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

Startup Funding: Q2 2024


AI drew more investors to the chip industry in Q2. Four AI-focused chip startups receiving rounds of more than $100 million, targeting data center ASICs for transformers, highly flexible platforms for the embedded edge, dataflow processors, and mixed-signal neuromorphic chips. In-memory computing also helped boost AI, with three companies either incorporating it into their chips or providing sp... » read more

Securing Data In Heterogeneous Designs


Data security is becoming a bigger concern as chips are disaggregated into chiplets and various third-party IP blocks. There is no single solution that works for all designs, and no single tool or methodology that addresses everything in any design. Data is being transmitted across time zones, political borders, and even across multiple designs. Laws and the need to comply with standards may... » read more

Language’s Role In Embodied Agents


Large Language Models (LLMs) and models cross-trained on natural language are a major growth area for edge applications of neural networks and Artificial Intelligence (AI). Within the spectrum of applications, embodied agents stand out as a major developing focal point for this AI. This article will address developments in this space and how the application of language-trained models improves t... » read more

When To Expect Domain-Specific AI Chips


The chip industry is moving toward domain-specific computation, while artificial intelligence (AI) is moving in the opposite direction, creating a gap that could force significant changes in how chips and systems are architected in the future. Behind this split is the amount of time it takes to design hardware and software. In the 18 months since ChatGPT was launched on the world, there has ... » read more

Chip Industry Week In Review


Rapidus and IBM are jointly developing mass production capabilities for chiplet-based advanced packages. The collaboration builds on an existing agreement to develop 2nm process technology. Vanguard and NXP will jointly establish VisionPower Semiconductor Manufacturing Company (VSMC) in Singapore to build a $7.8 billion, 12-inch wafer plant. This is part of a global supply chain shift “Out... » read more

Vision Is Why LLMs Matter On The Edge


Large Language Models (LLMs) have taken the world by storm since the 2017 Transformers paper, but pushing them to the edge has proved problematic. Just this year, Google had to revise its plans to roll out Gemini Nano on all new Pixel models — the down-spec’d hardware options proved unable to host the model as part of a positive user experience. But the implementation of language-focused mo... » read more

Chip Industry Week In Review


Absolics, an affiliate of Korea materials company SKC, will receive up to $75 million in direct funding under the U.S. CHIPS Act for the construction of a 120,000 square-foot facility in Covington, Georgia, for glass substrates in advanced packaging. imec will host a €2.5 billion (~$2.72B) pilot line for researching chips beyond 2nm, partially funded through the EU Chips Act. imec CEO Luc ... » read more

Will Domain-Specific ICs Become Ubiquitous?


Questions are surfacing for all types of design, ranging from small microcontrollers to leading-edge chips, over whether domain-specific design will become ubiquitous, or whether it will fall into the historic pattern of customization first, followed by lower-cost, general-purpose components. Custom hardware always has been a double-edged sword. It can provide a competitive edge for chipmake... » read more

Dealing With AI/ML Uncertainty


Despite their widespread popularity, large language models (LLMs) have several well-known design issues, the most notorious being hallucinations, in which an LLM tries to pass off its statistics-based concoctions as real-world facts. Hallucinations are examples of a fundamental, underlying issue with LLMs. The inner workings of LLMs, as well as other deep neural nets (DNNs), are only partly kno... » read more

← Older posts