Learning to feel time again in the Permaweird
Math Academy
Q. Michael Pershan’s main critique of spaced repetition in the context of Math Academy?A. It reinforces his memory of a shallow understanding.
The Great Reckoning - The Ideas Letter
The world feels unsettled, as if history itself were changing tempo. The familiar landmarks of the modern age are blurring, slipping away, and the stories we once told ourselves about…
The Great Reckoning - The Ideas Letter
The world feels unsettled, as if history itself were changing tempo. The familiar landmarks of the modern age are blurring, slipping away, and the stories we once told ourselves about…
Excess Capacity Learning
How do humans learn from experience? Traditionally, cognitive scientists have assumed that discovering generalizable patterns requires that humans compress rich and noisy experiences. However, recent computer science results suggest otherwise — systems can learn by ‘overfitting’ and expanding all the details of their experiences. We offer a new perspective on learning based on a cognitive system’s representational capacity, which can be constrained (forcing the system to compress details of past experiences), sufficient (to memorize past experiences), or excess (allowing the system to expand on the details of past experiences). This framework has implications for understanding learning across cognitive, clinical, and developmental contexts.
Letta
Making machines that learn. Create stateful agents that remember everything, learn continuously, and improve themselves over time.
To Make Sense of the Present, Brains May Predict the Future | Quanta Magazine
A controversial theory suggests that perception, motor control, memory and other brain functions all depend on comparisons between ongoing actual experiences and the brain’s modeled expectations.
Prophecy And Future Coding
Preface: On Prophecy and the Search for Certainty in an Age of Reflexive Time
How are we writing the future of humanity?
Consciousness spinning
Permacomputing Update 2021 | viznut
It is now more than a year since I wrote my "early notes" about Permacomputing. At that time, I was not yet aware of anyone else having similar ideas, so I've now decided to write an update that connects my ideas with the existing discussions and activities. I also want to share some new ideas I have been pondering about. This text is about 33K characters / 4900 words long, so allocate your time accordingly.
Living with two clocks
Staying with unbearable thoughts, and searching for a politics that’s equal to these times.
On AI as model organism for human learning
I've a pretty taste for paradox
Ever thought we acquire generalizable knowledge by discarding details and compressing our experiences? In a new BBS paper, @sabinasloman.bsky.social and I argue otherwise, proposing a novel way of studying human learning inspired by double descent in ML. Disagree? Propose a commentary by May 15 :)
