Entropica Labs’ Post

Last week, Tommaso Demarie, our CEO at Entropica Labs, had the honor of speaking at the French-Singaporean Quantum Symposium, an incredible event focused on strengthening quantum partnerships between Singapore and France. This presentation was a milestone for us, as we unveiled EKA—a novel data structure designed to represent, interpret, and validate #QuantumErrorCorrection (QEC) codes, developed by Entropica Labs. EKA moves us closer to making quantum error correction more accessible, paving the way for scalable, reliable quantum computing. Curious to learn more about EKA? Stay tuned for upcoming updates! In the meantime, explore what Entropica Labs is building at www.entropicalabs.com. A special thanks to Alexia Auffèves and the organizers of the #FrenchSingaporeanQuantumSymposium for inviting our CEO, Tommaso Demarie, to present our work on data structures for quantum error correction. #QuantumComputing #QuantumErrorCorrection #QuantumTechnology #FrenchSingaporeanQuantumSymposium #EntropicaLabs #QEC

I'm currently tackling the intricacies of FlowNet's code for optical flow estimation. It's a challenging but rewarding endeavor, and I'm determined to unravel the logic behind those convolutional layers. #MachineLearning #ComputerVision #OpticalFlow #DeepLearning

This study proposes an #advanced #bisection #samplingbased #stochastic #solution #enhancement (#BSSE) algorithm to minimize the systemfs overall #energy-#time cost by #jointly #optimizing #task #offloading and #resource #allocation strategies. The formulated problem is a #mixed-#integer #nonlinear programming problem due to its inherently combinatorial linkage with task-offloading decisions and strong correlation with resource allocation. The proposed algorithm operates iteratively through the following steps: 1) narrowing the search space through a #one-#climb #policy, 2) developing a #closed-#form #solution for optimal CPU frequency and transmit power, and 3) implementing randomized task offloading, which updates it in the direction of reducing objective value. ----Muhammad Awais, Haris Pervaiz, Qiang Ni, Wenjuan Yu More details can be found at this link: https://lnkd.in/g6FxTPRF

https://lnkd.in/dFBVwTKS "ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy" The paper compares ConvNet and Vision Transformer architectures across supervised and CLIP training paradigms. While models show similar ImageNet accuracies, they exhibit significant differences in robustness, calibration, transferability, and feature invariance. CLIP models, trained on diverse data, perform better in generalization and transferability, while supervised models excel in robustness and calibration. The study highlights the need for nuanced evaluation beyond ImageNet accuracy for better model selection in various applications.

𝗪𝗵𝗶𝘁𝗲 𝗽𝗮𝗽𝗲𝗿 | 𝗘𝗺𝗯𝗲𝗱𝗱𝗲𝗱 𝗣𝗿𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗧𝗶𝗺𝗶𝗻𝗴 More and more electronic systems find their application in distributed, networked computing architectures. Synchronizing actions using precision timing concepts is becoming increasingly common, and with that the need for very high precision time. In the white paper ‘"𝗘𝗺𝗯𝗲𝗱𝗱𝗲𝗱 𝗣𝗿𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗧𝗶𝗺𝗶𝗻𝗴, 𝗔 𝗱𝗲𝗲𝗽 𝗱𝗶𝘃𝗲 𝗶𝗻 𝘀𝘂𝗯-𝗻𝗮𝗻𝗼𝘀𝗲𝗰𝗼𝗻𝗱 𝘁𝗶𝗺𝗲 𝘀𝘆𝗻𝗰𝗵𝗿𝗼𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻" Embedded Systems Architect Dirk van den Heuvel zooms in on the implementation aspects of precision timing, how it can be facilitated in various solutions, and how it can be used in specific applications. Addressing precision timing in general, White Rabbit specifically as well as the various implementations that TOPIC has been working on.   🔺Interested to learn more? Request the white paper for free via the following link: https://lnkd.in/eWfZZj2e For more information or an informal chat about this topic feel free to contact Dirk van den Heuvel.   #precisiontiming #embeddedsystems #whiterabbit #technology #systemonmodules

"Learning about logic gates in Digital Logic Design has been an amazing journey! 🔑 From simple AND, OR, and NOT gates to more complex combinations like multiplexers and decoders, these are the essential elements that power digital systems. Understanding how these gates process binary inputs to produce specific outputs has deepened my appreciation for the technology behind modern computing. Looking forward to expanding my knowledge and taking on more complex circuit designs! #LogicGates #DigitalLogic #CircuitEngineering #Innovation"

🚀 Excited to share a new blog post on "MATADOR: Automated System-on-Chip Tsetlin Machine Design Generation for Edge Applications," which discusses the significant throughput gains for machine learning edge inference applications through the design of co-processor accelerator systems using System-on-Chip Field-Programmable Gate Arrays (SoC-FPGAs). The post presents MATADOR, an automated boolean-to-silicon tool with GUI interface capable of implementing optimized accelerator design of the TM model onto SoC-FPGA for inference at the edge. Learn more about this cutting-edge technology and its implications here: https://bit.ly/3vji3Kd #machinelearning #SoCFPGA #edgeinference

This paper develops a low-complexity suboptimal non-coherent receiver for a multi-level energy-based coded modulation system. Inspired by the turbo processing principle, the authors incorporate the fundamentals of #bit-#interleaved #coded #modulation #with #iterative #decoding (#BICM-#ID) into the proposed receiver design. The resulting system is called #bit-#interleaved #coded #energy-#based #modulation #with #iterative #decoding (#BICEM-#ID) and its error performance is analytically studied. Specifically, they derive upper bounds on the average #pairwise #error #probability (#PEP) of the non-coherent BICEM-ID system in the #feedback-#free (#FF) and #error-#free #feedback (#EFF) scenarios. ----Ali Fazeli, @Ha H. Nguyen More details can be found at this link: https://lnkd.in/evr27mqb

Simplify debugging with Quantum EDGE No coding expertise? No problem! Our intuitive user interface lets you easily rerun experiments with updated settings or parameters, helping you fine-tune your approach effortlessly. Watch the video to see it in action - link in the comments. Start exploring now! Vishal Chatrath, Dominic Lennon, Andrew Briggs, Natalia Ares, Jelena Trbovic, Freddie Faulkner, Tanushree Gollapalli, Juha Seppä, Kati Suard, Timo Tuukkanen, Anton Vladyka Qblox, Quantum Machines , Zurich Instruments #QuantumComputing #QuantumEDGE #QuantumTechnology #Automation

Contemporary quantum processors vary widely in terms of instruction set, connectivity, and even underlying computational model. Programs written with one processor in mind cannot generally be run on another. Triple Alpha allows developers to write programs with hardware-agnostic code which can then be compiled to target specific processors, resulting in performant hardware-optimised implementations ready to deploy. For a full overview of Triple Alpha: https://lnkd.in/gRYMd8k6