News from the AI & ML world
DeeperML
@www.marktechpost.com
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The Allen Institute for AI (Ai2) has launched OLMoTrace, an open-source tool designed to bring a new level of transparency to Large Language Models (LLMs). This application allows users to trace the outputs of AI models back to their original training data. This data traceability is vital for those interested in governance, regulation, and auditing. It directly addresses concerns about the lack of transparency in AI decision-making.
The tool is available for use with Ai2’s flagship model, OLMo 2 32B, as well as the entire OLMo family and custom fine-tuned models. OLMoTrace works by identifying long, unique text sequences in model outputs and matching them with documents from the training corpus. The system highlights relevant text and provides links to the original source material, allowing users to understand how the model learned the information it uses. The technology identifies long, unique text sequences in model outputs and matches them with specific documents from the training corpus.
According to Jiacheng Liu, lead researcher for OLMoTrace, this tool marks a pivotal step forward for AI development, laying the foundation for more transparent AI systems. By offering greater insight into how AI models generate their responses, users can ensure that the data supporting their outputs is trustworthy and verifiable. The system supports OLMo models including OLMo-2-32B-Instruct and leverages their full training data—over 4.6 trillion tokens across 3.2 billion documents.
References :
The tool is available for use with Ai2’s flagship model, OLMo 2 32B, as well as the entire OLMo family and custom fine-tuned models. OLMoTrace works by identifying long, unique text sequences in model outputs and matching them with documents from the training corpus. The system highlights relevant text and provides links to the original source material, allowing users to understand how the model learned the information it uses. The technology identifies long, unique text sequences in model outputs and matches them with specific documents from the training corpus.
According to Jiacheng Liu, lead researcher for OLMoTrace, this tool marks a pivotal step forward for AI development, laying the foundation for more transparent AI systems. By offering greater insight into how AI models generate their responses, users can ensure that the data supporting their outputs is trustworthy and verifiable. The system supports OLMo models including OLMo-2-32B-Instruct and leverages their full training data—over 4.6 trillion tokens across 3.2 billion documents.
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References :
- the-decoder.com: The Allen Institute aims to decode language model behavior with its new OLMoTrace tool.
- Ken Yeung: Ai2’s OLMoTrace Tool Reveals the Origins of AI Model Training Data
- AI News | VentureBeat: What’s inside the LLM? Ai2 OLMoTrace will ‘trace’ the source
- THE DECODER: Everyone can now trace language model outputs back to their training data with OLMoTrace
- MarkTechPost: Allen Institute for AI (Ai2) Launches OLMoTrace: Real-Time Tracing of LLM Outputs Back to Training Data
- www.marktechpost.com: Allen Institute for AI (Ai2) Launches OLMoTrace: Real-Time Tracing of LLM Outputs Back to Training Data
Classification:
- HashTags: #LLMTransparency #OpenSourceAI #Ai2OLMoTrace
- Company: Ai2
- Target: AI Developers
- Product: OLMoTrace
- Feature: LLM Transparency
- Type: AI
- Severity: Informative