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Research#AI and Neuroscience📝 BlogAnalyzed: Jan 3, 2026 01:45

Your Brain is Running a Simulation Right Now

Published:Dec 30, 2025 07:26
1 min read
ML Street Talk Pod

Analysis

This article discusses Max Bennett's exploration of the brain's evolution and its implications for understanding human intelligence and AI. Bennett, a tech entrepreneur, synthesizes insights from comparative psychology, evolutionary neuroscience, and AI to explain how the brain functions as a predictive simulator. The article highlights key concepts like the brain's simulation of reality, illustrated by optical illusions, and touches upon the differences between human and artificial intelligence. It also suggests how understanding brain evolution can inform the design of future AI systems and help us understand human behaviors like status games and tribalism.
Reference

Your brain builds a simulation of what it *thinks* is out there and just uses your eyes to check if it's right.

Research#Cognition🔬 ResearchAnalyzed: Jan 10, 2026 14:37

Bayesian Inference Unveils Mechanism Behind Comparative Illusions

Published:Nov 18, 2025 16:33
1 min read
ArXiv

Analysis

This article, drawing from an ArXiv preprint, suggests a novel explanation for the varying strengths of comparative illusions using Bayesian inference. The research potentially offers insights into human perception and cognitive biases.
Reference

Graded strength of comparative illusions is explained by Bayesian inference

Research#Hallucinations🔬 ResearchAnalyzed: Jan 10, 2026 14:50

Unveiling AI's Illusions: Mapping Hallucinations Through Attention

Published:Nov 13, 2025 22:42
1 min read
ArXiv

Analysis

This research from ArXiv focuses on understanding and categorizing hallucinations in AI models, a crucial step for improving reliability. By analyzing attention patterns, the study aims to differentiate between intrinsic and extrinsic sources of these errors.
Reference

The research is based on ArXiv.

Illusion Diffusion: Optical Illusions Using Stable Diffusion

Published:Feb 13, 2023 04:01
1 min read
Hacker News

Analysis

The article introduces a novel application of Stable Diffusion for generating optical illusions. This suggests advancements in image generation and potentially opens new avenues for artistic expression and research in visual perception. The focus on Stable Diffusion indicates a reliance on a specific AI model, which could be a limitation if the model's capabilities are restricted.
Reference

Attacking machine learning with adversarial examples

Published:Feb 24, 2017 08:00
1 min read
OpenAI News

Analysis

The article introduces adversarial examples, highlighting their nature as intentionally designed inputs that mislead machine learning models. It promises to explain how these examples function across various platforms and the challenges in securing systems against them. The focus is on the vulnerability of machine learning models to carefully crafted inputs.
Reference

Adversarial examples are inputs to machine learning models that an attacker has intentionally designed to cause the model to make a mistake; they’re like optical illusions for machines.