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

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Anthropic

This article was written by[19659002]and

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Anthropic

Samsung Galaxy S25 in for review

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Samsung Galaxy A36 & A56 repairability scores revealed ahead of launch

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The Best Gadgets of January, 2025

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Apple

Get four Apple AirTags at $70 plus the rest of this...

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OpenAI launches new model o3-mini

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Deepseek AI model is easy to jailbreak

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Microsoft’s latest AI feature may just stop working. Here’s why

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OpenAI’s O3-mini is now available for all users

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Elon Musk has said that Tesla will launch its self-driving taxi...

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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...