Siemens has introduced the Fuse EDA AI Agent, an autonomous system designed to plan and orchestrate complex workflows across the entire electronic design automation (EDA) lifecycle. By integrating with existing tools for RTL coding, physical implementation, and manufacturing sign-off, the agent automates multi-step tasks that previously required extensive manual scripting. This domain-specific approach allows the […]
Artificial Intelligence
Agentic AI toolkit accelerates RTL verification and debug workflows
Siemens has introduced the Questa One Agentic Toolkit, adding domain-scoped agentic AI workflows to its verification portfolio to improve RTL design and verification efficiency. The toolkit deploys autonomous agents for RTL code generation, linting, clock-domain crossing analysis, verification planning, and debug. These agents operate within defined governance boundaries and integrate directly with existing verification tools, […]
AI’s demand for faster, more reliable IC testing
Artificial intelligence (AI) models are being applied to almost everything, from helping people write emails to microcontrollers understanding the meaning of IoT sensor data at the edge of the network. This is creating massive demand for AI computing resources, particularly CPUs, GPUs, and xPUs used in data centers to train and run large language models. […]
What are attention mechanisms, and how do they work in speech and audio processing?
Attention mechanisms are very useful innovations in the field of artificial intelligence (AI) for processing sequential data, especially in speech and audio applications. This FAQ talks about how attention mechanisms work at their core, how they are used in automatic speech recognition systems, and how transformer architectures can handle advanced audio processing. What are the […]
Understanding ADC specs and architectures: part 1
Analog-to-digital converters are the heart of most test equipment, setting the stage for the digital processing of analog signals. Several posts over the past year or so have involved digital signal processing. For example, we have covered the fast Fourier transform (FFT), the inverse FFT, and discrete convolution. To perform these operations on real-world signals, […]
9 mm square module achieves -100 dBm receive sensitivity
Insight SIP is launching the ISP2554-HM module. This module represents a dynamic IOT node, with support for Bluetooth Low Energy, Thread, and Zigbee radios and high-performance computing including an ability to run AI at the Edge. It can thus form the core of a complex IOT device with an unparalleled mixture of features, performance, and […]
How AI and ML optimize functional verification for EDA
Functional verification ensures that the register transfer layer (RTL) implementation of semiconductor designs operates according to specified requirements. Electronic engineers typically perform functional verification using hardware verification languages (HVLs) such as SystemVerilog paired with the universal verification methodology (UVM). Other HVLs, such as VHSIC Hardware Description Language (VHDL) and Property Specification Language (PSL), may be […]
EE Training Days kicks-off 2025 with The A to Z of Multi-die Design
Did you know that multi-die architectures now represent over 50% of new semiconductor designs, marking a significant shift in chip development strategy? It’s true. There’s now a clear trend towards more multi-die designs, especially in data center, AI, and server applications where the complexity of the chips is too large to fit on a single […]
What are the different types of AI accelerators?
Whether in data centers or at the edge, artificial intelligence (AI) accelerators address the limitations of traditional von Neumann architecture by rapidly processing massive datasets. Despite the gradual slowing of Moore’s law, these accelerators efficiently enable key applications such as generative AI (GenAI), deep reinforcement learning (DRL), advanced driver assistance systems (ADAS), smart edge devices, […]
How do generative AI, deep reinforcement learning, and large language models optimize EDA?
Artificial intelligence (AI) and machine learning (ML) are playing an increasingly crucial role in optimizing electronic design automation (EDA) across the semiconductor industry. This article explores the rising complexity and costs of designing chips at advanced nodes. It highlights how generative AI (GenAI) and deep reinforcement learning (DRL) help semiconductor companies accelerate time to market […]
