Neural Networks and Novelty: A Window Into Harvard’s Innovators | Harvard Independent
Gauri Soodharvardindependent.com
Neural Networks and Novelty: A Window Into Harvard’s Innovators | Harvard Independent
What the neural network “learns” is emergent rather than deduced. For example, it may notice a pattern that if it’s cloudy, then people are more likely to carry an umbrella. But it would not be able to explain that this is because cloudy implies rain and rain implies umbrella. Instead it effectively identifies a “rainy” vibe through correlations of... See more
Nameless Feeling
Elena added
The neural networks coded by human scientists are often the result of trial and error. There is little theory to what does and doesn’t work, and no guarantee that the best designs have been found.
Will Douglas Heaven • AI is learning how to create itself
Kasper Jordaens added
As human brains increasingly interact with technology that mimics their own capabilities, the need for students to understand both the science and engineering of intelligence continues to grow as well. Addressing these challenges will require a deeper understanding of how the brain produces intelligent behavior and how we may be able to replicate i... See more
MIT • Course 6-9: Computation and Cognition | Brain and Cognitive Sciences
Juan Orbea added
Clune also stresses the importance of thinking about the ethics of the new technology from the start. There is a good chance that AI-designed neural networks and algorithms will be even harder to understand than today’s already opaque black-box systems.
Will Douglas Heaven • AI is learning how to create itself
Kasper Jordaens and added
If machines can rapidly weave together complex ideas from diverse schools of thought to uncover conceptual connections, would this type of academic activity still be deemed intelligent, and will the knowledge we’re boasting to have — our prideful capacity to activate our brain’s net of associations and comparisons — retain any significance?
Shai Tubali • The Mechanized Mind: AI’s Hidden Impact on Human Thought
Daniel Santos added
For researchers interested in the intersection of animal and machine intelligence, moreover, this “supervised learning” might be limited in what it can reveal about biological brains. Animals—including humans—don’t use labeled data sets to learn. For the most part, they explore the environment on their own, and in doing so, they gain a rich and rob... See more
Self-Taught AI May Have a Lot in Common With the Human Brain
Laura Pike Seeley added
But mostly things have been discovered by trial and error, adding ideas and tricks that have progressively built a significant lore about how to work with neural nets.
Stephen Wolfram • What Is ChatGPT Doing ... And Why Does It Work?
Kaustubh Sule added
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
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