Materials


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MIT News

When applied to previously-collected atmospheric samples and data, their findings support evidence that on average these bioaerosols globally make up less than 1 percent of the particles in the upper troposphere -- where they could influence cloud formation and by extension, the climate -- and not around 25 to 50 percent as some previous research suggests. While atmospheric and climate modeling suggests that bioaerosols, globally averaged, are not abundant and efficient enough at freezing to significantly influence cloud formation, research findings have varied significantly. The group leveraged the presence of phosphorus in the mass spectra to train the classification machine learning algorithm on known samples and then, primed, applied it to field data acquired from Desert Research Institute's Storm Peak Laboratory in Steamboat Springs, Colorado, and from the Carbonaceous Aerosol and Radiative Effects Study based in the town of Cool, California. Knowing that the principal atmospheric emissions of phosphorus are from mineral dust, combustion products, and biological particles, they exploited the presence of phosphate and organic nitrogen ions and their characteristic ratios in known samples to classify the particles.


Lettuce-Weeding Robots, Coming Soon to a Farm Near You

#artificialintelligence

The Sunnyvale, California-based company makes farming machines. Blue River's machines are robots that help farmers manage their fields more efficiently. The jury is still out on whether this will be a fruitful sector for venture capitalists like those backing Blue River Technology, since large exits have been thin on the ground since Monsanto's 2013 acquisition of the Climate Corporation for more than $1 billion. Lawyer Roger Royse, whose California law firm specializes in representing agtech companies, tells Inc. that he thinks Blue River is a prime acquisition target, especially as the industry consolidates.


MIT students hack assistive technology solutions for local clients

MIT News

Students have one day to create prototype assistive devices to suit client needs. Students had access to a wide range of resources, including working space, machinery, and building materials, within Beaver Works and technical assistance from several mentors: John Vivilecchia, Kurt Krueger, and Richard Landry of MIT Lincoln Laboratory; Don Fredette of The Boston Home; Michael Buchman of the MIT Department of Mechanical Engineering; and Mary Ziegler of the MIT Office of Digital Learning. The team decided to hack a universal remote that communicates via Wi-Fi with a web interface from which Dan could control television power, volume, and channels. Once the build time was over, several judges, including the ATHack organizers, David Crandelle and David Binder of the Spaulding Rehabilitation Network; John Vivilecchia; Don Fredette; and Mary Ziegler evaluated each team's device.


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#artificialintelligence

For companies to realize the full potential of IoT enablement, they need to combine IoT with rapidly-advancing Artificial Intelligence (#AI) technologies, which enable'smart machines' to simulate intelligent behavior and make well-informed decisions with little or no human intervention. Let's start by defining both terms first: IoT is defined as a system of interrelated Physical Objects, Sensors, Actuators, Virtual Objects, People, Services, Platforms, and Networks that have separate identifiers and an ability to transfer data independently. By applying the analytic capabilities of AI to data collected by IoT, companies can identify and understand patterns and make more informed decisions. Scientists are trying to find ways to make more intelligent data analysis software and devices in order to make safe and effective IoT a reality.


Machine learning in the mining industry -- a case study

@machinelearnbot

A gold mining company -- Newcrest Mining -- provided operating data for a number of its plants, with the aim that some of the teams attending could provide useful solutions grounded in Data Science. To keep autoclave sizes and capital costs down, Newcrest's autoclaves instead rely on purified oxygen, provided by an air separation unit (ASU). This presents an opportunity to minimise the excess oxygen and therefore reduce ASU electricity consumption -- saving money and reducing GHG emissions. The variables included temperature measurements, ore flow rate, and operating pressure.


The learning curve: From the Internet to Big Data to IoT - Industrial Internet Now

#artificialintelligence

I say this because what essentially facilitates Big Data are the digital interfaces created for customer connectivity to machines." Since 2006, Big Data has evolved to partly define what IoT is today, as we are now able to gain insights from thousands of data points, analyze these insights in real-time and ultimately use them to drive services. "Within the last few years, there has been a change in how companies approach future developments. Regardless of leaders thinking ahead, the questions posed above require action in order to gain answers, and that's what is currently so compelling about IIoT and IoT.


The coal miner who became a data miner

@machinelearnbot

President Trump has said he will work to bring coal jobs back by removing regulations, but experts say that low natural gas prices, green energy and automation actually pose a greater -- and irreversible -- threat to the industry. At Galvanize, she took part in a 13-week program and learned about natural language processing, recommending systems, Python and data science. Now she's doing a full-time paid data science residency at Galvanize, helping teach new students, while she looks for her next job. Ideally, Evans is looking for a position as a data scientist and Python developer, or data scientist and business analyst.


Phil Libin exits General Catalyst for All Turtles, a new AI 'startup studio'

#artificialintelligence

The idea with All Turtles is not necessarily to seek out fully formed businesses, but to find and develop interesting concepts en route to them possibly becoming businesses (or at least good ideas that other businesses might like to buy), with people and startups collaborating together to collectively grow. This is not Libin's first attempt to foster a group of AI startups: last year, after he parted ways with Evernote, Libin joined General Catalyst and kicked off a new project there to find, fund and grow startups building bots -- tools that chatted with you, a human, using conversational artificial intelligence, to help you find information, solve a problem, order a sofa, and much more. For starters, several startups that Libin backed as part of that bot effort at General Catalyst are now joining All Turtles as foundation members. I had a conversation with Libin about what led to him starting All Turtles, what he hopes to achieve, and what he thinks about AI today.


Robotics, Smart Materials, and their Future Impact for Humans

#artificialintelligence

The boundaries between smart materials, artificial intelligence, embodiment, biology, and robotics are blurring. Smart materials largely cover the same set of physical properties (stiffness, elasticity, viscosity) as biological tissue and state-of-the-art soft robotic technologies that have the potential to deliver this capability. We can foresee smart skins, assist and medical devices, biodegradable and environmental robots or intelligent soft robots. Ultimately wearable assist devices will make conventional assist devices redundant.