Aaron Hertzmann

@aaronhertzmann.com

www.dgp.toronto.edu/~hertzman

Storytelling is, first and foremost, about people, and AI in fiction are typically modified people, not genuine explorations of a scientific concept. Viewers can identify with Data as a smart-but-naive nerd, with Terminator (in T2) as an emotionally-closed-off father figure, etc.

Andres Guadamuz@technollama.bsky.social · 3w ago

Why does AI in science fiction so often miss the mark? A few days ago there was an interesting post by Andrew Curran that got a lot of responses which was discussing why AI in science fiction often does not have the capabilities that AI already has in reality. I thoroughly agree with that take,…

For years, I've heard from my fellow computer scientists that "the brain is a computer" or "we can simulate brains in a computer." I think both are wrong, and, now that we're hearing them from corporate tech leaders too, it's no longer just an academic topic. 🧵 aaronhertzmann.com/2026/07/13/b...

The Brain Is Not Just A Computer, and Cannot Be Simulated by One

Digital computers perform fixed logical operations on clock cycles; brains are biological systems of staggering complexity.

aaronhertzmann.com

1. A bit of evolutionary biology. I'm really intrigued by a new perspective piece from Steve Frank that explores connections between how natural selection creates systems that generalize and recent work in machine learning about the surprising capabilities of massively overparameterized systems.

Generalization as the great leap in evolvability: insights from machine learning

Abstract. Natural selection encodes learned information in the genome. Learned solutions may be tuned specifically to past challenges, failing in altered e

academic.oup.com

I haven’t yet finished reading this review, but it already lead me to reading Rosa Cao’s 2022 paper on “multiple realizability” today and it’s my new favorite paper on computational functionalism. Might post most about the key points

Raphaël Millière@raphaelmilliere.com · 2mo ago

Now published in open access! Your one-stop shop for the philosophy of language models. It's the spiritual descendant of our two-part preprint from 2024, fully updated. This should be particularly useful for anyone looking for an entry point into this rapidly growing field.

SIGGRAPH 2026 is just around the corner! Planning to attend? Join us for Lines & Minds: Visual Abstraction in Art, Psychology, and Computer Graphics 🎨🧠🫖 We’ll explore how visual abstraction shapes how we think, create, and communicate. 🔗 lines-and-minds.github.io 📅 Sunday, July 19

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New blog post pointing out some interesting observations about sketching and how it relates to theories of visual perception. In short, I don't think there's a good account for how scribbly art is recognized (or if there is I don't know it). 1/ aaronhertzmann.com/2026/06/01/s...

Scribbling, abstract art, and visual recognition

Sometimes when I sketch quickly, I feel like I’m scribbling some random squiggles, and, yet, recognizable shapes of my subjects emerge:

aaronhertzmann.com

I enjoyed my second #VSS2026 a few weeks ago. I found the session on peer review fascinating, especially the way an editor argued strongly against double-blind review using strawman arguments. Basically “optional blind review doesn’t fully solve all bias, so there’s no point to blind reviewing.”

New blog post on dog intelligence, based on my experiences with my own dog and volunteering at a shelter. We often describe dog behaviors in terms of knowledge: “She knows that if she sits, she gets a treat.” “He knows his name" etc. But I think dogs don't have knowledge, they have behaviors. 1/

Dogs Do Not Know Things

When you spend time with a dog, you have some ideas about what’s going on in its head. You get a sense of its moods, whether it is happy or tired or afraid. Taking care of a dog, or training it requir...

aaronhertzmann.com

Writing forces your brain to coordinate memory, reasoning, and meaning-making simultaneously. Every time you write, you rewire toward clearer thinking. Every time you let an LLM do it, you rewire toward consumption.

This editorial discusses the critical value of human-generated scientific writing in the era of large language models (LLMs), arguing that writing is essential to structured thinking and research comprehension. 
Writing as Thinking: The act of writing structure's thoughts, sorting research data, and identifying the main message, unlike LLMs which may lack true understanding or accountability.
LLM Hallucinations: LLM-generated text requires rigorous verification because these models can produce incorrect information or fake references.
Human vs. AI Roles: While LLMs are useful tools for brainstorming, improving grammar, or overcoming writer's block, human researchers must maintain control to engage in the creative task of shaping a compelling narrative.

If navigation apps like Google Maps were invented today, they would be called "AI" and hyped as "AI agents." It's truly amazing how well they work, and now everyone completely takes them for granted, and many people completely outsource the mental task of navigation to them.