Chuck Moore is bad at presentations to outside audiences. This should surprise no one familiar with the man. This doesn't make the tech less useful, though.
If those were really obvious, tachyonbeam wouldn't have to ask ;-)
In your opinion, what are problems for which this chip would be a solution?
The most obvious one is AI. These things are incredibly parallel & entirely self-contained, and a consumer desktop PSU could power countless amounts of them without a second thought. At $2,000 for 100 chips ($20/chip), you can start to do some really interesting stuff for the cost of a consumer laptop.
It's natural that AI is a problem this chip excels at, given Moore studied under McCarthy and all.
If you feel morally okay with playing with proprietary software, I really recommend playing a little bit with the simulator of the chip. Given what's intuitive with one or two, you'll probably be able to see the possibilities much better after an hour or so of play.
I seriously doubt that. The cores on that chip are extremely memory-limited: 72 bytes per core, that's about 10 kiB per Chip! And if you want to access SDRAM, you need an external SDRAM controller and bit-bang it. Gee, I wonder what that does to throughput and latency...
This chip's competition isn't GPUs and AI engines, but very low-cost, low-performance FPGAs, and it would probably lose. Given the extremely constrained environment of the individual cores (no cache, extremely little memory, a stack-based architecture), FPGAs are probably even easier to program.
There are no commercial applications, it's a toy.
That'll be really wonderful to see!
https://news.ycombinator.com/item?id=23157949
AI is just the most obvious usage, though.
It'd be unimaginative to just consider embedded uses: there are terribly practical uses for it. Consider that most big companies buy hardware based on performance per watt, then consider that GA144 blows most things out of the water on that front.
GA also has a few recommendations (ripped from their site):
APPLICATIONS
Energy harvesting applications
Portable devices
Remote sensing and data reduction
Ideal for parallel and/or pipelined work
Image processing
Complex control systems
Cryptography
High speed signal processing
Simulation and synthesis
Inexpensive, massively parallel systems for research and education
Artificial intelligence, neural nets