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

Tuesday, January 31, 2023

 stanfird HAI issued it latest report on climate ai in january 2023  https://hai.stanford.edu/sites/default/files/2023-01/HAI_IndustryBrief6_v8.pdf

These are definitions used in the climate report

Intelligence might be defined as the ability to learn and perform a range of techniques to solve problems and achieve goals—techniques that are appropriate to the context in an uncertain, ever-varying world. A fully pre-programmed factory robot is flexible, accurate, and consistent, but not intelligent. 

Artificial Intelligence (AI) (seee language alteady popularuised by Vine Neumann and peers - eg computer & the brain -, is a term coined in 1955 by John McCarthy, Stanford’s first faculty member in AI, who defined it as “the science and engineering of making intelligent machines.” Much research has human program software agents with the knowledge to behave in a particular way, like playing chess, but today, we emphasize agents that can learn, just as human beings navigating our changing world. Autonomous systems can independently plan and decide sequences of steps to achieve a specified goal without being micromanaged. A hospital delivery robot must autonomously navigate busy corridors to succeed in its task. In AI, autonomy doesn’t have the sense of being self-governing common in politics or biology. Machine Learning (ML) is the part of AI that studies how computer systems can improve their perception, knowledge, decisions, or actions based on experience or data. For this, ML draws from computer science, statistics, psychology, neuroscience, economics, and control theory. In supervised learning, a computer learns to predict human-given labels, such as particular dog breeds based on labeled dog pictures. Unsupervised learning does not require labels, but sometimes adopts selfsupervised learning, constructing its own prediction tasks such as trying to predict each successive word in a sentence. Reinforcement learning enables autonomy by allowing an agent to learn action sequences that optimize its total rewards, such as winning games, without explicit examples of good techniques. Deep Learning is the use of large multi-layer (artificial) neural networks that compute with continuous (real number) representations, similar to the hierarchically organized neurons in human brains. It is successfully employed for all types of ML, with better generalization from small data and better scaling to big data and compute budgets. A recent breakthrough is the transformer, a neural net architecture which flexibly incorporates context via an attention mechanism, allowing powerful and computationally efficient analysis and generation of sequences, such as words in a paragraph. Foundation models are an emerging class of models, often transformers trained by self-supervision on large-scale broad data, that can be easily adapted to perform a wide range of downstream tasks. The best-known examples are large pretrained language models like GPT-3, but the term extends to models for all modalities of data and knowledge. An algorithm is a precise list of steps to take, such as a computer program. AI systems contain algorithms, but typically just for a few parts like a learning or reward calculation method. Much of their behavior emerges via learning from data or experience, a fundamental shift in system design that Stanford alumnus Andrej Karpathy dubbed Software 2.0. Narrow AI is intelligent systems for particular tasks, e.g., speech or facial recognition. Human-level AI, or artificial general intelligence (AGI), seeks broadly intelligent, context-aware machines. It is needed for effective, adaptable social chatbots or human-robot interaction. Human-Centered Artificial Intelligence is AI that seeks to augment the abilities of, address the societal needs of, and draw inspiration from human beings. It researches and builds effective partners and tools for people, such as a robot helper and companion for the elderly. Text by Professor Christopher Manning, v 1.2, April 2022

=================bard on computer and the brain

what can you tell me about computer and the brain - lectures given at Yale soon after death of John Von Neumann

Sure. The Computer and the Brain is a series of lectures given at Yale University in 1958 by John von Neumann, a Hungarian-American mathematician and polymath. The lectures were given shortly after von Neumann's death, and they were published posthumously in 1958.

In the lectures, von Neumann discusses the similarities and differences between computers and brains. He argues that computers and brains are both information-processing systems, but that they use different methods to process information. Computers use digital logic, while brains use analog logic.

Von Neumann also discusses the potential for computers to surpass human intelligence. He argues that computers have the potential to be more intelligent than humans because they can be programmed to learn and adapt.

The Computer and the Brain is a seminal work in the field of artificial intelligence. It has been influential in the development of computer science and neuroscience. The lectures are still relevant today, and they continue to be studied by researchers and scholars.

Here are some of the key points that von Neumann made in the lectures:

  • Computers and brains are both information-processing systems.
  • Computers use digital logic, while brains use analog logic.
  • Computers have the potential to surpass human intelligence.
  • Computers can be programmed to learn and adapt.

The Computer and the Brain is a valuable resource for anyone interested in artificial intelligence, computer science, or neuroscience. It is a thought-provoking and insightful work that continues to be relevant today.

Thursday, January 26, 2023

 I started playshool's nextdoor group, MD, for 2 reasons. My daughter wants to advance as a 20-play school something educator and linguist- hopefully breathing good energy into this for 40+ more years.. Meanwhile, 40 years ago I-co-authored the start of a genre www.2025report.com which explored the idea that how education and digital grew up with each other would explain life's community ups and downs far more than any economist's or policy making algorithms or Justice's supreme overlords. 

My dad was an economist www.economistdiary.com who had met von neumann in princeton in 1951 and been told to quiz leaders -what goods can peoples unite with 100 times more tech per decade? Not everyone would get equal ops to be first explorers of virtual worlds and non human intellects. For example, since 1965 those lucky to be near enough intel's silicon valley have enjoyed 100 times more chips (blending real and artificial intel), 

One of the first readers to contact us in 1984 surprised us out of new zealand- he said he wanted to map learning from cradle to grave- and make sure that families understood half of human development happened before the age of 6. Now this included the fact that in poor humid places cut off from communications - half of infants may die of diarrhea or have their brain stunted unless their chief nurturer knows what to do. But its also about how much play versus violence surrounds a kid up to age 6, and indeed whether a kid gets a chance at double  linguistic literacy or some other special skill of her family's tree. His book sold a few thousand copies in NZ and 10 million in china of the late1990s. At least 10 million chinese school kids now never see an examination before the age of 11 - see latest laureate at hong kong's www.yidanprize.org. My 1984 inspiration guide Gordon Dryden's The Learning Revolution can be downloaded for free - say if you need help (some of the servers seem to have their bad hair days) 

Anyway 9/11 woke me up to how far off millennials' world was spinning so eventually i found a national servant leader (actually 8th most populous place) who spent more than 40 years linking partners from around the world in bridging learning non-linearly- ok there is a ladder of what to experience by what age but what's urgent is to assist a kid who may have missed a rung or two. By age 6 if a child is not as literate as most peers there is a 90 day by 20 minutes - 30 hours total remedy. Better still kids who have learnt this way can with a bit of supervision do most of the coaching of the next kid in need (much as montesorri demonstrated between the world wars. By age 9 your school could have included aflatoun financial literacy and some emotionally intelligent teamworking experiences, including maryland's own www.openspaceworld.com - 100 nations can testify to Afla's intercultural good: the modular lessons began in an indian orphanage but like most youth-friendly stuff out of Europe now meta-hubs out of Netherlands . By age 11 you could have enrolled your kid in a peer to peer mental and bodily health network. It took me 25 Asian trips between 2007 and the covid years ,and one to HK since to update worldwide contributions (and of course when I show people my maps they are welcome to show my friends and I what cooperations we haven't begun to linkin yet. 

Mother earth offers an amazingly deep and diverse world to unite 8 billion brains around if only we believed we can race ahead of the Arts & the Bigs. Apart from women's kindness www.beingai.com, All we really need to agree with are HG Well's bon mots- civilisation is a race between education and catastrophe.

Or as New York  Leon Botstein (founder of American Symphony Orchestra) wrote back in 1999 in Jefferson's Children from pre-teen on subjects like coding need practice/apprenticeships daily as much as music or sports- what they don't need is classroom examinations/brainwashing which tell the kid how wrong she is, how stupid she is relatively when she could be told what the system hasn't yet let her practice. It seems that in the US of A its been quite easy since 1995 for big business like Amazon Alexa to hollow out community shopping  but not to prioritise inclusion of a sister alexa for personal learning. Apparently american education as a system blocks the majority of a country's educators to be the change communally however much love they energise individually. So instead of 30 years of smoothly integrating digital ways ahead from berners lee first invite to do so in 1990, america had to wait to covid test of how broken health and education's and food (ie human energy) community systems were, or will be. http://ed3envoy.un.com From this month on, what is good and bad news is its not competition with other nations we need politicians to most urgently serve; - its cooperation communally. That's if you want millennials to be the first sustainability generation instead of the first generation whose kids are doomed to extinction. 

Ok all if this is a viewpoint (all reporting errors are mine alone- likely my grey cells 'last 40 years of tracking this are inferior to most younger people reading this)  and yes be warned about fake media's sickness:  every place or time I have tried to discuss this in this region or other parts of USA, a lot of hate has eventually been directed at the experimenters especially the youth. That said if anyone thinks this is the right time to try again we can meet marriott n bethesda coffee or i can zoom you in to communities around the world that are demonstrating this purpose. +1 240 316 8157 chris.macrae@yahoo.co.uk 

- may your child have a joyful and curious day. and stay out of covid's way - 

refs www.ed3dao.com (I am not sure if crypto is workable in the west but if it is this space will attract 6000 changeteacher.com while Guterres leads the UN ;  https://www.un.org/techenvoy/content/ongoing-work Next east-west reunion - singapore is moving everything it knows on Goal 6 water & sanitation  www.worldtoilet.org to NY March 22-24 https://sdgs.un.org/conferences/water2023 -the road show continues in Brazil Apeil and I am still surveying where's water who's up for "moore" of humansAI 2023. The college year 23-24 will be unique in the cooperative pedias of mankind because millennials will by then know who is their most heroic storyteller sdgoal by goal http://www.sdgmetaverseprize.org  http://worldrecordjobs.com https://pioneer.app/changeteacher/progress-updates/382f460e/2023-01-23  jargon pedia :: From Ancient Greek παιδεία (paideía, “upbringing, education”)