The hottest new field in biotech is synthetic biology: Scientists can now re-program life at the cellular level, just like a computer program. Syn-bio experts (also known as bio-hackers) are re-programming the DNA in viruses and creating novel life forms that can replicate and grow just like natural single cell organisms.
Joining Robert Tercek in the discussion are Andrew Hessel, Distinguished Research Scientist with the Bio/Nano Programmable Matter Group at Autodesk, and Dr. William Hurlbut, Physician and Consulting Professor at Stanford University.
Inventing the Future is a live news program featuring coming trends that will shape society. In today's world, success means knowing "What's Next After What's Next?" Lead by Robert Tercek, Inventing the Future offers insight into the future of the world after tomorrow.
Machine learning – the ability of computers to understand data, manage results, and infer insights from uncertain information – is the force behind many recent revolutions in computing. Email spam filters, smartphone personal assistants and self-driving vehicles are all based on research advances in machine learning. Unfortunately, even as the demand for these capabilities is accelerating, every new application requires a Herculean effort. Even a team of specially-trained machine learning experts makes only painfully slow progress due to the lack of tools to build these systems.
The Probabilistic Programming for Advanced Machine Learning (PPAML) program was launched to address this challenge. Probabilistic programming is a new programming paradigm for managing uncertain information. By incorporating it into machine learning, PPAML seeks to greatly increase the number of people who can successfully build machine learning applications and make machine learning experts radically more effective. Moreover, the program seeks to create more economical, robust and powerful applications that need less data to produce more accurate results – features inconceivable with today’s technology.
“We want to do for machine learning what the advent of high-level program languages 50 years ago did for the software development community as a whole,” said Kathleen Fisher, DARPA program manager.
“Our goal is that future machine learning projects won’t require people to know everything about both the domain of interest and machine learning to build useful machine learning applications. Through new probabilistic programming languages specifically tailored to probabilistic inference, we hope to decisively reduce the current barriers to machine learning and foster a boom in innovation, productivity and effectiveness.”
To familiarize potential participants with the technical objectives of PPAML, DARPA will host a Proposers' Day on Wednesday, April 10, 2013. For details, visit:http://www.solers.com/BAAinfo-reg/ppaml. Registration closes on Friday, April 5, 2013 at 5 p.m. ET.
The PPAML program is scheduled to run 46 months, with three phases of activity from 2013 to 2017. Fisher believes a successful solution will involve contributions from many areas, including statistics and probabilistic modeling, approximation algorithms, machine learning, programming languages, program analysis, compilers, high-performance software, and parallel and distributed computing.
The DARPA Special Notice document describing the specific capabilities sought is available at http://go.usa.gov/2PhW.
The term has been popularized by the Department of Artificial Architecture (Institute of Artificial Art Amsterdam), where remarkable efforts in this area have been made employing visual grammar to generate random specifications of 3-dimensional objects and structures.
The concept of artificial architecture was theoretically proposed and thoroughly used in the title and the content of a PhD Thesis developed at Polytechnical University of Madrid (Spain): Arquitectura Artificial o Manierismo por Computadora (Artificial Architecture or Computer Aided Mannerism). 
There has been much speculation about the future of humanity in the face of super-humanly intelligent machines. Most of the dystopian scenarios seem to be driven by plain fear that entities arise that could be smarter and stronger than us. After all, how are we supposed to know which goals the machines will be driven by? Is it possible to have “friendly” AI? If we attempt to turn them off, will they care? Would they care about their own survival in the first place?
With Flexpad, paper, plastic film or another flexible material is transformed into a computer input device and moveable display.
Recently at the 2013 IFA international trade show for consumer electronics and home appliances in Berlin, major electronics manufacturers displayed new types of displays that are thin, and even curved, but expensive. IT experts in Saarbrücken have gone a step further. Their more cost-effective approach, called Flexpad, allows a simple, standard sheet of paper to be transformed into a moveable, flexible display. Already today, this could help patients better review the results of a computer tomography, for example. In the long term, the IT experts want to discover what new applications are viable in future for ultra-thin, deformable, mobile end devices, and how they can best be operated.
Human organs shimmer in red on a sheet of paper displaying a longitudinal view of the human abdomen. The spinal column and pelvic bones form contrasting yellow islands. As the sheet of paper is bent downwards at the ends, the bones appear to come into the foreground while the soft tissue recedes (see video). What appears to be science fiction at first glance, is the result of the “Flexpad” research project developed under the leadership of Jürgen Steimle in the Media Lab at the Massachusetts Institute of Technology in the US and the Max Planck Institute for Informatics in Saarbrücken, in cooperation with Kiel University. In the meantime, Steimle heads the Embodied Interaction research group at the Multimodal Computing and Interaction Cluster of Excellence.
“We routinely deform objects intuitively in many different ways. We bend back pages in books, deflate balls, fold paper, and sculpt clay”, explains Jürgen Steimle. “And by projecting user interface elements onto tangible, deformable objects we can control computers and other technical devices better and more easily.”
Flexpad thereby works as follows: The motion sensor records the user and the paper, capturing the paper’s deformation and movement. So that the recording takes place precisely and in real time despite the rather coarse image data from the Kinect camera, the researchers have developed and implemented two algorithms. The first initially subtracts out the interference caused by the fingers and hands of the user. If the user moves the paper - whether left or right, or bends it into an arc or wavy form - the camera senses this. A specially developed computer model subsequently describes these movements in fractions of a second, so that the projector can reproduce it on the sheet in near real time.
Nevertheless, Flexpad has certain limits: The user must stand in a particular area under the camera and projector for the system to work properly. Therefore, the user cannot move freely around the room.
“The paper takes on two simultaneous functions in our system”, explains Steimle. “It is input device and display at the same time.” The user can interact with the device in a similar way to using a mouse for controlling a computer. Other materials besides paper are also suitable, for example sheets of plastic or other deformable materials. The only important thing is that they possess a certain malleability and flexibility.
(PhysOrg.com) -- The Kilobots are coming. Computer scientists and engineers at Harvard University have developed and licensed technology that will make it easy to test collective algorithms on hundreds, or even thousands, of tiny robots.
"The Precision Information Environment (PIE) Activity Awareness Environment was designed to improve the information synthesis process by bringing in multiple, disparate data feeds and sources, extracting features of interest and visualizing the information to give emergency response professionals insight and situational understanding in a timely and intuitive manner. The system also applies a user recommendation system to help filter the data based on the needs and activities of the user thereby giving them the right information at the right time. http://precisioninformation.org"
Researchers from the National University of Singapore’s (NUS) Faculty of Engineering has created efficient artificial, or “robotic” muscles, which could carry a weight 80 times its own and able to extend to five times its original length when carrying the load – a first in robotics.
Sci-News.com Immune Cells in Brain Can Influence Your Mood Sci-News.com Bibliographic information: Eric S. Wohleb et al. 2013. Stress-Induced Recruitment of Bone Marrow-Derived Monocytes to the Brain Promotes Anxiety-Like Behavior.
Online Course Introduction to Social Network Analysis (SNA) taught by Dr. Jennifer Golbeck at Statistics.com.This course will teach a mix of quantitative and qualitative methods for describing, measuring and analyzing social networks.
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