Tag: computational efficiency
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Cloud Blog: 65,000 nodes and counting: Google Kubernetes Engine is ready for trillion-parameter AI models
Source URL: https://cloud.google.com/blog/products/containers-kubernetes/gke-65k-nodes-and-counting/ Source: Cloud Blog Title: 65,000 nodes and counting: Google Kubernetes Engine is ready for trillion-parameter AI models Feedly Summary: As generative AI evolves, we’re beginning to see the transformative potential it is having across industries and our lives. And as large language models (LLMs) increase in size — current models are reaching…
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Hacker News: Iterative α-(de)blending and Stochastic Interpolants
Source URL: http://www.nicktasios.nl/posts/iterative-alpha-deblending/ Source: Hacker News Title: Iterative α-(de)blending and Stochastic Interpolants Feedly Summary: Comments AI Summary and Description: Yes Summary: The text reviews a paper proposing a method called Iterative α-(de)blending for simplifying the understanding and implementation of diffusion models in generative AI. The author critiques the paper for its partial clarity, discusses the…
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Hacker News: SVDQuant: 4-Bit Quantization Powers 12B Flux on a 16GB 4090 GPU with 3x Speedup
Source URL: https://hanlab.mit.edu/blog/svdquant Source: Hacker News Title: SVDQuant: 4-Bit Quantization Powers 12B Flux on a 16GB 4090 GPU with 3x Speedup Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The provided text discusses the innovative SVDQuant paradigm for post-training quantization of diffusion models, which enhances computational efficiency by quantizing both weights and activations to…
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Hacker News: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces
Source URL: https://arxiv.org/abs/2410.09918 Source: Hacker News Title: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses a new model called Dualformer, which effectively integrates fast and slow cognitive reasoning processes to enhance the performance and efficiency of large language models (LLMs).…
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The Register: Fujitsu delivers GPU optimization tech it touts as a server-saver
Source URL: https://www.theregister.com/2024/10/23/fujitsu_gpu_middleware/ Source: The Register Title: Fujitsu delivers GPU optimization tech it touts as a server-saver Feedly Summary: Middleware aimed at softening the shortage of AI accelerators Fujitsu has started selling middleware that optimizes the use of GPUs, so that those lucky enough to own the scarce accelerators can be sure they’re always well-used.……
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Hacker News: Fine-Tuning LLMs: A Review of Technologies, Research, Best Practices, Challenges
Source URL: https://arxiv.org/abs/2408.13296 Source: Hacker News Title: Fine-Tuning LLMs: A Review of Technologies, Research, Best Practices, Challenges Feedly Summary: Comments AI Summary and Description: Yes Summary: This guide extensively covers the fine-tuning of Large Language Models (LLMs), detailing methodologies, techniques, and practical applications. Its relevance to AI and LLM security professionals is underscored by discussions…
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Simon Willison’s Weblog: lm.rs: run inference on Language Models locally on the CPU with Rust
Source URL: https://simonwillison.net/2024/Oct/11/lmrs/ Source: Simon Willison’s Weblog Title: lm.rs: run inference on Language Models locally on the CPU with Rust Feedly Summary: lm.rs: run inference on Language Models locally on the CPU with Rust Impressive new LLM inference implementation in Rust by Samuel Vitorino. I tried it just now on an M2 Mac with 64GB…
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Hacker News: Addition Is All You Need for Energy-Efficient Language Models
Source URL: https://arxiv.org/abs/2410.00907 Source: Hacker News Title: Addition Is All You Need for Energy-Efficient Language Models Feedly Summary: Comments AI Summary and Description: Yes Summary: The paper presents a novel approach to reducing energy consumption in large language models by using an innovative algorithm called L-Mul, which approximates floating-point multiplication through integer addition. This method…
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Slashdot: Researchers Claim New Technique Slashes AI Energy Use By 95%
Source URL: https://science.slashdot.org/story/24/10/08/2035247/researchers-claim-new-technique-slashes-ai-energy-use-by-95?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Researchers Claim New Technique Slashes AI Energy Use By 95% Feedly Summary: AI Summary and Description: Yes Summary: Researchers at BitEnergy AI, Inc. have introduced Linear-Complexity Multiplication (L-Mul), a novel technique that reduces AI model power consumption by up to 95% by replacing floating-point multiplications with integer additions. This…