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Dharmendra Modha, Manager of the Cognitive Computing program at IBM, explaining what they're working on right now.

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Cognitive Computing starts taking shape

IBM just announced that they successfully simulated 530 billion neurons and 100 trillion synapses running only 1542 times slower than real time using their own IBM-Cornell neurosynaptic cores. These cores incorporate central elements from neuroscience, including 356 leaky integrate-and-fire neurons, 1024 axons and 256x1024 synapses, fitting a 4.2mm square area.

This project is part of the DARPA SyNAPSE program which brings together nanotechnology, neuroscience and supercomputing to lay the foundation of a novel cognitive computing architecture that complements today's von Neumann machines. DARPA aims to develop electronic neuromorphic (brain-simulating) technology to scale to biological (and human) levels.

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The Consequences of Machine Intelligence

If machines are capable of doing almost any work humans can do, what will humans do?

The Atlantic's take on the role of humans after the singularity arrives. A skeptical, but fairly objective, look into this delicate subject. The author goes through many possible scenarios, coming to the conclusion that man will eventually be helpless when it comes to competing with machines in both physical and intelectual activities.

This article, however, doesn't take into consideration the fact that human intelligence and machine intelligence grow in tandem towards convergence. The line between what is human and what is machine is bound to grow thinner over the years, specially as we make breakthroughs in nanotechnology.

Mainstream media outlets, even reputed ones like 'The Atlantic', seem to have difficulty in grasping this concept of convergence.

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Everything about this ad seems taken out of a sci-fi movie, however, it's actually a real product that you can soon find on shelves. Now, I can't tell if this particular product works as advertised, but that doesn't matter.

What is becoming increasingly clear is that the quantified self movement is growing quickly and this sort of scenario may become something perfectly normal in just a couple of years (maybe months).

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Google's Sergey Brin overseeing the signing of the bill that will allow driverless cars in the state of California

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Steve Jobs talking about a new medium for transmitting knowledge. From knowledge passed through conversation, to stored knowledge , as in books, back to conversation. A very interesting vision for the future uses of virtual characters.

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Singularity University preparing AI Professors

Robot Professors Come With Singularity University’s Massive Upgrade

Big changes coming to Singularity University.

“Not a faculty member that teaches artificial intelligence — we want a faculty member that is artificial intelligence. We’re dead serious. … If anyone should be testing that, it should be us.”

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A believable emotional agent in use as a "compendium of all human knowledge". Scene from the movie "The Time Machine" (2002). Notice how the emotional features of the agent make it much more engaging.

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On Making Believable Emotional Agents Believable

Andrew Ortony, 2002:

I think that these categories [collapsed OCC model] have enough generative capacity to endow any agent with the potential for a rich and varied emotional life. As the information processing capabilities of the agent become richer, more elaborate ways of characterising the good and the bad become possible, so that one can imagine a system starting with only the competence to differentiate positive from negative and then developing progressively more elaborate categories. A simple example of this idea is that fear can be viewed as a special case of a negative feeling about something bad happening - with the bad thing being the prospect of something bad happening. If one adopts this position, then one is left with the idea that the main driving force underlying all emotions is the registration of good and bad and that discrete emotions can arise to the extent that the nature of what is good and bad for the agent can be elaborated. Indeed, this may well be how humans develop increasingly sophisticated emotion systems as they move from infancy through childhood to adulthood.

I wonder why we haven't seen ANY believable emotional agents with all the resources and information on this topic.

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A sci-fi short set in the near future where it's common to have Augmented Reality contact lenses that allow interaction with the real world through various apps, much like what happens with smartphones nowadays. It will be interesting to see if Google takes this direction with Google Glasses because, as this short shows, it comes with a few undesirable consequences...

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Legendary E. O. Wilson giving some very pratical and thought provoking advice to young scientists.

He encourages them to learn about disparaging fields and to become experts in specific topics that can be mastered in a short amount of time. Also, he stresses the need to not be afraid of parting from the establishment and to expand the frontiers of science towards unknown territories. On a surprising note, he reveals that many scientists lack mathmatical skills and diminishes their relevance, saying that when the time comes, they can always find a mathematician to cooperate. 

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An interesting explanation of some theories from learning science, such as why we forget things and how to avoid it. Regardless of the product they're actually selling.

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Graphic used by Omri Amirav-Drory on Solve for X laying out the similarities between computer science and biology. The Genome Compiler is the missing piece that he's working on.

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Omri Amirav-Drory, PhD in Biochemistry from Stanford, points out the similarities between computer science and biology. He demonstrates the Genome Compiler software he's developing that enables both researchers and amateurs to design genomic structures intuitively from other genomes, proteins, enzymes, etc., available on their database.

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Tomorrow’s cover today: as robots grow more autonomous, society needs to develop rules to manage them.

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Contextual Understanding by Computers by Joseph Weizenbaum 1967

Discussing machine understanding, conversational context and belief structures. Also, a 'new' ELIZA capable of inferential data acquisition with a script to reveal, rather than conceal, lack of understanding and misunderstanding.

It is too much to insist that a machine understands a sentence (or a symphony or a poem) only if that sentence invokes the same imagery in the machine as was present in the speaker of the sentence at the time he uttered it. For by that criterion no human understands any other human. Yet, we agree that humans do understand one another to within acceptable tolerances