Self-supervised features are typically used in place of filter-bank features in speaker verification models. However, these models were originally designed to ingest filter-banks as inputs, and thus, training them on self-supervised features assumes that both feature types require the same amount of learning for the task. In this work, we observe that pre-trained self-supervised speech …
The Cohere Rerank 3 Nimble foundation model (FM) is now generally available in Amazon SageMaker JumpStart. This model is the newest FM in Cohere’s Rerank model series, built to enhance enterprise search and Retrieval Augmented Generation (RAG) systems. In this post, we discuss the benefits and capabilities of this new model with some examples. Overview …
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It’s one of the best times of the year to score a new mattress. Here are all the best deals (plus some exclusive sale codes) to snag ahead of the long weekend.
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Preparing categorical data correctly is a fundamental step in machine learning, particularly when using linear models. One Hot Encoding stands out as a key technique, enabling the transformation of categorical variables into a machine-understandable format. This post tells you why you cannot use a categorical variable directly and demonstrates the use One Hot Encoding in …
Read more “One Hot Encoding: Understanding the “Hot” in Data”
Whether you want a backyard presenter or a theater-quality behemoth, our projector picks will help you upgrade your movie nights.
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Think NightCafe’s Behind in the AI Art Scene? Think Again. If you’ve been following NightCafe, you know we’re all about staying ahead in the AI art game. Over the past month, we’ve rolled out some updates that you might have missed. Here’s a quick look at what’s new: 1. Selfie Generator Upload 2-4 photos, type …
Read more “Behind the Scenes: NightCafe’s Latest Updates August 2024”
AI won’t replace you, but someone using AI will — so it’s time to embrace AI, and it’s possible to do so even on a low budget.Read More
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