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Analysis

This paper proposes a novel approach to address the limitations of traditional wired interconnects in AI data centers by leveraging Terahertz (THz) wireless communication. It highlights the need for higher bandwidth, lower latency, and improved energy efficiency to support the growing demands of AI workloads. The paper explores the technical requirements, enabling technologies, and potential benefits of THz-based wireless data centers, including their applicability to future modular architectures like quantum computing and chiplet-based designs. It provides a roadmap towards wireless-defined, reconfigurable, and sustainable AI data centers.
Reference

The paper envisions up to 1 Tbps per link, aggregate throughput up to 10 Tbps via spatial multiplexing, sub-50 ns single-hop latency, and sub-10 pJ/bit energy efficiency over 20m.

Research#llm👥 CommunityAnalyzed: Jan 3, 2026 09:45

Chiplet ASIC supercomputers for LLMs like GPT-4

Published:Jul 12, 2023 04:00
1 min read
Hacker News

Analysis

The article's title suggests a focus on hardware acceleration for large language models (LLMs) like GPT-4. It implies a move towards specialized hardware (ASICs) and a chiplet-based design for building supercomputers optimized for LLM workloads. This is a significant trend in AI infrastructure.
Reference