Everything that doesn't have a discrete GPU has unified memory these days. If you're asking for something closer to the RTX Spark or Apple Silicon then look at AMD's Strix Halo systems.
Also, if you'd like to know of an earlier example, the very first Raspberry Pi has fully unified memory. Released 2012, SoC from 2011. It's not exposed in the usual APIs which is why you have a configurable RAM allocation for the GPU, so you need to write special code targeting the GPU cores. You can pass a pointer from the CPU and have the GPU read data directly. Results are written back to RAM which can be read by the CPU.
The M1 isnt particularly good at inference, so pretty much every major current competitor with a 256+ bit unified memory system is better: AMD Strix Halo, NVIDIA DGX Spark, possibly Intel Panther Lake
You are missing a major detail: integrated GPUs are crap. They win on efficiency but not on raw compute. Before AI (and crypto too, I guess) people bought GPUs to render graphics and that was their main consumer. People built more and more demanding games that required increasingly powerful GPUs to render well. Gaming systems always had a discrete GPU so there was no reason to scale up integrated GPUs because they wouldn't sell, or they would be a waste of die space.
I don't think the M1 specifically focused on inference. Their goal was to replace Intel/AMD/Nvidia with their own chips, and since the previous Macs shipped discrete GPUs, they had to match or beat those so they don't ship something slower.