If AI implementation is important to your business’s 2025 goals, you will want to watch the AI chipset market closely

With Project Strawberry (the newest iteration of ChatGPT which is touted to boost it’s reasoning capabilities amongst other new features) on the horizon and more and more businesses taking advantage of AI tools such as Microsoft Co-Pilot and Google Gemini, the AI train doesn’t look like it will be slowing down anytime soon.

So, if AI is going to be a priority for your businesses 2025 are you planning on how can you make sure you have devices that can fully take advantage of what AI is capable of? AI workloads can be strenuous on the average machine (see our chart on the minimum specifications we recommend below).

Why is AI so hardware intensive? AI relies on machine learning to operate, if your computer has to slog through the requests you’re making of it (for example, making presentations, automating tasks and performing searches on your behalf) then that’s going to hinder your ability to use AI to it’s full potential. That may lead to you and your users becoming frustrated and resorting to just returning to prior methods of performing these tasks and stifling the ability to use this emerging innovation in technology.

Failing to adapt to emerging technologies can be a death knell to many businesses (anyone remember Blockbuster?).

No one knows more how important keeping up with emerging technologies is than chip makers like Intel, Nvidia and AMD who all have chips set to release next year that will reportedly take full advantage of advancements in AI.

Nvidia so far has led in this race, with their chips utilizing its own programming language, CUDA (which stands for Compute Unified Device Architecture), which has become standard amongst AI developers. This means they’re dominating this market so far, especially in the data center space. Having direct access to this language from an architecture perspective means that chips made by Nvidia can accelerate processes for AI purposes (thus completing AI tasks more efficiently). Their innovations in the AI space and technology as a whole have led to Nvidia representing 11.7% of the total US GDP.

AMD hopes to compete with Nvidia and reclaim some of their market share with their new chips, set to be released in early 2025 which will feature their own programing language called ROCm. It’s being said making the switch from CUDA to ROCm will be a painless process and offer more competition in the market (which will only improve things from a cost perspective).

For example, the current cost of a processor intended for a supercomputer with AMDs new chip set is $14,813 per chip, drastically outside the range of most customers’ comfortable price point for a new device. As competitions and advancements become more common place, we may be getting closer to an age where super computers are not just found in scientific and government settings and there’s no telling how that will change the average workplace in the future.

There’s also the hardware portion of chip making to consider especially amongst earlier concerns of semiconductors maxing out their capacity for growth and shortages that continued past the height of the pandemic. TSMC also reached a new market share height of over a trillion dollars this week putting fears of that rest for the moment.

If taking advantage of AI or replacing aging hardware is on your 2025 to-do list, Valley Techlogic can help. We offer tailored advice and procurement assistance as an included feature in our support plans for businesses located in California. Reach out today for more information.

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