mirro’s Post

The AI hype bubble is great excuse to rediscover the near history of personal computing. There are plenty of lessons for people working on AI x Future of Work/Home/Office life from 50 years of computers + internet. My time at PARC shaped who I am as a researcher, but reflecting on the ubiquitous computing future we worked towards and where we are today brings up complicated feelings about unintended consequences. But this event looks terrific, too bad it's too far from Berlin to swing by. Thanks for sharing Bo Begole. More about the tech in the exhibit here: https://lnkd.in/dqkMdDXi

Excited to announce that my paper titled "Object Detection Using SSD" has been published! In a rapidly evolving automotive industry, staying ahead of market trends is crucial. Our research, presented at the 2023 5th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), focuses on object detection using the Single Shot MultiBox Detector (SSD). It emphasizes the SSD's ability to perform object localization and classification in a single forward pass, ensuring high-speed detection. This achievement underscores our commitment to innovative approaches in forecasting and highlights the potential of image classification in addressing real-world challenges. DOI: 10.1109/ICAC3N60023.2023.10541704 https://lnkd.in/egCmAQyt #achievement #ssd #share

"The cold, hard facts Cooling systems become less efficient at lower temperatures. To make it worse, the systems we use today to control the qubits are intertwining messes of wires reminiscent of ENIAC and other huge computers of the 1940s. These systems increase heating and create physical bottlenecks to making qubits work together. The more qubits we try to cram in, the more difficult the problem becomes. At a certain point the wiring problem becomes insurmountable. After that, the control systems need to be built into the same chips as the qubits. However, these integrated electronics use even more power – and dissipate more heat – than the big mess of wires."

𝗘𝘅𝗰𝗶𝘁𝗲𝗱 𝘁𝗼 𝗽𝗿𝗲𝘀𝗲𝗻𝘁 𝗼𝘂𝗿 𝗽𝗮𝗽𝗲𝗿 𝗼𝗻 "𝗔𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗔𝗜 𝗼𝗻 𝗥𝗜𝗦𝗖-𝗩: 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗶𝗻𝗴 𝗕𝗙𝗹𝗼𝗮𝘁𝟭𝟲 𝗳𝗼𝗿 𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝗱 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆" 𝗮𝘁 𝗥𝗜𝗦𝗖-𝗩 𝗦𝘂𝗺𝗺𝗶𝘁 𝗘𝘂𝗿𝗼𝗽𝗲! We propose an end-to-end open-source design for a low-cost, modular BFloat16 FPU micro-architecture for RISC-V embedded cores. Our design relaxes certain features of the IEEE Floating-Point Standard to realize a cost-effective hardware implementation that is integrated with cv32e40p (RI5CY core). Using these optimizations, we have achieved almost 𝟯𝟱% reduction in silicon area compared to an IEEE compliant FP32 implementation with minimal impact on accuracy. Come visit us at poster stand B-13 on Thursday, June 27th at RISC-V EU Summit 2024, Germany to learn more! #RISCV #RISCVSummitEurope #AI #MachineLearning #BFloat16 Visit: https://lnkd.in/eAaZ7AA9

#DYK that #OnThisDay in 1932 Norman Abramson was born, American computer scientist who created ALOHANET, the first modern data network, which formed the basis of the protocols essential in the Ethernet now in wide use. It opened in 1970, operating at 9600 bits per second, using radio to provide a wireless packet-switched data network between several Hawaii islands. Its innovations included the first packet radio sensors, the first packet radio repeaters, the first satellite packet network and the first radio access to the Internet. Abramson's U.S. patents include the first patent for CRC redundancy checks to provide data error control technique (No. 3,114,130), and the first patent issued for the design of burst errors in digital systems (No. 3,163,848). https://lnkd.in/exa35DJc

IEEE Open Journal of the Solid-State Circuits Society (OJ-SSCS): This paper presents an overview of trends, challenges and promising directions to support ubiquitous and sustainable hardware security in in next-generation silicon chips at the edge of distributed and connected systems. https://bit.ly/46Jc1zz

We encourage you to read the July TCAS-II paper highlight, "A 28nm 8Kb Reconfigurable SRAM Computing-In-Memory Macro With Input-Sparsity Optimized DTC for Multi-Mode MAC Operations". 📝 Authored by: Kanglin Xiao; Xin Qiao; Xiaoxin Cui; Jiahao Song; Haoyang Luo; Xin’an Wang; Yuan Wang Computing-in-memory (CIM) is an emerging approach for alleviating von Neumann bottleneck and improving energy efficiency and throughput. This brief presents a reconfigurable SRAM CIM macro supporting multi-mode multiply-and-accumulate (MAC) operations, including binary weight network (BWN) MAC, ternary weight network (TWN) MAC, and multi-bit MAC operations. 🔗 Read more on IEEE Xplore here: https://loom.ly/7CbDOMw #TCASII #PaperHighlight #CircuitsandSystems #ResearchBriefs

In this paper, a vision-based #Dynamic #Traffic #Light #System (#DTLS) is proposed using the #YOLO (#You #Only #Look #Once) object detection algorithm that detects and counts the total number of vehicles on the roads of a traffic signal junction. The traffic signals are tuned based on the computed traffic to minimize the overall delay at that junction. Moreover, the traffic junctions are facilitated to communicate with the adjacent junctions to transmit the cumulative traffic delay observed. This delay is used to prioritize traffic passing through salient blocks like schools, offices, hospitals, etc. The paper aims to minimize the overhead incurred in both computations of traffic (using approximate computing) and in communication networks (using low-power technologies of IEEE 802.15.4 standard, specifically DSME MAC and/or LoRaWAN). ---- Anakhi Hazarika, Dr. Nikumani Choudhury, Dr. Moustafa Nasralla PhD, SMIEEE, FHEA, Sohaib Bin Altaf Khattak, Dr. Ikram Ur Rehman, PhD More details can be found at this link: https://lnkd.in/eMdQ87xp

In this paper, the authors present #LensFD, a scalable method to enable cost-effective massive MIMO #full-#duplex operation in sub-6 GHz frequencies with a focus on the CBRS band of 3.5 GHz. LensFD uses a low-cost lens array combined with #transmit #precoding to reshape the effective beam pattern of antennas in massive MIMO arrays to reduce self-interference. The authors tested three lens configurations in LensFD experimentally with a software-defined 40-antenna base-station and demonstrate a significant improvement in self-interference reduction and hence overall increased system capacity to 1.6× over the #time-#division #duplex (#TDD) counterpart. As an important contribution, they will open-source the large measurement dataset from their experiments. ---- Zhican(West) Chen, C. Nicolas Barati Nt, Jon Veihl, Clayton Shepard, Ashutosh Sabharwal More details can be found at this link: https://lnkd.in/eznE5MgW

This paper focuses on #investigating #uplink (#UL) data transmission in #cell-#free #massive #MIMO based on #orthogonal #frequency #division #multiplexing (#CF-#mMIMO-#OFDM) systems, taking into account the effects of #hardware #impairments (#HWIs). Specifically, the HWIs arise from #nonlinear #distortions (#NLD) caused by power #amplifiers (#PAs) at user equipments (UEs). These NLD have a significant impact on both channel estimation and data transmission in UL CF-mMIMO-OFDM. To mitigate NLD while maintaining a good #power-#efficiency, the authors propose a #successive #NLD cancellation approach that is adequate for CF-mMIMO-OFDM. Specifically, a novel #frequency-#domain #channel #estimation method is introduced that incorporates NLD cancellation. This method aims to accurately estimate the #channel despite the presence of #hardware #impairments. ----Asma Mabrouk, Rafik Zayani More details can be found at this link: https://lnkd.in/gyvHcyQY