human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "turing then now and still key"
  Abstract: This paper looks at Turing’s postulations about Artificial Intelligence in his paper ‘Computing Machinery and Intelligence’, published in 1950. It notes how accurate they were and how relevant they still are today. This paper notes the arguments and mechanisms that he suggested and tries to expand on them further. The paper however is mostly about describing the essential ingredients for building an intelligent model and the problems related with that. The discussion includes recent work by the author himself, who adds his own thoughts on the matter that come from a purely technical investigation into the problem. These are personal and quite speculative, but provide an interesting insight into the mechanisms that might be used for building an intelligent system.

Connected through hyperedge HE-1 (induced by source paper "using stigmergy to incorporate the time into artificial neural networks"):
  with members:
    - "measuring physical activity of older adults via smartwatch and stigmergic receptive fields"
    - "recent advances in convolutional neural networks"
    - "deep learning in neural networks"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-2 (induced by source paper "a repeated signal difference for recognising patterns"):
  with members:
    - "a tutorial on principal component analysis"

Connected through hyperedge HE-3 (induced by source paper "a brain like cognitive process with shared methods"):
  with members:
    - "concept trees building dynamic concepts from semi structured data using nature inspired methods"
    - "one shot adaptation of supervised deep convolutional models"

Connected through hyperedge HE-4 (induced by source paper "new ideas for brain modelling 4"):
  with members:
    - "concept trees building dynamic concepts from semi structured data using nature inspired methods"
    - "a metric for modelling and measuring complex behavioural systems"
    - "tree pruning for new search techniques in computer games"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.AI(Artificial Intelligence)