Can AI Create Missing Models?


Key takeaways Models are an essential part of EDA flows, each capturing necessary detail while retaining good execution performance. Models have been expensive to create, maintain and verify, restricting their utilization, but AI may be able to significantly reduce their cost. A deeper question remains. Should AI be used to create models that help existing flows, or should AI be used... » read more

Creating Agentic EDA Methodologies


Key takeaways Agentic methodologies need to be able to reason across multiple data formats and abstractions. It is not clear how much data from previous designs is useful in new designs. Standards may help, but the lack of them may only impact cost. The relationship between tools and methodologies is bidirectional. Tools enable methodologies, and methodologies are dependent ... » read more

Startup Funding: Q1 2026


The new year started off with a bang for private semiconductor companies, with 18 garnering mega funding rounds exceeding $100 million, and two, Rapidus and Cerebras, reaching the $1 billion mark. Predictably, the vast majority of those are either designing chips primarily for AI inference workloads or attempting to overcome bandwidth limitations by improving interconnects from the chip level t... » read more

Chip Industry Week In Review


Arm uncorked its first internally developed CPU chip this week, aimed squarely at the agentic AI data center market. Arm CEO Rene Haas (pictured) emphasized the CPU's power efficiency and performance/watt compared to other AI processor architectures. "We are obsessed with efficiency, and if you think about one of the biggest appeals that Arm has had over the years, it is power profile," he ... » read more

Using Data And AI More Effectively In EDA


Key Takeaways The data being produced by EDA tools tends to be for human consumption and has weak semantics. Agents are attempting to create actionable information from unstructured data. The Model Context Protocol may provide AI with access to better data. Semiconductor design generates a lot of data, but how much of that is useful or currently being used by AI tools? And h... » read more

Chip Industry Week In Review


Big deals and fundings Teradyne and MultiLane are forming a joint venture, MultiLane Test Products (MLTP), to accelerate the development of test solutions for high speed data connections.  Teradyne will be the majority owner. Ricursive Intelligence raised $300M Series A for AI-driven IC design. IonQ plans to acquire SkyWater for ~$1.8B, creating a "vertically integrated full-stack q... » read more

AI Plays Multiple Roles Within EDA


AI's infusion into our world may seem sudden and unexpected, but EDA has been quietly adopting it for more than a decade. What's changed is that it's now becoming more visible, thanks to increasingly powerful large language models (LLMs) and the need to apply them to increasingly challenging multi-physics problems. Two fundamental shifts underlie AI's increasing prominence. First, heat is be... » read more

The Limits Of AI’s Role In EDA Tools


The world has been inspired by generative AI models like ChatGPT. These are very applicable to things like copilots and agentic AI, but the adoption of these models into EDA tools is less obvious. What may be appropriate, and can AI make EDA tools faster or better? EDA has been enabling Moore's Law for the past 40 years, and that has required pushing the limits of many of the algorithms and ... » read more

Chip Industry Week in Review


Lines are blurring between government and industry: On the heels of last week's resignation demand, Intel CEO Lip-Bu Tan met with President Trump on Monday, with the President later saying, "The meeting was a very interesting one. His success and rise is an amazing story."  Now, Bloomberg reports the Trump administration is in talks with Intel for the U.S. government to take a stake in th... » read more

Re-Architecting AI For Power


The industry is becoming increasingly concerned about the amount of power being consumed by AI, but there is no simple solution to the problem. It requires a deep understanding of the application, the software and hardware architectures at both the semiconductor and system levels, and how all of this is designed and implemented. Each piece plays a role in the total power consumed and the utilit... » read more

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