Ever since the dawn of computing, the comparison between machines and the human brain has been a subject of intrigue. Two pioneers in computing, John von Neumann and Alan Turing, laid the groundwork for this analogy. Von Neumann authored “The Computer and the Brain,” while Turing famously speculated in 1949 about computers competing with human intellect.
However, traditional central processing units (CPUs) do not emulate the brain’s functions. CPUs are embedded with mathematical and logical structures. In contrast, neural processing units (NPUs) adopt a different approach, simulating the human brain’s architecture and processes.
The Birth of NPUs
The concept of electronic brains dates back to the mid-1940s with the inception of modern computing. Neurophysiologist Warren McCulloch and logician Walter Pitts introduced a “neural network” of circuitry, laying the foundation for future research in the 1950s and 1960s. Despite initial enthusiasm, interest in neural networks waned due to the superior number-crunching abilities of classical computers.
French-American computer scientist Yann LeCun, a pivotal figure in AI, noted the decline of neural networks as a field until the resurgence in 1986. It wasn’t until the success of speech recognition technology in the early 2000s that neural networks regained respect in computer science. LeCun mentioned, “We didn’t want to use the word neuron nets because it had a bad reputation, so we changed the name to deep learning.”
The Advent of NPUs in the Tech Industry
The term NPU emerged in the late 1990s. However, it required significant investment from tech giants like Apple, IBM, and Google to transition NPUs from university labs to mainstream products. These companies invested billions into silicon development, transforming past research into processors inspired by the human brain. Today, LeCun serves as the chief AI scientist at Meta, reflecting the improved fortunes of neural processing technologies.
Future Prospects of NPUs
In the coming years, AI experts predict that NPUs will follow a developmental trajectory similar to early CPUs, potentially adhering to a pattern akin to Moore’s Law. This would mean a doubling of teraflops every year or two, exponentially increasing processing abilities.
Such advancements could enable local creation of realistic AI artwork on personal computers, eliminating the need for external programs like Midjourney. As software evolves alongside hardware, personal AI agents may emerge, capable of understanding and performing tasks for users by “living” inside their computers.
NPUs are expected to expand beyond phones and laptops, finding applications in various devices. Televisions could deliver personalized news services through avatar presenters, while fitness trackers might recommend workouts tailored to users’ moods and schedules. In the future, humanoid robots equipped with NPUs could potentially serve as companions, understanding humans better than fellow humans.
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Note: This article is inspired by content from https://www.livescience.com/technology/electronics/what-is-a-neural-processing-unit-npsu. It has been rephrased for originality. Images are credited to the original source.