A Coding Implementation on Introduction to Weight Quantization: Key Aspect in Enhancing Efficiency in Deep Learning and LLMs

A Coding Implementation on Introduction to Weight Quantization: Key Aspect in Enhancing Efficiency in Deep Learning and LLMs

In today’s deep learning landscape, optimizing models for deployment in resource-constrained environments is more important than ever. Weight quantization addresses this need by reducing the precision of model parameters, typically from 32-bit floating point values to lower bit-width representations, thus yielding smaller models that can run faster on hardware with limited resources. This tutorial introduces…

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Millions of new materials discovered with deep learning

Millions of new materials discovered with deep learning

Research Published 29 November 2023 Authors Amil Merchant and Ekin Dogus Cubuk AI tool GNoME finds 2.2 million new crystals, including 380,000 stable materials that could power future technologies Modern technologies from computer chips and batteries to solar panels rely on inorganic crystals. To enable new technologies, crystals must be stable otherwise they can decompose,…

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OpenAI unveils Responses API, open source Agents SDK, letting developers build their own Deep Research and Operator

OpenAI unveils Responses API, open source Agents SDK, letting developers build their own Deep Research and Operator

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI is rolling out a new suite of APIs and tools designed to help developers and enterprises build AI-powered agents more efficiently. These are delivered atop some of the very same technology powering its own first-party…

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Prioritizing patching: A deep dive into frameworks and tools – Part 1: CVSS

Prioritizing patching: A deep dive into frameworks and tools – Part 1: CVSS

Back in August 2022, Sophos X-Ops published a white paper on multiple attackers – that is, adversaries targeting the same organizations multiple times. One of our key recommendations in that research was to prevent repeated attacks by ‘prioritizing the worst bugs first’: patching critical or high-profile vulnerabilities that could affect users’ specific software stacks. While…

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