Search Results for : Neural Processing Unit

Portland-based embedded device manufacturer Wilderness Labs has introduced the Meadow F7 Core-Compute System on Module based on the popular F7 Feather microcontroller development board. The hardware is aimed to expand the reach of the IoT platform to enable the 10MM+ .NET developer...

There have been several recent developments around TinyML and edge AI applications, and to supply the increasing demand from the developer community, many embedded electronic device manufacturers around the world are designing AI development boards. Beijing-based online embedded...

After the hype around BeagleBoard Foundation’s BeagleV StarFive RISC-V SBC, the cancellation came as a shock to the embedded developers' space. However, as an alternative to the original RISC-V single-board computer and continuing most of its features, StarFive unveiled the VisionFive...

Wireless power network provider, Energous Corporation, has revealed its association with Syntiant, to develop Energous’ WattUp wireless power network technology with Syntiant’s Neural Decision Processors (NDPs) for edge artificial intelligence deployments across a wide range of...

SMART Wireless Computing, Inc., an SGH company and leading provider of edge computing embedded solutions, today announced the Inforce 68A1 system-on-module (SoM), a powerful new tool based on one of the latest and most advanced IoT solutions from Qualcomm Technologies, Inc., the...

The conventional style of using network connectivity in bringing artificial intelligence models to improve performance and efficiency needs some modification to meet the demands from the embedded systems to the automobile industry. Before directly jumping to the role of AI inference at...

We have come across multiple hardware development boards and MCUs that employ Edge AI for processing and computing. On the other hand, cloud computing was traditionally preferred as an alternative for implementation due to its scalability and easier to develop applications on the cloud...

For real-time AI applications, it is important to process incoming data using a trained neural network model. For faster data processing, the introduction to AI inference at cloud did support many aspects, increasing efficiency, but the need to process the data at the end device has...