Looks like a Tiny Analytic transformer, RNN is arguably a better choice if you are gonna handwire an architecture to mechanically do addition. Learning is about discovering the patterns and algorithm from data. Wiring a machine to follow a procedure defeats that purpose.

I understand that what Taalas is claiming. I was trying to actually describe that model on a hardware is some not something new Or unthought of The natural progression of FPGA is ASIC. Taalas process is more expensive And not really worth it because once you burn a model on the silicon, the silicon can only serve that model. speed improvement alone is not enough for the cost you will incur in the long run. GPU's are still general purpose, FPGA's are atleast reusable but wont have the same speed. But this alone cannot be a long term business. Turning a model to hardware in two months is too long. Models already take quite a long time to train. Anyone going down this strategy would leave wide open field to their competitors. Deployment planning of existing models already so complicated.

There is nothing new here. This has been demonstrated several times by previous researchers:

https://arxiv.org/abs/2511.06174

https://arxiv.org/abs/2401.03868

For a real world use case, you would need an FPGA with terabytes of RAM. Perhaps it'll be a Off chip HBM. But for s large models, even that won't be enough. Then you would need to figure out NV-link like interconnect for these FPGAs. And we are back to square one.

Boston dynamics is far behind plus the robots are so cheap , even their dog is cheaper than BD. I dont think their humanoid can even catch up to this price. I am sure US Army and for the chinese counterpart Chinese army will be their biggest customers. But i wonder how will this workout in situations like Plane hijack, fire fighting and other such places where human lives cant be risked to save more human lives. (Please Dont downvote because your american patriotism is poked try replying.)

Not for the entire world, with their pricing it is only good for US market, for the rest of the world we have ChatGPT and cheaper Chinese models.