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Optimizing Human-System Performance — Dr. Greg Lieberman, Ph.D., Neuroscientist / Lead, U.S. Army Combat Capabilities Development Command Army Research Laboratory, U.S. Army Futures Command

Dr. Greg Lieberman, Ph.D. (https://www.arl.army.mil/arl25/meet-arl.php?gregory_lieberman) is a Neuroscientist, and Lead, Optimizing Human-System Performance, at the U.S. Army Combat Capabilities Development Command, Army Research Laboratory (DEVCOM ARL).

DEVCOM ARL, as an integral part of the Army Futures Command, is the Army’s foundational research laboratory focused on operationalizing science to ensure overmatch in any future conflict. DEVCOM ARL shapes future concepts with scientific research and knowledge and delivers technology for modernization solutions to win in the future operating environment.

With a Ph.D. from the University of Vermont in Neuroscience, a Postdoctoral Fellowship in Cognitive Neuroscience from University of New Mexico, and a BA from University of Massachusetts Amherst in Psychology, Dr. Lieberman’s research and research leadership experience ranges from genetics to learning theory, animal behavior to artificial intelligence, and human variability to team dynamics; with additional expertise in S&T strategy and the opportunities afforded by the Future of Work.

Specific areas of Dr. Lieberman’s technical expertise include maximizing human potential, human-autonomy teaming; neuroanatomical organization and connectivity; brain structure-function coupling; learning-driven neuroplasticity; non-invasive neurostimulation and cognitive enhancement; neuroimaging; mind-body medicine and mindfulness meditation; and the mechanisms of neurodegenerative disease, neuropathology, and brain injury.

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In today’s episode of Cutting Edge, Lee Pierson, Bob Stubblefield & Steve Richins will be joined by special guest Trent Fowler to discuss the topic of Singularity.

Clubhouse aftershow: https://www.clubhouse.com/event/P0L7Kw1N?utm_medium=ch_event…UNg-368685

Trent Fowler’s Podcast: https://www.youtube.com/channel/UCRSov16ZLE2UgekgBTgnrjw/featured.

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The steel structures will be fabricated at Westcon’s shipyard in Florø and then transported to Dommersnes Industrial Area for complete assembly and testing. The complete turbine is then towed to Bokn, where it will be installed.

SeaTwirl has been around for a while now. In July 2015, the company first deployed its prototype named S1 off the coast of Lysekil in Sweden. The S1 is a small, 30-kW test version of its floating turbine technology. Rising 13 meters above the waterline and reaching down 18 meters below, it offers energy-producing companies an attractive test platform for offshore wind power and an alternative to diesel generators in remote areas that are off-grid or prone to power outages. It’s been connected to the grid and tested according to plan since its deployment. S1 has withstood harsh weather conditions, autumn and winter storms reaching hurricane wind speeds.

SeaTwirl describes its design as simple and robust, with a minimum of breakable moving parts, which means less downtime and more output. It is a vertical-axis wind turbine that has a high structural limit and can be built larger than horizontal-axis wind turbines.

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In June, South Korean regulators authorized the first-ever medicine, a COVID vaccine, to be made from a novel protein designed by humans. The vaccine is based on a spherical protein ‘nanoparticle’ that was created by researchers nearly a decade ago, through a labour-intensive trial-and error-process1.

Now, thanks to gargantuan advances in artificial intelligence (AI), a team led by David Baker, a biochemist at the University of Washington (UW) in Seattle, reports in Science2,3 that it can design such molecules in seconds instead of months.

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Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Watch here.

Artificial intelligence (AI) pioneer Geoffrey Hinton, one of the trailblazers of the deep learning “revolution” that began a decade ago, says that the rapid progress in AI will continue to accelerate.

In an interview before the 10-year anniversary of key neural network research that led to a major AI breakthrough in 2012, Hinton and other leading AI luminaries fired back at some critics who say deep learning has “hit a wall.”

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