Intrinsic announced the immediate availability of its SRAM PUF-based hardware IP “QuiddiKey for Intel FPGAs”. QuiddiKey for Intel FPGAs is device-level security IP that comes pre-integrated as part of the security infrastructure of several Intel FPGA families. It creates a more secure platform by providing access to Intrinsic ID’s SRAM PUF technology on the FPGAs. […]
Machine learning
Smart parking reference design incorporates machines learning
XMOS announced its reference solution for Automatic License Plate Recognition (ALPR), designed to move ALPR in parking garages away from complex, resource-intensive hardware and towards simple on-device AI. Developed in partnership with computing specialist Cloudtop, the reference design can read slow-moving license plates at a distance of 3-5 meters with high accuracy. Thanks to […]
Rad-hard eFPGA IP works with 90-nm rad-hard fab process
QuickLogic Corporation announced it has teamed with SkyWater Technology to make a “fast boot” rad-hard eFPGA IP available to users of SkyWater’s 90 nm rad-hard (RH90) process. This technology can be embedded as an IP core in ASIC and SoC devices or implemented as a custom rad-hard FPGA for mission-critical and/or ruggedized applications. QuickLogic’s eFPGA […]
tinyML platform supports deep learning anomaly detection
Imagimob announced that its new release of the tinyML platform Imagimob AI supports end-to-end development of deep learning anomaly detection. A big strength of deep learning anomaly detection is that it delivers high performance as well as eliminates the need for feature engineering, thus saving costs and reducing time-to-market. Not only is deep learning anomaly […]
3U OpenVPX DSP processing module features 10-core Intel Xeon D-1700 processor, Xilinx FPGA
Curtiss-Wright’s Defense Solutions introduced the CHAMP-XD3, its highest performance, security-enhanced, 3U OpenVPX digital signal processing (DSP) processing module. Based on the just-announced Intel XeonD-1700 processor, the SOSA-aligned payload card represents a “quantum leap” for sensor data processing capability in size, weight, and power (SWaP) constrained applications. The CHAMP-XD3 combines a 10-core Intel Xeon D-1700 processor for DSP […]
New memory chip includes computing capabilities
SK hynix announced that it has developed PIM*, a next-generation memory chip with computing capabilities. It has been generally accepted that memory chips store data and CPU or GPU, like a human brain, processes data. SK hynix, following its challenge to such notion and efforts to pursue innovation in the next-generation smart memory, has found […]
Machine learning ICs operate in analog domain
launched the first member of its analogML family, the AML100, which is the industry’s first and only tiny machine learning (ML) solution operating completely within the analog domain. As such, the AML100 reduces always-on system power by 95%, allowing manufacturers to dramatically extend the battery life of today’s devices or migrate walled powered always-on devices to the […]
IoT development tools work on ultra-low power PSoC 6 MCUs
Infineon Technologies AG is collaborating with SensiML for building intelligent Internet of Things (IoT) endpoints. Together they offer developers an easy and seamless process to capture data from Infineon XENSIV sensors, train Machine Learning (ML) models, and deploy real-time inferencing models directly on ultra-low-power PSoC 6 microcontrollers (MCUs). This can be completed by using the SensiML […]
AI/ML software runs on PSoC TM 6 MCUs
SensiML Corporation announced that it has teamed with Infineon Technologies to deliver a complete AI/Machine Learning (ML) solution for the Infineon PSoCTM 6 family of microcontrollers (MCUs) and the wide range of sensors they support. The collaboration combines SensiML’s Analytics Toolkit AI development software with the Infineon ModusToolboxTM and ultra-low power dual-core PSoC 6 MCUs, […]
How to improve ADAS with hardware designed to support real-time decision making
By Dustin Seetoo, Director of Product Marketing, Premio Inc. Deep learning for autonomous vehicle systems requires a blended software and hardware strategy In-step deep learning training and inference Deep learning training and deep learning inference are very different processes, each with a specific role in developing more advanced autonomous driving systems. Deep learning training taps […]
