• Title/Summary/Keyword: Winner Takes All

Search Result 13, Processing Time 0.02 seconds

Development of A High-Speed Digital Maximum Selector Circuit With Internal Trigger-Signal Generator (내부 트리거 발생회로를 이용한 고속의 디지털 Maximum Selector 회로의 설계)

  • Yoon, Myung-Chul
    • Journal of the Institute of Electronics Engineers of Korea SD
    • /
    • v.48 no.2
    • /
    • pp.55-60
    • /
    • 2011
  • Most of neural network chips use an analog-type maximum selector circuit (MS). As the increase of integration level, the analog MS has difficulties in achieving sufficient resolution. Contrary, the digital-type MS is easy to get high resolution but slower than its analog counterparts. A new high-speed digital MS circuit called MSIT (Maximum Selector with Internal Trigger-signal) is presented in this paper. The MSIT has been designed to achieves both the high reliability by using trigger-signals and high speed by removing the unnecessary waiting times. The response time of MSIT is 3.4ns for 32 data with 10-bit resolution in the simulation with 1.2V, $0.13{\mu}m$-process model parameters, which is much faster than its analog counterparts. It shows that digital MS circuits like MSIT can achieve higher speed as well as higher resolution than analog MS circuits.

Frequency-Code Domain Contention in Multi-antenna Multicarrier Wireless Networks

  • Lv, Shaohe;Zhang, Yiwei;Li, Wen;Lu, Yong;Dong, Xuan;Wang, Xiaodong;Zhou, Xingming
    • Journal of Communications and Networks
    • /
    • v.18 no.2
    • /
    • pp.218-226
    • /
    • 2016
  • Coordination among users is an inevitable but time-consuming operation in wireless networks. It severely limit the system performance when the data rate is high. We present FC-MAC, a novel MAC protocol that can complete a contention within one contention slot over a joint frequency-code domain. When a node takes part in the contention, it generates randomly a contention vector (CV), which is a binary sequence of length equal to the number of available orthogonal frequency division multiplexing (OFDM) subcarriers. In FC-MAC, different user is assigned with a distinct signature (i.e., PN sequence). A node sends the signature at specific subcarriers and uses the sequence of the ON/OFF states of all subcarriers to indicate the chosen CV. Meanwhile, every node uses the redundant antennas to detect the CVs of other nodes. The node with the minimum CV becomes the winner. The experimental results show that, the collision probability of FC-MAC is as low as 0.05% when the network has 100 nodes. In comparison with IEEE 802.11, contention time is reduced by 50-80% and the throughput gain is up to 200%.

Examining the Generative Artificial Intelligence Landscape: Current Status and Policy Strategies

  • Hyoung-Goo Kang;Ahram Moon;Seongmin Jeon
    • Asia pacific journal of information systems
    • /
    • v.34 no.1
    • /
    • pp.150-190
    • /
    • 2024
  • This article proposes a framework to elucidate the structural dynamics of the generative AI ecosystem. It also outlines the practical application of this proposed framework through illustrative policies, with a specific emphasis on the development of the Korean generative AI ecosystem and its implications of platform strategies at AI platform-squared. We propose a comprehensive classification scheme within generative AI ecosystems, including app builders, technology partners, app stores, foundational AI models operating as operating systems, cloud services, and chip manufacturers. The market competitiveness for both app builders and technology partners will be highly contingent on their ability to effectively navigate the customer decision journey (CDJ) while offering localized services that fill the gaps left by foundational models. The strategically important platform of platforms in the generative AI ecosystem (i.e., AI platform-squared) is constituted by app stores, foundational AIs as operating systems, and cloud services. A few companies, primarily in the U.S. and China, are projected to dominate this AI platform squared, and consequently, they are likely to become the primary targets of non-market strategies by diverse governments and communities. Korea still has chances in AI platform-squared, but the window of opportunities is narrowing. A cautious approach is necessary when considering potential regulations for domestic large AI models and platforms. Hastily importing foreign regulatory frameworks and non-market strategies, such as those from Europe, could overlook the essential hierarchical structure that our framework underscores. Our study suggests a clear strategic pathway for Korea to emerge as a generative AI powerhouse. As one of the few countries boasting significant companies within the foundational AI models (which need to collaborate with each other) and chip manufacturing sectors, it is vital for Korea to leverage its unique position and strategically penetrate the platform-squared segment-app stores, operating systems, and cloud services. Given the potential network effects and winner-takes-all dynamics in AI platform-squared, this endeavor is of immediate urgency. To facilitate this transition, it is recommended that the government implement promotional policies that strategically nurture these AI platform-squared, rather than restrict them through regulations and stakeholder pressures.