Fishing


Doctors use fish skin to treat burn victims, ease the pain

FOX News

FORTALEZA, BRAZIL – Researchers in Brazil are experimenting with a new treatment for severe burns using the skin of tilapia fish, an unorthodox procedure they say can ease the pain of victims and cut medical costs. Related Image Doctors wrap a child's burnt skin with sterilized tilapia fish skin at Dr. Jose Frota Institute in the northeastern costal city of Fortaleza, Brazil, May 3, 2017. A tilapia fish and tilapia fish skins are displayed in Jaguaribara, Brazil, April 26, 2017. After about 10 days, doctors remove the bandage.


AI Saves the Elephants, Sharks, Frogs, Sea Birds and Everything Else

@machinelearnbot

Google partnered with nonprofits to found Global Fishing Watch to detect illegal fishing activity using satellite data in near real time. The algorithm for detecting apparent fishing activity uses AIS data from roughly 35,000 fishing vessels worldwide (out of the roughly 200,000 vessels on the seas in the course of a year). The system captures the navigation pattern information of these 35,000 vessels with 22 million data points per day allowing deep learning algorithms to learn and then detect patterns that indicate fishing. Satellite intelligence startup Orbital Insight partnered with Global Forest Watch to detect illegal logging and other causes of global forest degradation.


The skeptic's guide to artificial intelligence

#artificialintelligence

Before you see data -- whether you are a baby learning a language or a scientist analyzing some data -- you start with a lot of uncertainty and then as you have more and more data you have more and more certainty," Ghahramani said. One of the center's area of study is trust and transparency around AI, while other areas of focus include policy, security and the impacts that AI could have on personhood. Adrian Weller, a senior researcher on Ghahramani's team and the trust and transparency research leader at the Leverhulme Centre for the Future of Intelligence, explained that AI systems based on machine learning use processes to arrive at decisions that do not mimic the "rational decision-making pathways" that humans comprehend. But by providing a means for making AI functions more transparent, commercial users of AI tools and their consumers could better understand how it works, determine its trustworthiness, and decide whether it is likely to meet the company's or its customer's needs.


Fishermen claim that Siri saved their lives after their boat began sinking

Mashable

While we love to hate Apple's virtual assistant, Siri, she has been hailed a hero by some fishermen in Florida, who claim that it saved their lives. Though it seems like Siri is incapable of doing anything well aside from dishing out sass, the assistant is actually pretty good at making hands-free phone calls. Though simple, this feature did save lives this weekend. Here's why that's a big problem Three boaters ran into rough seas on Saturday morning while fishing four miles off of the coast of Key Biscayne, and Siri came to their rescue, according to Fox 4.


A Yelp bot will deliver your sushi in San Francisco

Engadget

The company is partnering with Marble to use their wheeled drone, which is designed to carry perishable cargo, to try out unmanned food delivery for its Seamless-like Yelp Eat24 service. Naturally, it's starting the drone delivery trials on the streets of San Francisco. Specifically, they're sending Marble's robots on trips around SF's Mission and Potrero Hill districts, so lucky Eat24 patrons might get the option to have their grub delivered via the boxy drones -- and their humans. Someday, these robots could progress to truly unmanned courier jobs -- and then, folks living above ground level will learn a cruel truth about the limits of our wheeled autonomous robo-coolers and their inability to defeat stairs.


7 companies that used machine learning to solve real business problems - TechRepublic

#artificialintelligence

The premise behind Google's Cloud Machine Learning Engine and TensorFlow technologies is to democratize access to machine learning tools and technologies. Here are seven companies that implemented Google's machine learning tools to solve problems in their business. The deep learning tools used for fraud monitoring achieved 80-90% accuracy in detecting fraud and alerting the company to take action. As a food quality and safety company in Japan, Kewpie's problem was properly detecting defective potato cubes that would be used in a stew.


Simulating data to combat illegal fishing in R

@machinelearnbot

For example, less responsible owners (e.g., ScummyFishCo) are more likley to have older ships YearBuilt - function(owner){ ### Now we will assign years built as a function of the owner. I could have randomly assigned ship sizes across all the simulated ships, then assigned classes.. however, I wanted to operate with the assumption that classes 1 and 5 were more likely to be associated with irresponsible countries and owners. For example, ScummyFishCo is the 4th most responsible owner, and Tortuga is the 5th most responsible country, therefore a ship owned by ScummyFishCo and registered in Tortuga would receive a score of 9. Using the ship classes, we randomly assign a size from the range of sizes within each class.


How machine learning can help protect life below water

#artificialintelligence

New advances in satellite observation, open data and machine learning now allow us to process the massive amounts of data being produced. For example, Global Fishing Watch uses satellite-based monitoring to track all fishing vessels in real-time to protect fisheries around the world. The project, ClimatePrediction.net, relies on volunteer computing to run advanced climate models that prove to be even too large to run on supercomputers. The results are better models that can help predict the future of Earth's climate and help understand how our oceans will cope with higher temperatures, acidification and other climate shocks.


How AI Can Help Keep Ocean Fisheries Sustainable

#artificialintelligence

In the region of the Pacific Ocean from Indonesia and the Philippines to Hawaii--the source of the majority of the world's tuna harvest--a mere 2% of fishing operations are watched by observers, says Mark Zimring, director of The Nature Conservancy's Indo-Pacific tuna program. The Nature Conservancy is working with governments in the region, including in Palau, Micronesia, the Marshall Islands, and the Solomon Islands, to implement alternative monitoring programs, capturing video footage of fishing vessels instead of placing observers on each boat. To make analyzing the footage more feasible, The Nature Conservancy is investigating ways to use machine learning techniques to process that video material. "It's been difficult to get observers onto these boats, and we've been working with them to develop electronic monitoring as an alternative," says Chris Rilling, director of the Fisheries Monitoring and Analysis Division at NOAA's Alaska Fisheries Science Center.


AI Saves the Elephants, Sharks, Frogs, Sea Birds and Everything Else

@machinelearnbot

Google partnered with nonprofits to found Global Fishing Watch to detect illegal fishing activity using satellite data in near real time. The algorithm for detecting apparent fishing activity uses AIS data from roughly 35,000 fishing vessels worldwide (out of the roughly 200,000 vessels on the seas in the course of a year). The system captures the navigation pattern information of these 35,000 vessels with 22 million data points per day allowing deep learning algorithms to learn and then detect patterns that indicate fishing. Satellite intelligence startup Orbital Insight partnered with Global Forest Watch to detect illegal logging and other causes of global forest degradation.