Sobre los chips sinapticos de IBM

Estos días se ha estado hablando mucho sobre los chips neuronales de IBM.

Computer chips with worm-like intelligence were unveiled today by researchers at IBM, a breakthrough, they say, on the road to creating computers that function like the human brain.
For now, achieving the goal of human-like intelligence in a computer with the size and power needs of our brains is a long ways off, Dharmendra Modha, the researcher leading the project, told me, but the chips he held as we spoke were proof that a "new generation" of computers are in the offing.
"It is IBM's first cognitive computer core that brings together computation in the form of neurons, memory in the form of synapses and communication in the form of axons," he said.
Such chips, he said, could form the basis of computers that are able to monitor real-time traffic-light cameras, notice an anomaly and dispatch an ambulance in time to save lives.

Fuente: MSNBC IBM unveils brain-like chip

Para completar un festejo por sus 100 años,IBM anunció que el proyecto Synapse busca desarrollar en el futuro un ordenador de 10.000 millones de neuronas y lograr 100 billones de operaciones sinápticas, algo que significaría superar la potencia del cerebro humano 10 veces. Ahora sí puedes asustarte.

Fuente: Neoteo Proyecto Synapse: Chips basados en el cerebro humano


Parece que estamos a la vuelta de la esquina de conseguir una Inteligencia Artificial de nivel humano o superior. Pero las cosas no son así.

Ben Goertzel, experto transhumanista en IA comenta lo siguiente.

Complexity such as that revealed in Modha and Singh's diagrams always comes to my mind when I read about someone's "brain inspired" AGI architecture -- say, Hierarchical Temporal Memory architectures (like Numenta or DeSTIN, etc.) that consist of a hierarchy of layers of nodes, passing information up and down in a manner vaguely reminiscent of visual or auditory cortex. Such architectures may be quite valuable and interesting, but each of them captures a teensy weensy fraction of the architectural and dynamical complexity in the brain. Each of the brain regions in Modha and Singh's diagram is its own separate story, with its own separate and important functions and structures and complex dynamics; and each one interacts with a host of others in specially configured ways, to achieve emergent intelligence. In my view, if one wants to make a brain-like AGI, one's going to need to emulate the sort of complexity that the actual brain has -- not just take some brain components (e.g. neurons) and roughly simulate them and wire the simulations together in some clever way; and not just emulate the architecture and dynamics of one little region of the brain and proclaim it to embody the universal principles of brain function.

Fuente: The Multiverse According to Ben Unraveling Modha & Singh's Map of the Macaque Monkey Brain


Simular un cerebro humano, va a ser más complejo que decir, el cerebro tiene X neuronas con Y sinapsis, si creamos un procesador que simule X neuronas e Y sinapsis, lo tendremos. Necesitamos conocer con más detalle la complejidad del cerebro, y solo hemos empezado.
Si hiciésemos un cultivo de neuronas con sus conexiones, e igualásemos en numero a un cerebro humano, ¿ Creéis que emergería una conciencia de este?