We found more optimizations. Now fitting a infinite gaussian mixture model from 0 to 0.99 ARI on 1 Billion rows and 2 columns in < 20 sec. No variational inference. No subsampling. Just good old fashioned MCMC. π€―
28.01.2025 02:14 β π 6 π 0 π¬ 1 π 0
This is Lace's successor, which is in still development. Hoping to have a demo showing scaling to trillions of records via distributed inference in couple of months.
22.01.2025 18:01 β π 1 π 0 π¬ 0 π 0
To the people out there saying we need boosted trees and neural nets because we can't be #bayesian at scale: here I am using MCMC to fit a *100 million* row Infinite Mixture Model in #rustlang in less than 30 seconds on a Macbook Pro.
22.01.2025 16:53 β π 11 π 1 π¬ 1 π 1
OpenAI Pleads That It Canβt Make Money Without Using Copyrighted Materials for Free
OpenAI is begging Parliament to allow it to use copyrighted works because it's "impossible" for the company to make money without them.
"Sorry, we can't make this technology that sucks and nobody wants and that uses enough power to blow up the moon unless we *also* steal people's shit to throw into our content woodchipper in order to produce mediocre digital particleboard out of the cumulative artbarf."
futurism.com/the-byte/ope...
20.12.2024 14:05 β π 6291 π 2105 π¬ 224 π 216
If you have a lot of people in your house that like pancakes try a Dutch baby instead. Way easier. And fancier (according to my 6yo)
22.12.2024 16:29 β π 0 π 0 π¬ 0 π 0
Making PPLs More Useful With Two New Operators | Heresy
Probabilistic programming is a counter play to black box machine learning. Probabilistic programming practitioners seek to build interpretable models of phenomena and to captuβ¦
PPLs have struggled to gain traction in industry. Conventional wisdom blames scaling. I argue that PPLs' challenges aren't about scaling at all. They're about learning. And sometimes, to go faster, we need to slow down.
heresy.ai/a-better-ppl/
#bayesian #machinelearning
19.12.2024 16:15 β π 3 π 1 π¬ 0 π 1
WRT the last post re: compile-time-generated Dirichlet process mixture models in #rustlang: we are doing a sweep of serial collapsed Gibbs on a 100k rows by 5 columns table in ~55ms on an M4 Macbook pro.
12.12.2024 21:55 β π 0 π 0 π¬ 0 π 0
For those in the thread: we're comparing against standard serial Gibbs.
We have implementations of split-merge and parallel slice in Lace. The times per-iteration and to-converge are quite different for these kernels. It's usually best to alternate as they're better at different kinds of moves.
12.12.2024 20:06 β π 2 π 0 π¬ 0 π 0
#rustlang has been an awesome choice for our probabilistic programming language backend. We've been experimenting with using declarative macros to build custom ML structures at compile time. We're seeing 3-4x inference speedups over using Vecs and enums π₯
11.12.2024 00:47 β π 6 π 0 π¬ 0 π 0
Plover Found 9 Errors in the UC Irvine AI4I Predictive Maintenance Dataset
Finding errors in the code behind the synthetic data
Found a small number of errors in the UCI ML repo AI4I synthetic predictive maintenance dataset. Cleaned version hosted on our site.
note that data arenβt erroneous per se, the processes and code behind them are. Iβve used similar techniques to find bugs in my own code
redpoll.ai/blog/errors-...
30.11.2024 14:08 β π 0 π 0 π¬ 0 π 0
Plover Demo - Try Plover in your browser
Plover is a tool that finds errors/anomalies in databases. We were able to compile bits of it to web assembly (it is written in #rustlang) so you can try it in your browser client-side (no sending your data off to some server). If you have a s CSV, it's mostly drag and drop.
21.11.2024 19:09 β π 2 π 0 π¬ 0 π 0
Professor of AI, DTAI, KU Leuven; Wallenberg Guestprofessor AASS, Γrebro University; Director http://Leuven.AI, AAAI and EurAI Fellow, Former PC Chair IJCAI, ICML, ECAI and ECMLPKDD, ERC AdG 2015 and 2023
Data scientist interested in causal inference, Bayesian statistics and data visualization.
writing about methods models and stats in evolutionary social sciences.
Engineering | Finances | Complex System Dynamics
HPC | AI | QC | DACS
Infrastructure, Construction, Energy, Defense, FinTech, BioTech.
DACS .- Dynamically Adaptive Complex Systems
Autistic. Rustation. Pythonista. Ecmascribe. Fan of deadpan or absurd humor.
https://ender.yoga/about/
Love computers and coding.
While I'm particularly passionate about Rust, it's not the only language I work with.
Recently started loving embedded programming
Recently a principal scientist at Google DeepMind. Joining Anthropic. Most (in)famous for inventing diffusion models. AI + physics + neuroscience + dynamical systems.
AI for Life Sciences at NVIDIA | trained as a scientist from JGI, UW & UC Berkeley | views are all mine
Assistant Professor at Duke in Biomedical Engineering (@dukeubme.bsky.social) and Biostatistics & Bioinformatics. Research focus on digital biomarker development. All views are my own.
aneeshsathe.com
π§ͺπ§¬π»π€π¬π¦ π©Ίππ
physician-scientist, interested in AI safety/interpretability in biology/medicine. jjanizek.github.io
Assistant Professor at Stanford. Trustworthy, deployable ML/NLP for healthcare.
Assistant Professor in Computer Science, McGill University /
Mila Quebec AI Institute. Co-Founder and Chair, Climate Change AI. MIT Tech Review "Innovator Under 35". he/him/his
applying math, computation, and machine learning to problems in chemical engineering | associate professor, Oregon State University | views mine
https://simonensemble.github.io/
BioDesign, Machine Learning, Drug Discovery | Rosenkranz Award 2021 | Dad | Polyglot | Capybarist | plissonf.github.io
Founding ingeniebio.com
ORCID 0000-0003-224
Protein and coffee lover, father of two, professor of biophysics and sudo scientist at the LinderstrΓΈm-Lang Centre for Protein Science, University of Copenhagen π©π°
autonomous science & digital molecular designer | assistant professor @cmu with @gpggrp.bsky.social | https://gpggrp.com | https://aithera.ai | h(e/im), views my own
interpretable machine learning for atmospheric and astronomical data analysis, near-IR spectra, climate tech, stars & planets; bikes, Austin, diving off bridges into the ocean.
physical oceanography π, geophysical fluid dynamics π, machine learning π€, coding climate models π, #JuliaLang π», surfing ππ½ββοΈ, horses π, dancing ππΌ, bicycles π΄π½ββοΈ
π
πNaarm-Melbourne
π‘ www.navidconstantinou.com
web @ https://argmin.xyz
interests: machine learning, ai4science, algorithms, coding
member of technical staff @ https://cusp.ai
past @ MSR, DeepMind, MPI-IS
home @ Heimbach (Gilserberg), Berlin, Europe
born @ 353 ppm
block toxicity
he/him