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Eliza review – an ambitious, unsettling play about the birth of AI45m ago Reviewing my LessWrong post history with Claude59m ago Low-Background Minds1h ago Report: Anthropic targets pre-Thanksgiving IPO launch, despite warning of AI’s ‘existential risks’1h ago Your AI Agents Can Write Code. Can They Understand Your Business?2h ago Meta open sources code to let you make Muse AI gadgets2h ago Robotics AI developer FieldAI reportedly raising $700M in funding2h ago Japan's entertainment robots diversify with AI, offer comfort3h ago OpenAI safety leader David Robinson resigns as the team's upheaval mounts3h ago Apple to Tighten Mac Data Controls in Guard Against AI Agents4h ago Contest-Winning Microscope Video Is Full of AI Confabulations, Scientists Say4h ago The Mulleted, Meme-Loving Billionaire Behind Meta’s Hit AI App4h ago What is recursive self-improvement and what would it mean to ban it?4h ago Cerebras stock hits post-IPO low, tumbling 20% for the week on Nvidia pressure and lockup expiration4h ago

Machine Learning Dev4 min reading time

Linkup Research Releases SPARSEUP: A 149M-Parameter Open-Source Sparse Embedding Model

MarkTechPostPublished 14 days ago

Read the full article

Linkup Research has launched SPARSEUP, a 149M-parameter open-source sparse embedding model based on ModernBERT, achieving a 56.4 average nDCG@10 on BEIR-13 and available under Apache 2.0 on Hugging Face.

#hugging-face #information-retrieval #linkup-research #modernbert #sparseup

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