Javier Burroni

@jburroni.bsky.social

“Machines take me by surprise with great frequency” A. M. T.

Wednesday El Niño update - Sea surface temperature anomalies continue to steadily rise in the key Niño 3.4 monitoring area, which also remain at record high levels for this time of year. Over the last week, there has been a general warming across the central Pacific. Data from NOAA OISSTv2.1. 🌊

Line graph time series of daily sea surface temperature anomalies in the Nino3.4 region. Years are shown from 1982 to 2025 in shades of blue to light yellow, and 2026 is shown in red. Climatologically, the largest anomalies are during the boreal winter in terms of magnitude. Data is from OISSTv2.1. 
Map of July 21, 2026 average sea surface temperature anomalies in the ENSO monitoring regions. Data is from NOAA OISSTv2.1 with anomalies relative to a 1991-2020 baseline.Graphic showing the 1-week change in sea surface temperature anomalies across the tropical eastern Pacific Ocean. Data is from NOAA OISSTv2.1

An important reason to fix reviewing (solution is simple, by the way: phase out double blind) is to reduce the whole "If it were not for rectangular-headed reviewers, we were winning the Nobel Prize. Scholarship is dead, etc." shtick. Tired of this every cycle.

I am increasingly getting comfortable with the idea that estimation and uncertainty quantification can be treated in quite different ways, which would once have been quite strange to me.

I’m finding that GPT-5 with agent mode is really good for doing quick literature reviews. For example: “Make a report on how people use the Gauss-Newton approximation to the Hessian in VI.”

I ran the following experiment: for each person in the errata, I asked gpt to search for other books in which they appear. I learned about "Bayesian Filtering and Smoothing". Ended up buying it. I'm very impressed by the complexity of the query and the difference in performance –Claude found nothing

Bild
Javier Burroni@jburroni.bsky.social · 11mo ago

Interesting feeling: I'm reading a book and, on the errata page, I see many acquaintances' names. Feels like I'm late to the party. (Clearly one I should’ve read earlier.)

Far less focus on consumer product feature, and much more on its development as an enabling technology for industrial automation and robotics. Take a snapshot of one of their plans, for instance. For them integrating AI into industrial production, and building [+]

Bild

Unfortunately, our submission to #NeurIPS didn’t go through with (5,4,4,3). But because I think it’s an excellent paper, I decided to share it anyway. We show how to efficiently apply Bayesian learning in VLMs, improve calibration, and do active learning. Cool stuff! 📝 arxiv.org/abs/2412.06014

Post-hoc Probabilistic Vision-Language Models

Vision-language models (VLMs), such as CLIP and SigLIP, have found remarkable success in classification, retrieval, and generative tasks. For this, VLMs deterministically map images and text descripti...

arxiv.org

Just completed the formalization of the Kraft-McMillan lemma in lean. Quite an interesting experience and feeling: it is complete (there is nothing missing and all is correct), but clearly not finished (things can be made nicer). It took me quite a lot (1.3kloc). I hope I can get faster.🤖 helped!

welcome to the future, now your error-prone software can call the cops (this is an Anthropic employee talking about Claude Opus 4)

Tweet by Sam Bowman
@sleepinyourhat
If it thinks you're doing something egregiously immoral, for example, like faking data in a pharmaceutical trial, it will use command-line tools to contact the press, contact regulators, try to lock you out of the relevant systems, or all of the above.

I'm speaking at Programming Language Implementation Summer School (PLISS) next week. Let's see if I can get the attendees to implement a tiny version of Boxer: dl.acm.org/doi/pdf/10.1... It is a fun example of how interactive programming *systems* can do more than *languages*!