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

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Anthropic’s Claude AI gets major upgrade with new integrations

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Kids under 13 will be able to use Gemini AI soon

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Secret Xbox handheld exposed through regulatory filing images

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OpenAI to remain a non-profit organization for now

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New Amazon warehouse robot has human touch without the human salary

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Anthropic

Jumia expects to be profitable in 2027, as Q1 results show...

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Anthropic

Airtel plans IPO in 2026 for mobile money unit to compete...

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The Download: Neuralink AI boost and Trump’s tariffs.

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This patient’s Neuralink implant gets a boost by generative AI.

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Nvidia driver issues are still a mess

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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...