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

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DeepSeek downloads could result in jail time and a $1,000,000 fine...

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Could AI be the answer to our productivity woes? A personal...

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WhatsApp integrates voice and image inputs into its ChatGPT integration.

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Anthropic

How Thomson Reuters, Anthropic and other companies built an AI that...

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Anthropic

Galaxy S25 and S25 Plus Reviews: Just enough AI to not...

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Nvidia’s answer for AMD Fluid Motion Frames is compatible with all...

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The Download: DeepSeek’s new research agent and OpenAI’s new research agent.

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OpenAI doubles down on Asia, partners with Kakao after its big...

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OpenAI’s ChatGPT agent will do your research for you. Access it...

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OpenAI unveils deep research agent for ChatGPT

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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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AI Observer

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...