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Huawei Introduces Pangu Ultra MoE: A 718B-Parameter Sparse Language Model Trained...

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Oura + Dexcom Launch Glucose Tracking

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Zuckerberg Reveals Surreal Metaverse Vision

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Figma Launches AI Tools for Designers

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When AI Selfies Go Too Far

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AI Revives Lost Agatha Christie Tale

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The Climate Crisis Threatens Supply Chains. Manufacturers Hope AI Can Help

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Dozens of YouTube Channels Are Showing AI-Generated Cartoon Gore and Fetish...

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A DOGE Recruiter Is Staffing a Project to Deploy AI Agents...

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DOGE Is in Its AI Era

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The Dream of the Metaverse Is Dying. Manufacturing Is Keeping It...

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A Coding Implementation of Accelerating Active Learning Annotation with Adala and...

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LightOn AI Released GTE-ModernColBERT-v1: A Scalable Token-Level Semantic Search Model for...

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This AI Paper Introduces Effective State-Size (ESS): A Metric to Quantify...

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Technology

Dream 7B: How Diffusion-Based Reasoning Models Are Reshaping AI

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A Coding Implementation of Accelerating Active Learning Annotation with Adala and...

In this tutorial, we’ll learn how to leverage the framework to build a modular active learning pipeline for medical symptom classification. We begin by installing and verifying Adala alongside required dependencies, then integrate Google Gemini as a custom annotator to categorize symptoms into predefined medical domains. Through a...