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DeepNewz, mobile.
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Recent developments in the field of artificial intelligence focus on optimizing Large Language Models (LLMs) to extremely low bit-widths, such as 1-bit, to enhance inference speed and reduce latency. Companies like Google, Microsoft, and Groq are at the forefront of this advancement, introducing new techniques and models like BitNet b1.58 and LongRoPE to improve LLM performance and scalability. Collaboration between Groq and Joao Moura aims to leverage Groq's LPU technology for local AI deployment, while calls are made for designing new hardware and systems optimized for 1-bit LLMs.
"Recent work like Groq has demonstrated promising results and great potential for building specific hardware (e.g., LPUs) for LLMs. Going one step further, we envision and call for actions to design new hardware and system specifically optimized for 1-bit LLMs, given the new… https://t.co/DPIvTjoSDK
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits https://t.co/yVfIgqyn4o
Groq Desktop: A Game-Changer for Local AI Deployment and Innovation Collaboration between @GroqInc and @joaomdmoura? Groq's groundbreaking LPU technology offers unprecedented performance for language model processing. I propose a Groq Desktop solution to bring this power…
