Drew Farris

🎙️🎉 New pod episode is live! S2Ep3: "Evaluating Real-World Adversarial ML Attack Risks and Effective Management: Robustness vs. Non-ML Mitigations" with guests, Drew Farris and Edward Raff. 👀 Watch, listen, or read the transcript ➡️bit.ly/47BUomi #MLSecOps #ProtectAI

Thanks so much to @EdwardRaffML and @drewfarris for joining us in the studio for this conversation. Check out their paper that inspired the talk here: arxiv.org/abs/2306.09951 "You Don't Need Robust Machine Learning to Manage Adversarial Attack Risks."

@simplechris It’s a fascinating, challenging, sometimes frustrating, yet incredibly rewarding space to be in. I love it too.

It’s been well over a decade since I’ve been obsessed with search. The past few years have been such an interesting time. Technology is amazing. I could life 10 lifetimes and still not know half of what I want to be a ‘actual’ expert on. I just love it.

When AI startup discovers their RAG problems are the same old search relevance problems we've struggled with mightily for years :)

By 𝑅𝑒𝑐𝑎𝑠𝑡𝑖𝑛𝑔 𝑆𝑒𝑙𝑓-𝐴𝑡𝑡𝑒𝑛𝑡𝑖𝑜𝑛 𝑤𝑖𝑡𝘩 𝐻𝑜𝑙𝑜𝑔𝑟𝑎𝑝𝘩𝑖𝑐 𝑅𝑒𝑑𝑢𝑐𝑒𝑑 𝑅𝑒𝑝𝑟𝑒𝑠𝑒𝑛𝑡𝑎𝑡𝑖𝑜𝑛𝑠 you too can classify sequence with 1 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 𝘁𝗼𝗸𝗲𝗻𝘀! New #neurosymbolic awesomeness led by @rea1mma w @BlancheMinerva @oatesbag @icmlconf

Seconded! I am proud of the work @BlancheMinerva has done, continues to develop, and the fact @BoozAllen can support and drive value from open research.

What is the state-of-the-art for Semantic Search over text? Actual semantic *search*, not some chatbot hallucinating content that I need to go check.

@kshashi @gsingers @strandbookstore I would definitely cover things like byte pair encoding, positional embeddings, transformers, attention, reader/retriever and RLHF to name a few but the general structure still holds up pretty well. It is exciting to see the progress made over the past 10 years.

@gsingers @strandbookstore @drewfarris If you were to update this book, how much of it will you remove and how much LLM will you add? PS - I will totally buy the revised edition with LLM.

@gsingers @strandbookstore It is always fun to find a copy in the wild.

(7/7) LEACE wouldn’t be possible without @TheDavidSJ, who proved the theorem that led to this paper. I'd also like to thank our other coauthors @ravfogel @ryandcotterell @EdwardRaffML @BlancheMinerva!

Ever wanted to mindwipe an LLM? Our method, LEAst-squares Concept Erasure (LEACE), provably erases all linearly-encoded information about a concept from neural net activations. It does so surgically, inflicting minimal damage to other concepts. 🧵 arxiv.org/abs/2306.03819

“We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.” - Amara’s Law en.m.wikipedia.org/wiki/Roy_Amara

“When there is a smart person in the loop, unreliable advice [from an LLM] is better than no advice, and the advice comes much more explicitly than from carrying out a conventional search on a search engine” - Rodney Brooks rodneybrooks.com/what-will-tran…

A nice analysis of how parameters are used in transformer models. Good Sunday morning reading. lesswrong.com/posts/3duR8Crv…

OH “Hey, that’s Flea!”

Congratulations on the publication of Inside Deep Learning @EdwardRaffML! It is great to finally hold it - it’s Chonky! @ManningBooks manning.com/books/inside-d…

@Kate_MLA_SF I think this belongs on r/choosingbeggars

Come by today for the @iclr_conf #MLEvaluationStandards workshop. Also super excited that @drewfarris and I @BoozAllen received an outstanding paper award! And another for reviewing! A thread on two papers in the workshop: 🧵

Excited to share the @icmlconf 2022 Workshop on Knowledge Retrieval and Language Models knowledge-retrieval-workshop.github.io Please consider submitting! We welcome work across topics including LM grounding, open-domain Q&A, bias in retrieval, analyses of scale, transfer and LM phenomena.

List of ICML Workshops. Please add yours to this thread. ➡️Follow this list for updates. twitter.com/i/lists/126110…