Researchers have developed an artificial intelligence (AI) program that can automatically provide species-level identification of microscopic marine organisms. The next step is to incorporate the AI into a robotic system that will help advance our understanding of the world’s oceans, both now and in our prehistoric past.
Specifically, the AI program has proven capable of identifying six species of foraminifera, or forams – organisms that have been prevalent in Earth’s oceans for more than 100 million years.
Forams are protists, neither plant nor animal. When they die, they leave behind their tiny shells, most less than a millimeter wide. These shells give scientists insights into the characteristics of the oceans as they existed when the forams were alive. For example, different types of foram species thrive in different kinds of ocean environments, and chemical measurements can tell scientists about everything from the ocean’s chemistry to its temperature when the shell was being formed.
However, evaluating those foram shells and fossils is both tedious and time consuming. That’s why an interdisciplinary team of researchers, with expertise ranging from robotics to paleoceanography, is working to automate the process.
“At this point, the AI correctly identifies the forams about 80 percent of the time, which is better than most trained humans,” says Edgar Lobaton, an associate professor of electrical and computer engineering at North Carolina State University and co-author of a paper on the work.
“But this is only the proof of concept. We expect the system to improve over time, because machine learning means the program will get more accurate and more consistent with every iteration. We also plan to expand the AI’s purview, so that it can identify at least 35 species of forams, rather than the current six.”
The current system works by placing a foram under a microscope capable of taking photographs. An LED ring shines light onto the foram from 16 directions – one at a time – while taking an image of the foram with each change in light. These 16 images are combined to provide as much geometric information as possible about the foram’s shape. The AI then uses this information to identify the foram’s species.
The scanning and identification takes only seconds, and is already as fast – or faster – than the fastest human experts.
“Plus, the AI doesn’t get tired or bored,” Lobaton says. “This work demonstrates the successful first step toward building a robotic platform that will be able to identify, pick and sort forams automatically.”
Lobaton and his collaborators have received a grant from the National Science Foundation (NSF), starting in January 2019, to build the fully-functional robotic system.
“This work is important because oceans cover about 70 percent of Earth’s surface and play an enormous role in its climate,” says Tom Marchitto, an associate professor of geological sciences at the University of Colorado, Boulder, and corresponding author of the paper.
“Forams are ubiquitous in our oceans, and the chemistry of their shells records the physical and chemical characteristics of the waters that they grew in. These tiny organisms bear witness to past properties like temperature, salinity, acidity and nutrient concentrations. In turn we can use those properties to reconstruct ocean circulation and heat transport during past climate events.
“This matters because humanity is in the midst of an unintentional, global-scale climate ‘experiment’ due to our emission of greenhouse gases,” Marchitto says. “To predict the outcomes of that experiment we need a better understanding of how Earth’s climate behaves when its energy balance is altered. The new AI, and the robotic system it will enable, could significantly expedite our ability to learn more about the relationship between the climate and the oceans across vast time scales.”
The Latest on: Machine learning
via Google News
The Latest on: Machine learning
- AWS SageMaker’s new machine learning IDE isn’t ready to win over data scientistson December 8, 2019 at 8:45 am
AWS SageMaker, the machine learning brand of AWS, announced the release of SageMaker Studio, branded an “IDE for ML,” on Tuesday. Machine-learning has been gaining traction and, with its compute-heavy ...
- Machine learning could transform medicine. Should we let it?on December 8, 2019 at 6:00 am
In deep learning, a subset of a type of artificial intelligence called machine learning, computer models essentially teach themselves to make predictions from large sets of data. The raw power of the ...
- Learn Python for data science and machine learning for just $10on December 8, 2019 at 2:00 am
TL;DR: Whether you're a programming beginner or expert, you can grab the Python for Data Science and Machine Learning Bootcamp for $9.99, a 94% savings. Both beginners and experienced coders are ...
- The NFL And Amazon Want To Transform Player Health Through Machine Learningon December 6, 2019 at 7:40 am
Injury prevention in sports is one of the most important issues facing a number of leagues. This is particularly true in the NFL, due to the brutal nature of that punishing sport, which leaves many ...
- Improving personalization with machine learningon December 6, 2019 at 7:16 am
And in order to become a market leader you are expected to work seriously on personalization but doing this at scale because you must focus on the global market, must require automation and that is ...
- Machine Learning Answers: If Freeport-McMoRan Stock Drops 10% A Week, What’s The Chance It’ll Recoup Its Losses In A Month?on December 6, 2019 at 5:35 am
Is it very likely that the stock will recover the next week? What about the next month or a quarter? You can test a variety of scenarios on the Trefis Machine Learning Engine to calculate if Freeport ...
- Why AWS is selling a MIDI keyboard to teach machine learningon December 6, 2019 at 3:17 am
The first thing that’s important to remember here is that DeepComposer is a learning tool. It’s not meant for musicians — it’s meant for engineers who want to learn about generative AI. But AWS didn’t ...
- NFL-AWS partnership hopes to reduce head injuries with machine learningon December 5, 2019 at 2:33 pm
Today at AWS re:Invent in Las Vegas, NFL commissioner Roger Goodell joined AWS CEO Andy Jassy on stage to announce a new partnership to use machine learning to help reduce head injuries in ...
- Fugro using machine learning to map boulders on the sea flooron December 5, 2019 at 1:38 pm
"This system is boulder and not boulder. "We're hoping to convert weeks and months to work to just a couple of days. See also: Five steps for getting started in machine learning: Top data scientists ...
- Apple attending & presenting at NeurIPS Machine Learning conferenceon December 5, 2019 at 5:59 am
Apple has announced that it will again be appearing at and sponsoring the NeurIPS conference on Machine Learning, from December 8 to December 14. Apple's Machine Learning icon Members of Apple's ...
via Bing News