Physical AI (PAI) in autonomous and electric vehicles (EVs) involves systems that perceive the environment, make intelligent decisions, and execute appropriate actions in real-time, bridging the gap between digital intelligence and physical motion. PAI is autonomous, and electric vehicles can be used for several functions. Initially, it’s helping improve battery management and energy efficiency. In […]
What are the applications of physical artificial intelligence?
Physical artificial intelligence (PAI) enables machines to perceive, reason, and act within the real world, bridging the gap between digital AI (DAI), sometimes called virtual AI, and physical action. PAI often leverages spatial artificial intelligence (SAI) technology. PAI applications span numerous industries, from basic automation to autonomous vehicles and complex surgical procedures. PAI applications represent […]
What is physical artificial intelligence and why is it important?
Physical artificial intelligence (PAI) refers to AI systems that can perceive, understand, reason about, and interact with the physical world in real time through sensors and actuators. Unlike digital AI (DAI), which operates in virtual domains, PAI powers tangible actions in dynamic, real-world environments. PAI is used in closed-loop systems where the AI model not […]
MCUs and MPUs, which does your project really need?
The basics of microcontroller units (MCUs) and microprocessor units (MPUs) haven’t changed too much. But application requirements have. What was once a simple automotive, industrial, or medical control system may now include edge AI processing, increasingly demanding security requirements, or complex 3D animated human machine interfaces (HMIs). That can change the game when choosing between […]
How is a transformer used in neural networks?
Transformers are a neural network (NN) architecture, or model, that excels at processing sequential data by weighing the importance of different parts of the input sequence. This allows them to capture long-range dependencies and context more effectively than previous architectures, leading to superior performance in natural language processing (NLP) tasks like translation and in computer […]
A practical guide to microcontroller structure and performance factors
Microcontroller units (MCUs) are single-chip computers optimized for performing embedded computing tasks like controlling a coffee machine or a medical device, an industrial robot, or an electric vehicle battery charger. They don’t require a complex operating system (OS) like those found on personal computers and servers. The central processing unit (CPU) is a key element […]
Reimagining EV design with AI-enhanced EDA tools
Artificial intelligence (AI)-driven chatbots, tools, and techniques are being deployed across various stages of electric vehicle (EV) design and simulation to support validation and manufacturing. AI can be used as an assistant to increase the effectiveness of conventional EDA tools. When combined with data-driven methods, it can also be used to create reduced-order models (ROMs) […]
Are there any benefits from generative AI hallucinations?
Generative artificial intelligence (AI) hallucinations, where an AI delivers incorrect or fabricated information, can offer benefits, especially in creative and exploratory domains like drug discovery. There are four common types of AI hallucinations (Figure 1). Not all types are equally desirable or useful. General contradictions include context conflicts and sentence contradictions. For example, an AI […]
Why is the Matter 1.4.2 update important?
Matter 1.4.2 is a maintenance release that improves security, streamlines certification, and optimizes infrastructure operation. This article presents only highlights. In addition to improving certain areas of performance, it adds more new features than most maintenance releases. And, like most maintenance releases, it addresses issues found in previous versions and fine-tunes operations to improve reliability, […]
When should you use RAG, TAG, and RAFT AI?
Retrieval-augmented generation (RAG) and table-augmented generation (TAG) are both techniques to improve the ability of artificial intelligence (AI) to generate accurate and relevant information by leveraging external data. Other choices include retrieval-augmented fine-tuning (RAFT) and retrieval-centric generation (RCG). Understanding when to use RAG, TAG, RAFT, and RCG can be crucial to successful and efficient AI […]
