Uke 30
Medfølelse er et instinkt
Emma Seppala skriver i en artikkel i Psychology Today om forskning som indikerer at medfølelse er et instinkt som er grunnleggende hos alle mennesker. Det er en forutsetning for overlevelse som art.
Dette er stikk i strid med hva økonomer, o.l. hevder, nemlig at alle mennesker er egoister.
Myten om gjennomsnittspersonen
Todd Rose argumenterer for at myten om gjennomsnittsstudenten er ødeleggende for utdanning og læring. Ingen er gjennomsnittlige. Noen har talent for realfag, men er dårlige til å lese. Andre er dyktige i språk, men ikke i matte.
Han mener derfor at man bør lage læring som er tilpasset kantene. Det kan tilsvare at hvis man utformer bygg med tanke på funksjonshemmede, vil det fungere for alle.Med digital teknologi er det ganske kurant at alle kan lære individuelt uten at det koster mer.
"Universal design for learning" kan gjerne være et sted å begynne.
Hjerneprotese
Jeg har lenge syslet med tanken om at vi vil få hjerneproteser.
Nå har Universitetet i Zurich kunngjort at man har laget en mikrochip som imiterer hjernen i sanntid, dvs. den er istand til å utføre kompliserte kognitive oppgaver (artikkel vedlagt).
De har brukt nevromorfe kretser for å få det til:
Fig. 1. Synthesis of a target FSM in neuromorphic VLSI neural networks.
(A) State diagram of the high-level behavioral model. Circles represent states and arrows indicate the transitions between them, conditional on input symbol X. In this example state machine, the active state flips between S1 and S2 in response to X and outputs either the response A or the response B, depending on the previous state.
(B) The computational substrate composed of three sWTA networks: two “state-holding” networks (vertical and horizontal rectangles) and a third transition network (central square). The shaded circles in each sWTA represent populations of spiking neurons that are in competition through a population of inhibitory neurons (not displayed). The state-holding sWTA networks are coupled population-wise (γ-labeled arrow, red with red, blue with blue, etc.) to implement working memory. Solid arrows indicate stereotypic couplings, and the dashed arrows indicate couplings that are specific to the FSM (in this case the one shown in A). The gain and threshold in the transition sWTA are configured such that each population becomes active only if both of its inputs are presented together. The sWTA competition ensures that only a single population in the network is active at any time. An additional output sWTA network is connected to the transition network to represent the output symbols. To program a different state machine, only the dashed arrows need to be modified.
(C) The multineuron chips used in the neuromorphic setup feature a network of low-power I&F neurons with dynamic synapses. The chips are configured to provide the hardware neural substrate that supports the computational architecture consisting of sWTA shown in B. Each population of an sWTA network is represented in hardware by a small population of recurrently coupled spiking neurons .N . 16., which compete against other populations via an inhibitory population.