October ’19 Startup Funding: Mega Harvest


Seventeen startups took in mega-rounds of $100 million or more during October, with a cumulative total of just over $3.2 billion. Cybersecurity startups continued to be popular with private investors during the month of October, with 15 financing rounds. Twenty automotive and mobility technology firms picked up new investments. Analytics firms, artificial intelligence/machine learning techno... » read more

Understanding Side Channel Attacks


Side channel attacks (SCAs) differ considerably from conventional cryptographic attacks. Essentially, side channel attacks – which can be very low-cost and non-invasive – exploit data gathered from side channels. A side channel can be exploited by simply placing an antenna, magnetic probe, or other sensor near a device or system. This allows an attacker to measure power consumption, voltage... » read more

Week in Review: Iot, Security, Automotive


IoT STMicroelectronics is now supporting LoRaWAN firmware updates over the air (FUOTA) in the STM32Cube ecosystem. Microsoft is adding ANSYS Twin Builder to its Microsoft Azure Digital Twins software, which companies use to create digital twins of machinery and IoT devices that are deployed in remotely. The digital replica of actual devices helps companies predict when maintenance is needed... » read more

The Last Mile


The race to autonomous driving is looking a lot less like a race these days. German automakers pushed the likely date for Level 5 autonomous driving back to 2032 from 2027, according to attendees at the International Congress for Automotive Electronics (ELIV) in Bonn last month. There are a number of reasons for this. The first is cost. The amount of processing needed to make the split-secon... » read more

Safety Islands In Safety-Critical Hardware


Safety and security have certain aspects in common so it shouldn’t be surprising that some ideas evolving in one domain find echoes in the other. In hardware design, a significant trend has been to push security-critical functions into a hardware root-of-trust (HRoT) core, following a philosophy of putting all (or most) of those functions in one basket and watching that basket very carefully.... » read more

Planning For Failures In Automotive


The automotive industry is undergoing some fundamental shifts as it backs away from the traditional siloed approach to one of graceful failure, slowing the evolution to fully autonomy and rethinking how to achieve its goals for a reasonable cost. For traditional automakers, this means borrowing some proven strategies from the electronics world rather than trying to evolve traditional automot... » read more

Traceability Of Functional Safety Requirements In Automotive IP And SoCs


By Shivakumar Chonnad, Vladimir Litovtchenko, and Rohit Bhardwaj Developing functional safety systems, including all the components such as the system-on-chip (SoC) and IP, hinges on the ability to meet the stringent automotive functional safety requirements such as definition, implementation, verification, and validation. Depending on the Automotive Safety Integrity Level (ASIL), the functi... » read more

How Does A Changing Automotive Ecosystem Affect Tier-1 Suppliers?


Tier-1 automotive suppliers have an enormous opportunity in the development of autonomous vehicles (AVs). Fortune.com sees these vehicles contributing $7 trillion in economic activity by the year 2050. But this opportunity comes with a challenge: the whole supply chain is being disrupted by new participants and new technologies that are making these AVs possible. Semiconductor companies and spe... » read more

How Secure Is Your Face?


Biometric security, which spans everything from iris scans to fingerprint sensors, is undergoing the same kind of race against hackers as every other type of sensor. While most of these systems work well enough to identify a person, there are a number of well-known ways to defeat them. One is simply to apply newer technology to cracking algorithms used inside these devices. Improvements in p... » read more

Modeling AI Inference Performance


The metric in AI Inference that matters to customers is either throughput/$ for their model and/or throughput/watts for their model. One might assume throughput will correlate with TOPS, but you’d be wrong. Examine the table below: The Nvidia Tesla T4 gets 7.4 inferences/TOP, Xavier AGX 15 and InferX 1 34.5. And InferX X1 does it with 1/10th to 1/20th of the DRAM bandwidth of the ... » read more

← Older posts