The semiconductor industry recently reached supersonic speed due to the booming field of artificial intelligence. With something as nebulous as AI, it can be difficult to remember that even generative AI can be bounded by the reality of hardware availability. AI semiconductors are more than conductive mediums. Right now, there’s an argument to be made that they are the hinge on which the entire industry hangs.
But what are they, exactly? Better yet how is their necessity driving innovation in ways that might have been a little unexpected? Read on for our breakdown of this vital piece of AI hardware.
What is a Semiconductor?
You might think of an AI semiconductor as one neuron in a massive network underpinning a generative AI model. Semiconductors are an umbrella term indicating the series of materials or devices that control electrical signals in all computers. They are also a piece of the hardware suite forming the basis of AI’s massive computing power, which far outstrips the processing power of the standard CPUs used in our computers.
Artificial intelligence relies on an untold number of complex computations, allowing these platforms to parse information and generate complex answers. This means many AI models, such as OpenAI, use supercomputers to train their models. These specialised machines require plenty of hardware, but semiconductors enable these massive workhorses to process trillions of computations per second.
While we could go deeper into the science of semiconductors, the pertinent information here is that this small piece of hardware has suddenly become vital because AI cannot grow or function without it. Despite the power of these new platforms, they’re just as limited by their hardware as ours. So, companies investing in building AI platforms are – by extension – investing in the semiconductors market.
How Startups Are Driving Innovation in Superconductors
For startups, in particular, semiconductors are a massively important puzzle. AI is popping up in all sorts of products and services, with smaller models using the computing power of larger models like OpenAI’s. With this kind of expansion happening so rapidly, there’s increasing demand for faster, better, more efficient semiconductors to handle calculations.
This pushes the industry to innovate faster, and as with most industries, a huge portion of that innovation happens at the startup level. Whether companies are producing better semiconductors for use in other places or producing their own semiconductors to drive their own generative AI models, this trend has interestingly tied manufacturing ability with the ability to innovate in what is often considered an exclusively digital space.
In other words, semiconductors could act as either the restrictive leash or the unlocking key for startups in the AI industry. The more efficient chips can be, the faster AI can compute, and the more the innovating startup can benefit. While companies like Google, Amazon, and Microsoft are producing their own chips in-house, there have been many instances where a massive leap from a small tech company has catapulted an industry into hyperdrive.