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High-End Fashion Dupes Are Soaring Where Knock-Offs Never Could
High-quality imitations of luxury products are rising, and people aren’t ashamed to buy them anymore. How do designer brands retain their appeal?
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Cells From Different Species Can Exchange ‘Text Messages’ Using RNA
Long known as a messenger within cells, RNA is increasingly seen as life’s molecular communication system—even between organisms widely separated by evolution.
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‘Piece by Piece’ Director Morgan Neville Will Never Use AI Again
Back in 2021, Morgan Neville thought using AI to recreate the late Anthony Bourdain’s voice would be an interesting Easter egg in his documentary. He ended up being a canary in Hollywood’s AI coal mine.
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ConceptAgent: A Natural Language-Driven Robotic Platform Designed for Task Execution in Unstructured Settings
Robotic task execution in open-world environments presents significant challenges due to the vast state-action spaces and the dynamic nature of unstructured settings. Traditional robots struggle with unexpected objects, varying environments, and task ambiguities. Existing systems, often designed for controlled or pre-scanned environments, lack the adaptability required to respond effectively to real-time changes or unfamiliar tasks.…
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The Best Curling Irons of 2024, Tested and Reviewed
We tried the most popular curling irons on the market, and here are the 11 that stood out.
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This AI Paper Introduces a Comprehensive Study on Large-Scale Model Merging Techniques
Model merging is an advanced technique in machine learning aimed at combining the strengths of multiple expert models into a single, more powerful model. This process allows the system to benefit from the knowledge of various models while reducing the need for large-scale individual model training. Merging models cuts down computational and storage costs and…
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Stochastic Prompt Construction for Effective In-Context Reinforcement Learning in Large Language Models
Large language models (LLMs) have demonstrated impressive capabilities in in-context learning (ICL), a form of supervised learning that doesn’t require parameter updates. However, researchers are now exploring whether this ability extends to reinforcement learning (RL), introducing the concept of in-context reinforcement learning (ICRL). The challenge lies in adapting the ICL approach, which relies on input-output…
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On Running Cloudboom Strike LS Review: More Bounces for Less Ounces
The On Running Cloudboom Strike LS marathon shoes are sprayed together by robots.
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Researchers from Moore Threads AI Introduce TurboRAG: A Novel AI Approach to Boost RAG Inference Speed
High latency in time-to-first-token (TTFT) is a significant challenge for retrieval-augmented generation (RAG) systems. Existing RAG systems, which concatenate and process multiple retrieved document chunks to create responses, require substantial computation, leading to delays. Repeated computation of key-value (KV) caches for retrieved documents further exacerbates this inefficiency. As a result, RAG systems struggle to meet…
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OPTIMA: Enhancing Efficiency and Effectiveness in LLM-Based Multi-Agent Systems
Large Language Models (LLMs) have gained significant attention for their versatility in various tasks, from natural language processing to complex reasoning. A promising application of these models is the development of autonomous multi-agent systems (MAS), which aim to utilize the collective intelligence of multiple LLM-based agents for collaborative problem-solving. However, LLM-based MAS faces two critical…