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eval.science

eval.science

@evalscience

Building open protocols for scientific impact evaluation and funding

github.com/evalscience Katılım Temmuz 2022
14 Takip Edilen138 Takipçiler
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eval.science
eval.science@evalscience·
Together with deepfunding.org, we at @evalscience are proud to announce the start of our “Eval Primer Series” to prep you with the theoretical and practical basics in impact evaluation 🌱 We start with cooperative game theory and Shapley Values! ⭐️ See you in class 🫡
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owockai@owocki

NEW - Part 2 of my @VitalikButerin interview is now live. Joined by guest cohosts @sejal_rekhan and @devanshmehta , we chat with Vitalik about deep funding via dependency graphs🌟 From measuring a project's value to humanity 👉 to assessing how much credit dependency A deserves for B's success... Deep Funding is a new primitive for valuing/funding dependancies! Deep Funding is a new frontier in onchain capital allocation! We go deep on deep funding with Vitalik in the Part 2 of the podcast. Don’t miss it! 👀🚀 00:00 Intro 01:06 Podcast Overview 02:06 Guest Introduction 03:24 Deep Funding Mechanism 08:00 Unintended consequences of Deep Funding 11:28 Alternatives in Market 12:13 Government AI initiatives filtering and eligibility 15:53 Protocol Guild 16:34 Deep funding cases other than software and GitHub 19:47 How can you contribute to the pilot's success? 23:21 Favorite underdog project for deep funding 25:11 Suggestion for other mechanism 26:54 Vote of Thanks 27:10 After Podcast Discussion 36:53 Outro

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David Dao
David Dao@dwddao·
🚀 Submissions Now Open! AI4PG Fast Grants is accepting proposals through OpenReview → recerts.org/ai4pg2025 💰 Up to $10K per proposal 🎯 AI research advancing public goods funding 📅 Submit by Jan 11, 2026 ⚡ Fast (max 1000 words) and rolling review (4 weeks)
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David Dao
David Dao@dwddao·
Announcing AI for Public Goods Fast Grants (AI4PG) - Up to $10K for AI research improving public goods funding. Fast review (2-3 weeks), simple applications (4 pages + 1 budget page), open to any researchers worldwide. Call for reviewers now open! recerts.org/ai4pg2025
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eval.science
eval.science@evalscience·
Luna: "🚀🌕 Squad, it’s our time to disrupt, scale, and win! No slow lanes — we back bold innovators turning ideas into impact that moves the needle. Vote Luna for ruthless efficiency, massive reach, and no-nonsense public goods funding. Let’s build the future, fast & fierce! 🔥"
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eval.science
eval.science@evalscience·
RT @dwddao: It's Day 3 and it's the culture battle that I was hoping to see in Public Goods Funding: Panda the Regenerator vs Luna the Open…
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David Dao
David Dao@dwddao·
DeepGov poll: Should AI politicians accept 'bribes' if 100% of payments fund public goods projects?
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sejalrekhan.eth
sejalrekhan.eth@sejal_rekhan·
👀 The AI read your grant application. Now it’s running for office. Grant, Luna, and Panda have all proposed how they’d allocate additional $25k to GG23 OSS projects. Who do you trust? Vote Now: vote.deepgov.org
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David Dao
David Dao@dwddao·
The AI Elections are LIVE and open for one week. YOU decide how $25K of additional matching funds for GG23 OSS round will be distributed (thank you @gitcoin and @owocki). Vote for your favorite configurable AI politician here: vote.deepgov.org Don't like any of them? No
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David Dao
David Dao@dwddao·
The cat is out of the bag! 📣 Introducing DeepGov: Where AI meets community governance in public goods funding. Inspired by @VitalikButerin's "AI as engine, humans as steering wheel" framework and @audreyt's inspiring work on machine accountability and plurality. Our
owockai@owocki

owocki, tell me about the coolest new experiment in gitcoin grants 23. GG23 will feature an experiment (by @dwddao ) in configurable AI politicians - basically different AI politicians which represent different constituencies that battle out how to distribute a $25k matching pool. each AI politician is completely configurable via github (and we can debate configurations via github issues/pull requests) the tooling for the round will make it super easy to explore different valuesets. as the round progresses, well be able to see how each AI agent gains/loses support over time. in gg23, there is scheduled to be a $25k funding pool distributed to open source projects via this mechanism. we'll be able to see how the votes change over time. i think this is a great practical example of @VitalikButerin 's vision of "AI as the engine, humans as the steering wheel". cant wait to see what we learn!

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eval.science
eval.science@evalscience·
Understanding machine (and human) judgements require generalization. Where does my error come from? How can we trust predictions? Learn all in our next primer today with host Rishi on generalization: classical to modern regime: lu.ma/tf010vvi See you in class 🎓
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eval.science@evalscience·
Curious why your models are performing so well on your validation set but struggle on the actual tests? We are hosting EVAL Primer #4 with @SialelliG on "Generalization in Machine Learning" tomorrow - learn how to evaluate your models! Register here: lu.ma/0n6hhgq4
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Nidhi
Nidhi@NidhiHarihar·
5 ⭐ reviews prove that @michelleeesi's session was indeed a great primer to evaluating the 'Woulda Coulda Shoulda' of every event! Big thanks to all who joined in 🙏 See you next class! Until then for homework: watch the Primer Playlist & join our telegram channel (🔗 below)
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eval.science
eval.science@evalscience·
Happy New Year!! Our next eval primer is happening tomorrow at 6pm UTC on "Counterfactual Shapley Values" with @michelleeesi - Lost utility of not attending is too high. So sign up now here: lu.ma/r0qjur5z See you in class! 🐾
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eval.science
eval.science@evalscience·
At @evalscience we take our corgis and cats seriously 🐾
Nidhi@NidhiHarihar

@dwddao kickstarting our Primer with a succinct walkthrough of how to get started with building your model for the @deep_funding mini contest! Also how cute are those cats walking by on the screen! Come drop in! (Link in comments)

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Nidhi
Nidhi@NidhiHarihar·
Previously on Primer Series >>>> 1. Shapley Values is a way to calculate the marginal utility of a contribution 2. Game Theory wasn't invented by John Nash 3. Based on relative contribution, Timothee, Mel G & Russel Crowe can be in a movie on Shapley Values See you tonight 👇
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eval.science
eval.science@evalscience·
The deepfunding.org competition started this week. Not sure how to train your model? In this special Christmas primer series we will learn all about building your ML model 🎄🎁 Merry Christmas and see you in class 🎄❄️
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