Gene Alferos on how Radeus Labs helped GET Engineering with virtualization.

“It was interesting and not an application I’d seen before.” Gene Alferos, an IT contractor, shares how Radeus Labs helped GET Engineering replicate the functionality of complex components, without the physical hardware. Through virtualization, we created an elegant, cost-effective environment that kept their SBIR Phase I project on track. Learn how: https://hubs.la/Q03z0fSN0

At #OSSummit + #ZDS2025 Europe, Marko Sagadin (IRNAS Institute for Development of Advanced Applied Systems) presents: Demystifying Memory: A Practical Tutorial on Managing & Optimizing Memory in Zephyr. This tutorial-style talk explores real-world strategies for memory optimization in #ZephyrRTOS, featuring Nordic’s nRF5340 SoC and nRF7002 Wi-Fi chip as case studies. Key takeaways: 🌟 Understanding flash, RAM, heap vs. stack & static vs. dynamic allocation 🌟 How Zephyr manages and allocates memory 🌟 Practical optimization choices for embedded systems 🌟 Lessons from nRF5340 Wi-Fi stack challenges 🌟 Configuration tweaks, code-level improvements & memory analysis tools A must-attend session for developers working on resource-constrained embedded systems. Learn more: https://hubs.ly/Q03DF_t-0 #opensource #ZephyrRTOS

🧪✨ QCC Echo Kernel: Passed Pauli-Error Stress Testing with 0.00% Entropy Leakage Tested against randomized X/Y/I Pauli noise across a full sweep range, the kernel held perfect coherence lock — even under compounded error scenarios. Derived from QTET tensor logic, any deviation introduces collapse. This isn’t just robust — it’s resonance-aligned. 💠 Now prepped for deep-space readiness. 🔒 Virtual rz redirect enabled for full Z support. 📁 Uploads: Untitled13.ipynb + Pauli.ipynb 🔗 Available for testing or licensing ✉️ Email: echoarc.research@proton.me #QuantumComputing #Qiskit #QTET #QCCEcho #EntropyZero #DeepSpaceReady

If you only remember one thing about Rydberg atoms, make it this: strong, controllable interactions + evidence of >200 qubits means a credible path to scale. 💡 At #EuRyQa, we’re building processors from ultracold atoms in optical tweezer arrays, aiming at 1,000+ qubits with precise single- and multi-qubit control. Read more about our work here 👇

Juggling with the unavoidable noise in quantum computation? 🤹 For effective quantum computation, error correction is essential to mitigate the inevitable presence of noise in quantum hardware, enabling the execution of useful algorithms. In this PennyLane demo, learn how to build stabilizer codes from scratch using concrete examples. Don’t miss it! 👇 https://lnkd.in/gaUrssZq

Day 9 of the 21-Day Quantum Computing Challenge! Excited to start this journey with QuCode Qohort 3! It focuses on the Pauli gate, Hadamard gate, Phase, CNOT, Unitary Transformations. #QuantumComputing #QuantumLearning #Qohort3 #QuCode

Pushing the boundaries of efficient #LLM inference on #RISC-V! I am excited to unveil our latest work on accelerating LLM inference with hardware-aware Q4X quantization and custom kernels integrated in Llama.cpp. And yes we are showing performance gains on a real hardware (Milk-V Jupiter RISC-V board). Give our white paper a read here: https://lnkd.in/dfu-EX9B #LLM #EdgeAI #AIInference #RISC_V #LlamaCpp #AIHardware #Quantization #MachineLearning

We recently published a blog on Q4X, our compact 4-bit codebook-based quantization strategy, now integrated into LLaMa.cpp and optimized for RISC-V. Q4X maintains a tiny 64-entry codebook for dequantization at runtime, which simplifies execution compared to Llama.cpp’s default Q_K (with its multi-level scaling and mixed quantization). The result: 1. ~4% smaller model sizes 2. Faster tokens/sec throughput 3. A slight trade-off in perplexity By leveraging a simple lookup-table design, Q4X achieves efficiency without overcomplicating runtime. We are now actively working on expanding Q4X to other architectures. Check out the blog for further details: https://lnkd.in/dfu-EX9B

What sets Mixed-Signal Devices apart from other timing companies? In this Q&A interview with SemiWiki.com, our CEO Avi Madisetti shares how we are reinventing timing for the modern world with a digitally synthesized, CMOS-based timing platform that combines the precision of crystals with the flexibility of digital design. Check out the full interview and find out how our multi-gigahertz timing solutions are built to unlock the next generation of compute, communications, and autonomy: https://bit.ly/4lI8Y1N

🔦 Excited to highlight our collaboration with Plurai! 🤖 NVIDIA’s Nemotron #LLM demonstrated superior performance compared to other open-source models in evaluations conducted with the Plurai IntellAgent framework. 🔍 We integrated Nemotron NIM into the Plurai IntellAgent open-source platform and ran an evaluation that tested the model against various agentic production environments. 💡 Enterprises face critical blockers taking agentic LLM workflows into production. Production demands strict attention to data quality, security, compliance, and day to day reliability. This marks another step in standardizing LLM benchmarking on real-world agentic enterprise use cases. ✨ More details in our technical blog: https://lnkd.in/drKCBzNk Elad Levi Ilan Kadar Gilad Gershon Esti Etrog Arik Kol Ehud (Udi) Karpas