Why It’s So Hard To Secure AI Chips


Demand for high-performance chips designed specifically for AI applications is spiking, driven by massive interest in generative AI at the edge and in the data center, but the rapid growth in this sector also is raising concerns about the security of these devices and the data they process. Generative AI — whether it's OpenAI’s ChatGPT, Anthropic’s Claude, or xAI’s Grok — sifts thr... » read more

AI For Data Management


Data management is becoming a significant new challenge for the chip industry, as well as a brand new opportunity, as the amount of data collected at every step of design through manufacturing continues to grow. Exacerbating the problem is the rising complexity of designs, many of which are highly customized and domain-specific at the leading edge, as well as increasing demands for reliabili... » 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

Securing AI In The Data Center


AI has permeated virtually every aspect of our digital lives, from personalized recommendations on streaming platforms to advanced medical diagnostics. Behind the scenes of this AI revolution lies the data center, which houses the hardware, software, and networking infrastructure necessary for training and deploying AI models. Securing AI in the data center relies on data confidentiality, integ... » read more

Overcoming Chiplet Integration Challenges With Adaptability


Chiplets are exploding in popularity due to key benefits such as lower cost, lower power, higher performance and greater flexibility to meet specific market requirements. More importantly, chiplets can reduce time-to-market, thus decreasing time-to-revenue! Heterogeneous and modular SoC design can accelerate innovation and adaptation for many companies. What’s not to like about chiplets? Well... » read more

Earning Digital Trust


The internet of things (IoT) has been growing at a fast pace. In 2023, there were already double the number of internet-connected devices – 16 billion – than people on the planet. However, many of these devices are not properly secured. The high volume of insecure devices being deployed is presenting hackers with more opportunities than ever before. Governments around the world are realizin... » read more

2024 Open Source Risk In M&A By The Numbers


Here’s what we know: Most of today’s codebases contain open source components. Vulnerabilities and licensing issues in codebases are as pervasive as open source itself. Unpatched software vulnerabilities are one of the biggest cyberthreats organizations face. Failure to comply with open source licenses can put businesses at significant risk of litigation and threat to IP. T... » read more

Adapting To Evolving IC Requirements


As chip designs become increasingly heterogeneous and domain-specific, packing a device with one-size-fits-all chips or chiplets doesn't make sense. The key is rightsizing different components based on real workloads, so they don't waste power when there is too little utilization of logic, and so they don't struggle to complete tasks because they are undersized. Jayson Bethurem, vice president ... » read more

Research Bits: April 30


Sound waves in optical neural networks Researchers from the Max Planck Institute for the Science of Light and Massachusetts Institute of Technology found a way to build reconfigurable recurrent operators based on sound waves for photonic machine learning. They used light to create temporary acoustic waves in an optical fiber, which manipulate subsequent computational steps of an optical rec... » read more

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