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Live at St. Mark's School with Dr. William Dunham discussing Leonhard Euler, the "Master of Us All". He was almost exact contemporary with Benjamin Frankin

Happy to share the preprint for our #icassp2021 paper "Error-driven Pruning of Language Models for Virtual Assistants" w/ the Siri Speech team at Apple – arxiv.org/abs/2102.07219

Andrej Karpathy We've built an openly available, massive text dataset with 800GB: pile.eleuther.ai We're also building a massive image and image-text dataset that are open with each image having either CC0, CC-BY or CC-BY-SA license. I'm truly excited for the future of open datasets!

An early draft of the machine learning interviews book is out 🥳 The book is open-sourced and free. Job search is a stressful process, and I hope that this effort can help in some way. Contributions and feedback are appreciated! huyenchip.com/ml-interviews-…

Proud to share the webpage for the brand-new Microsoft Research Lab Amsterdam where we will work on molecular simulation for green technology and healthcare. We are hiring deep learning for computational chemistry researchers and engineers. microsoft.com/en-us/research…

Most of the #trec2021 baselines on the MS MARCO V2 data are now available in Anserini as reproducible regression tests. Enjoy! github.com/castorini/anse…

Just discovered Hedy, a gradual programming language. It's a new idea on how to teach programming to beginners. Very cool! hedycode.com Hedy

If you are into Information Retrieval and Search, you should join this 😉 x.com/i/communities/…

We've built THE list of VC lists. 23 databases. 220k+ investors. 100% free. Please like + RT this tweet to help a founder out. Aaaand... here we go 👇

1) What is LaMDA and What Does it Want? cajundiscordian.medium.com/what-is-lamda-… 2) Interview cajundiscordian.medium.com/is-lamda-senti… What can be said with confidence imo is that things are about to get a lot weirder because models appear to follow smooth scaling laws and data+model size can still plenty grow.

The times are a-changin’? Google for general search, and TikTok for lifestyle search? A more elaborate version of this thread would make an interesting IR paper.

The misconception that there is no sound in space originates because most space is a ~vacuum, providing no way for sound waves to travel. A galaxy cluster has so much gas that we've picked up actual sound. Here it's amplified, and mixed with other data, to hear a black hole!

Still going through the #SIGIR2022 proceedings. Here is another gem: a neat workflow of which metric to choose for which ranking problem. From "Ranking Interruptus: When Truncated Rankings Are Better and How to Measure That" by Enrico Amigó et al. PDF: damianospina.com/publication/am…

Code search seems an interesting area for IR w/ a mix of challenges from (micro-)blog and desktop search: rapid updates, and little internal structure (e.g., links). Do we have datasets for code search? theregister.com/2023/02/07/git…

Just in time for the holidays, we are releasing some new software today from Apple machine learning research. MLX is an efficient machine learning framework specifically designed for Apple silicon (i.e. your laptop!) Code: github.com/ml-explore/mlx Docs: ml-explore.github.io/mlx/build/html…

This is the nerdiest article on org design I have ever read. Inject it straight into my brain! codahale.com//work-is-work/

New reqs for low to high level researcher positions: jobs.careers.microsoft.com/global/en/job/… , jobs.careers.microsoft.com/global/en/job/…, jobs.careers.microsoft.com/global/en/job/…, jobs.careers.microsoft.com/global/en/job/…, with postdocs from Akshay and Miro Dudik x.com/MiroDudik/stat… . Please apply or pass to those who may :-)

"What Matters In Transformers?" is an interesting paper (arxiv.org/abs/2406.15786) that finds you can actually remove half of the attention layers in LLMs like Llama without noticeably reducing modeling performance. The concept is relatively simple. The authors delete attention

Making LLMs run efficiently can feel scary, but scaling isn’t magic, it’s math! We wanted to demystify the “systems view” of LLMs and wrote a little textbook called “How To Scale Your Model” which we’re releasing today. 1/n

Today in Nature: our research on world and human action models (WHAM) - generative ai models of video games, aimed towards supporting game creatives in gameplay ideation : nature.com/articles/s4158… - huge congrats to everyone who made this happen, I couldn't be more proud 🥳