Archives mensuelles : décembre 2024

Replacing Python loops: Fancy Slicing and Broadcasting

This article highlights how to perform fancy slicing and broadcasting.

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Python Loop Replacement: Handling Conditional Logic (PyTorch & NumPy)

This article highlights how to vectorize a loop even though it contains tricky conditional logic. 

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Optimizing Retail Through AI: Refabric’s Vision for Sustainable Fashion

The world of retail never stands still – especially when it comes to fashion. But speed and dynamism have unwelcome byproducts: overproduction, waste, and inefficiencies that strain resources and contribute to the fashion industry’s sustainability problem.Enter Refabric, a generative AI-powered … Continuer la lecture

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Intel Labs AI Researchers Featured as Part of Innovation Selects 2024

Intel’s Innovation Selects features a collection of specially curated technical talks and demos, including product deep dives, tailored for developers and tech enthusiasts. The collection highlights groundbreaking work from Intel Labs in artificial intelligence, including new open-source tools and open … Continuer la lecture

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Five Reasons for Choosing Intel® Xeon® 6 Processors to Drive AI Success

While GPU and AI accelerator products will always play an important role for AI use cases, the host CPU will remain critical for new-age AI-accelerated systems. Intel® Xeon® processors are best positioned to support critical AI workloads as the host … Continuer la lecture

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Beyond GPUs: Why JamAI Base Moved Embedding Models to Intel® Xeon® CPUs

What if a spreadsheet could think, create, and collaborate? Thanks to Intel® Liftoff member Embedded LLM and their innovative platform, JamAI Base, the familiar spreadsheet transforms into an AI powerhouse. From auto-generating content and extracting data from images to building … Continuer la lecture

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PyTorch Enhancements for Accelerator Abstraction

Optimizing the PyTorch Frontend to support diverse AI accelerators

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CLIP-InterpreT: Paving the Way for Transparent and Responsible AI in Vision-Language Models

CLIP-InterpreT offers a suite of five interpretability analyses to understand the inner workings of Contrastive Language-Image Pretraining (CLIP) vision-language models, which is crucial for responsible artificial intelligence (AI) development.

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The 24.11 Intel® Tiber™ Edge Platform Release is Now Available.

This release includes support for onboarding new set of optimized applications and software, plus support for multi-tenancy and simplified concurrent onboarding of multiple edge nodes.

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LVLM-Interpret: Explaining Decision-Making Processes in Large Vision-Language Models

Understanding the internal mechanisms of large vision-language models (LVLMs) is a complex task. LVLM-Interpret helps users understand the model’s internal decision-making processes, identifying potential responsible artificial intelligence (AI) issues such as biases or incorrect associations. The tool adapts multiple interpretability … Continuer la lecture

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