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Rasa Algorithm Whiteboard - TED Policy
Rasa Algorithm Whiteboard - Diet Architecture 1: How it Works
Rasa Algorithm Whiteboard - Understanding Word Embeddings 3: GloVe
Rasa Algorithm Whiteboard - Measuring Quality with Markers
Rasa Algorithm Whiteboard - Incremental Training
Rasa Algorithm Whiteboard: Measuring Bias in Word Embeddings
Rasa Algorithm Whiteboard - Detecting Names
Rasa Algorithm Whiteboard: Debiasing via Projections Doesn't Always Work
Rasa Algorithm Whiteboard - General Embeddings vs. Specific Problems
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Last Updated: September 27, 2026
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Summary
In the age of deep learning and transformers, rule-based systems can still be a great idea. In this video, we hope to demonstrate ... In this video we'd to demonstrate an new tool that we've open-sourced. It's called "whatlies" and the goal of the package is to ... In this video we'll highlight the main points of the starspace paper. It's an influencial piece of work and here at In this video, we will discuss some technical details that are in the UnexpecTEDIntentPolicy. The UnexpecTEDIntentPolicy really is ... When you're making a digital assistant you'll need more than just This video explains the separate parts of the DIET architecture and how they are combined into an architecture that is useful in a ... It turns out that you can drop a lot of weights from your neural network without seeing a drastic effect on accuracy. In this video ... This is the second video on attention mechanisms. In the previous video we introduced self attention and in this video we're going ... How do you judge the quality of a virtual assistant? Can we look at the intent classification scores and call it a day? Or do we need ... When you iterate on your data, you also want to iterate on your model. It'd be a shame to have to retrain from scratch every single ... Word Embeddings have a bias issue. In this video we'll explore what this means by looking at gender bias. We will try to find a ... In this video, we'll highlight a qualitative argument of why you may not need to worry about pre-trained embeddings too much.