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NVIDIA Spark Hack: Seattle

lumaHosted on Luma

Fetched about 21 hours ago

Saturday, August 15, 2026

to Sunday, August 16, 2026

•

2 days long

Artificial IntelligenceData ScienceSocial Impact

Event Type

in person

62

Participants

5

Est. Projects

See. Do. Spark. Build AI that perceives the world, takes autonomous action, and pushes the limits of what's possible—all running on DGX Spark. NVIDIA is bringing the Spark Hack Series to Seattle. This event brings together frontier builders, applied ML engineers, systems thinkers, and startup teams to explore what's possible when vision AI, agentic workflows, and open models meet high-performance local compute. Whether you're building systems that see, systems that act, or something no one's thought of yet—bring it. We'll provide every team with an Acer Veriton GN100—powered by the NVIDIA GB10 Grace Blackwell Superchip—to use throughout the weekend. ✏️ How to Participate This hackathon is limited to a maximum of 35 teams. Once we reach capacity, additional applicants will be placed on a waitlist and notified if a spot becomes available. Application Guidelines: You must be able to attend the event in person.Team Size: Minimum 3 members, maximum 5 members.Priority: Full team applications will be prioritized over individual applications. We highly encourage you to form and apply as a team.Individuals: If you apply as an individual, team formation will happen the first day of the event. If accepted, you will be required to compete with your assigned team. 🔥 Challenge Tracks Teams can use any publicly available open data as long as the problem you're solving is real. The City of Seattle open data portal is a great starting point, but you're not limited to it. Each track defines how your AI works, not what problem it solves—teams are free to tackle any real-world challenge through the lens of their chosen track. 👀 1. See Focus: AI that understands the physical world. The Goal: Build systems that process visual data—cameras, video streams, images, satellite imagery, maps—to detect, classify, or respond to what's happening in real space. Teams in this track will work with NVIDIA's VSS (Visual Search and Summarization) skills to build perception-first applications. 💪🏻 2. Do Focus: AI that plans, acts, and gets things done. The Goal: Build autonomous systems that don't just answer questions—they take action. Multi-step reasoning, tool use, API calls, data retrieval, decision-making across sources. This track is built for long-running agentic workflows that orchestrate across multiple tools and data sources. 🧨 3. Spark Focus: AI that surprises us. The Goal: No constraints on modality or approach. Build something generative. Create a digital twin. Remix the tracks above. The only rule: build it on the Spark and make us wish we'd thought of it first. 💰 What You Can Win Qualifying submissions, depending on the unique track requirements, are eligible to win the following and more: Acer Veriton GN100Brev creditsInvestor meetingsSocial media amplification ​📓 Preparation Resources Start Building on DGX Spark: Find instructions and examples to run AI workloads on the NVIDIA GB10 Grace Blackwell Superchip.NVIDIA Build Model Endpoints: Access low-latency, high-accuracy endpoints designed for agentic systems.NVIDIA VSS Spark Playbook: Deploy NVIDIA's Video Search and Summarization (VSS) AI Blueprint to build intelligent video analytics. NVIDIA Privacy Policy: https://www.nvidia.com/en-us/about-nvidia/privacy-policy/

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