I do not have the intellectual capacity to understand the implications of this acquisition but a friend broke it down for me. Hope this add (and does not detract) from the discussion:
They specialize in fusion of sensor data (for contextual AI-NN). Probably top of heap there or at least top 3. Don’t have time to detail currently, but think of it as taking ‘pixels’ from multiple cameras (and/or other sensors) and merging them (correlating differences) BEFORE making object recognition and other higher level determinations (which can bias NN decision making when made too early).
There’s not a perfect analogy, but it may help to think about multiple humans looking at the same scene, and instead of comparing each interpretation of what is seen, a single cortex combines each human’s retina data before deciding what the objects are (or are doing). It attacks not only edge cases but mimics our own brains BELOW the synaptic level where weighted chemical reaction influences when and if synopsis actually fire. The analogies aren’t perfect, but gives some contextual perspective.
As of a few years ago fusion of sensory data was impractical at the application level of higher order NN. Because the local processing had insufficient bandwidth and the power requirements to do so were prohibitive (hence this company’s expertise in processing under lower power and chip design to accomplish etc).
Important take-aways here:
1) This is a level of integration nobody else is even thinking of much less in a position to utilize, as only Tesla has a chip capable of this, and only Tesla is approaching L4/5 edge case and super intelligent decision making. This is 2nd and 3rd order (think differential equations) vertical integration
2) The knee jerk reports this is some sort of replacement of Tesla AI people who left is WRONG WRONG WRONG. This is a completely new level of skill set not related to what those other folks were even qualified to do.
