Get in contact with @OzzieGooen. Ill fund a continuation of what he has
2
AI Safety Atlas: a searchable directory of everyone in AI safety
ProposalGrant
Closes July 5th, 2026$4,000raised
$1,500minimum funding
$7,000funding goal
Offer to donate
17 daysleft to contribute
You're pledging to donate if the project hits its minimum goal and gets approved. If not, your funds will be returned.
Project summary
ATLAS is a searchable directory of everyone in AI safety, the people and the orgs, in one place you can actually query.
Right now it holds 754 real people and 183 real orgs. Each person has a profile, a photo, a focus area, and links. You can search and filter the whole thing instantly, by field, focus area, org.
This grant makes it comprehensive, fresh, and queryable: a weekly scraper that keeps real people and orgs current from public sources (LinkedIn, personal sites, GitHub, arXiv, the Alignment Forum), AI that drafts each profile and tags its focus area, semantic search, claim-your-profile editing, and an API.
The idea comes from Austin Chen's "Sixteen schemes for AI safety", #1 (Triplebyte for AI safety jobs) and #2 (a database of every AI safety person). Money is pouring into the field, so money stops being the bottleneck and finding the right people becomes it.
What are this project's goals? How will you achieve them?
The field is impossible to see. Recruiters can't find talent, newcomers can't find roles or mentors, people can't find collaborators, independent researchers can't find funders, and nobody can see the shape of the field, where the work is and where the gaps are. People have tried databases and org-maps, but databases rot because nobody updates a spreadsheet, and the maps show orgs, not people, and don't let you query anything.
The goal: kill the search cost for all of that at once, over real and comprehensive data, and put the global south on the map instead of treating it as an afterthought. The two questions a funder actually asks, "who do I reach out to for this role" and "who should I invite to speak on this topic", should take one search.
What "done well" means, and what I'm building toward:
Comprehensive: every relevant person and org is in it. Started with the full Manifund roster; the scraper widens it from there.
Accurate and fresh: a weekly refresh keeps it current, with provenance badges showing where each profile came from and whether it's been claimed.
Fast: a lightweight table, virtualized lists, and a CDN.
Useful: direct and semantic search, filters on every field, real Projects and Jobs tabs, and a queryable API.
Trusted: opt-out and removal from day one, claim-your-profile editing behind magic-link auth, and moderation.
Three-month plan:
Month 1: fill the data gaps so coverage is real, ship the Projects and Jobs tabs, auto-tag everyone's focus area, and turn on the weekly refresh.
Month 2: real AI matching and semantic search, claim-and-edit profiles with magic-link auth, moderation, and provenance badges.
Month 3: richer profiles, a queryable API, speed and scale (virtualized lists, CDN), polish (mobile, accessibility, SEO), and light community features.
How will this funding be used?
Three months of me building it full time, plus what it costs to scrape and run it on real data.
My time: $1500/month × 3 = $4500
AI and scraping embeddings, LLM for profiles and search, scraping compute about $1,200
Servers, database and the email service for claim-your-profile invites it's about $1,200
Domain is about $100
Who is on your team? What's your track record on similar projects?
Just me. Volunteers welcome if anyone is interested.
The best evidence I can build this is that I already built it. I designed and shipped the whole ATLAS demo alone: six surfaces (the map with live clustering of 1,020 people, a skill-similarity galaxy, a directory, live rooms, community rooms, conferences), a working match engine, and a full design system, deployed and running at aisa.nahdha.tech.
Background: around 4 years of applied ML and NLP engineering. MSc in Mathematical Sciences (AI for Science) at AIMS South Africa / University of Cape Town on a Google DeepMind Scholarship, thesis on neural reasoning for ARC-AGI. Research engineer on ARC-AGI at Peking University, Nov 2025 to Feb 2026. At Sultan Qaboos University I built a proposal-evaluation NLP system using multilingual embeddings scored against Oman Vision 2040 the same embedding and retrieval work the matching engine runs on. Hackathon wins: first in Qatar, first in Kigali, third at the Deep Learning Indaba. My interp work is public at github.com/AhMedDa1/mech-interp-journey.
And I'm the user. I work from Sudan, Rwanda, Oman, outside every AI safety hub, with no ready-made network. Finding mentors, collaborators and funding from here is exactly the problem this fixes. I'm building the thing I needed and couldn't find, for the people in the same spot.
What are the most likely causes and outcomes if this project fails?
Most likely ways it fails:
Nobody claims their profile. The scraper means the map is never empty, but if people don't come back to claim and edit, the data drifts. Fix: AI-drafted profiles make claiming nearly free, and it's built to be worth looking at, so people want to be on it.
Consent and privacy. Putting people on a public map is sensitive, and some people in this field keep a low profile on purpose. Opt-out and removal work from day one, profiles default to public-information-only, and anyone can take themselves off.
If it fails anyway the downside is small. The scraped public map stays up as a free reference, the code and match engine are reusable, and I'll know what makes people claim a profile and what matches they actually want, which is useful to whoever tries next.
How much money have you raised in the last 12 months, and from where?
$0 for this project. I paid for the demo and hosting myself.
Offers
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Comments
12
🐔
Ahmed
about 24 hours ago
@MarcusAbramovitch thanks for the pointer, I dug into Ozzie's work properly. I think we're solving different problems. His own vision doc (https://www.longtermwiki.com/wiki/E883) calls LongtermWiki "a strategic intelligence platform for AI safety prioritization" for funders and researchers asking "where should the next dollar or researcher-hour go", built around cruxes, worldviews and intervention rankings. People and orgs are minor background entities there, and he lists "community features" as a non-goal.
Connecting and matching people is exactly that, and it's the core of ATLAS: the point is the people, and getting them fast to what they need, a hire, a collaborator, a talk, funding. So I see them as complementary rather than the same thing, his data could even feed mine. I've emailed Ozzie to figure out how we can collaborate. Curious where you see the line between the two.
🐔
Ahmed
2 days ago
I've been thinking about where this goes after the directory is solid and wanted to share it here.
The bigger goal is to make ATLAS the matching layer for the field, not just a place to browse:
For hiring: a lab or recruiter posts a role and gets a ranked shortlist of people who actually fit, instead of searching. Same for new labs/startups that just want newcomers or fresh people in the field, we surface them. And the reverse, a person sees the orgs and roles that fit them.
For projects: match projects with collaborators and with funders.
Richer profiles: using the scraper, show real signal on each profile, publications and their actual work and links, so labs can see who they're looking for.
The part I'm most interested in, but it only works with the labs: a portable candidate signal. Right now, every lab runs its own screening and work tests, and every candidate redoes them from scratch. If labs want to co-design or share an assessment that lives here, ATLAS could be the top of the funnel, a candidate does it once, gets feedback on what to work on, and the lab gets a shortlist of aligned people, recently validated. The hard part is labs trusting the signal, so this is more an invitation to labs than something I build alone, and it comes after the directory is solid.
For funding: Surface fundable people and projects to funders based on their real record, to feed existing funders like Manifund.
All of this is stage two, on top of the funded plan. Curious if any of it is useful, and whether any labs or funders would want to be part of it.
🐔
Ahmed
2 days ago
I've been thinking about where this goes after the directory is solid and wanted to share it here.
The bigger goal is to make ATLAS the matching layer for the field, not just a place to browse:
For hiring: a lab or recruiter posts a role and gets a ranked shortlist of people who actually fit, instead of searching. Same for new labs/startups that just want newcomers or fresh people in the field, we surface them. And the reverse, a person sees the orgs and roles that fit them.
For projects: match projects with collaborators and with funders.
Richer profiles: using the scraper, show real signal on each profile, publications and their actual work and links, so labs can see who they're looking for.
The part I'm most interested in, but it only works with the labs: a portable candidate signal. Right now, every lab runs its own screening and work tests, and every candidate redoes them from scratch. If labs want to co-design or share an assessment that lives here, ATLAS could be the top of the funnel, a candidate does it once, gets feedback on what to work on, and the lab gets a shortlist of aligned people, recently validated. The hard part is labs trusting the signal, so this is more an invitation to labs than something I build alone, and it comes after the directory is solid.
For funding: Surface fundable people and projects to funders based on their real record, to feed existing funders like Manifund.
All of this is stage two, on top of the funded plan. Curious if any of it is useful, and whether any labs or funders would want to be part of it.
Ronak Mehta
10 days ago
Love the project idea, but the frontend site is extremely heavy; would appreciate a default/landing page that doesn't cause my fans to spin up :). Would be nice if there's a version that's literally just a table/database that can be searched/filtered directly or semantically.
Also highly recommend frontend projects prioritize a feedback button. :) Good luck!
🐔
Ahmed
11 days ago
Hi @Austin, I thought you might be interested to check this out: http://aisa.nahdha.tech -- I welcome feedback!
Austin Chen
10 days ago
@Ahmed briefly, I think this is going in an interesting direction, but I'm not as interested in a fancy world map thing; like Ronak says, a version that's just a plain table or db (and maybe with a straightforward API or sth) would be useful to answer questions I have, which are often of the shape "who might I reach out to hire for a role at Mox" or "who should I invite to speak at this conference".
I think being quite comprehensive is important -- like, knowing that all the relevant orgs and people are included would be quite helpful. Right now there's only 1k people on there and basically no people who I would think are relevant (eg the Manifund regrantors).
https://www.longtermwiki.com/ is a thing to look at for inspiration, perhaps.