infyr

5 ms·

1.
by infyr 10y ago
It is. I tried it out but it doesn't have the fidelity w.r.t I/O and 'hooks' I was looking for. Then again, I'm working beyond reinforcement learning. More advanced A.I necessitates more advanced gym. I highlighted
2.
by infyr 10y ago
To test out increasingly 'general' and advanced A.I, you need a sandbox/playground environment... You can use a real-world environment with a robot (noisy, more latency, computationally restrictive , more headaches, and extra
3.
by infyr 10y ago
It depends on what your aim is. If you want to jump into the field, follow what the field is doing and/or suggesting. If you want to go down the rabbit hole, i'd suggest Jeff Hawkin's book (On Intelligence) The essential tak
4.
by infyr 10y ago
Basically yes. But that's not only incredibly effective, it's quite possibly how real brains work too. A lot of people do believe it is a path to AGI. > It's only incredibly effective in a static world. The world is not st
5.
by infyr 10y ago
Isn't deep learning the correct approach though? > No. It's a piece of a much larger puzzle and only a partial piece at that. An overfit piece that people are over-applying. This is why things are overly complex and filled with
6.
by infyr 10y ago
Lots of theoretical models, philosophical, and metaphysical thinking... The scientific method... Actual in-depth studies centered on the system you're trying to understand and duplicate in another form. You know.. Everything but the fo
7.
by infyr 10y ago
"Very few people today would have the audacity to explicitly try building human-level AI." Hmmm, there are a considerable number of people/groups who have this audacity... Have for decades... and they have been explicitly try
8.
by infyr 10y ago
So, a probability driven dynamic call-stack FSM. I have seen this concept used in many ways before without the fanfare (i.e : code coverage/test suites and game A.I Engines) It is indeed a cool approach and no doubt deeply inspired. Ri