Technology

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

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Anthropic

The default TV setting that you should turn off ASAP and...

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News

Amazon has slashed $200 off the price of this Asus gaming...

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OpenAI launches GPT-4o with improved text rendering, instruction following and OpenAI...

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OpenAI’s new image generator aims to be practical enough for designers...

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Microsoft adds Copilot AI with ‘deep reasoning,’ for data analysis and...

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Deepseek’s new AI is smarter, faster, cheaper, and a real rival...

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Anthropic

UBA lost N1.14 Billion to fraud in 2024 despite record profits

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Anthropic

M-PESA’s true cost is catching up to it

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Anthropic

Google fixes a major compatibility issue with its Drive app for...

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Hands-on with Half-Life 2’s RTX-powered graphics

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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...