Fiddler AI is a platform for AI observability and security that enables monitoring, explanation, and analysis of LLM applications and ML models. It provides actionable insights, model monitoring, and responsible AI practices to enhance AI governance and mitigate risks.
To use Fiddler AI, start by requesting a demo or exploring the resource library for guides. Implement the observability tools in your AI applications to monitor and analyze models effectively.
More Contact, visit the contact us page(https://www.fiddler.ai/contact-sales?utm_source=toolify)
Fiddler AI Company name: Fiddler AI .
More about Fiddler AI, Please visit the about us page(https://www.fiddler.ai/about?utm_source=toolify).
Fiddler AI Pricing Link: https://www.fiddler.ai/pricing?utm_source=toolify
Fiddler AI Youtube Link: https://www.youtube.com/@FiddlerAI
Fiddler AI Linkedin Link: https://linkedin.com/company/fiddler-ai
Fiddler AI Twitter Link: https://x.com/fiddler_ai
Fiddler AI Github Link: https://github.com/fiddler-labs
Basic Plan
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Introductory plan for small teams.
Enterprise Plan
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Comprehensive plan for large organizations with extensive needs.
For the latest pricing, please visit this link: https://www.fiddler.ai/pricing?utm_source=toolify
Social Listening
Fiddler Guardrails for Safeguarding LLM Applications
The Fiddler Trust Service includes low-latency guardrails to moderate LLM applications for hallucination, safety violations, and prompt injection attacks. In this chatbot demo, you can see how Fiddler Guardrails quickly and proactively reject malicious inputs like jailbreak attempts, ensuring the integrity of LLM responses without needing to reach the underlying model. ✦ Get a customized demo: https://bit.ly/fiddler-demo ✦ https://www.fiddler.ai https://www.linkedin.com/company/fiddler-ai/ https://twitter.com/fiddler_ai
LLM-based Embedding Monitoring
Learn how to track the performance of LLM-based embeddings from OpenAI, Cohere, Anthropic, and other LLMs by monitoring drift using Fiddler. Visit Fiddler.ai for more information.
AI Explained: AI Safety and Alignment
Large-scale AI models trained on internet-scale datasets have ushered in a new era of technological capabilities, some of which now match or even exceed human ability. However, this progress emphasizes the importance of aligning AI with human values to ensure its safe and beneficial societal integration. In this talk, we will provide an overview of the alignment problem and highlight promising areas of research spanning scalable oversight, robustness and interpretability. Watch this AI Explained to learn: - Scalable oversight: Developing methods for scalable AI oversight to keep decisions and actions aligned with human guidance. - Robustness: Strengthening AI's robustness to manipulation and ensuring consistent performance in varied and unforeseen situations. - Interpretability: Creating human-in-the-loop techniques for clear AI decision-making to enhance human understanding, trust, and management. AI Explained is our AMA series featuring experts on the most pressing issues facing AI and ML teams. 00:00 Introductions 00:49 The Importance of AI Safety and Alignment 00:59 The Evolution and Capabilities of AI Models 09:58 The Process of Training AI Models 27:39 Understanding the Model's Internal Belief System 29:32 Exploring the Model's Bias and Confidence 31:51 Research Community's Approach to Model Alignment 37:23 Operationalizing Alignment and Safety for LLM Apps 46:46 Interpretability Issues in LLMs 54:46 Closing Thoughts on the Future of LLMs ✦ Get a customized demo: https://bit.ly/fiddler-demo ✦
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