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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, October 30, 2020

Nutrition leaps that may be expected first from ai like alphafold

 

Are there some (US) fruits and vegetables that are likely to gain first from new protein database published by alphafold?

Yes, there are some fruits and vegetables that are likely to gain first from the new protein database published by AlphaFold. These include:

  • Apples: Apples are a good source of fiber, vitamin C, and potassium. They are also a good source of antioxidants, which can help protect against cell damage. AlphaFold can be used to identify the proteins in apples that are responsible for their nutritional value and health benefits. This information can be used to develop new varieties of apples that are even more nutritious and beneficial to human health.
  • Grapes: Grapes are a good source of antioxidants, potassium, and vitamin K. They are also a good source of resveratrol, a compound that has been shown to have anti-aging and anti-cancer properties. AlphaFold can be used to identify the proteins in grapes that are responsible for their nutritional value and health benefits. This information can be used to develop new varieties of grapes that are even more nutritious and beneficial to human health.
  • Potatoes: Potatoes are a good source of carbohydrates, potassium, and vitamin C. They are also a good source of dietary fiber, which can help regulate digestion and promote heart health. AlphaFold can be used to identify the proteins in potatoes that are responsible for their nutritional value and health benefits. This information can be used to develop new varieties of potatoes that are even more nutritious and beneficial to human health.
  • Tomatoes: Tomatoes are a good source of lycopene, an antioxidant that has been shown to have anti-cancer properties. They are also a good source of vitamin C, potassium, and fiber. AlphaFold can be used to identify the proteins in tomatoes that are responsible for their nutritional value and health benefits. This information can be used to develop new varieties of tomatoes that are even more nutritious and beneficial to human health.

These are just a few examples of how AlphaFold can be used to improve the nutritional value and health benefits of fruits and vegetables. As AlphaFold technology continues to develop, we can expect to see even more innovative applications emerge.