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‎docs/verifiable-ai-hackathon/0-onboarding-guide.mdx‎

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This guide provides all necessary steps to get onboarded for the **Verifiable AI Hackathon**. Participants will set up their **Google Cloud infrastructure**, acquire necessary **API keys**, and deploy their **Confidential Compute VMs**.
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## 1. Setup
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## 1. Initial Setup
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1. **Google Account**
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### 1.1. Google Account
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- Create or use an existing Google account
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- This account will be used for all hackathon resources
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- Create or use an existing Google account
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- This account will be used for all hackathon resources
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2. **Project Registration**
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### 1.2. Project Registration
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- Submit your email address during registration
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- The Flare Infra Team will onboard you to `google-hackathon-project`
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- Submit your email address during registration
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- The Flare Infra Team will onboard you to `google-hackathon-project`
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3. **Gemini API Key**
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### 1.3. Gemini API Key
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1. Navigate to [Get a Gemini API key in Google AI Studio](https://aistudio.google.com/app/apikey)
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2. Click on "Create API key"
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3. Select `google-hackathon-project` from the dropdown
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4. Click "Create API key in existing project"
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1. Navigate to [Get a Gemini API key in Google AI Studio](https://aistudio.google.com/app/apikey)
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2. Click on "Create API key"
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3. Select `google-hackathon-project` from the dropdown
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4. Click "Create API key in existing project"
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4. **VM Instance Creation**
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- Choose between CLI or Console setup methods below
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### 1.4. VM Instance Creation
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Choose between CLI or Console setup methods detailed in Section 2.
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## 2. VM Instance Setup Methods
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### Option A: Using gcloud CLI (Recommended)
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### 2.1. Option A: Using gcloud CLI (Recommended)
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Follow these steps to set up a GCP instance using Confidential Space with Cloud Logging.
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- `<ENV_VAR_VALUE1>`: First environment variable value
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- Add additional environment variables as needed
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### Option B: Using GCP Console
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### 2.2. Option B: Using GCP Console
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Follow these steps to set up a GCP instance using the web console.
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- Go to the [GCP Console](https://console.cloud.google.com/)
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- Click "Create Instance"
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{" "}
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<img src={CreateInstance} />
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2. **Configure Machine**
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1. Basic Settings:
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- Name: `<project-name>-<team-name>` (e.g., agent-gemini-john)
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- Region: us-west2
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- Machine Type: n2d-standard-2 (2 vCPU, 1 core, 8 GB memory)
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<img src={MachineConfiguration} />
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2. Security Settings:
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- Service account: confidential-sa
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- Access scopes: "Allow full access to Cloud APIs"
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- Confidential VM service: Enable
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- Shielded VM: Check "Turn on Secure Boot"
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<img src={Security} />
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3. OS and Storage:
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1. Click "Change"
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2. Select "Confidential Space Debug 240900"
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3. Keep other values default
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4. Click "Select"
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<img src={OsAndStorage} />
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4. Networking:
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- Enable "Allow HTTPS traffic"
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<img src={Networking} />
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5. Advanced Settings:
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1. Click "Add Item" under Metadata
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2. Add the following items:
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```bash
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tee-image-reference: <ghcr.io/john/agent-gemini:main>
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tee-container-log-redirect: cloud_logging
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```
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3. Additional API keys should be prefixed with `tee-env-`
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<img src={AddMetaData} />
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3. **Launch Instance**
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<div align="center">
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<img
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src={CreateInstance}
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alt="Create Instance Button"
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style={{ maxWidth: "80%", margin: "20px 0" }}
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/>
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</div>
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2. **Configure Machine Settings**
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a. **Basic Settings:**
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- Name: `<project-name>-<team-name>` (e.g., agent-gemini-john)
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- Region: us-west2
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- Machine Type: n2d-standard-2 (2 vCPU, 1 core, 8 GB memory)
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<div align="center">
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<img
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src={MachineConfiguration}
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alt="Machine Configuration"
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style={{ maxWidth: "80%", margin: "20px 0" }}
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/>
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</div>
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b. **Security Settings:**
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- Service account: confidential-sa
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- Access scopes: "Allow full access to Cloud APIs"
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- Confidential VM service: Enable
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- Shielded VM: Check "Turn on Secure Boot"
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<div align="center">
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<img
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src={Security}
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alt="Security Settings"
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style={{ maxWidth: "80%", margin: "20px 0" }}
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/>
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</div>
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c. **OS and Storage:**
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1. Click "Change"
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2. Select "Confidential Space Debug 240900"
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3. Keep other values default
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4. Click "Select"
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<div align="center">
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<img
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src={OsAndStorage}
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alt="OS and Storage Configuration"
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style={{ maxWidth: "80%", margin: "20px 0" }}
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/>
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</div>
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d. **Networking:**
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- Enable "Allow HTTPS traffic"
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<div align="center">
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<img
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src={Networking}
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alt="Networking Configuration"
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style={{ maxWidth: "80%", margin: "20px 0" }}
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/>
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</div>
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e. **Advanced Settings:**
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1. Click "Add Item" under Metadata
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2. Add the following items:
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```bash
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tee-image-reference: <ghcr.io/john/agent-gemini:main>
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tee-container-log-redirect: cloud_logging
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```
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3. Additional API keys should be prefixed with `tee-env-`
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<div align="center">
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<img
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src={AddMetaData}
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alt="Add Metadata Configuration"
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style={{ maxWidth: "80%", margin: "20px 0" }}
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/>
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</div>
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3. **Launch and Monitor Instance**
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- Click "Create" to start the VM
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- Monitor progress:
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1. System logs: Click "Serial Port (console)"
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2. Container logs: Click "Logging" after startup
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- System logs: Click "Serial Port (console)"
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- Container logs: Click "Logging" after startup
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<img src={FinalStep} />
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<div align="center">
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<img
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src={FinalStep}
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alt="Final Step Configuration"
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style={{ maxWidth: "80%", margin: "20px 0" }}
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/>
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</div>
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## Resource Allocation
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## 3. Resource Allocation
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The hackathon provides the following resource allocations per track:
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### Track Allocations
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| Track | Prize Share | Compute | Gemini API | BigQuery | Total |
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| ------------------ | ----------- | ------- | ---------- | -------- | ----- |
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| AI x DeFi | 35% | $250 | $100 | $400 | $750 |
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| Consensus Learning | 20% | $250 | $100 | $300 | $650 |
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**Notes:**
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**Important Notes:**
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- Total credits required: ~$3,000
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- Buffer allocation: 100% ($6,000 total)
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- Resources monitored via Billing → Budget & Alerts
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- Consumption tracked per service
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## Service Usage Assumptions
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## 4. Service Usage Guidelines
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### BigQuery Usage
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### 4.1. BigQuery Usage
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- 50% team activity at any time
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- Free tier (1 TiB) distributed equally
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- 48-hour usage period
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- Query patterns vary by track
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- Storage costs not included
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### Gemini API Usage
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### 4.2. Gemini API Usage
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- Uses Gemini 1.5 Flash pricing
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- 50% team activity rate
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- No context caching included
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- No Google Search grounding
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### Compute Resource Usage
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### 4.3. Compute Resource Usage
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- Confidential Compute: $0.123/hour per instance
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- Total hourly cost: $15.65 (125 teams)

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