Anthropic

Sparkle’s ‘Thundermage’ concept pitches Thunderbolt as a GPU port

AI Observer
Anthropic

Oracle Cloud security SNAFU: IT giant accused as evidence disappears

AI Observer
Anthropic

Check Point confirms breach but says it was “old” data and...

AI Observer
Anthropic

AI datacenters are going nuclear. Too bad they needed this yesterday

AI Observer
Anthropic

Sabi focuses on TRACE to ensure transparent mining of Africa’s mineral...

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Anthropic

Lipa Later enters administration after failed fresh fundraising efforts

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Anthropic

Sony’s best wireless headphones are on sale for $250 today

AI Observer
Anthropic

Google’s Colossus system relies on HDDs to store the majority of...

AI Observer
Anthropic

Former PlayStation CEO says that he left Sony partly because of...

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Anthropic

WhatsApp can now set as the default messaging app and calling...

AI Observer
Anthropic

Dems call Trump’s cuts to export controls on chips a ‘gift...

AI Observer

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News

Researchers at UT Austin Introduce Panda: A Foundation Model for Nonlinear...

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Education

Qwen Researchers Proposes QwenLong-L1: A Reinforcement Learning Framework for Long-Context Reasoning...

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Natural Language Processing

Meta AI Introduces Multi-SpatialMLLM: A Multi-Frame Spatial Understanding with Multi-modal Large...

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News

A Step-by-Step Coding Implementation of an Agent2Agent Framework for Collaborative and...

AI Observer
AI Observer

Researchers at UT Austin Introduce Panda: A Foundation Model for Nonlinear...

Chaotic systems, such as fluid dynamics or brain activity, are highly sensitive to initial conditions, making long-term predictions difficult. Even minor errors in modeling these systems can rapidly grow, which limits the effectiveness of many scientific machine learning (SciML) approaches. Traditional forecasting methods rely on models trained on specific...