RISC-V takes over IoT and automotive with custom chips

🚀 Demystifying Processors: From CPUs to NPUs In today’s tech-driven world, processors are everywhere – powering your phone, car, laptop, and even the AI models behind generative tools. 🤔But did you know there are different types of processors, each designed with a specific purpose in mind? 💡 Each comes with unique applications, from cloud computing to automotive, IoT, telecom, aerospace, and AI. 🚀 “The brains behind modern tech: A deep dive into different processor types and their applications.” #Semiconductors #Processors #ChipDesign #ElectronicsEngineering #HardwareDesign #Learning #CareerGrowth #ProfessionalDevelopment #STEM #KnowledgeSharing #ArtificialIntelligence #MachineLearning #AIChips #NPUs #QuantumComputing #FutureOfTech #qsemi #bengaluru #karnataka

Ambiq has announced the Apollo510B, an expansion of its Apollo5 family with a wireless-capable System-on-Chip (SoC) designed for energy-efficient edge AI devices. Featuring an integrated 48MHz network processor and BluetoothLE5.4, this SoC delivers up to 30× better power efficiency and 16× faster AI performance than Cortex-M4 counterparts. #Apollo510B #EdgeAI #UltraLowPower #BluetoothLE54 #ArmCortexM55 #TurboSPOT #IoT #Wearables #SmartDevices #RemotePatientMonitoring #IndustrialAutomation #powerelectronics #powermanagement #powersemiconductor https://lnkd.in/dXnkAPku

Ambiq launches Apollo510B SoC with BLE 5.4 & Cortex-M55 to supercharge power-efficient edge AI for wearables & smart devices. #EdgeAI #IoT #Ambiq https://lnkd.in/g-eeWKNU

Grinn Launches GenioSOM-700 and GenioSOM-510 Powered by MediaTek Genio Processors: Wrocław, Poland. Grinn has announced a partnership with MediaTek extending the employment of AI and IoT technologies based on its off-the-shelf ... #iot #data #internetofthings

This is how far we have come! #Apple’s new #M4Chip is raising the bar for performance and efficiency, but did you know what exactly makes it so powerful? Built on a #3Nanometer process, the M4 packs about #28Billion transistors into a single chip. This incredible density allows it to deliver #HigherPerformance while using #LessPower, a key requirement as devices get thinner, lighter, and more energy-efficient. Shrinking transistor size means signals travel shorter distances, reducing energy loss and heat buildup while increasing speed. That is why the M4 can manage everything from #AI powered applications to 4K video editing while still managing to preserve battery life. It also continues Apple’s trend of integrating powerful #CPUs, #GPUs and #NeuralEngines into a single #SoC (System on a Chip), ensuring faster communication between components and improved overall efficiency. Breakthroughs like the M4 prove that high performance with low power is not merely possible. It is rather quickly becoming the new standard, driving a shift toward devices that deliver more capability, last longer on a single charge and open doors for entirely new design possibilities. #ADME #ADMETech #AppleM4 #Semiconductors #ChipDesign #ElectronicsInnovation #FutureOfTech #HighPerformanceComputing #IoT #EmbeddedSystems

The edge computing revolution is reshaping how we think about processing power. The diversity of compute elements for AI inference at the edge has never been more complex or more exciting. As highlighted in this insightful piece from Semiconductor Engineering, the mix varies significantly by application, creating both opportunities and challenges for our industry. At Imagination Technologies, we believe that the GPU is capable of bringing extraordinary AI capabilities to edge devices, and we're seeing firsthand how different applications demand different processing approaches: 🎯 Mobile devices need ultra-efficient GPU architectures that balance performance with battery life 🚗 Automotive systems require safety-critical processing with ASIL-B compliance 🏠 IoT endpoints demand minimal power consumption while maintaining AI capabilities 📱 Consumer electronics need flexible, programmable solutions that can adapt to evolving workloads The future isn't about one-size-fits-all processors. It's about intelligent, application-specific compute architectures that can deliver the right performance at the right power envelope. What's your take? Are we heading toward more specialized silicon, or will general-purpose processors find new ways to adapt? Article link in comments #EdgeAI #ProcessorArchitecture #GPU #SemiconductorInnovation #WeAreImagination

Grinn seals strategic partnership with MediaTek - New Electronics: Grinn, a specialist in the design of advanced IoT and embedded solutions, signs a strategic partnership with MediaTek. #iot #data #internetofthings

Energy-Efficient On-Device AI: Ambiq Apollo510B Wireless SoC The race to bring intelligence directly onto ultra-low-power devices just progressed. Ambiq’s newly announced Apollo510B SoC (Aug 2025) pushes the boundaries of what’s possible for wearables, smart sensors, and always-on AI applications. At its core, the Apollo510B integrates a 250 MHz Arm Cortex-M55 with Helium vector extensions and Ambiq’s turboSPOT® dynamic voltage scaling. The result? 30× better power efficiency and 16× faster performance compared to Cortex-M4 MCUs. But performance isn’t the only story: - 3.75 MB system RAM + 4 MB flash support larger, more capable ML models. - Built-in Bluetooth LE 5.4 and a 48 MHz network coprocessor enable robust connectivity. - Integrated graphiqSPOT GPU brings smooth 2D/2.5D graphics to resource-constrained devices. - secureSPOT 3.0 + TrustZone offer hardware-level security and OTA firmware protection. - High-fidelity audio I/O opens the door to always-listening, ultra-low-power voice assistants. The Apollo510B enters a competitive field alongside Renesas’s RA8P1 MCUs (1 GHz Cortex-M85 + Ethos-U55 NPU) and edge-focused NPUs like Axelera’s Metis M.2 Max. The spectrum is clear: from ultra-efficient MCUs powering wearables to heavy-hitting NPUs running large models at the edge. For embedded engineers and product designers, the Apollo510B allows meaningful AI on the smallest, most power-sensitive devices. Think medical wearables, industrial IoT, and edge-first consumer electronics—all benefiting from intelligence that doesn’t rely on the cloud. The Apollo510B is a signpost for where ultra-low-power AI silicon is headed. #EdgeAI #Ambiq #Apollo510B #LowPowerAI #EmbeddedML #embeddedAI

EMASS, a subsidiary of Nanoveu, has introduced the ECS-DoT, a 22nm microprocessor designed to bring milliWatt-scale intelligence directly to edge and IoT devices. #riscv #IoT

TinyML (Tiny Machine Learning) TinyML is the field of running machine learning models on ultra-low-power, resource-constrained devices (like microcontrollers). Key Points Runs on devices with kilobytes of RAM & low MHz CPUs. Enables on-device intelligence → no need to send all data to the cloud. #TinyML #AIoT #IoT #EdgeAI #MachineLearning #FutureTech #DigitalTransformation #SmartDevices #HealthcareTech #Industry40