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Google AI Research Examines Random Circuit Sampling (RCS) for Evaluating Quantum Computer Performance in the Presence of Noise

Marktechpost

Evaluating the performance of quantum computers has been a challenging task due to their sensitivity to noise, the complexity of quantum algorithms, and the limited availability of powerful quantum hardware. Researchers have made several attempts to analyze how noise affects the ability of quantum computers to perform useful computations.

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Agent-as-a-Judge: An Advanced AI Framework for Scalable and Accurate Evaluation of AI Systems Through Continuous Feedback and Human-level Judgments

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The lack of effective evaluation methods poses a serious problem for AI research and development. Current evaluation frameworks, such as LLM-as-a-Judge, which uses large language models to judge outputs from other AI systems, must account for the entire task-solving process. If you like our work, you will love our newsletter.

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Refined Local Learning Coefficients (rLLCs): A Novel Machine Learning Approach to Understanding the Development of Attention Heads in Transformers

Marktechpost

Artificial intelligence (AI) and machine learning (ML) revolve around building models capable of learning from data to perform tasks like language processing, image recognition, and making predictions. A significant aspect of AI research focuses on neural networks, particularly transformers.

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CMU Researchers Introduce ReLM: An AI System For Validating And Querying LLMs Using Standard Regular Expressions

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The regular expression, LLM decision rules, and the traversal algorithm are all stored in the Query Object. A regular expression inference engine that effectively converts regular expressions to finite automata has been designed and implemented. They are the first group to use automata to accommodate these variant encodings.

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Google AI Researchers Propose ‘MODEL SWARMS’: A Collaborative Search Algorithm to Flexibly Adapt Diverse LLM Experts to Wide-Ranging Purposes

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Upcoming Live Webinar- Oct 29, 2024] The Best Platform for Serving Fine-Tuned Models: Predibase Inference Engine (Promoted) The post Google AI Researchers Propose ‘MODEL SWARMS’: A Collaborative Search Algorithm to Flexibly Adapt Diverse LLM Experts to Wide-Ranging Purposes appeared first on MarkTechPost.

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This AI Paper from Google Presents a Set of Optimizations that Collectively Attain Groundbreaking Latency Figures for Executing Large Diffusion Models on Various Devices

Marktechpost

FlashAttention, on the other hand, is a precise attention algorithm that considers hardware configurations to achieve better performance. Check Out The Paper and Google AI Article. Reformer uses a sparse approximation to reduce computing cost, while other works use low-rank or a combination of approximation techniques.

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DIFFUSEARCH: Revolutionizing Chess AI with Implicit Search and Discrete Diffusion Modeling

Marktechpost

Large Language Models (LLMs) have gained significant attention in AI research due to their impressive capabilities. Existing methods to address the challenges in AI-powered chess and decision-making systems include neural networks for chess, diffusion models, and world models. If you like our work, you will love our newsletter.