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8 articles
This explainer explores how specialized AI training infrastructure enables startups to achieve rapid growth and high valuations by dramatically improving computational efficiency and development speed.
French startup Kog is challenging the notion that GPUs are poorly suited for agentic AI workflows by developing innovative techniques to maximize GPU inference efficiency.
Researchers used an AI coding agent to discover a novel algorithm that cuts AI compute by 70% while maintaining accuracy, demonstrating the potential for AI to surpass human-designed solutions.
A new tutorial explores the implementation of OpenMythos, a theoretical reconstruction of the Claude Mythos architecture, focusing on recurrent-depth transformers and adaptive computation techniques.
This explainer explores how AI model optimization techniques have made older smartphones more efficient than newer models, challenging the assumption that newer is always better.
Learn how Neural Computers — a new AI concept — could revolutionize computing by combining thinking, remembering, and communication into one system.
A Stanford study reveals that multi-agent AI systems' advantages often stem from increased compute rather than inherent collaboration, with notable exceptions where specialized agents deliver superior results.
This explainer explores Google's TurboQuant technology, a real-time quantization approach that reduces AI computational costs and enables local deployment of large models.
