Appending "do not use defensive programming" to the end of my queries makes AI generated code much more terse and useful. I can handle weird edge cases after, but I want to start by getting the core functionality in place.

I've been surprised by how much I like OpenAI Atlas. It's so fast and it's the best AI-based search engine I've used. UX is amazing.

I reserve the right to dislike it in the future when it presumably tries to bake ADs into LLM outputs in a mublock-proof way :'(.

LLMs I've used have been almost completely useless at formalizing anything to do with denotational or operational semantics.

I find it so shocking how good models are at advanced math and coding, and then how bad they are at the intersection of the two.

I can't get any LLM to make a type system :(. PL folks have to write more papers to train the LLMs.

I remember when Windows added ads to the start menu. I think apple turned on a default to show ads (at least it can be toggled off for now). I left Linux because of the driver bugs, but Linux is looking pretty good now.

I believe these techniques can lead to:
new simulators that enable optimization through contact
new probabilistic algorithms with discontinuities
new differentiable renderers that better model occlusion
new ways to solve ML problems e.g. selecting MOEs and doing image gen in continuous space

Full abstract
www.eecs.mit.edu/eecs-events/...

TLDR: Modeling discontinuities (occlusion, cracks, and contact) is hard, but distribution theory gives a systematic way to model these phenomena. I introduce distribution programming, which enables implementation/autodiff by using programming primitives that denote distributions.

Successfully defended my thesis:
Distribution Programming for Physics-Based Computations

I'd love a good biking route from Cambridge to Logan Airport and a safe place to park the bike at the airport 🚲 ✈️ .

I know this isn't exclusively in Cambridge, but is this possible @realBurhanAzeem @Marc_C_McGovern? Thanks for all you've done for bikers!

I got an email that was clearly automated but had a personalized tag line about my research in it. Something of the form: "I was interested in your research on ..."

I'm just bracing for a new wave of spam like this. I need an AI to screen my emails from this slop.

My defense talk is completely hopeless. There is nothing anyone can do for it.

Manual, light-weight intuition building, automation to get a robust setup that can easily be edited, and manually edit.

Plotting workflow: prototype in Desmos, use chat to write matplotlib code, and do by-hand checking and tuning.

I want more of this workflow.

Does Meta stand for metadata because they store all your data and sell it to advertisers?

I just randomly joined a member of the MIT admin for lunch. He's part of the office that helps students reserve space at MIT. It was a great reminder of all the wonderful staff at MIT who made helped make my days at MIT better. Thanks Aaron!

April 25, 2025Russ Tedrake, MITTitle: A Careful Examination of Multitask Transfer in TRI’s Large Behavior Models for Dexterous ManipulationAbstract: Many of ... Stanford Seminar - Multitask Transfer in TRI’s Large Behavior Models for Dexterous Manipulation

Russ Tedrake's recent talk about the robotics/AI work at TRI is soooo good www.youtube.com/watch?v=TN1M...

It would be so nice if there was more competition for WiFi.

Unfortunately, there's a monopoly in Cambridge. Xfinity is the only fast WiFi. They have these random price hikes (a high baseline price with "promotions" that randomly expire). Their customer support is terrible.

Today marks the second time that Faà di Bruno's formula was super useful to me.
en.wikipedia.org/wiki/Fa%C3%A...
It expresses a higher-order derivative of a composition of functions and uses the Bell polynomials. It came up in a distribution theory proof for my dissertation.

Cursor tab needs to stop repeatedly trying to modify the same line. If I rejected the last three recommendations, the fourth isn't going to change my mind...

Screw theory, differential kinematics, and singularities.

These are all topics that I'm interested in.

Cursor repeated tries to delete everything in my dissertation. It really understands me.

LLMs are excellent at choosing notation for math. They tend to be very concise and elegant.

Unfortunately, they also commonly make many mistakes in distribution theory :(.

Not to brag, but Elon has lost orders of magnitude more money than I have.

The audio and video aren't great early on, but improve later in the video. It has a pretty pedagogical introduction to distribution theory and why it's relevant to differentiable rendering.

Full Program: https://2024.splashcon.org/program/program-splash-2024/ [SPLASH'24] San Gabriel - OOPSLA (Oct 24th)

I found a recording of my talk on differentiating parametric discontinuities from OOPSLA:
www.youtube.com/live/ltA6hQA...

I explain some of the math techniques (e.g., distribution theory) and PL tools (e.g., formal semantics) behind developing a language for differentiable rendering.

gpt-4o makes for a solid technical editor. It finds missing words, repeated words, and issues with parallelism. I don't know how many mistakes it didn't find and I'm sure that there were definitely some false positives.

Why is accepting/rejecting AI-generated edits to a file so buggy in VSCode? There are so many cases where it duplicates lines or text disappears.

The biggest upgrade to MIT ever: baby bananas in the banana lounge.

I put a calls to an LLM in a loop and if it gives an answer (rather than a tool call) in too few iterations, I tell it to analyze what it did and then improve the results.

Does that mean I turned a regular LLM into an ✨ LLM with reasoning ✨?