Technology

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

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News

The Rundown: Nvidia’s GTC showcases new AI capabilities that span many...

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Nvidia RTX5060 may have just joined the queue of hardware delayed...

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01.AI founder Kai-Fu Lee names DeepSeek the frontrunner in China’s AI...

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OpenAI’s new voice-AI model gpt-4o transcribe allows you to add speech...

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ChatGPT falsely claims you are a child killer, and you want...

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Anthropic

Euclid spacecraft captures over 26 million galaxies within a week

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Anthropic

Microsoft emails Windows 10 users recommending recycling or trading in outdated...

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Anthropic

Telegram reaches 1 billion active users, as CEO Pavel Durov criticizes...

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Anthropic

What is the elephant in the room when it comes to...

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Nvidia Bets Big On Synthetic Data

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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...