Choosing Between Metrics and Inferences for Model Monitoring
Compare metrics and inferences for AI observability to help enterprises monitor models effectively with Fiddler’s AI observability platform.
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Safety
Disrupting malicious uses of AI by state-affiliated threat actors
We terminated accounts associated with state-affiliated threat actors. Our findings show our models offer only limited, incremental capabilities for malicious cybersecurity tasks.
How To, Search
Fine-Tuning Cohere’s Reranker
Learn how to fine-tune Cohere’s reranker and generate synthetic data using DSPy!
Product
Memory and new controls for ChatGPT
We’re testing the ability for ChatGPT to remember things you discuss to make future chats more helpful. You’re in control of ChatGPT’s memory.
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The Advantage of Language Model-Based Embeddings
Fiddler’s patented clustering-based drift monitoring method detects subtle behavior changes in text, computer vision, and LLM-based models.
How To, integrations
Weaviate in Snowflake’s Snowpark Container Services
An end-to-end generative feedback loop demo using Weaviate, Ollama, Mistral and Snowflake’s Snowpark Container Services!
ai, Graph Mining, Graphs, Learn, Machine Learning, Release Notes, Tensorflow
Graph neural networks in TensorFlow
Posted by Dustin Zelle – Software Engineer, Research and Arno Eigenwillig – Software Engineer, CoreML
This article is also shared on the Google Research Blog
Objects and their relationships are ubiquitous in the world around us, and rel…
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Thinking about High-Quality Human Data
[Special thank you to Ian Kivlichan for many useful pointers (E.g. the 100+ year old Nature paper “Vox populi”) and nice feedback. 🙏 ]
High-quality data is the fuel for modern data deep learning model training. Most of the task-specific lab…