure, and those in this 21st C still in ignorance of it.

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Life saving marketing's inconvenient truth stems from seeing humans living in the tropics (expected to be half the world) cannot develop without this cure or access to electricity grids (lots of energy needed to stay coll in a place that is humid day and night). When you look at the G8 biggest empires that fought world war 2 you will find all their capitals are north of the tropics. Not a cent of all the paper money they print goes directly to linking in this life saving cure's practice network- even the development economics world failed to trickle down a cent until our greatest marketing hero had made the good news multipliers of saving lives the number 1 currency og asia's poorest vilage mothers (wh became billiongirls.com)

Today, this may explain how these same G8 leaders (and 7 of their notions of democracy -ie us canada uk france germany italy japan EU (yup i kow that's 8 but the EU cheats in double conuting its bureaurats importance) bear the most responsibility for not stopping covid. They still dont understand health networking where the massive frailest populations multiply connectivity fastest.. OK the man who marketed this life saving cure was far more polite than I am about fake economists, fake professions and politicial rivalries, fake media men, fake celebrities et al. But since he died 2 years ago (20 Dec 2019), and since at least one leading scot who mediated 2020-1760 age of humans and machines died of this disease (founder of the economist james wilson) and since "only teachers can sustain humanity is the main lesson by family were gifted by john von neumann with my dadd being his biographer- when morals and politeness crash into species extinction i chose morals over politeness. I am just a maths guy. If you want to fame me for rudeness, sure i deserve that. If you want to tell me the intel of the world's number 1 life saving sure isnt relevnt to how technolgists humanise artificial intelligence- let 3.75 billions under 30s be our judges.

 5.1  5.2  5.3  5.4  5.5  5.64.3

50 years ago, in 1972, The Economist called for (and updated in dialogues to 1993's Sweden's New Vikings) an Educational Entrepreneurial Revolution so that millennials' 20 year old graduates of the 2020s could celebrate being the first truly sustainable generation> This would need the greatest collaborations of all time as far as mother nature was concerned, and as far as 3 generations of humanity without borders would be concerned: today's under30, parents, and grandparents. While nature has always been bodreless as minimal data on climate shows, 2025 completes the 6 decade of 100 times more borderless tech being the legacy of john von neumann. In the first 100 fold leap, leaders of next generation inspiration chose the moon race to celebrate how soon no mission would be impossible. When we hit 2025 that will be a trillion times moore- where have leaders of borderless trust in our youths futures gone?


Two clear and present hypotheses mediated the coming global readership from 1972:

von neumann's legacy of 100 times moore tech per decade was in full swing - the west coast hub around intel rebranded itself silicon valley- its ai crown jewel stanford was in its 12 yeae as pacific coast lab twinned with MIT's east coast. Stanford had a lot to catch up with coding wise- it was mit women who coded moon landing

...come back soon if you want a guided tour through every continent on the magic bicyclical ride to sustaining kids, teachers and so all of us (some early cluetrails economistwomen.com abedplay.com teachforscotland.org ecop26.com 2025report.com - surviving co-author 1984 updates of the economist's first 140 years of smithian moral mapmaking chris.macrae@yahoo.co.uk

by the 2020s the most valuable knowhow of both teachers and teens would change every 3 years- think about that put college students in debt to get a bit of paper examining perfection the way an old non-adaptive professors mind finds convenient will do one of 2 things - it will send you nation into being undeveloped as far as sustainability generation are concerned or make your nation the leader of extinction


The good news is 50 years of studying education's entrepreneurial revolution has been searched out by the world's poorest women and those who relentlessly valued collaborating with them - the greatest COLLABs earth has ever seen a species empower

MYW -Milliondollarteacher*YidanPrize&Luminaries*Wise 10th year of nobels of edu

If you are curious 3 of humanity's 4 most exciting summits of education revolution are on replay - peculiarly the one mainly convened by the united nations hasn't yet clarified its online presence. Meanwhile 2021 is the 50th birthday of Bangladesh where the whole of aid was changed by village mothers into platforms for collaboration entrepreneurial revolution with the help of probably the world's greatest ever educator Fazle Abed (first WISE laureate , inspiration of Yidan Luminaries ... and the greatest economist never to be a Nobel)


Story 1 - i am just a maths guy- probably in the bottom 10% of MA's from Cambridge DAMTP where such as steve hawkings used to run us over with a wheel chair traveling at 12 mph in extraordinary narrow corridors of mill lane's 1972 building. In 1989 I got a chance to help research her were the world's greatest maths greats educated - dad was doing von neumann's biography whose promise of 100 tikes more tech per decade he had scooped back in 1955. So the greatest maths minds of all time were home schooled by a street of merchants until they were 5th grade when in john's case he entered budapest gymnasium the best maths class of his age the city could provide.

worldrecordjobs tip 1 - we accept that practice makes sports wizards Csikszentmihalyi has studied brilliantly skillful people - their secret in plain sight: maximise experiential edge of unique competence- having met von neumann my father coined term post-industrial revolution in the economist (some now call this industrial revolution 3 as places who blend tech and human school designs to maximise experiential learning)- whats hopeful is this an above zero sum game unlike consuming up things. We don't need to compete between nations for millennial youth to maximise community enriching skills let alone sustainability. What is it above washington dc political barons of all sides that makes them waste our youth so.

When you look at how maths is taught in usa (which i have as my daughter grew up here ) you do wonder - is american education designed never again to value maths minds like von neumann's and what does that tell you. No Mr Biden its not china's fault usa has chosen not to train any extraordinary maths minds -there's something very wrong in the DC climate with how bureaucrats of all parties have designed schooling fir where 100 times more engineering code evert decade determined what human innovations valuing community sustainability mattered. Now of course 400 billion dollars into playschools could be extraordinary but please dont let the same failed adminstrators design the schools- 20 years of work now in 50 countries has piloted playschools -abedplay.com

Story 2: This years Yidan Prize has roped in 2019's 2 economics nobel prize winners to ask will it be 4th time lucky for 6 year old children who grow up in south asia- thats where one quarter of the worlds' youth grow up. They were unlucky in 1860 when the Scot Queen Victoria sent over to Calcutta died within 9 months of landing of diarrhea; when from 1906 the penny dropped on Gandhi that his profession bar of london barrister applied laws designed to stunt his own people (intriguingly instead of confrointing London immediately Gandhi aimed at total redesign of education recognising the empire system of graded standard exams is designed to throw out 99% as not being fit to adminster empire- in discovering maria montessori, Gandhi had found the ticket for every indian child to be valued but he was neither able to see that gift blossom i Independent India and worse at the last moment of designing national boders the 2 great trading pors then called bombay and calcutta were partitioned off so tow pakistans were born blocked off from world trade -that was never gandhi's map of the future nor my grandfather who wrote up the legalese of indi's independence) . Yidan is incidentally billionaire hubbing 21st c education's futures for all out of Hong Kong a city that knows more than anywhere how much the locations and upbringing of youth at our world's superports determines the futures of all of us.

Monday, November 30, 2020

AI & Blockchain

 

can you give me some examples of how advances in human centric ai and blockchain support each other?

Sure. Here are some examples of how advances in human-centric AI and blockchain support each other:

  • Blockchain can be used to store and secure data that is used to train AI models. This data can include things like text, images, and videos. By storing this data on a blockchain, it can be made more secure and tamper-proof. This can help to ensure that AI models are trained on accurate and reliable data.
  • Blockchain can be used to create decentralized AI applications. These applications are not controlled by any single entity. This can make them more secure and resistant to censorship. It can also make them more transparent and accountable.
  • Human-centric AI can be used to improve the usability and security of blockchain applications. For example, human-centric AI can be used to create user interfaces that are more intuitive and easy to use. It can also be used to detect and prevent fraud and other malicious activity on blockchain networks.

Overall, advances in human-centric AI and blockchain can support each other in a number of ways. By working together, these technologies can help to create more secure, transparent, and accountable AI applications.

Here are some specific examples of how human-centric AI and blockchain are being used together today:

  • Insurance: AI is being used to assess risk and price insurance policies. Blockchain is being used to store and secure this data. This combination of technologies is making it possible to offer more personalized and affordable insurance policies.
  • Supply chain management: AI is being used to track and monitor the movement of goods. Blockchain is being used to create a secure and transparent record of this data. This combination of technologies is making it possible to improve the efficiency and security of supply chains.
  • Healthcare: AI is being used to diagnose diseases and recommend treatments. Blockchain is being used to store and secure patient data. This combination of technologies is making it possible to improve the quality of care and make healthcare more affordable.

These are just a few examples of how human-centric AI and blockchain are being used together today. As these technologies continue to develop, we can expect to see even more innovative applications emerge