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

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Anthropic

Disney is giving its awesome Star Tours toy a fresh coat...

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Anthropic

AI infrastructure investment could be $8T in the dark

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Anthropic

Chris Krebs loses Global Entry membership amid Trump’s feud

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NVIDIA denies reports that it will split off its China business...

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Meta

Mark Zuckerberg claims that Meta is a mulling ad and a...

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Wanna scan your iris for crypto? Sam Altman’s orb comes to...

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Microsoft’s new Phi 4 AI model, which is the most powerful...

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Sam Altman’s World unveiled a mobile verification device.

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Mark Zuckerberg plans to create a premium tier for Meta’s AI...

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OpenAI pulls plug on ChatGPT smarmbot that praised user for ditching...

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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...