When talking about AI, in most cases you’d be talking about some kind of software. 

That’s because an AI platform is a software tool or framework that provides various capabilities and tools for developing, deploying, and managing artificial intelligence applications. 

It is a software system that provides developers with the ability to build and train machine learning models, perform data analysis, and automate business processes using AI algorithms.

AI platforms typically consist of various software components, such as programming languages, libraries, APIs, and tools for data management, visualization, and model deployment. 

They may also include pre-built models and machine-learning algorithms that can be customized for specific applications.

And while pretty much all of this exists on hard drives and cloud storage systems, AI platforms also have a large hardware component. 

This software is taxing and requires extremely powerful physical components to work properly. 

The hardware requirements for powering AI platforms certainly differ depending on various factors such as the complexity of the AI algorithms, the size of the data sets used, and the type of application being developed. 

However, some general hardware requirements are common to most AI platforms.

In general, you would need things like high-powered central processing units (CPU), graphics processing units (GPU), random access memory arrays (RAM), hard drives, and networking systems, to name a few. 

So while there is a huge market for companies at the forefront of AI software, there is an equally huge market ready for capture by companies that provide the most cutting-edge hardware. 

The Crucial Pieces to the Puzzle 

As I mentioned above, there are quite a few hardware requirements for AI systems to work. Let’s take a deeper look at some of them and the companies that make them… 

Starting with CPUs, these are the main processing units in a computer, responsible for executing instructions and managing the flow of data. 

They’re used for general-purpose computation and are a crucial component in AI systems as well as any computer whether it be commercial or personal. 

Advanced Micro Devices Inc. (NASDAQ: AMD) and Intel Corp. (NASDAQ: INTC) are two of the most recognizable names in CPU research, development, and manufacturing. 

Next up, we have GPUs. 

GPUs are specialized processors designed to perform highly parallel computations, making them well-suited for AI applications that require a lot of matrix and vector operations. 

You’ve likely heard about GPUs from two of the most popular manufacturers: Nvidia Corp. (NASDAQ: NVDA) and Advanced Micro Devices Inc. (NASDAQ: AMD). 

Then, there are tensor processing units (TPUs). 

TPUs are specialized processors designed specifically for deep learning applications, capable of performing large-scale matrix operations with high efficiency.

Some of the most popular TPUs come from Alphabet Inc. (NASDAQ: GOOG).

Of course, you’ll also need storage systems and memory units for all the data that goes into AI systems. 

AI platforms require large amounts of memory to store data, model parameters, and perform operations efficiently. This includes both RAM (random access memory) and storage (hard drives or solid-state drives).

For network requirements, you’re going to need some sort of network interface card (NIC). 

A NIC provides network connectivity, which is critical for AI systems that rely on large datasets or require real-time processing. 

Again, Intel Corp. (NASDAQ: INTC) is a popular NIC manufacturer. 

Finally, you’d need some pretty standard computer equipment like power supplies and cooling systems to make sure that all of these components can run properly. 

Of course, this list is more for businesses that are building AI platforms for consumers or B2B applications, but sharing this list of hardware just goes to show some of the physical requirements for building an AI platform. 

And these components aren’t just needed individually, to service a large amount of customers companies will need to buy hundreds, if not thousands, of each of these components. 

And these pieces don’t come cheap… 

Needless to say, providing hardware to companies at the forefront of AI platform development can be a very lucrative endeavor. 

In the same way that the top contenders in the AI software market will see great success the more AI becomes integrated into our lives, so will the hardware manufacturers.

Lastly, I’d love to hear back from you on this. Are there any AI software or hardware companies you’d like me to look into? Have you been looking into AI platforms for personal or commercial use? Drop me a line and let me know here: feedback@technologyprofits.com