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Transformers can generate NFL plays : introducing QB-GPT
QB-GPT is a model that can generate football plays based on provided elements. It aims to recreate plays from minimal information to understand how player setups and contextual elements affect team paths on the field. The model uses data from the Next Gen Stats (NGS) tool of the NFL and relies on the GPT architecture.…
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Google AI Introduces MetNet-3: Revolutionizing Weather Forecasting with Comprehensive Neural Network Models
The development of MetNet-3 represents a significant breakthrough in meteorological research, addressing challenges in weather forecasting. This comprehensive neural network model integrates various data sources, such as radar data and satellite images, to generate precise and high-resolution weather predictions. With advanced techniques like topographical embeddings and model parallelism, MetNet-3 has the potential to revolutionize the…
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Deepfake awareness campaign turns vegans into meat lovers
Steak-umm’s latest advertising campaign involved confronting a group of vegans with deepfake videos of them enjoying meat. While the vegans initially reacted angrily, they eventually supported the campaign’s goal of highlighting the impact of deepfakes. Steak-umm hopes the campaign will attract meat eaters and also raises awareness for the proposed Deep Fakes Accountability Act, which…
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Bridging the expectation-reality gap in machine learning
Machine learning (ML) is increasingly important across industries, but there is a gap between business expectations and what engineers and data scientists can deliver. The first step to close this gap is fostering honest dialogue between teams and then democratizing ML across the organization. Companies can enable collaboration between technical and non-technical teams, provide the…
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Samsung AI Forum 2023: Samsung Forum Explores Generative AI
Samsung Electronics held the Samsung AI Forum 2023 to discuss generative AI and its impact on daily life and work. Samsung Research introduced its generative AI model, Samsung Gauss, highlighting the company’s commitment to this technology. Industry and academic leaders shared insights on large language models, multimodal AI technology, and graduate students presented groundbreaking research.…
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Creeping up the path to global AI regulation
The UK AI Safety Summit and Biden’s executive order have brought AI regulation into focus, but questions remain about the specifics. The Bletchley Declaration, endorsed by 28 countries, emphasizes international consensus on AI oversight. The US and EU have proposed their own regulations, while other countries consider their own initiatives. The implementation of regulations across…
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This AI Research Introduces Breakthrough Methods for Tailoring Language Models to Chip Design
ChipNeMo explores the use of domain adaptation techniques to improve the performance of language models (LLMs) in chip design. The study evaluates three LLM applications in chip design and highlights the potential for further refinement in domain-adapted LLM approaches. The goal is to enhance LLM performance and reduce model size while maintaining or improving performance…
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This AI Research Introduces Atom: A Low-Bit Quantization Technique for Efficient and Accurate Large Language Model (LLM) Serving
Atom is a new low-bit quantisation technique developed by researchers to increase the serving throughput of Large Language Models (LLMs). By using low-bit operators and quantisation, Atom reduces memory usage without sacrificing precision, resulting in improved end-to-end throughput by up to 7.73 times compared to existing approaches. Atom addresses the need for more efficient LLM…
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Huawei takes on Nvidia with its own AI chips
US export restrictions on Nvidia have created a growing market in China for Huawei’s new AI chips, specifically the Ascend 910B. Chinese AI companies are turning to Huawei’s chip as a viable alternative to Nvidia’s high-end chips. The export controls, intended to slow Chinese AI innovation, may have inadvertently accelerated China’s path to self-reliance. As…
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How to Style Plots with Matplotlib
This article discusses various methods to style plots using Matplotlib. It covers topics such as changing runtime configuration parameters, creating and using style files, applying style sheets, and limiting styling to code blocks. These techniques allow for customization and consistency in plotting styles.