tag: artificial intelligence

A Broad Look Inside Advanced Packaging
By Mark LaPedus - 18 Nov, 2021 - Comments: 0

Choon Lee, chief technology officer of JCET, sat down with Semiconductor Engineering to talk about the semiconductor market, Moore’s Law, chiplets, fan-out packaging, and manufacturing issues. What follows are excerpts of that discussion. SE: Where are we in the semiconductor cycle right now? Lee: If you look at 2020, it was around 10% growth in the overall semiconductor industry. ... » read more

Enablers And Barriers For Connecting Diverse Data
By Anne Meixner - 09 Nov, 2021 - Comments: 0

More data is being collected at every step of the manufacturing process, raising the possibility of combining data in new ways to solve engineering problems. But this is far from simple, and combining results is not always possible. The semiconductor industry’s thirst for data has created oceans of it from the manufacturing process. In addition, semiconductor designs large and small now ha... » read more

Improving Medical Image Processing With AI
By SE Staff - 04 Nov, 2021 - Comments: 0

Machine learning is being integrated with medical image processing, one of the most useful technologies for medical diagnosis and surgery, greatly expanding the amount of useful information that can be gleaned from scan or MRI. For the most part, ML is being used to augment manual processes that medical personnel use today. While the goal is to automate many of these functions, it's not clea... » read more

Competing Auto Sensor Fusion Approaches
By Bryon Moyer - 07 Oct, 2021 - Comments: 0

As today’s internal-combustion engines are replaced by electric/electronic vehicles, mechanical-system sensors will be supplanted by numerous electronic sensors both for efficient operation and for achieving various levels of autonomy. Some of these new sensors will operate alone, but many prominent ones will need their outputs combined — or “fused” — with the outputs of other sensor... » read more

Why TinyML Is Such A Big Deal
By Bryon Moyer - 02 Sep, 2021 - Comments: 1

While machine-learning (ML) development activity most visibly focuses on high-power solutions in the cloud or medium-powered solutions at the edge, there is another collection of activity aimed at implementing machine learning on severely resource-constrained systems. Known as TinyML, it’s both a concept and an organization — and it has acquired significant momentum over the last year or... » read more

Thermal Floorplanning For Chips
By Brian Bailey - 10 Jun, 2021 - Comments: 0

Heat management is becoming crucial to an increasing number of chips, and it's one of a growing number of interconnected factors that must be considered throughout the entire development flow. At the same time, design requirements are exacerbating thermal problems. Those designs either have to increase margins or become more intelligent about the way heat is generated, distributed, and dissi... » read more

Customizing Chips For Power And Performance
By Ed Sperling - 10 Jun, 2021 - Comments: 0

Sandro Cerato, senior vice president and CTO of the Power & Sensor Systems Business Unit at Infineon Technologies, sat down with Semiconductor Engineering to talk about fundamental shifts in chip design with the rollout of the edge, AI, and more customized solutions. What follows are excerpts of that conversation. SE: The chip market is starting to fall into three distinct buckets, the e... » read more

Failure Mechanism Detection Algorithm With MOSFET Body Diode
By Fraunhofer IIS/EAS - 09 Jun, 2021 - Comments: 0

Autonomous driving is playing a big role in the automotive industry and defines the future of mobility on a big scale. However, autonomous driving faces several challenges, such as the performance of artificial intelligence and hardware reliability. To ensure safe functionality, the reliability of the electronic components plays an essential role and must be taken into consideration. One aspect... » read more

Fab Fingerprint For Proactive Yield Management
By Onto Innovation - 08 Jun, 2021 - Comments: 0

The following paper presents a case study describing how to improve yield and fab productivity by implementing a frequent pattern database that utilizes artificial intelligence-based spatial pattern recognition (SPR) and wafer process history. This is important because associating spatial yield issues with process and tools is often performed as a reactive analysis, resulting in increased wafer... » read more

Security Solutions for AI/ML
By Rambus - 02 Jun, 2021 - Comments: 0

AI/ML is increasingly pervasive across all industries driven by a massive wave of digitization. Data, the raw material of AI/ML and Deep Learning algorithms, is available in enormous quantities from all aspects of business operations. AI/ML promises great gains in responsiveness and adaptability in an ever-changing technology landscape, and industries are enthusiastically responding to that app... » read more

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