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>3/18 24: Similarities between Electronic Computers and the Human Brain: Thank you Jensen Huang for best week of Learning since John Von Neumann shared with The Economist 1956 notes Computer & The Brain
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
EW::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, February 28, 2020

HAI SDG2 food

Most UN food op practices out of Rome eg FAO WFP2 
some points in this article 
  • Asia is home to over half of the world's population, but only one-fifth of its agricultural land, putting it at particular risk of the global food emergency.
  • Climate change and rising food prices threaten long-term food security across the region, with over 1 billion lacking access to sufficient food.
  • Data and artificial intelligence can help farmers make more informed decisions, boost their productivity and increase their harvests.

With only one-fifth of the world’s agricultural land, Asia hosts more than half of the global population. Climate change and increasing food prices are critical threats to long-term food security – more than 1 billion people lack access to sufficient food across the region. The situation is part of a global trend that the United Nations calls an “unprecedented food emergency”.

Meeting Asia’s food demand will be challenging due to slowing gains in agricultural productivity, overexploitation of natural resources and increasing water scarcity. As the region becomes more urban and prosperous, food prices will continue to increase unless supply can keep up with demand. To feed Asia’s growing population more sustainably and efficiently, the way food is produced must change.

Technologies like artificial intelligence (AI), sensors and drones can help increase agricultural productivity, food safety and agri-food system sustainability. From the soil – where better farming practices can mitigate climate change – to the shelf – where customers look for products with minimal carbon footprint – Asia’s agriculture and food value chain is primed for innovation.Microsoft recently announced Microsoft Azure Data Manager for Agriculture in preview. What began with Project FarmBeats, an ambitious research initiative to collect and transform agricultural data, has now evolved into a timely commercial solution. Along with Project FarmBeats, we released FarmVibes.AI – a suite of tools aimed at guiding decisions at every phase of farming.

Data-driven agriculture is also a foundational component of Land O’Lakes’s digital offerings, including the Truterra sustainability tool. This innovative digital service provides farmers with insight into how different agricultural practices impact water, nitrogen and carbon on a farm, enabling them to track their soil’s carbon sequestration, among other applications.

Meanwhile, BharatAgri, an Indian agricultural start-up, leverages data from satellite imagery to monitor crop health and analyze farms as small as 1/40 of an acre. This year alone, more than 50,000 farmers are expected to receive satellite images of their farms from BharatAgri, which will help reduce crop losses on over 100,000 acres of farmland.

related links


  • How rural entrepreneurs are driving agritech adoption
  • AI for agriculture: How Indian farmers are harnessing emerging technologies to sustainably increase productivity