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47 articles

What are the top programming languages for machine learning?

What are the top programming languages for machine learning?

Nikhil Agnihotri August 6, 2026

Artificial intelligence (AI) and machine learning (ML) are continuing to become more mainstream and you’ll find the technology in everything from your smartphone apps and computer programs to smart tech and appliances, and automobiles (think self-driving cars). These technologies are no longer confined to scientific computing and statistical research but have, for the most part, become a…

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What are the top development boards for AI and ML?

What are the top development boards for AI and ML?

Nikhil Agnihotri August 5, 2026

Machine learning (ML) and artificial intelligence (AI) are no longer limited to high-end servers or cloud platforms. Thanks to new developments in integrated circuits (IC) and software technology, it’s possible to implement ML algorithms and deep learning neural networks on tiny controllers and microcomputers. And these embedded devices installed at edges must no longer rely…

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What’s the symbiosis between AI and solid-state transformers?

What’s the symbiosis between AI and solid-state transformers?

Jeff Shepard June 28, 2026

There’s a critical symbiosis between artificial intelligence (AI) and solid-state transformers (SSTs), especially in hyperscale data centers, green energy systems, and electric vehicle (EV) infrastructure. Those applications increasingly rely on SSTs to maximize efficiency, and SSTs use AI to monitor, manage, and optimize complex grid dynamics and power conversion. Individual AI computing clusters in hyperscale […]

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Top AI domains and career paths in 2026

Top AI domains and career paths in 2026

Nikhil Agnihotri August 4, 2026

Artificial intelligence crossed a critical threshold in 2026. AI is no longer confined to research labs or narrow pilot programs. It sits at the strategic core of nearly every major industry, with global AI spending projected to exceed $2 trillion in 2026 alone. That is a 36% year-over-year increase. Enterprise adoption has reached 88%, though…

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How to choose the ideal AI subscription in 2026

How to choose the ideal AI subscription in 2026

Nikhil Agnihotri August 4, 2026

The artificial intelligence (AI) subscription market in 2026 has become one of the most saturated categories in consumer software. Nearly every major AI assistant now starts at around $20 per month for its flagship individual plan, making it challenging for users to understand which platform actually offers the best value for their needs. ChatGPT Plus,…

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What are the top edge AI chips of 2025?

What are the top edge AI chips of 2025?

Nikhil Agnihotri July 31, 2026

Edge AI refers to deploying artificial intelligence (AI) algorithms and models directly on local devices like sensors, smartphones, or Internet-of-Things (IoT) devices. This approach includes edge computing, which processes data closer to where it’s generated rather than sending it to a centralized Cloud for analysis. According to a report by Gartner, by the end of…

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What are the types of AI chips and how are they classified?

What are the types of AI chips and how are they classified?

Nikhil Agnihotri July 25, 2026

The demand for artificial Intelligence (AI) chips is increasing due to their suitability in certain AI applications. This development mirrors the rise of Graphic Processing Units (GPUs) for 3D applications years ago. However, traditional CPUs and even GPUs often fall short in handling the unique demands of AI workloads, prompting the emergence of AI-specific chips.…

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OpenClaw is open-source edge AI for (almost) every application

OpenClaw is open-source edge AI for (almost) every application

Jeff Shepard June 29, 2026

OpenClaw is being touted as the “operating system for personal AI.” It’s being supported by a wide array of companies, including NVIDIA. Target applications range from generative and agentic AI in consumer devices like smartphones, edge applications like medical devices, and physical AI (PAI) in robotics. Formerly called Clawdbot, OpenClaw is designed to fill a […]

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RISC-V for artificial intelligence, machine learning, and embedded systems

RISC-V for artificial intelligence, machine learning, and embedded systems

Jeff Shepard June 19, 2026

Several RISC-V development efforts are targeting applications such as artificial intelligence (AI), machine learning (ML), deep learning (DL), and other high-performance embedded applications. The previous two FAQs in this series considered the capabilities of RISC-V and the near-term risks associated with the technology, and the growing availability of tools that are helping to reduce the […]

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What are the different types of AI ASICs?

What are the different types of AI ASICs?

Nikhil Agnihotri June 18, 2026

In the previous article, we discussed the different types of AI chips. Among these, ASICs play a significant role. Compared to GPUs, ASICs are faster and more power-efficient, thanks to their customized architectures designed for specific AI tasks or algorithms. One common misconception about AI ASICs is that they’re used solely for inference applications. However,…

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How does AI use sensors for object recognition?

How does AI use sensors for object recognition?

Randy Frank June 17, 2026

In addition to its use in facial recognition, artificial intelligence (AI) also plays a critical role in advancing object recognition. Perhaps one of key and leading-edge applications for AI is in image recognition and diagnostics in healthcare. According to a technology assessment report published by the U.S. Government Accountability Office (GAO) with content from the […]

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How do sensors play into AI’s facial recognition capabilities? Part 1

How do sensors play into AI’s facial recognition capabilities? Part 1

Randy Frank June 17, 2026

Among the growing number of applications for artificial intelligence (AI) is advanced imaging capabilities for reliable facial recognition. Reliability is required for effective analysis by law enforcement agencies, access to commercial or industrial complexes, travel, or even a homeowner. While AI enables complex analysis and performs it in a remarkably short timeframe, effective analysis requires […]

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How does artificial intelligence relate to immersive audio?

How does artificial intelligence relate to immersive audio?

Jeff Shepard June 17, 2026

Tools like neural networks (NNs), machine learning (ML), and artificial intelligence (AI) are being applied to hard problems related to immersive audio. This FAQ will examine how NNs and ML are being used to up-mix audio tracks into their original constituent parts, how NNs are being used to produce personalized head-related transfer functions (HRTFs) and […]

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How TLVRs support extreme power demands in AI datacenters

How TLVRs support extreme power demands in AI datacenters

Jeff Shepard June 26, 2026

Trans inductor voltage regulators, occasionally referred to as transient load voltage regulators, (TLVRs) use coupled inductors with an additional secondary winding to create a series-connected secondary loop, allowing all phases to react simultaneously to load changes. That enables TLVRs to support the extreme power demands of GPUs in AI datacenters, and as detailed below, they […]

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What kinds of PAI dev kits are available for humanoid robotics?

What kinds of PAI dev kits are available for humanoid robotics?

Jeff Shepard June 17, 2026

Physical artificial intelligence (PAI) development kits for humanoid robotics range from high-end, industrial-grade platforms to prosumer and educational, modular do-it-yourself (DIY) kits, Raspberry Pi-based options, and more. Some kits are suited for specific functions like walking and navigation, using AI to understand natural language, sensor fusion, power conversion, and motion control, and handling objects in […]

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What are the applications of physical artificial intelligence?

What are the applications of physical artificial intelligence?

Jeff Shepard May 12, 2026

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 […]

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What are the top machine-learning frameworks for microcontrollers

What are the top machine-learning frameworks for microcontrollers

Nikhil Agnihotri July 29, 2026

Machine learning (ML) is becoming increasingly important for microcontrollers because it enables smart and autonomous decision-making in embedded systems. The many Internet of Things (IoT) applications, often called “smart devices”, only become intelligent thanks to ML. Microcontrollers are commonly used in edge computing devices where data is processed locally rather than being sent…

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What AI acceleration techniques are used for embedded devices?

What AI acceleration techniques are used for embedded devices?

Nikhil Agnihotri June 29, 2026

Artificial Intelligence (AI) is no longer confined to data centers. Today, AI is widely used and implemented in edge devices, smartphones, and embedded systems. This has been made possible through hardware and software acceleration methods that work together within embedded systems. It’s now feasible to run small machine-learning models on low-power, resource-constrained microcontroller units without…

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How to calculate efficiency across the AI power chain

How to calculate efficiency across the AI power chain

Jeff Shepard June 27, 2026

Like many aspects of artificial intelligence (AI), there’s not a single approach when calculating efficiency across the AI power chain. It depends on where you look. Are the calculations related to the facility layer, the compute and hardware layer, or the workload and algorithm layer? At the facility level, efficiency is discussed in terms of […]

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How does the open domain-specific architecture relate to chiplets and generative AI?

How does the open domain-specific architecture relate to chiplets and generative AI?

Jeff Shepard June 17, 2026

The Open Domain-Specific Architecture (ODSA) is a project within the Open Compute Project (OCP) community to establish open physical and logical die-to-die (D2D) interfaces for chiplets. The goal is to democratize the design and use of chiplets for domain-specific high-performance computing (HPC) applications like generative artificial intelligence (AI). Domain-specific architectures (DSAs) are an emerging approach […]

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What is new in UCIe 3.0?

What is new in UCIe 3.0?

Jeff Shepard June 4, 2026

Universal Chiplet Interconnect Express (UCIe) 3.0 is focused on increased bandwidth, improved power efficiency, and enhanced system-level management for next-generation chiplet-based designs. It’s designed to support artificial intelligence and high-performance computing while maintaining backward compatibility with UCIe 2.0 and 1.0.

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How ML and AI work in power conversion: part 2

How ML and AI work in power conversion: part 2

Jeff Shepard May 28, 2026

This article digs into how machine learning (ML) and artificial intelligence (AI) contribute to the optimization of green energy systems and electric vehicles (EVs). It looks at a few of the ways ML/AI enable designers to deploy dynamic models that learn from experience, and handle non-linearities and changing, complex conditions better than fixed algorithms. Part […]

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How do ML and AI work in power conversion? part 1

How do ML and AI work in power conversion? part 1

Jeff Shepard May 28, 2026

The use of machine learning (ML) and artificial intelligence (AI) in power converters represents the latest development in the field of digital power. They are being used in advanced converter control schemes, performance monitors of electrolytic capacitors to support preventative maintenance, and power management systems to improve efficiency and enhance reliability.

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How can AI enhance DVFS in processor power management?

How can AI enhance DVFS in processor power management?

Jeff Shepard May 28, 2026

Dynamic voltage and frequency scaling (DVFS) is a common energy-saving technique used in computer processor ICs based on the quadratic relationship between power consumption and operating voltage and the linear relationship between power consumption and frequency. It reacts to changing operating demands on the processor to minimize energy consumption. The addition of artificial intelligence (AI) […]

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How do AI agents and model context protocol work together?

How do AI agents and model context protocol work together?

Jeff Shepard May 13, 2026

An AI agent, combined with a model context protocol (MCP), can create more contextual AI systems that can perform a wide range of tasks, from automating processes to providing insights and interacting with users. MCP helps AI agents connect to data sources, enabling them to access information, collaborate with other systems, and make decisions based on real-time data.

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What type of interconnects and connectors link accelerator cards in AI data centers?

What type of interconnects and connectors link accelerator cards in AI data centers?

Aharon Etengoff May 13, 2026

Many data centers are packed with racks of high-performance graphics processing units (GPUs) and tensor processing units (TPUs). These accelerators process massive artificial intelligence (AI) and machine learning (ML) datasets, executing complex operations in parallel and exchanging data at high speed. This article explores the interconnects and connectors that link AI accelerator clusters together.

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How do heterogeneous integration and chiplets support generative AI?

How do heterogeneous integration and chiplets support generative AI?

Jeff Shepard June 17, 2026

Chiplets are here, and more are coming. They can overcome the yield limitations of large ASICs, support a mix-and-match strategy for heterogeneous semiconductor IPs and multiple process nodes, improve thermal performance, and speed time to market. They are being used in a range of high-performance computing (HPC) applications, notably generative artificial intelligence (AI) and machine […]

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How twin axial cable assemblies support high-performance computing for AI/ML systems

How twin axial cable assemblies support high-performance computing for AI/ML systems

Jeff Shepard June 17, 2026

The high-performance computing platforms used for artificial intelligence (AI) and machine learning (ML) in hyperscale data centers need high-speed interconnects like 112 Gbps PAM 4 and faster inside the servers. High-speed interconnects are also required between the servers and storage devices. Twin axial (Twinax) cable assemblies are one way to address those needs. This article […]

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Beyond SDVs: how AI optimizes electric vehicles

Beyond SDVs: how AI optimizes electric vehicles

Aharon Etengoff June 17, 2026

Many automotive manufacturers classify new cars and trucks as software-defined vehicles (SDVs). As SDVs by design, electric vehicles (EVs) optimize vital systems and functions with sophisticated artificial intelligence (AI) and machine learning (ML) capabilities. This article discusses AI’s crucial role in EVs, from smart charging and advanced driver assistance systems (ADAS) to predictive maintenance and…

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Accelerating high-performance AI workloads with photonic chips

Accelerating high-performance AI workloads with photonic chips

Aharon Etengoff May 13, 2026

Artificial intelligence (AI) and machine learning (ML) continue to push the limits of conventional semiconductor architectures. To increase speeds, lower latency, and optimize power consumption for high-performance workloads, semiconductor companies, and research institutions are developing advanced photonic chips that operate on the principles of light rather than electrical currents.

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How to approach AI hardware design to address the memory wall?

How to approach AI hardware design to address the memory wall?

Rakesh Kumar May 13, 2026

The transition from general-purpose computing to AI-specific hardware is driven by the specific computational and energy requirements of deep learning models. As these models scale to trillions of parameters, traditional architectures face the memory wall, where the energy required for data movement between memory and processing units significantly exceeds the energy consumed by the computation itself.

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How does the IEEE MagNet Challenge use AI for power magnetics modeling?

How does the IEEE MagNet Challenge use AI for power magnetics modeling?

Jeff Shepard March 27, 2026

The IEEE Power Electronics Society (PELS) Google-Tesla MagNet Challenge is an annual competition. It’s designed to accelerate innovation in magnetic modeling using artificial intelligence (AI). This article reviews some of the highlights from the first two MagNet Challenges in 2023 and 2024. The first installment ran from February to December 2023, with the winners announced […]

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How to approach AI hardware design to address the memory wall?

How to approach AI hardware design to address the memory wall?

Rakesh Kumar May 13, 2026

The transition from general-purpose computing to AI-specific hardware is driven by the specific computational and energy requirements of deep learning models. As these models scale to trillions of parameters, traditional architectures face the memory wall, where the energy required for data movement between memory and processing units significantly exceeds the energy consumed by the computation itself.

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