Running More Efficient AI/ML Code With Neuromorphic Engines


Neuromorphic engineering is finally getting closer to market reality, propelled by the AI/ML-driven need for low-power, high-performance solutions. Whether current initiatives result in true neuromorphic devices, or whether devices will be inspired by neuromorphic concepts, remains to be seen. But academic and industry researchers continue to experiment in the hopes of achieving significant ... » read more

Power/Performance Costs In Chip Security


Hackers ranging from hobbyists to corporate spies and nation states are continually poking and prodding for weaknesses in data centers, cars, personal computers, and every other electronic device, resulting in a growing effort to build security into chips and electronic systems. The current estimate is that 60% of chips and systems have some type of security built in, and that percentage is ... » read more

Securing The World’s Data: A Looming Challenge


A combination of increasingly complex designs, more connected devices, and a mix of different generations of security technology are creating a whole new set of concerns about the safety of data nearly everywhere. While security experts have been warning of a growing threat in electronics for decades, there have been several recent fundamental changes that elevate the risk. Among them: ... » read more

Blog Review: May 15


Cadence's Anika Sunda suggests that RISC-V has opened numerous doors for innovation and believes EDA tools can help bridge the knowledge gap and foster a growing community of RISC-V developers. Synopsys' Alessandra Costa chats with industry experts about challenges facing analog design, what's needed for multi-die designs, and the potential of AI. Siemens' Bill Ji explains why understandi... » read more

Ambient Intelligence eBook


Get the lowdown on future ambient computing use cases and benefit from simple considerations you can build into your product roadmap today to ensure your platform is ready to capitalise on this burgeoning trend. This tech trends guide covers: Laying the foundations for ambient experiences Future use cases Challenges facing ambient computing use cases Six considerations to addre... » read more

Using AI/ML To Combat Cyberattacks


Machine learning is being used by hackers to find weaknesses in chips and systems, but it also is starting to be used to prevent breaches by pinpointing hardware and software design flaws. To make this work, machine learning (ML) must be trained to identify vulnerabilities, both in hardware and software. With proper training, ML can detect cyber threats and prevent them from accessing critic... » read more

Software-Defined Vehicle Momentum Grows


Experts at the Table: The automotive ecosystem is undergoing a transformation toward software-defined vehicles, spurring new architectures with more software. Semiconductor Engineering sat down to discuss the impact of these changes with Suraj Gajendra, vice president of products and solutions in Arm's automotive line of business; Chuck Alpert, R&D automotive fellow at Cadence; Steve Spadon... » read more

Blog Review: May 8


Synopsys' Manuel Mota and Michael Posner look to UCIe as a complete stack for the die-to-die interconnect in multi-die chip designs, finding it can help maintain latency while reducing power and enhancing performance along with providing assurance of interoperability. Cadence's Durlov Khan highlights the Octal SPI interface for serial NAND flash, which enables 8-bit wide high bandwidth synch... » read more

Blog Review: May 1


Cadence's Vatsal Patel stresses the importance of having testing and training capabilities for high-bandwidth memory to prevent the entire SoC from becoming useless and points to key HBM DRAM test instructions through IEEE 1500. In a podcast, Siemens' Stephen V. Chavez chats with Anaya Vardya of American Standard Circuits about the growing significance of high density interconnect and Ultra ... » read more

Dealing With AI/ML Uncertainty


Despite their widespread popularity, large language models (LLMs) have several well-known design issues, the most notorious being hallucinations, in which an LLM tries to pass off its statistics-based concoctions as real-world facts. Hallucinations are examples of a fundamental, underlying issue with LLMs. The inner workings of LLMs, as well as other deep neural nets (DNNs), are only partly kno... » read more

← Older posts Newer posts →