This isn’t the first time Intel has flirted with things outside their core competence. They dabbled with SSDs, mobile phone modems, … etc. It’s just something Intel does. Why? Don’t know.
Of course, it works well as a tech demo and in controlled environments, and it's easy to understand and then brute-force with custom hardware. The problem is that it sucked the life out of better techniques which might actually work in the real world.
So, intel made a custom processor for this that's really good at the correlations. The original one was the D4, and later they used their movidius chip. Both have lots of multiplier-accumulate silicon, so it can do the computations in parallel. Their architectures are also set up for convolution (which re-uses a lot of data) rather than random-processing (like a CPU does), so they could feed these math engines without a lot of data transfer -- this makes it more power efficient. You could do something similar in an FPGA, but dedicated silicon is going to be faster, cheaper, and use less power.
Google's core is search & advertising. But they are also in email, video streaming, messaging & video chat, cloud computing, mobile phones, gaming (Stadia), self-driving cars, drone delivery, quantum computing, and probably many other things that I can't think of.
Edit: Yes I know it’s technically Alphabet, but in practical terms, it’s Google
Lidar has high computational needs, which directly influences accuracy, and both spacial and time resolution.
Post-processing steps also have high computational needs, such as infering structure, do coregistration, handle point density, etc.
Also, practical applications often demand and depend on meeting constraints such as low power requirements and size.
If a company such as Intel managed to leverage their know-how to provide Lidar hardware that was competitive in both performance and price then they could as well develop a machine that prints money.
They can keep on trucking with R&D