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

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Alibaba launches open-source Qwen3 model that surpasses OpenAI R1 and DeepSeek...

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Ex-OpenAI CEO, power users warn against AI sycophancy

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Alibaba unveils Qwen3, an AI reasoning model family that is ‘hybrid.’

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Perplexity will make AI images for you, but ChatGPT is the...

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OpenAI fixes a bug that allowed minors

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OpenAI Adds shopping to ChatGPT

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ChatGPT now offers a new browsing feature for products

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How to Avoid Ethical Red Flags when Working on AI Projects

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Anthropic

Home Panel is now available for Chromecast and Google TV

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Anthropic

The 2,700 reasons why a Made-in-USA iPhone is a non-starter.

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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...