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Large language models are machine learning models trained to predict and generate text and other language-based outputs.
The explosive growth of large language models (LLMs) has created substantial new requirements for chip-to-chip interconnects. These very large models are trained in high-performance data centers. Multiple accelerators need…
…Generic LLMs (and even models fine-tuned on proprietary engineering data) cannot capture the deep, experience-based knowledge verification engineers apply when diagnosing failures on real silicon. Runtime context from the live…
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…The headline figure of $31.3B … CEO Interview with Nagesh Gupta of llmda.ai by Daniel Nenni on 05-15-2026 at 6:00 am View Forum Posts View Articles Private Message…
…Researchers and commercial EDA vendors are increasingly using large language models (LLMs), graph neural networks (GNNs), and reinforcement learning algorithms to optimize chip development flows and reduce time-to-market. Recent academic…
…qualifying LLM behavior with customers to prevent hallucinated commands or inconsistent results before any skill ships to end users. The Demo: From One Prompt to a Fully Integrated SoC The most compelling…
…He also led the first industrial LLM-for-chip-design effort, ChipNeMo. His work spans design automation across digital, analog, and PCB, and has been recognized with two DAC Best Paper Awards…
Daniel is joined by Nagesh Gupta, CEO of llmda.ai. Nagesh has built a career spanning multiple aspects of system design and development at companies including Hewlett-Packard, Cadence, Xilinx, and Lattice…
…A solid understanding of modern machine-learning primitives and LLMs. A background in Python, modern AI frameworks and ecosystem (e.g., Torch, HuggingFace, llama.cpp, etc.). Requirements listed would be obtained through…
…Running on a Linux KVM virtualization platform, the system launched two virtual machines, each executing a Large Language Model (LLM) based on the Llama2 architecture. The live demo highlighted TinyStories, a lightweight…