Adam L reposted
New working paper with @corymccartan.com on the Gaussian Process limit of BART! (Bayesian Additive Regression Trees... not the Bay Area Rapid Transit sadly) arxiv.org/abs/2607.28844
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Adam L
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Directory member with public evidence across AI business, AI research.
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Data Scientist. Poli sci PhD. Cyclist (Gravel, MTB, road). Bayes, causal inference, etc. Also: cats, food opinions. Views & opinions my own. Not investment advice. He/him
What they're sharing
Seeing the Forest for the Trees: The Gaussian Process Limit of BART arxiv.org
View on Bluesky →
Bounding Treatment Effects by Pooling Limited Information across Observations arxiv.org
View on Bluesky →
Episode 193 - Is AI Coming for Our Jobs?! podcasts.apple.com
Causal Inference with Missing Exposures and Missing Outcomes arxiv.org
Does intelligence need a hard cap? platformer.news
probml.github.io
From Frequency to Meaning: Vector Space Models of Semantics | Journal of Artificial Intelligence Research jair.org
“Probabilistic machine learning”: a book series by Kevin Murphy probml.github.io
Articles & links
Adam L reposted
"Bounding Treatment Effects by Pooling Limited Information across Observations" Link: arxiv.org/abs/2111.05243 Partial pooling applied to partial identification! Cool idea. R package: cran.r-project.org/web/packages... polisky 📉📈 #stats
A really interesting discussion of AL (LLMs) for athletic coaching, from experienced coaches. Their take: the training plans it gives you are good, but as w/many domains, you'll get the most out of it if you have some background knowledge. Overall they're positive, but with ca…
This is a very cool looking paper, but the title ("Causal Inference with Missing Exposures and Missing Outcomes") is funny to me: it sounds like you can estimate treatment effects when you're missing both exposures and outcomes for the same observation. Paper: arxiv.org/abs/25…
Ultimately, I think the Bsky user base's hostility towards AI researchers is a massive own goal. Sure, you kept them off here, but instead they're on X, marinating in far-right propaganda, which is a significantly worse outcome overall! (src: www.platformer.news/does-intelli...)
AI Weekly's analysis
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- Lab executives at The Curve conference in Berkeley privately floated capping how intelligent future large language models can become, Platformer reports.
- Anthropic CEO Dario Amodei has publicly called for a 'speed limit' on recursive self-improvement, one mechanism discussed at the conference.
- No enforcement mechanism exists for such caps, and the current US government opposes them, even after labs signed a 'morally binding' accord with the president.
Read full analysis →
If you read Kevin Murphy’s 2012 book “Machine Learning: a Probabilistic Perspective,” an encyclopedic tome for ML, he devotes only one chapter to neural net methods (at the end). NNs were basically seen as curiosities! (Free via author: probml.github.io/pml-book/boo...)
similarly, if you read this 2010 article on pre-NN vectorization, vectors are basically curiosities - they're interesting, but not that effective: www.jair.org/index.php/ja... It's a great article, because it's *right* before NNs changed everything.
The newer versions, released in 2022 & 2023, have much more NN/DL stuff, because the combination of GPUs, Cuda, and Tensorflow was a game-changer! There was no longer a need to calculate gradients by hand, and optimize code manually.
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What if the AI doesn't want to kill us, and instead, because it was (effectively) trained on the internet, just wants to see cute animals? Seems like the best bet would be adopting a cat.
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