The semiconductor industry is entering a transformative new phase, driven by the convergence of artificial intelligence, cloud computing, and increasingly complex chip architectures. That message took center stage during the keynote talks at the Siemens EDA User2User 2026 North America conference. Executives from Siemens,… Read More
Agentic AI is often presented as a revolutionary shift in semiconductor manufacturing, driven by large language models and generative AI. However, this framing overlooks an important reality: today’s advances are built on decades of prior work. As Jonathan Holt of PDF Solutions emphasizes in his recent keynote at the APCM 2026… Read More
Agentic AI is emerging as a transformative paradigm in semiconductor design and manufacturing, driven by the exponential growth in data, system complexity, and performance demands. Modern semiconductor fabs generate massive volumes of heterogeneous data at unprecedented velocity. For instance, a single minute of operation
Agentic AI emerges in this Synopsys Converge keynote not as a futuristic add-on, but as a practical response to the growing complexity of engineering. In the speaker’s view, the traditional way of designing chips, systems, and intelligent products is no longer sufficient for the era of physical AI. Engineers are now dealing with… Read More
In a break from our academic-centric picks, here we look at an agentic verification flow developed within a semiconductor company. Paul Cunningham (GM, Verification at Cadence), Raúl Camposano (Silicon Catalyst, entrepreneur, former Synopsys CTO and lecturer at Stanford, EE292A) and I continue our series on research ideas.… Read More
NetApp recently hosted a webinar on Agentic AI as the future for EDA and implications for infrastructure. Good list of panelists including Mahesh Turaga (VP Cadence Cloud) with an intro preso on infrastructure and agentic AI at Cadence, then our own Dan Nenni (Mr. SemiWiki) moderating, Khaled Heloue (Fellow AMD, CAD CAD/Methodology/AI),… Read More
Custom IC design has demanding technical requirements to produce accurate simulation results for timing and power analysis in the shortest run times. EDA vendors have been rushing to use AI and ML technology to meet these analysis requirements. I attended a webinar from Siemens on accelerating iterative design cycles with Solido… Read More
I have seen a lot of EDA tool demos in my time. More than I want to admit. The perceived quality of the demo usually came down to a combination of the speed of the tool, quality of results and the ease of navigating through the graphical user interface. For the last item, how easy the interface was on the eyes, how clear were the relationships… Read More
For decades, chip design has been a delicate balance of creativity and drudgery. Architects craft detailed specifications, engineers read those documents line by line, and teams write and debug thousands of lines of Verilog and UVM code. Verification alone can consume up to 35 percent of a project’s cost and add many months to … Read More
In the business press today I still find a preference for reporting proof-of-concept accomplishments for AI applications: passing a bar exam with a top grade, finding cancerous tissue in X-rays more accurately than junior radiologists, and so on. Back in the day we knew that a proof-of-concept, however appealing, had to be followed… Read More
