On Artificial Intelligence
108 subscribers
27 photos
36 files
466 links
If you want to know more about Science, specially Artificial Intelligence, this is the right place for you
Admin Contact:
@Oriea
Download Telegram
Chris_Bailey_Hyperfocus__The_New.epub
5.6 MB
A practical guide to managing your attention— a powerful resource you have to get stuff done, become more creative, and live a meaningful life.
Wharton's Entrepreneurship Specialization covers the conception, design, organization, and management of new enterprises. This five-course series is designed to take you from opportunity identification through launch, growth, financing and profitability. With guidance from Wharton's top professors, along with insights from current Wharton start-up founders and financiers, you'll develop an entrepreneurial mindset and hone the skills you need to develop a new enterprise with potential for growth and funding, or to identify and pursue opportunities for growth within an existing organization.
https://www.coursera.org/specializations/wharton-entrepreneurship
Artificial neural networks (ANNs) have undergone a revolution, catalyzed by better supervised learning algorithms. However, in stark contrast to young animals (including humans), training such networks requires enormous numbers of labeled examples, leading to the belief that animals must rely instead mainly on unsupervised learning. Here we argue that most animal behavior is not the result of clever learning algorithms—supervised or unsupervised—but is encoded in the genome. Specifically, animals are born with highly structured brain connectivity, which enables them to learn very rapidly. Because the wiring diagram is far too complex to be specified explicitly in the genome, it must be compressed through a “genomic bottleneck”. The genomic bottleneck suggests a path toward ANNs capable of rapid learning.
https://www.nature.com/articles/s41467-019-11786-6
An insightful website which contains a history of cybernetic animals and early robots
https://cyberneticzoo.com
Steps Toward Artificial Intelligence.pdf
5.8 MB
Discussions about several issues relevant to trial-and-error learning (Reinforcement Learning), including prediction,
expectation, and what this paper called the basic credit-assignment problem for complex reinforcement
learning systems: How do you distribute credit for success among the many
decisions that may have been involved in producing it? (Published 1961)
StatisticalLearningTheory.pdf
359.2 KB
A Brief introduction to Statistical Learning theory