Anthropic

Week 19 review: Galaxy S25 Edge, Realme prototype with 10k-battery, and...

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Anthropic

AI or Not raises 5M dollars to stop AI fraud, deepfakes,...

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Anthropic

You can now fine tune your own version AI image maker...

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Anthropic

Anthropic agrees with music publishers to work together to prevent copyright...

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Anthropic

Claude AI and other system could be vulnerable to worrying Command...

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Anthropic

Can AI save the public sector? Will it deliver on its...

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Anthropic

L’Oreal: Making AI worthwhile

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Anthropic

Anthropomorphizing Artificial intelligence: The consequences of mistaking human-like AI for humans...

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Anthropic

Anthropic AI Case on Copyright Centers on ‘Guardrails for Song Lyrics’

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Anthropic

Mark Zuckerberg and Sheryl Sandberg want you to know they’re still...

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Anthropic

Here’s what we know about the Nintendo Switch 2 so far.

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Education

A Coding Implementation of Accelerating Active Learning Annotation with Adala and...

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News

LightOn AI Released GTE-ModernColBERT-v1: A Scalable Token-Level Semantic Search Model for...

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News

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...