C REATING AI: A UNIQUE INTERPLAY BETWEEN THE DEVELOPMENT OF LEARNING ALGORITHMS AND THEIR EDUCATION Authors: Anat Treister-Goren and Jason L. Hutchens Presentation by: Carlos Fernández Musoles

I NTRODUCTION Alan Turing “Can machines think?” = Turing Test: conversational scenario, whereby if a human interrogator cannot distinguish between a machine and a human, then it can be said to be thinking. Artificial Intelligence NV (Ai) goal is to create a machine capable of passing the Turing Test. Currently: HAL has a level of a 18 month child. Equal importance to the development of learning algorithms and their training and evaluation.

O VERVIEW Difficult to simulate adult level conversation Turing suggestion: instead produce a programme to simulate the child’s, and then subject it to appropriate education to develop it to an adult level. Traditional approach Fixed grammatical rules are sufficient. Failed to learn the essence of human intelligence. Ai approach More behaviouristic approach: stimuli from the environment (feedback) – response from the system (learning) Black box model (architecture is not important, behaviour is)

HAL’ S A RCHITECTURE Black box system from the trainer point of view Internally, two models: one makes predictions about the symbol it is likely to observe next (probability distribution); the second calculates correlations between HAL’s behaviour and reinforcement from the trainer The development team help improving learning algorithms

HAL’ S A RCHITECTURE Conversation HAL-trainer is enough to go from babbling in characters to generating meaningful sequences of words Feedback information is given in an intuitive way Trainer can edit HAL’s sentences by adding / deleting characters (with gives reinforcement)

T RAINING AND E VALUATION Our perception of intelligence is influenced by our expectations (monkeys, children, lecturers...) Setting different levels to be achieved by HAL helps in the learning HAL is given specific reinforcement on each level to achieve the necessary lingual behaviours

‘15 MONTH OLD ’ MILESTONE HAL’s performance comparable to a 15-month-old child Example:

‘18 MONTH OLD ’ MILESTONE Vocabulary grows, start combining words Remarkable: ‘monkeys eat bananas’; HAL remembered a previous conversation about zoo.

C ONCLUSION HAL can successfully learn up to a 18 month child level with the development-training model Good start point, but how do we jump from here to other basic aspects of our intelligence? Eg: abstract reasoning, creativity, independent thought... This model does not seem complex enough to achieve these.