Lifeboat Foundation

Trying to streamline an operation that spends more than $5 billion a year on developing new drugs, Novartis dispatched teams to jetmaker Boeing Co. and Swissgrid AG, a power company, to observe how they use technology-laden crisis centers to prevent failures and blackouts. That led to the design of something that looks like the pharma version of NASA’s Mission Control: a global surveillance hub where supercomputers map and chart Novartis’s network of 500 drug studies in 70 countries, trying to predict potential problems on a minute-by-minute basis.

A third of development costs comes from clinical trials. Novartis wants to make them cheaper and faster.

In May, 2016 I stumbled upon a highly controversial Aeon article titled “The Empty Brain: Your brain does not process information, retrieve knowledge or store memories. In short: your brain is not a computer” by psychologist Rob Epstein. This article attested to me once again just how wide the range of professional opinions may be when it comes to brain and mind in general. Unsurprisingly, the article drew an outrage from the reading audience. I myself disagree with the author on most fronts but one thing, I actually agree with him is that yes, our brains are not “digital computers.” They are, rather, neural networks where each neuron might function sort of like a quantum computer. The author has never offered his version of what human brains are like, but only criticized IT metaphors in his article. It’s my impression, that at the time of writing the psychologist hadn’t even come across such terms as neuromorphic computing, quantum computing, cognitive computing, deep learning, evolutionary computing, computational neuroscience, deep neural networks, and alike. All these IT concepts clearly indicate that today’s AI research and computer science derive their inspiration from human brain information processing — notably neuromorphic neural networks aspiring to incorporate quantum computing into AI cognitive architecture. Deep neural networks learn by doing just children.

By Alex Vikoulov.

Continue reading “Our Neural Code: A Pathway to AI Minds?” »

For the tenth consecutive year, #Deloitte, a global leader in audit and consulting, lists the technological trends that will transform the processes, products, and services of the most innovative companies in the world this year.

These technologies include advanced network architectures, serverless computing, and intelligent interfaces, as well as increased development of digital, cognitive and cloud experiences.

Yes, uncertainty is disconcerting. But much of the tech-driven disruption today—and, likely, going forward—is both understandable and knowable.

https://go.nasa.gov/2RR7KZ2

Oops sry wrong group…😁✨🕊.

A Northwestern University team is reshaping the world of graphene—literally.

Scientists made a ‘new’ periodic table of elements to show how smartphones (and party balloons) are draining Earth’s resources.

The human brain has amazing capabilities making it in many ways more powerful than the world’s most advanced computers. So it’s not surprising that engineers have long been trying to copy it. Today, artificial neural networks inspired by the structure of the brain are used to tackle some of the most difficult problems in artificial intelligence (AI). But this approach typically involves building software so information is processed in a similar way to the brain, rather than creating hardware that mimics neurons.

My colleagues and I instead hope to build the first dedicated neural network computer, using the latest “quantum” technology rather than AI software. By combining these two branches of computing, we hope to produce a breakthrough which leads to AI that operates at unprecedented speed, automatically making very complex decisions in a very short time.

We need much more advanced AI if we want it to help us create things like truly autonomous self-driving cars and systems for accurately managing the traffic flow of an entire city in real-time. Many attempts to build this kind of software involve writing code that mimics the way neurons in the human brain work and combining many of these artificial neurons into a network. Each neuron mimics a decision-making process by taking a number of input signals and processing them to give an output corresponding to either “yes” or “no”.

Continue reading “Quantum Computer: We’re Planning to Create One That Acts Like a Brain” »

Solar rays are a plentiful, clean source of energy that is becoming increasingly important as the world works to shift away from power sources that contribute to global warming. But current methods of harvesting solar charges are expensive and inefficient—with a theoretical efficiency limit of 33 percent. New nanomaterials developed by researchers at the Advanced Science Research Center (ASRC) at The Graduate Center of The City University of New York (CUNY) could provide a pathway to more efficient and potentially affordable harvesting of solar energy.