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Very interesting discovery about how our brain thinks; our brain isn’t always 100% error proof according to this report from Carnegie Mellon University. Therefore, when researchers are mapping the brain plus mimicking human brain functions; what is the tolerance level for error allowed then?


(Source: Carnegie Mellon University)A study conducted at Carnegie Mellon University investigated the brain’s neural activity during learned behavior and found that the brain makes mistakes because it applies incorrect inner beliefs, or internal models, about how the world works. The research suggests that when the brain makes a mistake, it actually thinks that it is making the correct decision—its neural signals are consistent with its inner beliefs, but not with what is happening in the real world.

“Our brains are constantly trying to predict how the world works. We do this by building internal models through experience and learning when we interact with the world,” said Steven Chase, an assistant professor in the Department of Biomedical Engineering and the Center for the Neural Basis of Cognition. “However, it has not yet been possible to track how these internal models affect instant-by-instant behavioral decisions.”

The researchers conducted an experiment using a brain-machine interface, a device that allows the brain to control a computer cursor using thought alone. By studying the brain’s activity, the researchers could see how the brain thinks an action should be performed. The researchers report that the majority of errors made were caused by a mismatch between the subjects’ internal models and reality. In addition, they found that internal models realigned to better match reality during the course of learning. “To our knowledge, this is the most detailed representation of a brain’s inner beliefs that has been identified to date,” said Byron Yu, an associate professor in the Department of Electrical and Computer Engineering and the Department of Biomedical Engineering.

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I shared this same point of view yesterday; and glad to see Princeton shares the same perspective on Quantum and it’s abundant capabilities. Again; Quantum is going to truly change (if not everything) almost everything that we consume, use, and interact with even in raw material enrichment will benefit from Quantum.


Claire White, an assistant professor of civil and environmental engineering and the Andlinger Center for Energy and the Environment, studies ways to make building materials more sustainable. It turns out that cement production creates a lot of carbon dioxide, so much that it accounts for roughly 5 to 8 percent of man-made carbon dioxide emissions globally. White and her team are developing new types of cement using industrial byproducts such as coal fly ash and blast-furnace slag. They make these materials more durable by adding nanoparticles.

Watch Assistant Professor Claire White explain her research on a more sustainable type of cement.

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REMINDER: DARPA’s Neural Engineering System Design (NESD) Program Proposers Days is tomorrow and Wed. (February 2–3, 2016) at The Westin Gateway Hotel, 801 N. Glebe Road, Arlington, VA 22203. This is part of the Brain Mind Interface development work. Good thing that the research on Graphene came out recently showing that it is a viable substance for BMIs.


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The burgeoning field of nanotechnology promises an indefinite range of capabilities in medicine, optics, communications, and other facets of applied science and engineering. On that front, the U.S. Defense Advanced Research Projects Agency’s (DARPA) Atoms 2 Products program (A2P) is funding 10 companies, universities, and institutions to develop mass-manufacturing techniques and technologies for functional products made up of nanoscale constituents. The project demonstrates a mere slice of the contributions in the mass movement to make nanotechnology a part of our everyday lives.

The following gallery highlights the work of five DARPA-funded projects in the program. The slides describe an atomic calligraphy technique for 2D atomic printing, a manufacturing method for producing high-frequency “Nanolitz” wires, the construction of pop-up sensors for laparoscopy, and a conjunct effort to use micro-robotics to build the assemblers of nanodevices.

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Finally, folks are getting the real picture around re-tooling and retraining folks for new jobs in an oncoming AI future. In my posts; I have highlighted the need for governments and businesses to retrain people as well as ensure that their is some level of funding established to assist displaced workers, and especially as we see the maturity of Quantum in the AI space this will definitely be a must.


Untitled“If every tool, when ordered, or even of its own accord, could do the work that befits it… then there would be no need either of apprentices for the master workers or of slaves for the lords.” – Aristotle.

Humans have such a love/hate relationship with technology that it’s almost comical. All of our own creation, once we’ve perfected amazing innovations, we often turn on them–when convenient. As the PC became common and marketed toward the masses in the 80s, a new world of automation, both good and bad, was predicted. As mad scientists tucked away in secret, underground labs began creating evil robots in a slew of sci-fi movies that we consumed greedily, along with becoming affectionate toward machines like C-3P0 and R2-D2 just birthed in what would be a continuing pop subculture with a momentum of its own, our imaginations ran wild. Fearmongers cited that automation would make many jobs obsolete; robots would begin doing what was left as an economic apocalypse ensued for the human race.

In truth, the birth of the computer created a huge industry of jobs, from manufacturing and maintenance to advanced software engineering and entire IT departments. And although it’s been predicted through the ages that robots would begin doing all of our tasks, how many of us are actually employing robots in the home or office–and how many people do you know who lost their jobs because it was given to a humanoid instead? Probably none. But still, yes, there are whispers saying that may change one day soon. And while we’ve all heard that talk for decades past, it is undeniable that innovation on nearly every level has been accelerated recently, and is predicted to continue as 3D printing, artificial intelligence, and robotics evolve–just as a few examples.

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With a growing number of Earth-like exoplanets discovered in recent years, it is becoming increasingly frustrating that we can’t visit them. After all, our knowledge of the planets in our own solar system would be pretty limited if it weren’t for the space probes we’d sent to explore them.

The problem is that even the nearest stars are a very long way away, and enormous engineering efforts will be required to reach them on timescales that are relevant to us. But with research in areas such as nuclear fusion and nanotechnology advancing rapidly, we may not be as far away from constructing small, fast interstellar space probes as we think.

There’s a lot at stake. If we ever found evidence suggesting that life might exist on a planet orbiting a nearby star, we would most likely need to go there to get definitive proof and learn more about its underlying biochemistry and evolutionary history. This would require transporting sophisticated scientific instruments across interstellar space.

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Maybe an opportunity to hire some pretty talented women in the mix this time. If you think about it, women are very strong in communications & multitasking which is perfect to lead Twitter’s product innovation; and not to mention what women could do for wearables innovation. Some amazing female execs in wireless (ISPs & Devices), online communications and marketing firms, Google and Microsoft has some amazing female leaders, etc. Tons of capable women that could really make some magic happen for Twitter.


Twitter CEO Jack Dorsey has confirmed the departures of Twitter execs, who oversaw the product, engineering, media and HR teams.

Was really hoping to talk to Twitter employees about this later this week, but want to set the record straight now: pic.twitter.com/PcpRyTzOlW

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DoD spending $12 to $15 billion of its FY17 budget on small bets that includes NextGen tech improvements — WOW. Given the DARPA new Neural Engineering System Design (NESD); guessing we may finally have a Brain Mind Interface (BMI) soldier in the future.


The Defense Department will invest the $12 billion to $15 billion from its Fiscal Year 2017 budget slotted for developing a Third Offset Strategy on several relatively small bets, hoping to produce game-changing technology, the vice chairman of the Joint Chiefs of Staff said.

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The technique, which also has near-term implications for growing organ-like tissues on a chip, was developed by researchers at MIT and is unveiled in a study published today in the journal Nature Communications.

Growing organs on demand, using derived from patients themselves, could eliminate the lengthy wait that people in need of a transplant are often forced to endure before one becomes available.

It could also reduce the risk of a patient’s immune system rejecting the transplant, since the tissue would be grown from the patient’s own cells, according to Ron Weiss, professor of biological engineering at MIT, who led the research.

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