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

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OpenAI’s operator can browse the internet and perform actions on your...

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Apple’s AI priorities for this year, according to a leaked memo

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iPhone 17 Pro: seven new features coming this year

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Trump says he is open to Musk or Ellison purchasing TikTok

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OpenAI and Softbank have launched a $500 billion AI Data Center...

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What is Agentic AI and how might it change the way...

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Capcom tests generative AI to manage ‘tens of thousands’ of ideas

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Apple Intelligence turned on by default in upcoming macOS Sequoia 15.3,...

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OpenAI launches Operator –

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eBay sellers are selling used phones with TikTok preinstalled

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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...