We’re not holding anything back, you should be able to recreate our findings from the paper. More broadly, there are a number of ways to recreate the network us

We’re not holding anything back, you should be able to recreate our findings from the paper. More broadly, there are a number of ways to recreate the network using the relatively simple learning rule we provide. In theory, this learning rule will continue to decrease your error forever (in our simulations our error goes down to machine precision). However, with any physical learning network you’re always gonna hit an error floor based on the precision of your components. With our current variable resistors and network size that floor is around 10^-3. With more precise components (like we mention at the end of the paper), that floor will go down significantly.