The home appliance can easily generate as much as 500 grams of microplastics each year. Breakthroughs, discoveries, and DIY tips sent every weekday. Fish gills may inspire an unexpected solution to one of our biggest sources of microplastics . According to researchers at Germany's University of Bonn, taking a cue from the animals' filtration systems might help remove the vast majority of harmful plastic particulates from washing machine wastewater. Microplastics are a huge problem.

We present a bio-hybrid environmental sensor system that integrates natural plants and embedded deep learning for real-time, on-device detection of temperature and ozone level changes. Our system, based on the low-power PhytoNode platform, records electric differential potential signals from Hedera helix and processes them onboard using an embedded deep learning model. We demonstrate that our sensing device detects changes in temperature and ozone with good sensitivity of up to 0.98. Daily and inter-plant variability, as well as limited precision, could be mitigated by incorporating additional training data, which is readily integrable in our data-driven framework. Our approach also has potential to scale to new environmental factors and plant species. By integrating embedded deep learning onboard our biological sensing device, we offer a new, low-power solution for continuous environmental monitoring and potentially other fields of application.

When customer experience or operations teams within communications service providers (CSPs) want to adopt artificial intelligence (AI), they first must find a way to'sell' it to finance executives, and perhaps more importantly to the employees who could be displaced by the technology. Neither is an easy job, according to a panel of experts gathered here at Action Week in Dallas. Jerrid Hamann, Digital Customer Experience Strategist, Verizon, who has worked for the company for about a year, spoke about his experience at another telco where he was trying to implement AI for customer service. "I was trying to convince finance that we needed the new tools to improve customer experience," he said. "Either they were very skeptical and suspicious saying it sounds like science fiction and is not something we want to invest our money in…or at the other end of the spectrum they say, 'Oh wow, we can save that much money? Let's lay off the entire contact center'. When you get that kind of reaction you have to dial it back and explain that it's something that has to be phased in."

From Siri and Alexa to driverless cars and robots, artificial intelligence and the many devices AI inhabits are well integrated into our everyday lives. But as the technology advances, ethical and moral questions arise. Ten Years Hence, an annual lecture series sponsored by the University of Notre Dame's Mendoza College of Business, will explore advances in AI and the potential implications for the human community. The series "Automation, Robotics and Artificial Intelligence: The Decade Ahead" takes place on select Fridays from 10:40 a.m. to 12:10 p.m. in Mendoza's Jordan Auditorium. The Ten Years Hence speaker series explores issues, ideas and trends likely to affect business and society over the next decade.

Robots and plants are being intricately linked into a new type of living technology that its creators believe could be used to grow a house. 'The growth is for free, but we have to control the plants to grow in the shapes we want,' explained Professor Heiko Hamann, from the University of Lübeck in Germany, who coordinates the EU-funded flora robotica project. The plants grow through a network of sensors, computers and 3D-printed robotic nodes that are connected to each other and constantly monitor the plants. The team uses a white plastic scaffolding with black strips woven into it to guide the growth. The strips contain LED lights and sensors that can cause plants to grow into pre-programed shapes.

Hendrik Hamann is into cloud computing -- as in real clouds, those puffy things in the sky. Working at IBM alongside some of the computer giant's most advanced systems, Hamann and his team seek a breakthrough in cloud-cover forecasting. They're aiming to help ease the introduction of solar electricity into the nation's major power grids, as solar-generated power is increasingly being loaded onto the grid, propelled by government mandates and solar-technology price declines. There's a big problem with solar power that the IBM team is trying to solve: You can't pump out much electricity on a cloudy day. Another source of power has to take its place.

Like many tech companies, IBM is starting the new year by making a few predictions. One of them has to do with a software concept they call a "macroscope," a software technology that can be used to analyze the complexities of the physical world. IBM predicts that within five years, such technology will "help us understand the Earth's complexity in infinite detail." Hyperbole aside, the goal is to better manage world's resources and commercial endeavors that use those resources by applying machine learning algorithms across an array of data sources. That includes geospatial data (weather, soil, water, etc.) as well as data about economic, social and political conditions.

We study a self-organized collective decision-making strategy to solve a site-selection problem using a swarm of simple robots. Robots can only move forward or turn in place; sense the intensity of the ambient light; and exchange 3-byte messages with peers in a limited range. The goal of the swarm is to collectively decide which of the sites available in the environment is the best candidate site. We define a distributed and iterative decision-making strategy: robots explore the available options, determine the options' qualities, decide autonomously which option to take, and communicate their decision to neighboring robots. We study the effectiveness and robustness of the proposed strategy using a swarm of 100 Kilobots and we focus on the impact of the neighborhood size over the dynamics of the system.