Small Language Models: A Solution To Language Model Deployment At The Edge?


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

Asia Government Funding Surges


Billions of dollars have been pouring into Asian countries for the past few years in an effort to boost their production capacity, explore leading-edge technology, compete on the global stage, and shore up supply chains in the face of geopolitical turmoil. Each country has its own plan to maintain a foothold in the global market, from China’s Big Fund to Korea’s Yongin Cluster and Japan�... » read more

Managing The Huge Power Demands Of AI Everywhere


Before generative AI burst onto the scene, no one predicted how much energy would be needed to power AI systems. Those numbers are just starting to come into focus, and so is the urgency about how to sustain it all. AI power demand is expected to surge 550% by 2026, from 8 TWh in 2024 to 52 TWh, before rising another 1,150% to 652 TWh by 2030. Commensurately, U.S. power grid planners have do... » read more

New AI Data Types Emerge


AI is all about data, and the representation of the data matters strongly. But after focusing primarily on 8-bit integers and 32‑bit floating-point numbers, the industry is now looking at new formats. There is no single best type for every situation, because the choice depends on the type of AI model, whether accuracy, performance, or power is prioritized, and where the computing happens, ... » read more

HW and SW Architecture Approaches For Running AI Models


How best to run AI inference models is a current topic of much debate as a wide breadth of systems companies look to add AI to a variety of systems, spurring both hardware innovation and the need to revamp models. Hardware developers are making progress with AI accelerators and SoCs. But on the model side, questions abound about whether the answer might come from revisiting older, less compl... » read more

Mass Customization For AI Inference


Rising complexity in AI models and an explosion in the number and variety of networks is leaving chipmakers torn between fixed-function acceleration and more programmable accelerators, and creating some novel approaches that include some of both. By all accounts, a general-purpose approach to AI processing is not meeting the grade. General-purpose processors are exactly that. They're not des... » read more

Using AI To Glue Disparate IC Ecosystem Data


AI holds the potential to change how companies interact throughout the global semiconductor ecosystem, gluing together different data types and processes that can be shared between companies that in the past had little or no direct connections. Chipmakers always have used abstraction layers to see the bigger picture of how the various components of a chip go together, allowing them to pinpoi... » read more

Chip Industry Week In Review


Synopsys agreed to sell its Optical Solutions Group to Keysight for an undisclosed amount, in a deal deemed necessary for Synopsys to win regulatory approval for its planned acquisition of Ansys. The sale to Keysight is contingent on the Synopsys-Ansys deal going through. Meanwhile, Ansys has its own optical business. The U.S. Department of Defense (DoD) made the first awards for Microelectr... » read more

Is PPA Relevant Today?


The optimization of power, performance, and area (PPA) has been at the core of chip design since the dawn of EDA, but these metrics are becoming less valuable without the context of how and where these chips will be used. Unlike in the past, however, that context now comes from factors outside of hardware development. And while PPA still serves as a useful proxy for many parts of the hardwar... » read more

Chip Industry Week In Review


The University of Texas at Austin’s Texas Institute for Electronics (TIE) was awarded $840 million to establish a Department of Defense microelectronics manufacturing center. This center will focus on developing advanced semiconductor microsystems to enhance U.S. defense systems. The project is part of DARPA's NGMM Program. The U.S. Dept. of Commerce announced preliminary terms with Global... » read more

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