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[tommib]

Why do Nvidia’s chips dominate the AI market?

The firm has three big advantages

www.economist.com

Nvidia’s ai chips, also known as graphics processor units (gpus) or “accelerators”, were initially designed for video games. They use parallel processing, breaking each computation into smaller chunks, then distributing them among multiple “cores”—the brains of the processor—in the chip. This means that a gpu can run calculations far faster than it would if it completed tasks sequentially. This approach is ideal for gaming: lifelike graphics require countless pixels to be rendered simultaneously on the screen. Nvidia’s high-performance chips now account for four-fifths of gaming gpus.

But even building better hardware may not be enough. Nvidia dominates ai chipmaking because it offers the best chips, the best networking kit and the best software. Any competitor hoping to displace the semiconductor behemoth will need to beat it in all three areas. That will be a tall order.

 

[Salz01]

I’m hoping Apple does or announces something with their M chips later this year.

 

[AJUMP23]

Because they leaned into it early and they had the vision to see that it would be a huge part of the market. They got out early with their message and people bought in.

 

[ChuckeRearmed]

In a right place in a right time with a right tech

 

[dave_d]

I do remember that at my last company the head of the AI department preferred CUDA since the software to actually use it was more mature. One thing he mentioned is that it actually supported multiple GPUs and they wanted to use that some of the time. (No idea myself if it's that much better than the tools for say OpenCL.) Admittedly they mostly used PyTorch which I guess uses CUDA. (I am no expert.)