Once you have a colonizing consciousness pattern, the limit of its capabilities are given by the effective size, plasticity, learning rate and determinism of its substrate. Multicellular evolution during which everyone tries to eat your brain is a very slow and noisy way to learn
RESEARCH
-
Self-organization learning principles in biological and abiological systems
By
–
Misha Gromov maintains that most of the library of genetic subroutines was discovered quickly and early on in biological evolution. I suspect that the core principle of a learning self organization that imposes itself on matter is either just the cell, or even abiological.
-
Can AI Learn Everything Biology Cannot Teach Us?
By
–
I don't think that we can learn anything from biological lifeforms that we cannot learn from AI, and the opposite is not true
-
Model Comparisons for Testing and Results Validation
By
–
Love this. These model comparisons are perfect for double checking my tests/results to
-
Attention Mechanism Breakthrough in AI Perception Demonstration
By
–
This is such a brilliant perception demo. Attention is all you need! https://t.co/S22SFu7cIL
— Nando de Freitas (@NandoDF) 10 février 2024This is such a brilliant perception demo. Attention is all you need!
-
Text versus 32-bit floats: lossless compression efficiency trade-offs
By
–
I don’t think that’s necessarily true! text is actually relatively few bytes, while each 32-bit float is 4 bytes, so at least at short lengths things could be lossless
-
The Problem With ‘Generates’: Language, AI, and Meaningful Communication
By
–
Right. Although the verb "generates" gives us very very little to go on, beyond signaling a deep disregard for the magical process of using and extending human language to relate to each other. There's simply nothing concrete or meaningful about this statement.
-
Word Count as Metric: Meaningless Quantification in Serious Analysis
By
–
Number of words is bare quantification signifying nothing. It's meaningless, uninteresting, beside the point as a serious person's metric. And yet…
-
Text Embeddings Lossy Collisions Detection Problem
By
–
yeah! but I don’t know if text embeddings are necessarily lossy? and if so how to locate collisions? (but yes; this is the entire point)
-
Making AI Topics Exciting Drives Deeper Learning
By
–
I think finding fun ways to get people excited about a topic is step 1 to getting them to WANT to do the “brain sweat” work. Excitement and enjoyment of the topic will let some get the surface level and inspire others to want to dive even deeper.