Artificial Intelligence (AI) in the World of Microsystem Manufacturing

The presence of artificial intelligence (AI) has become quite significant in many applications. Most notably in big data analytics, facial recognition software, military equipment, and self-driving cars, among others.

What is AI?


AI enables machines to think. It provides the ability of the machine or software application to learn, act, and reason like human cognition. The beginning of AI goes back to the 1950s. However, recent developments in AI technology catapults the concept into new abilities and uses.

This is possible by creating sophisticated machine-learning algorithms to process huge data sets, learn from experience, and improve over time. It was in 2010 that advances in deep learning came.

That enabled the processing of a wider range of data through a certain type of machine-learning, requiring fewer data preprocessing done by human operators, and often producing more accurate results.


What is the role of AI in microsystem manufacturing?


There is a significant role of AI in the semiconductor industry due to its potential of creating huge business value. In fact, microsystem manufacturing companies investing in AI/ML are already generating value.

These are companies making notable investments in AI/ML talent, particularly in data infrastructure, technology, and other factors. They have also fully scaled up their initial use cases for that matter.

Although many are still in the pilot phase in terms of AI/ML, forecasts suggest that its application of such technology can accelerate dramatically over the next few years. If companies will take steps to scale up now, they will be able to capture the full benefits of such technologies.


How AI offers opportunities for microsystem companies


Chips intended to work with machine learning, or the neural networks called AI accelerators are expected to have a growth rate of approximately 18% per annum. This is more than 5 times the growth seen for semiconductor companies using non-AI applications. These also include areas of high growth in AI chips for the broader field of neural networks and for autonomous vehicles.

Neural networks are specialized AI algorithms working just as the human brain does. These are able to interpret sensory data and deliver patterns in huge amounts of unstructured data. Such is quite useful for facial recognition, predictive analysis, self-driving cars, and targeted marketing.

This is when microsystem manufacturing will benefit from the creation of AI accelerators and multiple inferencing chips required in the development of such AI technologies.


How semiconductor companies profit from AI technology


There are various areas of microsystem manufacturing that can benefit from the adoption of AI technology which includes but are not limited to the following.

  • High-bandwidth memory
  • High-speed interconnected hardware
  • Networking chips
  • Non-volatile memory
  • On-chip memory
  • Storage
  • Workload-specific AI accelerators

Accordingly, investment in AI technology enables chipmakers to capture their share of markets if they can meet the upcoming demand. Demand for AI will increase which brings many opportunities for the semiconductor industry but also a crisis in the acquisition of talent.


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