Quo Vadis, Artificial Intelligence?

Since i ts conception in the m id 1950s, ar t ificial intel ligence w ith i ts g reat ambition to understand and emulate intel ligence i nnatur al and ar tificial env ironments alike is now a t r uly multidisciplinar y field that reaches out and i s inspired by a g reat diversit y ofother fields. R apid advances in research and technolog y in var ious fields have created env ironments into w hich ar t ificial intelligenceco uld embed itself natur ally and comfor tably. Neuroscience w i th its desire to understand n er vo us systems of biolog i cal organismsand s ystems biolog y w i th its l ong ing to comprehend, holistically, t he mu ltitude of complex inter actions i n biolog i cal s ystems aretwo such fi elds. T he y t arget i deals ar t ificial intelligence h as dreamt about for a long time including the computer s imulation of anentire biolog i cal br a in or the c reation of n ew life for m s f rom m a nipulations of ce llular and genetic infor mation in the l abor ator y.The s cope for ar t ificial intelligence i n n eu roscience and systems biolog y is ext remely w ide. This ar ticle investigates the standingof ar tificial intelligence i n relation to n eu ro science and systems biolog y and prov i des an outlook at new and exciting ch allengesfor ar t ificial intelligence i n t hese fields. These challenges inclu de, but are n ot necessar i ly limite d to, the abilit y to lear n f rom o therprojects and to b e inventive, to understand t he potential and exploit novel computing par a dig ms and env ironments, to specify andadhere to st r ingent s tandards and robust statistical f r amewor ks, to be integ r ative, and to embr ace openness pr inciples.