Peter Bailis @pbailis
Data and Analytics Before: @sisudata, Assistant Professor, Stanford CS bailis.org San Francisco, CA Joined August 2011-
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This is a cool paper, but @ChenLingjiao and team's recent research showed that with majority voting, performance can actually *decrease* past a certain number of agent calls. Check out x.com/chenlingjiao/s…. There's lots left to figure out how to best build compound AI systems.
This is a cool paper, but @ChenLingjiao and team's recent research showed that with majority voting, performance can actually *decrease* past a certain number of agent calls. Check out x.com/chenlingjiao/s…. There's lots left to figure out how to best build compound AI systems.
This surprised us. If you call #chatgpt multiple times and take the consensus, the quality of the answer can get worse as the # of #LLM calls increases. We explain why this happens in our new paper and also show how to estimate the optimal # of LLM calls arxiv.org/pdf/2403.02419…
This surprised us. If you call #chatgpt multiple times and take the consensus, the quality of the answer can get worse as the # of #LLM calls increases. We explain why this happens in our new paper and also show how to estimate the optimal # of LLM calls arxiv.org/pdf/2403.02419… https://t.co/s5ZP0avdUl
Missed opportunity to title this “call me, maybe”, nevertheless, a cool result!
Missed opportunity to title this “call me, maybe”, nevertheless, a cool result!
A surprising finding: a larger number of LLM calls can incur worse performance of compound AI systems! Why and what is the desired number of LLM calls? We initialize the study of scaling properties of compound AI systems both theoretically and empirically: arxiv.org/pdf/2403.02419…
Cool result: As people deploy more multi-step inference and ensembling strategies with LLMs, we found that these scale in nontrivial ways. Understanding this kind of inference strategy scaling is a natural question if you're interested in AI scaling. x.com/chenlingjiao/s…
Cool result: As people deploy more multi-step inference and ensembling strategies with LLMs, we found that these scale in nontrivial ways. Understanding this kind of inference strategy scaling is a natural question if you're interested in AI scaling. x.com/chenlingjiao/s…
Introduce lookahead decoding: - a parallel decoding algo to accelerate LLM inference - w/o the need for a draft model or a data store - linearly decreases # decoding steps relative to log(FLOPs) used per decoding step. Blog: lmsys.org/blog/2023-11-2… Code: github.com/hao-ai-lab/Loo…
Sisu is joining forces with Snowflake linkedin.com/posts/sisu-dat…
📢Excited to share my new blog post (petereliaskraft.net/blog/epoxy) about how to get transactions between almost any data stores. I'm presenting this at VLDB `23 tomorrow, so please stop by! #VLDB23
Awesome blog post by @muratdemirbas on our transactional caching work! But in defense of our paper title, it’s one you won’t forget 😉
Awesome blog post by @muratdemirbas on our transactional caching work! But in defense of our paper title, it’s one you won’t forget 😉
This is a big release: we've spent the past 3 years working on LLM pipelines and retrieval-augmented apps in my group, and came up with this rich programming model based on our learnings. It not only defines but *automatically optimizes* pipelines for you to get great results.
This is a big release: we've spent the past 3 years working on LLM pipelines and retrieval-augmented apps in my group, and came up with this rich programming model based on our learnings. It not only defines but *automatically optimizes* pipelines for you to get great results.
After a few months of testing and iteration, we're announcing AI Assist by @b12. Get high-quality drafts of entire pages, blog posts, or emails in a minute. See a demo, also in under a minute: youtube.com/watch?v=u-bIM4… Support us on Product Hunt: producthunt.com/posts/ai-assis…
After a few months of testing and iteration, we're announcing AI Assist by @b12. Get high-quality drafts of entire pages, blog posts, or emails in a minute. See a demo, also in under a minute: youtube.com/watch?v=u-bIM4… Support us on Product Hunt: producthunt.com/posts/ai-assis…
Hard to believe the systems community let TinyTOCS die!
So cool to see this game come to life: alpha.hideandseek.gg !!!!!!!!! Based on a research prototype we made a couple years back: x.com/ludaprojects/s…
So cool to see this game come to life: alpha.hideandseek.gg !!!!!!!!! Based on a research prototype we made a couple years back: x.com/ludaprojects/s…
2 years ago, our team in Google Research developed a novel technique for controllable LLMs coupled with charming gameplay that was accepted to NeurIPS ctrlgenworkshop.github.io/accepted_demos…
In 1972, "Ted [Codd] was not permitted to lead [System R, 'a prototype to test out his ideas'], and he went off to consider natural language interfaces to DBMSs." redbook.io/ch2-importantd…
I wrote a little retrospective about my experience and lessons learned from releasing Prophet as an open source project: medium.com/@seanjtaylor/a…
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Mad respect to Sentry for going full send using dots as nav icons.
Some of you noticed that megablocks is now databricks/megablocks. I gave the project to them this week and I couldn’t think of a better long-term home for it. I’m looking forward to watching it grow and seeing everyone continue to produce amazing models with it.
Congrats to my student @ChenLingjiao for having two papers cited in the White House 2024 Economic Report: HAPI and LLM shift, in chapter 7 on economics of AI. Lingjiao was prescient to start studying ML-as-a-service and did other cool work, like FrugalGPT. whitehouse.gov/cea/written-ma…
A second kid teaches you how zero-sum time truly is and how love is exactly the opposite.
Speaking of context windows, 20 minutes into an epic tantrum, my toddler stopped and asked me "why I'm crying?" lol
Want to efficiently query a vector DB while filtering on structured attributes? My student Liana Patel, together with @petereliaskraft and @guestrin, modified HNSW to do this efficiently in ACORN, to appear at SIGMOD: arxiv.org/pdf/2403.04871…
Interesting research on a pattern we think is going to become common: “compound AI systems” and which sample+filter many LLM calls Performance doesn’t monotonically improve with more calls in a simple voting system — hypothesis: +samples is better for easy, but not hard problems
It was very fun working on this project with Jared Quincy Davis, @BorisHanin, @pbailis, Ion Stoica, @matei_zaharia, @james_y_zou.
Thrilled to tie with @conor_power23 for best talk at the CIDR 2024 Gong Show!! We are now proud owners of movie posters autographed by the “King of Databases” aka Mike Stonebraker. Thank you @andy_pavlo for organizing!
Awesome to see DSPy accepted as a spotlight at ICLR!
Obligatory ICLR tweet: DSPy accepted as Spotlight. 1. This could be a notable start of a pattern at ML confs—as our metareviewer says, "refreshing to see this unconventional research style (developing programming models) at ICLR" 2. Time for a crisp thread on DSPy & what's new?
Just released ayb v0.1.6! Full release notes here: github.com/marcua/ayb/rel… Highlights include: support for web frontends, tenant isolation for databases (!!!), the client saving API tokens, user profiles, and various testing improvements and bugfixes.
[Me practicing active listening] Mom at preschool drop-off, with hazards flashing, frantically waving at me to move. Me, deliberately and in consciousness, stepping out of my car, tapping on her window: "I'm hearing you want me to move my car, is that right?'"
I am on the job market now. My research interests lie broadly in ML and data systems, with a recent focus on efficient and trustworthy ML-as-a-service and foundation model marketplace. I would love to hear about any opportunities that could be a good fit!
crazy how much this $6 box of artisanal pasta looks like kroger brand
It’s been the ride of a lifetime and I'm ready to take on my next big challenge. I've loved every moment of my 13 years at #Tableau and Salesforce. I’m glad that I got to play a part in this incredible community, and building this product. I am filled with gratitude. Thank you.
Excited to be a part of this incredibly diverse team! We're developing an open knowledge graph focusing on researchers, topics, and organizations to enhance research collaboration. Learn more about our project here: tinyurl.com/3nw48pm9.
"It all depends on your definition of open" -- Brad Smith, Microsoft
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