Monday, June 14, 2021

g-f(2)320 The Big Picture of Business Artificial Intelligence (6/14/2021), VB, DeepMind says reinforcement learning is ‘enough’ to reach general AI




ULTRA-condensed knowledge


Opportunity, There is a solid path to general AI
  • Reinforcement learning, a branch of AI that is based on reward maximization, can lead to the development of artificial general intelligence.
Lesson learned, Decades-long chase to create artificial intelligence
  • In their decades-long chase to create artificial intelligence, computer scientists have designed and developed all kinds of complicated mechanisms and technologies to replicate vision, language, reasoning, motor skills, and other abilities associated with intelligent life.
Lesson learned, Brilliant progress but far from general intelligence
  • While these efforts have resulted in AI systems that can efficiently solve specific problems in limited environments, they fall short of developing the kind of general intelligence seen in humans and animals.
Opportunity, A simple but powerful principle: reward maximization
  • Scientists at U.K.-based AI lab DeepMind argue that intelligence and its associated abilities will emerge not from formulating and solving complicated problems but by sticking to a simple but powerful principle: reward maximization.
Lesson learned, The inspiration is well founded
  • The inspiration from studying the evolution of natural intelligence as well as drawing lessons from recent achievements in artificial intelligence.


“genioux fact fast solution" condensed as an image


Condensed knowledge



  • Multiple updates (6/14/2021) for those traveling at high speed on GKPath!
Opportunity, There is a solid path to general AI
  • Reinforcement learning, a branch of AI that is based on reward maximization, can lead to the development of artificial general intelligence.
Lesson learned, Decades-long chase to create artificial intelligence
  • In their decades-long chase to create artificial intelligence, computer scientists have designed and developed all kinds of complicated mechanisms and technologies to replicate vision, language, reasoning, motor skills, and other abilities associated with intelligent life.
Lesson learned, Brilliant progress but far from general intelligence
  • While these efforts have resulted in AI systems that can efficiently solve specific problems in limited environments, they fall short of developing the kind of general intelligence seen in humans and animals.
Opportunity, A simple but powerful principle: reward maximization
  • Scientists at U.K.-based AI lab DeepMind argue that intelligence and its associated abilities will emerge not from formulating and solving complicated problems but by sticking to a simple but powerful principle: reward maximization.
Lesson learned, The inspiration is well founded
  • The inspiration from studying the evolution of natural intelligence as well as drawing lessons from recent achievements in artificial intelligence.


Category 2: The Big Picture of the Digital Age

[genioux fact deduced or extracted from VB]

This is a “genioux fact fast solution.”

Tag Multiple updates for those traveling at high speed on GKPath

Type of essential knowledge of this “genioux fact”: Essential Analyzed Knowledge (EAK).

Type of validity of the "genioux fact". 

  • Inherited from sources + Supported by the knowledge of one or more experts + Supported by research.


Authors of the genioux fact

Fernando Machuca


References

ABOUT THE AUTHORS


Ben Dickson

Ben Dickson is a software engineer and the founder of TechTalks, a blog that explores the ways technology is solving and creating problems. He writes about technology, business and politics. Follow him on Twitter: @BenDee983.  


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