"Cognitive science is the interdisciplinary study of mind and intelligence, embracing philosophy, psychology, artificial intelligence, neuroscience, linguistics, and anthropology. Its intellectual origins are in the mid-1950s when researchers in several fields began to develop theories of mind based on complex representations and computational procedures."
– Paul Thagard. Cognitive Science , in The Stanford Encyclopedia of Philosophy.
Cognitive overload happens to students and teachers. Often looking like ADHD, cognitive overload can happen for a variety of reasons including challenges to your working memory. Todd Finley some ways to help your students and yourself when you struggle with cognitive overload. What is it, and how do we work with it in our students and in ourselves? Today thought leader Todd Finley is going to help us understand this.
Recent evidence challenges the widely held view that the hippocampus is specialized for episodic memory, by demonstrating that it also underpins the integration of information across experiences. Contemporary computational theories propose that these two contrasting functions can be accomplished by big-loop recurrence, whereby the output of the system is recirculated back into the hippocampus. We use ultra-high-resolution fMRI to provide support for this hypothesis, by showing that retrieved information is presented as a new input on the superficial entorhinal cortex--driven by functional connectivity between the deep and superficial entorhinal layers. Our findings offer a novel perspective on information processing within the hippocampus and support a unifying framework in which the hippocampus captures higher-order structure across experiences, by creating a dynamic memory space from separate episodic codes for individual experiences.
Molecular biologist Feng Zhang has been named a winner of the prestigious Keio Medical Science Prize. He is being recognized for the groundbreaking development of CRISPR-Cas9-mediated genome engineering in cells and its application for medical science. Zhang is the James and Patricia Poitras Professor of Neuroscience at MIT, an associate professor in the departments of Brain and Cognitive Sciences and Biological Engineering, a Howard Hughes Medical Institute investigator, an investigator at the McGovern Institute for Brain Research, and a core member of the Broad Institute of MIT and Harvard. "We are delighted that Feng is now a Keio Prize laureate," says McGovern Institute Director Robert Desimone. "This truly recognizes the remarkable achievements that he has made at such a young age."
We can officially say this now, since Gartner included knowledge graphs in the 2018 hype cycle for emerging technologies. Though we did not have to wait for Gartner -- declaring this as the "Year of the Graph" was our opener for 2018. Like anyone active in the field, we see the opportunity, as well as the threat in this: With hype comes confusion. They have been for the last 20 years at least. Knowledge graphs, in their original definition and incarnation, have been about knowledge representation and reasoning.
Artificial intelligence and cognitive computing will generate more than $150 billion in savings for the healthcare industry by 2025, according to a report by the market research firm Frost & Sullivan. Today, only 15 to 20 percent of health IT end users have actively used AI to drive changes in healthcare delivery. China is also dominant in the AI space, while Japan and India are growing their AI footprints. Europe has struggled to maintain a stronghold in AI due to the region's more restrictive data policies. More articles on artificial intelligence: Google Cloud taps Carnegie Mellon professor to lead AI Elon Musk suggests he's only months from'merging' the human brain with AI Indiana U School of Medicine partners with Fujifilm for AI research
I started transforming businesses with technology 35 years ago. It was as true then as it is now that the biggest risk we have to mitigate is the resistance of people and organizations to change. It is a well-known fact that three in four transformation programmes fail to achieve their intended goals because people are not prepared to adopt new processes and technology. Mitigating these risks and helping people learn new technology-enabled processes has been good for the consulting industry, and continues to be one of the keys to successful programmes. With artificial intelligence (AI), change management and process reengineering get reinvented.
We also need to recognise that there will be specific points in our lives where our priorities, and therefore interests, might change. We are all used to talking about a mid-life crisis where we impulsively make rash decisions (such as buying a new sports car). However, research by LinkedIn has confirmed that we now have quarter-life crises.
Utopians believe that once AI far surpasses human intelligence, it will provide us with near-magical tools for alleviating suffering and realizing human potential. In this vision, super-intelligent AI systems will so deeply understand the universe that they will act as omnipotent oracles, answering humanity's most vexing questions and conjuring brilliant solutions to problems such as disease and climate change. But not everyone is so optimistic. The best-known member of the dystopian camp is the technology entrepreneur Elon Musk, who has called super-intelligent AI systems "the biggest risk we face as a civilization," comparing their creation to "summoning the demon." This group warns that when humans create self-improving AI programs whose intellect dwarfs our own, we will lose the ability to understand or control them.
The history of science and technology is often delineated by paradigm shifts. A paradigm shift is a fundamental change in how we view the world and our relationship to it. The big paradigm shifts are sometimes even referred to as an "age" or a "revolution". The Space Age is a perfect example. The middle of the 20th Century saw not only an incredible increase in public awareness of space and space travel, but many of the industrial and technical advances that we now take for granted were byproducts of the Space Age.
An enterprise's response to existing or emerging products depends upon its approach towards the two terms of machine thinking – artificial intelligence (AI) and cognitive computing. Is your enterprise an early adopter when it comes to leveraging technology to automate enterprise processes, configure chatbots, embed sensors or improve customer experience by drawing insights? Does your company stay on a constant lookout for fresh data sources coming via ever-increasing interactions or does it prefer to observe these changes from the sidelines, not sure of whether to adopt them or not? Three years ago, the C-suite was engaged in a fierce battle to bring disruptive technologies and innovations to the market. But today on an average, the C-suite is less inclined to view competition from outside the industry as a threat and is focusing extensively on searching for innovation externally among partners.