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SEAL Leaderboards
✓ verifiedFree
Scale AI provides training data and evaluation platforms; major AI company.
👁 625K/mo♥ 3.0K
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GitFluence
✓ verifiedFree
Free AI helper that turns a plain-English description of a task into the matching Git command to copy and run.
Pricing
No public pricing
No public pricing
No public pricing
No public pricing
Free trial available
No public pricing
Core features
- ✦High-quality training data for AI models
- ✦Scale Data Engine for data management and labeling
- ✦Scale GenAI Platform for full-stack Generative AI
- ✦Scale Donovan for AI-powered decision-making
- ✦AI model evaluation and red teaming
- ✦RLHF (Reinforcement Learning from Human Feedback)
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- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦Enhanced Context Engineering for deep codebase analysis and adaptive memory
- ✦Intelligent Agents for autonomous planning, coding, and testing
- ✦Spec-Driven Development for clarifying requirements and automating execution
- ✦Intelligent Codebase Search and Advanced Repository Insight
- ✦Context-aware code completions and next-edit suggestions
- ✦Support for leading AI models (Claude, GPT, Gemini)
- ✦Natural-language to Git command suggestions
- ✦AI-driven command matching
- ✦Copy-ready command output
- ✦Git guides and reference
Use cases
- →Developing self-driving car AI with high-quality training data.
- →Building Generative AI applications using the Scale GenAI Platform.
- →Improving AI model performance through supervised fine-tuning and RLHF.
- →Evaluating the safety and robustness of AI models using SEAL Leaderboards.
- →Integrating enterprise data into foundation models for strategic differentiation.
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- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Delegating complex software development tasks to AI agents for autonomous completion.
- →Performing multi-file code edits and refactoring through natural language chat.
- →Gaining deep architectural understanding of a codebase to resolve issues with precision.
- →Generating unit tests, code explanations, and uncovering codebase architecture.
- →Systematically tackling software development tasks from planning to testing.
- →Find the correct Git command quickly
- →Learn Git syntax by describing a goal
- →Avoid memorizing Git flags
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