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How 'Google Science' could transform academic publishing

How 'Google Science' could transform academic publishing | Science, Technology, and Current Futurism | Scoop.it
Google is allegedly working on a free, open access platform for the research, collaboration and publishing of peer-reviewed scientific journals

Via Ana Cristina Pratas
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Why Cognition-as-a-Service is the next operating system battlefield

Why Cognition-as-a-Service is the next operating system battlefield | Science, Technology, and Current Futurism | Scoop.it
Competition between CaaS platforms will enable smarter and more helpful products, from our phones to our homes.

 

App developers will soon need to choose which CaaS ecosystem to build on — Google, Apple, Facebook, Microsoft, or maybe even Wolfram’s new Wolfram Language ecosystem.

In the long-run however, a more vendor neutral cognition platform may emerge as the winner: one that is more like Amazon Web Services in that it just provides the underlying service and doesn’t compete with third-party apps that use it. This could come from Amazon, or Wolfram perhaps. CaaS platforms may eventually even be open-sourced and made widely available — perhaps via a Linux equivalent for the cognitive operating system era that might borrow from many of the original ideas and standards of the Semantic Web.

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Are these 8 trends the future of K-12? | eSchool News | eSchool News

Are these 8 trends the future of K-12? | eSchool News | eSchool News | Science, Technology, and Current Futurism | Scoop.it
What ed-tech trends or developments will impact the future of K-12 education? What will teaching and learning look like? Read on to find out.

Via Maria Lopez Alvarado, MBA
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Machine-learning algorithms could make chemical reactions intelligent leading to "smart drugs"

Machine-learning algorithms could make chemical reactions intelligent leading to "smart drugs" | Science, Technology, and Current Futurism | Scoop.it

Computer scientists at the Harvard School of Engineering and Applied Sciences (SEAS) and the Wyss Institute for Biologically Inspired Engineering at Harvard University have joined forces to put powerful probabilistic reasoning algorithms in the hands of bioengineers.

 

In a new paper presented at the Neural Information Processing Systems conference on December 7, Ryan P. Adams and Nils Napp have shown that an important class of artificial intelligence algorithms could be implemented using chemical reactions.

 

These algorithms, which use a technique called “message passing inference on factor graphs,” are a mathematical coupling of ideas from graph theory and probability. They represent the state of the art in machine learning and are already critical components of everyday tools ranging from search engines and fraud detection to error correction in mobile phones.

 

Adams’ and Napp’s work demonstrates that some aspects of artificial intelligence (AI) could be implemented at microscopic scales using molecules. In the long term, the researchers say, such theoretical developments could open the door for “smart drugs” that can automatically detect, diagnose, and treat a variety of diseases using a cocktail of chemicals that can perform AI-type reasoning.

 

“We understand a lot about building AI systems that can learn and adapt at macroscopic scales; these algorithms live behind the scenes in many of the devices we interact with every day,” says Adams, an assistant professor of computer science at SEAS whose Intelligent Probabilistic Systems group focuses on machine learning and computational statistics. “This work shows that it is possible to also build intelligent machines at tiny scales, without needing anything that looks like a regular computer. This kind of chemical-based AI will be necessary for constructing therapies that sense and adapt to their environment. The hope is to eventually have drugs that can specialize themselves to your personal chemistry and can diagnose or treat a range of pathologies.”

 

Adams and Napp designed a tool that can take probabilistic representations of unknowns in the world (probabilistic graphical models, in the language of machine learning) and compile them into a set of chemical reactions that estimate quantities that cannot be observed directly. The key insight is that the dynamics of chemical reactions map directly onto the two types of computational steps that computer scientists would normally perform in silico to achieve the same end.

 

This insight opens up interesting new questions for computer scientists working on statistical machine learning, such as how to develop novel algorithms and models that are specifically tailored to tackling the uncertainty molecular engineers typically face. In addition to the long-term possibilities for smart therapeutics, it could also open the door for analyzing natural biological reaction pathways and regulatory networks as mechanisms that are performing statistical inference. Just like robots, biological cells must estimate external environmental states and act on them; designing artificial systems that perform these tasks could give scientists a better understanding of how such problems might be solved on a molecular level inside living systems.


Via Dr. Stefan Gruenwald
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(HD) Dr. Michio Kaku: The Biotech Revolution - Vision of the Future - Full Documentary

(HD) Dr. Michio Kaku: The Biotech Revolution - Vision of the Future - Full Documentary ❶ HD Universe Channel: For all your Space, Universe and Science docume...

Via Socrates Logos, Claudia, Jim Lerman, Lynnette Van Dyke
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Socrates Logos's comment, October 22, 2013 4:17 PM
They recently changed it. Try this link http://www.youtube.com/watch?v=CG8TekgNEhA
malek's comment, October 22, 2013 5:25 PM
@socrates Logos: this link is active, thank you for sharing
Socrates Logos's comment, October 22, 2013 5:27 PM
Great - you are welcome
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The time machine in our mind. The imagistic mental machinery that allows us to travel through time

The time machine in our mind. The imagistic mental machinery that allows us to travel through time | Science, Technology, and Current Futurism | Scoop.it

“This article provides the first comprehensive conceptual account for the imagistic mental machinery that allows us to travel through time—for the time machine in our mind. It is argued that language reveals this imagistic machine and how we use it. Findings from a range of cognitive fields are theoretically unified and a recent proposal about spatialized mental time travel is elaborated on. The following novel distinctions are offered: external vs. internal viewing of time; “watching” time vs. projective “travel” through time; optional vs. obligatory mental time travel; mental time travel into anteriority or posteriority vs. mental time travel into the past or future; single mental time travel vs. nested dual mental time travel; mental time travel in episodic memory vs. mental time travel in semantic memory; and “seeing” vs. “sensing” mental imagery. Theoretical, empirical, and applied implications are discussed. (...) Many conceptualizations observed in language have also been found to exist in mental representations that are more basic than language itself. (…)

 

The evolution of the capacity to simulate possible future events, based on episodic memory, enhanced fitness by enabling action in preparation of different possible scenarios that increased present or future survival and reproduction chances. Human language may have evolved in the first instance for the sharing of past and planned future events, and, indeed, fictional ones, further enhancing fitness in social settings.”


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Stunning Progress in Technology Brings The Death of Unskilled Labor

Stunning Progress in Technology Brings The Death of Unskilled Labor | Science, Technology, and Current Futurism | Scoop.it

As part of the online web series Which Way Next, hosted by Singularity University, Vivek Wadhwa, VP of Academics and Innovation, sat down with Carl Bass, CEO at Autodesk, to explore some of the pivotal technologies coming online that promise to redefine the jobs available to humans in the 21st Century. Check out the video.


Via Sakis Koukouvis
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Your Brain in 2050: Neural Implants and Robotic Limbs : DNews

Your Brain in 2050: Neural Implants and Robotic Limbs : DNews | Science, Technology, and Current Futurism | Scoop.it
Brain technology could one day allow humans to naturally control robotic limbs or replace human sight.
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A 3-D Printing Breakthrough: Jennifer Lewis at Harvard 3-D Prints Biological Tissue | MIT Technology Review

A 3-D Printing Breakthrough: Jennifer Lewis at Harvard 3-D Prints Biological Tissue | MIT Technology Review | Science, Technology, and Current Futurism | Scoop.it
Inks made from different types of materials, precisely applied, are greatly expanding the kinds of things that can be printed.

 

Last year, Lewis and her students showed they could print the microscopic electrodes and other components needed for tiny lithium-ion batteries (see “Printing Batteries”). Other projects include printed sensors fabricated on plastic patches that athletes could one day wear to detect concussions and measure violent impacts. Most recently, her group printed biological tissue interwoven with a complex network of blood vessels. To do this, the researchers had to make inks out of various types of cells and the materials that form the matrix supporting them. The work addresses one of the lingering challenges in creating artificial organs for drug testing or, someday, for use as replacement parts: how to create a vascular system to keep the cells alive.

 

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A Scientist Predicts the Future

A Scientist Predicts the Future | Science, Technology, and Current Futurism | Scoop.it

When making predictions, I have two criteria: the laws of physics must be obeyed and prototypes must exist that demonstrate “proof of principle.” I’ve interviewed more than 300 of the world’s top scientists, and many allowed me into laboratories where they are inventing the future. Their accomplishments and dreams are eye-opening. From my conversations with them, here’s a glimpse of what to expect in the coming decades:


Via Pierre Tran
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Teresa Lima's curator insight, January 10, 4:38 AM

#Not 

I think the future is unpredictable, and no one  can predict the future!

Carlos Polaino Jiménez's curator insight, January 16, 7:38 AM

Predicción científica del futuro, esto es un tema a leer por lo menos.

Jesús Martinez's curator insight, January 18, 8:07 AM

add your insight...

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Medical schools try to entice more students to become primary-care doctors.

Medical schools try to entice more students to become primary-care doctors. | Science, Technology, and Current Futurism | Scoop.it
Amid a looming shortage of primary-care doctors in the U.S., medical schools and innovators try to entice more students to enter the field.
Sharrock's insight:

"Over 90% of medical training in the United States takes place in academic medical centers," says G. Richard Olds, the founding dean at Riverside, "but if we want students to go into primary care, we have to push training out into the community with a public-health agenda."

 
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Can We Survive the Sun’s Death?

Can We Survive the Sun’s Death? | Science, Technology, and Current Futurism | Scoop.it
In the distant future, our sun will begin its descent into death after using up all of the hydrogen fuel in its core. When that happens, the inner parts of our solar system will suffer horrible consequences.
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33rd Square: Breakthrough May Lead To Alzheimer's Vaccine

33rd Square: Breakthrough May Lead To Alzheimer's Vaccine | Science, Technology, and Current Futurism | Scoop.it
A team of scientists from Université Laval, CHU de Québec, and pharmaceutical firm GlaxoSmithKline has discovered a way to stimulate the brain's natural defense mechanisms in people with Alzheimer's disease.
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