1) Technology will either progress, or we will be wiped out by it.

babyandhelmetmedium-782882.jpgIf it progresses, we will re-engineer our biology, integrate it with wireless interconnectivity and manufactured computing power, and become as adult humans are to infants. Our powers will be beyond our current comprehension and wildest futuristic imagination.

3) Religious dogma doesn’t stand a chance against our coming intelligence.

4) Culture wars against dogmatic thinking are nearsighted. Technology will either kill us first, or make us too smart to be that stupid. The wealthy that have access to the technocrats inventions are our immediate threat, as are the smart hackers with ethics that allow for unleashing viruses. The new “viruses” will include self replicating nano-bots or biological bots.

rat_brain_implandfgt.jpg5) Once we are all borged up, virus writers will only be allowed to publish to virtual realities. Resistance will be futile to the borg. You can’t be invisible to all seeing and all pervasive intelligence – it won’t be humans against Arnold, it will be transhumans connected wirelessly and to each other and with cognitive capacity to enmesh their individualites as our neurons do into a whole cognition, connected second by second to second by second updated and manufactured technology. Creating biological circuitry and integrating it, all over the place.

6) Welcome the borg.

Update: This, on boingboing.net today:

Simulated mouse-brain running at 1/10 speed
IBM researchers have modelled a mouse’s brain at 10 percent speed — and what can be done at 10 percent speed today can be done at 1000 percent in a couple cycles of Moore’s Law. Super-intelligent virtual mice ahoy!
Neurobiologically realistic, large-scale cortical and sub-cortical simulations are bound to play a key role in computational neuroscience and its applications to cognitive computing. One hemisphere of the mouse cortex has roughly 8,000,000 neurons and 8,000 synapses per neuron. Modeling at this scale imposes tremendous constraints on computation, communication, and memory capacity of any computing platform.

We have designed and implemented a massively parallel cortical simulator with (a) phenomenological spiking neuron models; (b) spike-timing dependent plasticity; and (c) axonal delays.

We deployed the simulator on a 4096-processor BlueGene/L supercomputer with 256 MB per CPU. We were able to represent 8,000,000 neurons (80% excitatory) and 6,300 synapses per neuron in the 1 TB main memory of the system. Using a synthetic pattern of neuronal interconnections, at a 1 ms resolution and an average firing rate of 1 Hz, we were able to run 1s of model time in 10s of real time!

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