1) AI can play chess quite well. Chess is played on small 8x8 boards with strict rules, a task extremely fitting to AI. However, chess softwares are continuely being improved by humans.
Even for chess, I don't know for a fixed chess software without any farther tuning from humans, how long it can keep winning against top human players. Since humans can learn better than AI so far.
2) AI can play GO well, but not so well as chess, due to combinatorial explosion. GO is played on 19x19 boards, also with strict rules.
3) Auto car pilots. It runs on roads built for cars and with highly-regulated traffic rules. Only a few cases are reported so far. Don't know how well these systems can run in large scale and randomly picked road situations.
A reasonable guess is: potentially auto car pilots could do well in standard car racing competition if not already, which runs on routes regulated better than usual roads, easier for safety. Although improving performance might be more difficult initially than running at normal speeds, safety could be more difficult to solve eventually.
4) Robots' capabilities are highly constrained by AI.
They can play Rubiks Cube extremely well, since there are fixed algorithms. They can play music instruments well, with fixed actions. They can even play pingpong with humans, which is on simple platform with simple rules. Hopefully, robots could catch up with or even exceed humans soon with pingpong.
They can walk. With two legs, they can walk on flat places, or stairs with regular shapes, but not good at mountain surfaces yet. With four legs, they could walk on rough terrains, but may not on very steep hills or rocky mountains as deers and other animals can, not to mention to find a route by themselves there. With six legs, they can even climb on coarse walls or trees, but not seen on glass or steel walls (by me) yet, probably would in near future since glass or steel wall surface is well-defined.
They could emulate simple creatures like fishes, moths, somehow snakes, but not even behave like chicken, rats, cats, dogs, etc., yet so far.
So even to achieve goals of weak AI, robots still need much more advanced AI theories and methodologies.
There is one category: industrial robots, which already play significant roles in reality. They are designed for well-defined tasks. However, there are lessons could be taken from the Saturn project in 1980s, if people want to make big breakthrough.
5) Handwriting recognization, voice recognization, image and video-processing, etc. These can do well in certain contexts and with specific targets to recognize, such as moving objects. AI could recognize what people write better if it already knows what type of things are written: digitals, English letters, Chinese characters, mathematical signs, etc. Or for voice: what languages people are speaking, or they are singing a song, or just playing Kouji, etc.
......
People could add more to this list. However the list would still not be long. In most situations, computers only can aid and enhance humans, not replace them.
AI cannot do most things humans can. So IMHO, AI is still in poineering stage. Only a few things could be implemented in software so far. More research is needed, including much philosophical thinking.
Don't limit youself to software implementation in AI researches. Most of them cannot be implemented so far.
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