As artificial intelligence continues to shape everything from autonomous vehicles to personal health monitors, the trustworthiness of AI increasingly depends on what lies deep beneath the software: the chip itself.
What Does Chip Reliability in AI Systems Truly Entail?
“AI systems are only as reliable as the semiconductors that power them,” says Vijayaprabhuvel Rajavel, a veteran semiconductor architect and Technical Lead at HCL America. Speaking at a recent industry forum, Rajavel emphasized that public safety risks can arise not just from flawed algorithms, but from the hardware running them.
Rajavel, an IEEE Senior Member and recipient of the Cases & Faces award, has helped shape up next-generation chip design through his work in Design for Testability (DFT). His career includes significant roles at Cadence Design Systems, Samsung, and Alphawave Semi, where he has helped ensure that chips used in wireless, industrial robots, networking products, and healthcare devices perform flawlessly under real-world stress.
“People often overlook the fact that chips don’t operate in a lab, they face heat, pressure, and constant loads,” Rajavel noted.
How Does It Impact Everyday Technology?
“Even minor defects can create failure points in mission-critical AI applications.”
While leading DFT product development at Cadence Design Systems, Rajavel boosted scan coverage from four percent to over ninety-six percent on an advanced 18A chip, a leap that improved fault detection for AI-enabled hardware. His work not only secured key clients and revenue for the company, but also raised the bar for reliability in semiconductor testing.
During his tenure, Rajavel managed a broad portfolio of accounts, from startups to major semiconductor firms, resolving critical technical issues, managing timely product feature releases, and optimizing test flows for next-generation chip designs. He was recognized with awards like Creator, Explorer, and Team Player for driving innovation and customer success.
With AI devices now integral to public infrastructure and private life, experts warn that chip reliability is no longer just a technical concern, it’s a societal one.
“Everyday users might not see chip flaws, but the consequences can be serious, a robot that misplaces a component, a health tracker that misses a heartbeat, or a smart grid that mismanages power,” Rajavel explained.
What Can Be Done to Mitigate Risks?
He recommends three critical practices to mitigate risks:
● Stick with trusted brands: “Reputable manufacturers invest heavily in long-term safety and rigorous chip testing.”
● Keep devices updated: “Firmware updates aren’t optional, they often fix flaws that could cause system failures.”
● Be informed: “Understand the devices you’re using. Responsible use goes hand in hand with responsible design.”
For Rajavel, AI safety begins at the transistor level. As AI systems evolve, he believes public trust will hinge on how well engineers can embed resilience into the silicon itself. Reliability can’t be an afterthought.
“If we want smarter machines, we need smarter, safer chips,” he concludes.
