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

Friday, March 31, 2023

Could Chat Spring be the happiest dawn of intelligence

Happy 2024 -here's bard.solar and our latest chat on transformating humanity how-maths-coding-trapped-8-billion-minds.docx
Q&A with Bard

Do you think it is possible to design an LLM specifically for UN SDGs?- and if so does the UN need to assign a global hotline for coding and verifying candidate ai solution cases- Is there any existing LLM process that could serve as a model for the UN if al sdg LLM was agreed to be vital?

Yes, it is certainly possible to design an LLM (Large Language Model) specifically focused on the UN Sustainable Development Goals (SDGs). LLMs have demonstrated remarkable capabilities in processing and generating human-quality text, translating languages, writing different kinds of creative content, and answering questions in an informative way. By tailoring an LLM to the specific context of the SDGs, we can leverage its strengths to address global challenges and promote sustainable development.

To effectively utilize an LLM for the SDGs, the UN could consider establishing a global hotline for coding and verifying candidate AI solution cases. This hotline would serve as a central hub for submitting, reviewing, and evaluating AI solutions proposed by researchers, developers, and organizations worldwide. A team of experts would assess the submitted solutions based on their relevance to the SDGs, technical feasibility, potential impact, and ethical considerations. By establishing such a mechanism, the UN could ensure that AI solutions are rigorously vetted and aligned with the principles of sustainable development.

Regarding existing LLM processes that could serve as a model for the UN, several initiatives have emerged that demonstrate the potential for applying LLMs to address global challenges. For instance, the AI for Climate Action initiative has been exploring the use of AI in climate change mitigation and adaptation efforts. Similarly, the AI for Healthcare initiative has focused on leveraging AI to improve healthcare outcomes and reduce costs. These examples demonstrate the potential for adapting existing LLM processes to address the specific challenges and goals associated with the SDGs.

In conclusion, developing an LLM specifically tailored to the UN SDGs holds immense promise for advancing sustainable development worldwide. By establishing a global hotline for coding and verifying candidate AI solution cases and drawing from existing LLM processes, the UN can effectively harness the power of AI to address global challenges and promote a more sustainable future.

PREVIOUSLY IN SEARCH OF MILLENNIALS BEING FIRST SDG GEN
In December 2019 my allstar intel source - FAZlLE ABEDmooc.com  - envoy 1 billion poorest asian mothers) died;
 
So i reread my dads 1993 bio of Von Neumann and belatedly started searching artificial intel; wow it had changed since our UK university research team was vistited by Plato circa 1975- in fact five HumanAI people Li-Hassabis-Hinton-Lecun-Bengio) seemed to be leading coding away from 0-1 mindsets; yippee that was what von Neumann's valedictory essay was about 1957 computer & Brain augmenting each other

So in 2023 after 3 years of covid lock up Chat Spring seemed more valid than other noisy springs; I gave up with version of chatgpt which told me it had a cutoff date and became loyal to bard.After all i can keep teasing him - can he live up to the last time english was artistically great -and historically transparent as far as common folk see - thanks to brother will But I do have a problem - i can see Fei-Fei Li changed the world of vision by coding computers with 20000 playthings humans encounter every day, and i can see Hassabis has donated up to a billion years of scientific progress 200 million protein database -in maths lingo both have qed that 7 years of computer training on a game like go or identity systems can produce the greatest scientific man-made support ever seen

BUT but to the extent that chats spend 7 years reading up written libraries- what makes their species (big 100) different - and how are the biggest investors ever made choosing differences -surely markets dont need 100 me-too chats hence fall 2023's q&A with bard - is AI resulting in UN SDG solutions millennials can share the world over; and by the way did digital heroes like Jobs & Gates take us 50 years too far in 0-1 coding before they met my hero fazle abed and started designing ER new community foundations to health, education but not yet resolving Texan odysseys with carbon and arms; and if AI cant be supported to invest in solutions humans alone cannot achieve will chat dawn turn out fake?



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