>> Quantitatively, the QT-Opt approach succeeded in 96% of the grasp attempts across 700 trial grasps on previously unseen objects. Compared to our previous supervised-learning based grasping approach, which had a 78% success rate, our method reduced the error rate by more than a factor of five.
So what do you think, is vision-based robotic manipulation and grasping a solved problem, seven years later? Is QT-Opt now an established industry standard in training robots with RL?
Or was that just another project that was announced with great fanfare and hailed as a breakthrough that would surely lead to great increase of capabilities... only to pop, fizzle and disappear in obscurity without any real-world result, a few years later? Like most of DeepMind's RL projects do?
Absolutely comparable. Consider what can be done today with hardware as powerful as in the 1970's and it's obvious that the needle hasn't budged one tick.
But, like you say- let's wait and see. I always do the former but I'm still waiting for the latter.
I encourage you to read deepmind's work with robots.