<i>The first example involves counting skills, ability to compare small numbers, ability to associate the words &quot;your friend&quot; to a known person, ability to retrieve information about her age from the LTM, ability to use personal pronouns.</i><p>Leaving aside the bit about learning to count, I don&#x27;t see that the paper shows how the system displayed any &#x27;ability to associate the words &quot;your friend&quot; to a known person&#x27;.<p>The input to the system that represents said friend is a set of phrases:<p><i>As the system has no sensory input, apart from that provided by the text-based interface, all the information must be provided in the form of input sentences.</i><p>In particular, the information about the friend in question is in the form of sentences:<p><i>The sentences of this dataset have been prepared by personifying the system in a four years old little girl in her social environment, which includes the two parents, a sister, a friend, two cousins, the four grandparents, two aunts, two uncles and six other children, for a total number of twenty persons.</i><p>At best they showed their system can recognise sentences that refer to a specific person, but recognition, or knowledge, of an actual person, is going to take a lot more than that.<p>To be honest, I don&#x27;t think they show anything else than an elaborate natural language interface to a database.