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Finding the best ways for humans and robots to work together requires ‘swarm’ thinking

If the future of warehouse work belongs to humans and robots working side by side, a key question remains: What is the most effective way for them to collaborate?

Research published in Transportation Science suggests that the answer may be more flexible than many warehouse operators expect. The study, “Picking the Best Bot: Collaboration Strategies for Humans and Bots in Order Pick Systems with Traveling Salesman Problem Routing,” found that under many real-world conditions, warehouse workers achieve higher productivity when they dynamically switch among multiple autonomous mobile robots rather than work exclusively with a single robot.

The findings challenge a common assumption that fixed human–robot pairings are the most efficient approach.

The Colorado River Is Drying Out. I Paddled it to See What’s at Stake

With flows nearing record lows, the Colorado River and the people who depend on it are in for a rough summer. On a packrafting trip down a popular stretch of the river, a Backpacker editor finds a still-gorgeous landscape—and motivation to keep up the fight for one of America’s most important waterways.

Providing Low-cost Clean Water for a Billion People

This summer I attended Singularity University’s graduate studies program. Alongside 79 extraordinary entrepreneurs and scientists from around the globe, I had the opportunity to learn from some of the best minds in the world about a variety of rapidly advancing areas of technology. The context of these discussions was how we might use these technologies to implement solutions capable of affecting the lives of more than a billion people over the next decade.

Singularity University Limited Briefing: a Webinar Monday Sept. 13

Learn about the projects Singularity University (SU) students developed during its 2010 Graduate Studies Program, with SU Co-Founder and Chancellor Ray Kurzweil, SU Co-Founder & Chairman Peter Diamandis, and SU faculty head Dan Barry, three-time NASA astronaut.

Neuron ‘ground plans’ could simplify brain and behavior research

While E. Josie Clowney would never suggest that neuroscience is simple, a new study by her team at the University of Michigan could drastically reduce complexity in future studies. Their work focused on instinctual behaviors in fruit flies, but it has the potential to accelerate work to better understand the neurobiology that underlies behavior and decision-making in mammals, including humans.

The research establishes a new way to understand neurons, their connectivity and the behaviors they control. Within this new framework, the researchers can circumvent the conventional approach of considering each type of neuron individually and instead focus on groupings defined by shared structure and by two sets of regulatory genes. The work is published in the journal Nature.

While there are more than 8,000 kinds of neurons in the fruit fly cerebrum —the part of its brain where instinctual behaviors are hardwired—there are less than 200 major structural groups, or ground plans. Led by Najia Elkahlah, who recently defended her doctoral thesis in the Clowney lab, the team’s discoveries revealed how these ground plans get set up. There is a sort of order or hierarchy, where one set of genes coordinates the formation of the ground plan, and the other set produces small differences in shape and connectivity among neurons within each ground plan.

Artificial General Intelligence: So Close Yet So Far?

Despite its rapid development and widespread adoption, AI is a nascent technology with vast potential for enormous growth in the coming years.

Decades of science fiction make it easy to imagine a future in which AI evolves beyond task-focused point applications to offer broad, human-like intelligence. Although artificial general intelligence (AGI) is theoretical, the road to real AGI is fraught with serious technological and societal challenges. AGI developers face the daunting hurdles of making AGI work effectively, accurately, reliably — and, most of all, safely.

Why Nanoscale Droplets Don’t Coalesce

A well-shaken mixture of oil and vinegar will separate as the oil droplets eventually coalesce. Droplet growth, or coarsening, usually evolves according to standard rules. But puzzling exceptions persist. When two polymers are mixed in water and the concentration is high enough, droplets containing one or both species form and can remain stable for hours or days. These loose molecular condensates otherwise behave like liquid droplets, and they abound in biological cells. Now Feipeng Chen of the University of Hong Kong and his colleagues have developed a predictive model for coarsening behavior that works across a range of droplet sizes and explains why coarsening may be suppressed in living systems [1].

The researchers derived their model from observations of a solution containing water and two different polymers, opposite in charge and having very different molecular chain lengths. Using light-scattering techniques, the researchers monitored condensate growth over 12 hours. The initial size and subsequent growth rate of the liquid-like droplets, rich in both polymers, turned out to depend on the solution’s overall initial concentration. In the most dilute solutions, condensates tens-of-nanometers in diameter formed and promptly stopped growing for the remaining 12-hour observation period. In solutions having slightly higher concentration, hundreds-of-nanometer condensates formed and remained stable, then underwent abrupt, rapid growth in the later stages. And in the most concentrated solutions, micrometer-scale condensates formed and grew according to a power-law model.

Applying an electric field to the solutions indicated that the nanoscale condensates had significant surface charge. Modeling these measurements revealed that the asymmetric chain lengths of oppositely charged polymers imparted a net charge to the droplet surfaces. These charges led to size-dependent electrostatic barriers that drastically reduced merging efficiency below a critical diameter. The finding offers a principle for controlling size stability in biology, nanotechnology, and soft-matter assembly.

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