As far as I know, no true artificial general intelligent system (AGI) has been implemented or is practically useful.
Yes, there is Sophia and similar robots that may look like an AGI, but they aren't really AGI systems, as they lack several capabilities that we humans have and they can't really adapt to new circumstances. Despite their success, AlphaGo and AlphaStar are narrow AI systems, as they can only solve one specific problem (although the same approach can be adapted to solve very similar problems too, but only with the intervention of humans, so not autonomously).
Nevertheless, there are theoretical frameworks for AGI, such as AIXI, which, in any case, have several flaws, such as incomputability (in the case of AIXI). There are approximations of AIXI, but these approximations can only be used to solve toy problems (such as tic-tac-toe), so they aren't really useful to solve real-world problems.
If you want to know more about AGI, the Scholarpedia's article Artificial General Intelligence, curated by Ben Goertzel, one of the leading researchers of the AGI field, provides a good overview of the AGI field, including but not restricted to definitions of AGI and approaches to the development of AGI systems, such as
- universal (AIXI was created based on this approach),
- symbolic (Soar was created based on this approach), which is based on the physical symbol system hypothesis,
emergentist, which is based on the idea that general intelligence is expected to emerge from sub-symbolic dynamics (where a sub-symbolic system refers e.g. to an artificial neural network),
hybrid (e.g. CLARION), which is a combination of the universal, symbolic or sub-symbolic approaches.