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

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Stripe unveils AI foundation model for payments, reveals ‘deeper partnership’ with...

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OpenAI and FDA are reportedly talking about AI for drug evaluations.

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OpenAI and FDA Hold talks about using AI in drug evaluation

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Google disputes Eddy Cue’s claim that Apple users search less

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The telltale sign you used ChatGPT and a way to avoid...

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Anthropic

MIVA, Nigeria’s first private open University, targets 100,000 students through its...

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Anthropic

Google-backed Platos Health raises pre-seed $1.4 million to roll out preventive...

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AWS report: Generative AI surpasses security in global tech spending for...

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Nvidia and MediaTek could finally unveil their AI PC in this...

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Apple

You can still get a 4-pack Apple AirTags at 20% off...

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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...