Paul Karazuba

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Paul Karazuba is vice president of marketing at Expedera.

Author's Latest Posts

Next Generation AI: Transitioning Inference From The Cloud To The Edge
By Paul Karazuba - 11 Dec, 2025 - Comments: 0

AI inference deployments are increasingly focused on the edge as manufacturers seek the consistent latency, enhanced privacy, and reduced operational costs they can’t achieve in cloud-based deployments. While cloud-based platforms provide incredible computational power and enable widely adopted services, the dependence on network connectivity inherently creates variability, cost and security ... » read more

Transformers At The Edge: Efficient LLM Deployment
By Paul Karazuba - 17 Jul, 2025 - Comments: 0

Since the groundbreaking 2017 publication of “Attention Is All You Need,” the transformer architecture has fundamentally reshaped artificial intelligence research and development. This innovation laid the foundation for Large Language Models (LLMs) and Video Language Models (VLMs), fueling a wave of productization across the industry. A defining milestone was the public launch of ChatGPT in... » read more

Small Language Models: A Solution To Language Model Deployment At The Edge?
By Paul Karazuba - 18 Nov, 2024 - Comments: 0

While Large Language Models (LLMs) like GPT-3 and GPT-4 have quickly become synonymous with AI, LLM mass deployments in both training and inference applications have, to date, been predominately cloud-based. This is primarily due to the sheer size of the models; the resulting processing and memory requirements often overwhelm the capabilities of edge-based systems. While the efficiency of Exped... » read more

Unlocking The Power Of Edge Computing With Large Language Models
By Paul Karazuba - 30 Oct, 2023 - Comments: 0

In recent years, Large Language Models (LLMs) have revolutionized the field of artificial intelligence, transforming how we interact with devices and the possibilities of what machines can achieve. These models have demonstrated remarkable natural language understanding and generation abilities, making them indispensable for various applications. However, LLMs are incredibly resource-intensi... » read more

Generative AI: Transforming Inference At The Edge
By Paul Karazuba - 24 Aug, 2023 - Comments: 0

The world is witnessing a revolutionary advancement in artificial intelligence with the emergence of generative AI. Generative AI generates text, images, or other media responding to prompts. We are in the early stages of this new technology; still, the depth and accuracy of its results are impressive, and its potential is mind-blowing. Generative AI uses transformers, a class of neural network... » read more

A Buyers Guide To An NPU
By Paul Karazuba - 22 Jun, 2023 - Comments: 2

Choosing the right AI inference NPU (Neural Processing Unit) is a critical decision for a chip architect. There’s a lot at stake because as the AI landscape constantly changes, the choices will impact overall product cost, performance, and long-term viability. There are myriad options regarding system architecture and IP suppliers, and this can be daunting for even the most seasoned semicondu... » read more

An Ideal Always-Sensing Subsystem Architecture
By Paul Karazuba - 25 May, 2023 - Comments: 0

Always-sensing cameras are a relatively new method for users to interact with their smartphones, home appliances, and other consumer devices. Like always-listening audio-based Siri and Alexa, always-sensing cameras enable a seamless, more natural user experience. Through continuous sampling and analyzing visual data, always-sensing enables use cases such as: “Find a face” detection for... » read more

Can Compute-In-Memory Bring New Benefits To Artificial Intelligence Inference?
By Paul Karazuba - 27 Apr, 2023 - Comments: 0

Compute-in-memory (CIM) is not necessarily an Artificial Intelligence (AI) solution; rather, it is a memory management solution. CIM could bring advantages to AI processing by speeding up the multiplication operation at the heart of AI model execution. However, for that to be successful, an AI processing system would need to be explicitly architected to use CIM. The change would entail a shift ... » read more

Looking Beyond TOPS/W: How To Really Compare NPU Performance
By Paul Karazuba - 23 Mar, 2023 - Comments: 0

There is a lot more to understanding the true capabilities of an AI engine beyond TOPS per watt. A rather arbitrary measure of the number of operations of an engine per unit of power, the TOPS/W metric completely misses the point that a single operation on one engine may accomplish more useful work than a multitude of operations on another engine. In any case, TOPS/W is by no means the only spe... » read more

Latency Considerations Of IDE Deployment On CXL Interconnects
By Paul Karazuba - 14 Oct, 2021 - Comments: 0

Certain applications and hardware types – emerging memory, artificial intelligence/machine learning (AI/ML), and cloud servers, to name a few – can realize significant performance advantages when a low latency interface is employed. However, traditional interconnects like PCI Express (PCIe) often do not offer low enough latencies required to optimize these applications. In response, the Com... » read more

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