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

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Computer Vision

EU to Ban AI that Tracks Employee Emotions and Manipulates Customers

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DeepMind

US lawmakers move to prohibit DeepSeek AI tool (

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Anthropic

Deals: Realme GT 7 Pro, Xiaomi 14T Pro Prices Dropped. Huawei...

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Anthropic

Nothing may work on a pair headphones

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Anthropic

Imagen 3: Workspace in Gemini for Gmail can now generate people

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Acer’s new gaming notebooks with AI power won’t hurt your pocket

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Apple

Apple AirPods 4 are now available for just $100. Also, check...

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OpenAI responds with detailed reasoning traces to DeepSeek competition for o3...

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OpenAI plans to establish an office in Germany

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Google boasts about Gemini 2.0 Flash. But how does it compare...

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Education

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...