Robert Nowak
rdnowak.bsky.social
Robert Nowak
@rdnowak.bsky.social
770 followers 110 following 41 posts
Director of the Center for the Advancement of Progress
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Yes. Just write your thoughts in a rough and unpolished form, say rough paragraphs that contain terse points you want to make. then let 'er rip
Section 7 is a wonderful description of the process they went through.
something just isn't fully clicking. if you look at total yards and time of possession, they should have blown them out. well, better anyway to peak later in season, so let's hope that's what happens (like two seasons ago)
Packers get the win, but it wasn't pretty.
Thanks for participating and presenting your work!
Honored to have participated in this amazing event and meet great people and their work in the data science field.
Google promotes box shirts too
Reposted by Robert Nowak
Announcing the first workshop on Foundations of Language Model Reasoning (FoRLM) at NeurIPS 2025!

📝Soliciting abstracts that advance foundational understanding of reasoning in language models, from theoretical analyses to rigorous empirical studies.

📆 Deadline: Sept 3, 2025
“the only way to predict or to control the functioning of such systems is by an intricate system of charms, spells, and incantations”
See you there!
UChicago is thrilled to host #MMLS2025 in just a few days!
We can’t wait to welcome the ML community to campus.

Huge thanks to our amazing sponsors:
@schmidtsciences.bsky.social
University of Chicago Department of Computer Science
@dsi-uchicago.bsky.social
Invenergy

🧵(1/3)
More likely midges. The truest sign of a healthy ecosystem
Looking forward to a great MMLS!
The Midwest Machine Learning Symposium will happen in Chicago on June 23-4 on the University of Chicago campus (midwest-ml.org/2025/). We have an amazing lineup of speakers:@profsanjeevarora.bsky.social from Princeton, Heng Ji from UIUC, Tuomas Sandholm from CMU, @ravenben.bsky.social from UChicago.
This is collaboration with Ziyue Luo, @shroffness and @kevinlauka
SIEVE improves upon existing quality filtering methods in the DataComp-LM challenge, producing better LLM pretraining data that led to improved model performance.
This work is part of Jifan's broader research on efficient ML training, from active learning to label-efficient SFT for LLMs.
Why does this matter? High-quality data is the bedrock of LLM training. SIEVE enables filtering trillions of web data for specific domains like medical/legal text with customizable natural language prompts.
SIEVE distills GPT-4's data filtering capabilities into lightweight models at <1% of the cost. Not just minor improvements - we're talking 500x more efficient filtering operations.
🧵 Heard all the buzz around distilling from OpenAI models? Check out @jifanz's latest work SIEVE - showing how strategic distillation can make LLM development radically more cost-effective while matching quality.
Maybe Trump should have read my mom's book: "For the first six weeks, the embryo, whether XX or XY, coasts along in sexual ambiguity." p. 25
Reposted by Robert Nowak
Task vectors are akin to punchcards: you feed them to your LLM and it implements specific tasks, without in-context demonstrations. Liu's new paper examines at what scale, where in the network and when during training do they emerge, and how to encourage their emergence.

arxiv.org/pdf/2501.09240
p.s. we don't know for sure if I said this or not
Is the solution treating everything electronic as "fake"?
Maybe?