Cognitive Science

McGovern Institute investigator Michale Fee has been selected to receive a 2018 McKnight Technological Innovations in Neuroscience Award for his research on "new technologies for imaging and analyzing neural state-space trajectories in freely-behaving small animals." "I am delighted to get support from the McKnight Foundation," says Fee, who is also the Glen V. and Phyllis F. Dorflinger Professor in the Department of Brain and Cognitive Neurosciences at MIT. "We're very excited about this project which aims to develop technology that will be a great help to the broader neuroscience community." Fee studies the neural mechanisms by which the brain, specifically that of juvenile songbirds, learns complex sequential behaviors. The way that songbirds learn a song through trial and error is analogous to humans learning complex behaviors, such as riding a bicycle. While it would be insightful to link such learning to neural activity, current methods for monitoring neurons can only monitor a limited field of neurons, a big issue since such learning and behavior involve complex interactions between larger circuits.

MOSCOW (Reuters) - Russia's Federal Security Service has searched a research facility controlled by the country's space agency Roskosmos over the suspected leaking of secrets about new hypersonic weapons to Western spies, the TASS news agency reported on Friday.

Computers have always been faster than humans at consuming, calculating and computing data, and artificial intelligence is a boon for our global economy. Yet, computers do have their limitations. They are machines, after all, and lack native precision when attempting to recognize and interpret language, objects or images on demand. In those instances -- especially when verification is required to proceed with a transaction -- most programs require a fail-safe checkpoint. Ever notice the requests to verify that you're not a robot when submitting data online?

Finally, they tested the systems. In some cases, they used test problems with the same abstract factors as the training set -- like both training and testing the AI on problems that required it to consider the number of shapes in each image. In other cases, they used test problems incorporating different abstract factors than those in the training set. For example, they might train the AI on problems that required it to consider the number of shapes in each image, but then test it on ones that required it to consider the shapes' positions to figure out the right answer.

The simulated response of the seasonal cycle to historical changes in human and natural factors has prominent mid-latitude increases in the amplitude of TAC. These features arise from larger mid-latitude warming in the summer hemisphere, which appears to be partly attributable to continental drying. Because of land-ocean differences in heat capacity and hemispheric asymmetry in land fraction, mid-latitude increases in TAC are greater in the Northern Hemisphere than in the Southern Hemisphere. Qualitatively similar large-scale patterns of annual cycle change occur in satellite tropospheric temperature data. We applied a standard fingerprint method to determine (i) whether the pattern similarity between the model "human influence" fingerprint and satellite temperature data increases with time, and (ii) whether such an increase is significant relative to random changes in similarity between the fingerprint and patterns of natural internal variability.

The study, led by researchers at MIT's Picower Institute for Learning and Memory, undermines the classic belief that separate cortical regions play distinct roles. Instead, as animals in the lab refined what they saw down to a specific understanding relevant to behavior, brain cells in each of six cortical regions operated along a continuum between sensory processing and categorization. To be sure, general patterns were evident for each region, but activity associated with categorization was shared surprisingly widely, say the authors of the study published in the Proceedings of the National Academy of Science. "The cortex is not modular," says Earl Miller, Picower Professor of Neuroscience in the Department of Brain and Cognitive Sciences at MIT. "Different parts of the cortex emphasize different things and do different types of processing, but it is more of a matter of emphasis. This extends up to higher cognition."

Think back to your earliest memory. What age were you in it? In a recent survey, 40 percent of people say they remember events earlier than age two. But here's the problem: Most memory researchers argue that its essentially impossible to remember anything before those terrible twos. Understanding how and why our brains form memories in the first place might convince you that if you're in that 40 percent, perhaps your memory is a fictional one after all.

The future is in algorithms. Physical tasks that required effort were automated, which freed up human capital to explore new knowledge. Automation, however, never threatened human existence as much as...

One of the most contentious aspects of AI is the meaning of'intelligence.' No one debates the meaning of the word'strength,' or belittles the idea that machines can be stronger than humans, or even tries to re-define mechanical strength to mean some mysterious physico-spiritual capability that is unique to humans. The debate around the meaning of intelligence when it crops up in any conversation on AI is extremely baffling - until we take into account the fragile psychology of humans. Somehow, we've convinced ourselves that cognitive abilities are the sole province of the human brain, while we grudgingly cede the physical realm to the machines. Every encroachment on human cognitive abilities is fiercely contested.

So we all know Alexa-- but do you know Jibo? Jibo is "the world's first social robot for the home," and he just might give Alexa a run for her money. Normally priced at a steep $899, Amazon has this little robot friend at an unbeatable price of $499 for Prime Day. If you haven't met Jibo, he's just dying to know you. And we mean really know you.