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PEF CODERS, WE NEED YOU - Hackathon To Build the Tool That Exposes LLM Bias

lumaHosted on Luma

Fetched about 5 hours ago

Sunday, June 21, 2026

to Sunday, June 21, 2026

Artificial Intelligence

Event Type

in person

14

Participants

1

Est. Projects

At our last Hasbara session, Tomer Dean raised something we couldn't ignore: what if we built a dashboard that detects anti-Israel bias across LLMs - identifies the patterns, traces the sources, and gives us a real tool to push back? Lior Libman took that and said - let's build it together. So we're running a hackathon. And we need you. On June 21 we're getting a small group of technically-minded founders together at the Vine Ventures office in Sarona to do exactly that. This is a working session, not a panel. The plan: Hour one: brainstorm and lock the system architecture as a groupThen we split into teams and buildGoal: walk out with a proof of concept we can take to production and start promoting This is for founders who code, or who think in systems and want to get their hands dirty. We're keeping the group tight so every person in the room has real skin in the game. Food and refreshments courtesy of Vine Ventures. ⚠️ Bring your laptop. When: June 21, 10:00 AM Where: Vine Ventures, Sarona, Tel Aviv RSVP on Luma. Your country needs you.

Judge Accessibility

Organizer email available25/25
Student-run event15/15
Actively looking for judges25/25
Small event (120 participants)10/10
No corporate sponsors10/10
New or emerging organizer10/10
Public registration available5/5
Online format (judge from anywhere)10/10

Top signals

Organizer email available
Student-run event
Actively looking for judges

Organizers

Alex Johnson

alex@example.org

Jamie Rivera

jamie@example.org

Sam Chen

sam@example.org

Estimated Audience

Mostly Students
ExperienceStudent
OccupationStudents
Beginner Friendly
Women in Tech

Technical Focus

AI95%
Web80%
Mobile25%

Industries

Healthcare
Education
Climate

Technologies

Python
React
OpenAI

Why this estimate

  • • Hosted by a university
  • • Open to students
  • • MLH member event

Estimate inferred from event metadata, not actual attendee data.

Quality Score

Quality Score

72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
Operations12/15

Why this score

Strong organiser track record
Returning event
Well-sponsored

Missing data

Prize details
Code of conduct