Researchers at Caltech quantify human behavioral information throughput at approximately 10 bits/s across various tasks, highlighting a vast discrepancy with the brain's sensory input capacity,...
be diligent
For individuals It's challenging to work a process when it moves slower than feels appropriate. In the context of computer conversations, the tactic of s...
#precision #scaling #generalization #impact | Jean-Rémi King
Well, we did not expect that: in 10 days: 1.6K ⭐ on Github, 70K downloads on HuggingFace 🤗, >6M views on socials. 🧠 TRIBE v2, our new foundation model of the human brain responses to sight, sound, and language, has led to a surge of community demos, dozens of PRs and issues, and a level of engagement that rivals major flagships model at Meta (e.g. Llama4: 3.6M views, and DINOv3: 900K): https://lnkd.in/eQgqyDvf As this raised several questions, let me emphasize some elements of clarification: 1. #Precision: This model exclusively uses fMRI recordings. While powerful, these data are slow-paced proxy measurements of brain activity, and aggregate responses ~100k-3M neurons per data point. This means we are very far from a neuronal-level modeling of the brain. 2. #Scaling: We leveraged ~1,000 hours of naturalistic fMRI data. This is very substantial for a functional imaging study with naturalistic data; but still this is "small data" compared to medical or biology foundation models in general (e.g. structural MRI models are typically tens of thousands of individual brains). 3. #Generalization: The model shows surprising out-of-domain generalization, but it is **not** a replacement for new data collection. The model will almost surely fail in areas it hasn't seen: task-specific behaviors, memory protocols, touch sensation etc. And these are the "known unknowns" - I expect we'll discover many more unknown unknowns along the way. 4. #Impact: The goal of this model, and of our team in general, is fundamental research in neuroscience. While I am optimistic about how such foundation models will help clinical diagnosis, prognosis, and patient care, the physics of MRI is such that there is no clear path for making this kind of technology directly usable to consumer/wearable products. We're in for the science, hence the open sourcing: 📄 Paper: https://lnkd.in/e7cbunJp 💻 Code: https://lnkd.in/ebwBVuJp ▶️ Demo: https://lnkd.in/eEUVxP4S 🤗 Model: https://lnkd.in/e2T8nPJP
Cognitive Load | Laws of UX
The amount of mental resources needed to understand and interact with an interface.
Feeling of Computing — Conversations
Ultra-Processed Information: AI and the Coming Deluge of Noise | Frankly 128
Kin 0.5.0 — A Bigger Brain, a Fuller Voice, and Your Kin 🎉 | Notion
This is one of our biggest steps yet: new ways to work with memory, a collective of Advisors we call Your Kin, smoother conversations, and a stronger voice.
Diversity-enabled sweet spots in layered architectures and speed–accuracy trade-offs in sensorimotor control | PNAS
Nervous systems sense, communicate, compute, and actuate movement using distributed components with severe trade-offs in speed, accuracy, sparsity,...
Using AI for just 10 minutes erodes your ability to persist at hard things - Berkeley News
A UC Berkeley researcher co-authored a study that raises profound questions about how we interact with artificial intelligence in education — and daily life.
Abeba Birhane on Twitter / X
a classic case of “the human mind is afforded less complexity than is owed, and the computer is afforded more wisdom than is due.” Baria and Cross (2021)that "vibe" is at the core of what makes us human. it defies formalization and datafication https://t.co/AXELAqlYcq— Abeba Birhane (@Abebab) February 17, 2024
Close to the Metal — Real Life
The value of reintroducing friction into our interactions with computers
Our interfaces have lost their senses
We programmed them by punching cards, plugging in wires, and flipping switches. Programmers walked among banks of switches and cables, physically choreographing their logic. Being on a computer used to be a full-body experience.
Dec 2020 -- Jelle Bruineberg -- Embodied cognition and the attention crisis
Addressing the Precision-Breadth-Simplicity Impossible Trinity in Psychological Research: A Comprehensive Exploration Approach
Psychological research faces a fundamental challenge—the Precision-Breadth-Simplicity (PBS) impossible trinity. While experimental findings are often precise and simple, they tend to be narrow in scope. Conversely, broad-and-simple concepts frequently lack precision. Developing theories that are both precise and broad is scientifically valuable but inevitably introduces complexity, which conflicts with humans’ cognitive limitations in processing complexity. To address this impossible trinity, I propose a comprehensive exploration (CE) approach—a data-guided theory-building framework that involves: (1) designing experimental conditions in a stimulus-driven way, with minimal upfront theoretical specification; (2) conducting experiments with tens of millions of observations (e.g., 40 million responses in Huang, 2025a); (3) modeling the results through iterative improvements; and (4) producing the outcome: a moderately complex quantitative information-processing model to integrate diverse empirical findings. Inspired by similar strategies that drove breakthroughs in artificial intelligence (e.g., ImageNet’s role in advancing object recognition), the CE approach offers a promising path toward more integrative psychological theories. Initial implementations in visual working memory research demonstrate both its practicality and potential to transform how we study mental processes.
Satisficing and the Use of Keyboard Shortcuts: Being Good Enough Is Enough?
Keyboard shortcuts are generally accepted as the most efficient method for issuing commands, but previous research has suggested that many people do not use them. In this study we investigate the use of keyboard shortcuts further and explore reasons why they are underutilized by users. In Experiment 1, we establish two baseline findings: (1) people infrequently use keyboard shortcuts and (2) lack of knowledge of keyboard shortcuts cannot fully account for the low frequency of use. In Experiments 2 and 3, we furthermore establish that (3) even when put under time pressure users often fail to select those methods they themselves believe to be fastest and (4) the frequency of use of keyboard shortcuts can be increased by a tool that assists users learning keyboard shortcuts. We discuss how the theoretical notion of ‘satisficing’, adopted from economic and cognitive theory, can explain our results.
100% Utilization
Since the end of the Second World War, we have come to expect continual growth in computing power and the rapid development of digital technology. This dynam...
