Marco

But not all is bad: the addition of the 5th review brought the total length of the reviews on this paper to just above the average length of the reviews that I wrote for other papers.

/s

I'm crashing out y'all.

Our #AAAI2026 paper just got a last-minute review added to it (2 days before the rebuttal deadline and after we had already written our rebuttal) that also incredibly low quality.

Unclear how we are expected to provide rebuttals in situations like this with only 2500 characters total.

#ML

☕ The Pacific Northwest isn’t just known for coffee! Come connect, learn, and get inspired over three days of talks and tutorials at PyData Seattle 2025, Nov. 7-9 at Bellevue College. Be sure to check out the brand new schedule!! pydata.org/seattle2025

I’ll be at PyData Seattle talking about AI red teaming with PyRIT. Looking forward to chatting about everything Python and/or AI safety & security!

Forget kei truck coffee stands, I want a Jimny coffee stand.

www.instagram.com/p/DPqU7VyCD_N

This is so sick.

Next up, Toki Pona - Rust hybrid.

The number of languages in the world just got a lot higher! At least constructed ones.
Meet ConlangCrafter - a pipeline for creating novel languages with LLMs.
A Japanese-Esperanto creole? An alien cephalopod color-based language?
Enter your idea and see a conlang emerge. 🧵👇

Have you considered using the monitor as a desk?

On a more serious note, this is a real recurring problem I have with desks that are within my budget. If I had 5k for a rock solid desk with no wobble, I'd do it in a heartbeat.

Rate my setup.

(It's all coming together)

It actually did the misreading thing twice and both were really cut-and-dry wrong. Like it said (paraphrasing) "you wrote <this mathematical statement> on line X" and then we looked at line X and it's almost what we wrote, but with a small typo that changes the meaning completely.

The 6th was a notational thing that we overlooked in some pseudocode but is present in our actual experiments and in the main body of the paper. Easy 2 character fix in LaTeX.

No matter what the reviewer guidelines say, I am sure this will negatively impact our paper since we can't really rebut it (both by the rebuttal guidelines and the rebuttal length constraints).

The AI review for my AAAI paper made 6 concrete technical claims in the weakness section. 5 of them are 100% verifiably wrong.

Ranging from as bad as literally misreading the text (evidenced by it copy-pasting the text in the review but with a typo) to fundamentally misunderstanding an algorithm.

Rate my setup

Machine Learning / AI Internships - Jobs - Careers at Apple Apply for a Machine Learning / AI Internships job at Apple. Read about the role and find out if it’s right for you.

Our Responsible AI team at Apple is looking for spring/summer 2026 PhD research interns! Please apply at jobs.apple.com/en-us/detail... and email rai-internship@group.apple.com. Do not send extra info (e.g., CV), just drop us a line so we can find your application in the central pool!

This is my only cool, non-trivial one. How to dispatch on types with the same UnionAll but not necessarily the same eltype, without knowing the types ahead of time.

Like an `f` such that:

x = B{Int64}()
y = B{Float32}()
z = C{Int64}()

f(x, y) # does something
f(x, z) # fails
f(y, z) # fails

MIT Julia Lab: looking for postdoctoral researchers in #julialang open source software development, scientific machine learning (#SciML), and systems biological / pharmacological modeling (#QSP) for research in equation discovery for large stiff systems.

julia.mit.edu/projects/#po...

I think speedrunning is one of the coolest DL challenges that are immediately accessible to anyone with a GPU.

TBH I've just been clicking through @workspaces.bsky.social and seeing what everyone has. Idk how all these people are shelling out for the Apple Studio lol.

What monitors do you all recommend for a home office? Mostly for coding but some gaming (not a fan of curved monitors for gaming). 32-34" with a budget of ~$550 (a bit flexible).

Considering the Samsung M70D and _maybe_ the LG 32UN880-B (this is a bit out of the price range).

if you're interesting in gaining a better intuition for how llms behave at inference time, you should try logitloom🌱, the open-source tool i made for exploring token trajectory trees (aka looming) on base and instruct models! more info in thread

🌱 vgel.me/logitloom
💻 github.com/vgel/logitloom

Hi all,

Georgia Tech is holding its 2nd Summit on Responsible Computing, AI, and Society October 28-29th in Atlanta.

rcais.github.io

Our speakers and schedule is set. It's going to be great!

If you are planning to be in Atlanta and want to join us, registration is now open on the website.

Computer Science is no longer just about building systems or proving theorems--it's about observation and experiments.

In my latest blog post, I argue it’s time we had our own "Econometrics," a discipline devoted to empirical rigor.

doomscrollingbabel.manoel.xyz/p/the-missin...

(repost welcome) The Generative Model Alignment team at IBM Research is looking for next summer interns! Two candidates for two topics

🍰Reinforcement Learning environments for LLMs

🐎Speculative and non-auto regressive generation for LLMs

interested/curious? DM or email ramon.astudillo@ibm.com

The Turing Language Turing.jl is a probabilistic programming language and Bayesian modelling framework for the Julia programming language.

Oh, probabilistic programming is another really great related use case.

For example, Turing.jl

Find my students and collaborators at COLM this week!

Tuesday morning: @juand-r.bsky.social and @ramyanamuduri.bsky.social 's papers (find them if you missed it!)

Wednesday pm: @manyawadhwa.bsky.social 's EvalAgent

Thursday am: @anirudhkhatry.bsky.social 's CRUST-Bench oral spotlight + poster

GitHub - SciML/NeuralPDE.jl: Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation - SciML/NeuralPDE.jl

Imo the best deep learning use case in Julia is physics informed neural networks, which fits in very nicely with he original motivating fields for Julia.

But I'm a bit out of the loop. I haven't used Julia seriously since ~2023 (for various reasons; I'm still a big fan).

Of things to contribute to? Or use cases?

I wouldn't for anything serious, but it is a cool language.

One thing that I think it is really nice for is getting serious open-source contributions under your belt. Since the ecosystem is so much smaller, there is a lot of accessible work to be done (whereas PyTorch is very hard to break into).