Technology

MCP and the Innovation Paradox: Why open standards can save AI...

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Google DeepMind researchers introduce a new benchmark to improve LLM factuality...

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OpenAI has started building out its robotics teams

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Elon Musk wants the courts to force OpenAI into auctioning off...

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Alibaba Cloud’s Tongyi Lingma Artificial Intelligence Programmer is fully online

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Samsung Galaxy S25 could be subject to an unwelcome increase in...

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News Roundup: Meta’s Content Shakeup, Nvidia Gaming Revolution, and more

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Nvidia CEO teases consumer CPU plans following Project Digits, GB10 unveiling...

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Technology

Biden said to weigh global limits on AI exports in 11th-hour...

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A New York legislator is trying to salvage the California AI...

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Microsoft’s new rStar-Math technique upgrades small models to outperform OpenAI’s o1-preview...

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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...