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Artificial Intelligence May Aid Solving ‘Global Hunger’

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Subsistence farmer Joice Chimedza harvests maize on her small plot in Norton, a farming area outside Zimbabwe's capital, Harare, May 10, 2016. VOA
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Despite a global abundance of food, a United Nations report says 815 million people, 11 percent of the world’s population, went hungry in 2016. That number seems to be rising.

Poverty is not the only reason, however, people are experiencing food insecurity.

“Increasingly we’re also seeing hunger caused by the displacement related to conflict, natural disaster as well, but particularly there’s been an uptick in the number of people displaced in the world,” said Robert Opp, director of Innovation and Change Management at the United Nations World Food Program.

ALSO READ: ‘Artificial Intelligence yet to make its mark in India’ 

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Humanitarian organizations are turning to new technologies such as AI, or artificial intelligence, to fight global food insecurity. Pixabay

“What AI offers us right now, is an ability to augment human capacity. So, we’re not talking about replacing human beings and things. We’re talking about doing more things and doing them better than we could by just human capacity alone,” Opp said.

Analyze data, get it to farmers

Artificial intelligence can analyze large amounts of data to locate areas affected by conflict and natural disasters and assist farmers in developing countries. The data can then be accessed by farmers from their smartphones.

“The average smartphone that exists in the world today is more powerful than the entire Apollo space program 50 years ago. So just imagine a farmer in Africa who has a smartphone has much more computing power than the entire Apollo space program,” said Pranav Khaitan, engineering lead at Google AI.

“When you take your special data and soil mapping data and use AI to do the analysis, you can send me the information. So in a nutshell, you can help me [know] when to plant, what to plant, how to plant,” said Uyi Stewart, director of Strategy Data and Analytics in Global Development of the Bill and Melinda Gates Foundation.

“When you start combining technologies, AI, robotics, sensors, that’s when we see magic start to happen on farms for production, to increase crop yields,” said Zenia Tata, vice president for Global Impact Strategy at XPRIZE, an organization that creates incentivized competitions so innovative ideas and technologies can be developed to benefit humanity.

“It all comes down to developing these techniques and making it available to these farmers and people on the ground,” Khaitan said.

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However, the developing world is often the last to get new technologies. Pixabay

Breaking down barriers

As Stewart said, “815 million people are hungry and I can bet you that nearly 814 million out of the 815 million do not have a smartphone.”

Even when the technology is available, other barriers still exist.

“A lot of these people that we talked about that are hungry, they don’t speak English, so when we get insights out of this technology how are we going to pass it onto them?” Stewart said.

ALSO READ: Stephen Hawking believes Technology could end Poverty and Disease, says Artificial Intelligence could be the Worst or Best things for Humanity

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While it may take time for new technologies to reach the developing world, many hope such advances will ultimately trickle-down to farmers in regions that face food insecurity. Pixabay

“You’ve invented the technology. The big investments have gone in. Now you’re modifying it, which brings the cost down as well,” said Teddy Bekele, vice president of Ag Technology at U.S.-based agribusiness and food company Land O’Lakes.

“So, I think three to four years maybe we’ll have some of the things we have here to be used there [in the developing world] as well,” Bekele predicted.

Those who work in humanitarian organizations said entrepreneurs must look outside their own countries to adapt the new technologies to combat global hunger, or come up with a private, public model. Farmers will need the tools and training so they can harness the power of artificial intelligence to help feed the hungry in the developing world. VOA

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AI Helps Find Source Of Radio Bursts 3 Billion Light Years Away From Earth

The researchers developed the new, powerful machine-learning algorithm and reanalysed the 2017 data, finding an additional 72 bursts not detected originally.

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'AI helps track down mysterious cosmic signals', Pixabay

Scientists say they have used artificial intelligence (AI) to discover 72 new fast radio bursts from a mysterious source about three billion light years away from Earth.

The initiative may advance the search to find signs of intelligent life in the universe, said researchers from the University of California, Berkeley in the US.

Fast radio bursts are bright pulses of radio emission mere milliseconds in duration, thought to originate from distant galaxies.

However, the source of these emissions is still unclear, according to the research published in The Astrophysical Journal.

Theories range from highly magnetised neutron stars blasted by gas streams from a nearby supermassive black hole, to suggestions that the burst properties are consistent with signatures of technology developed by an advanced civilization.

 

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While most fast radio bursts are one-offs, the source here, FRB 121102, is unique in emitting repeated bursts. Wikimedia Commons

 

“This work is exciting not just because it helps us understand the dynamic behaviour of fast radio bursts in more detail, but also because of the promise it shows for using machine learning to detect signals missed by classical algorithms,” said Andrew Siemion from the University of California – Berkele.

 

Researchers are also applying the successful machine-learning algorithm to find new kinds of signals that could be coming from extraterrestrial civilisations.

While most fast radio bursts are one-offs, the source here, FRB 121102, is unique in emitting repeated bursts.

This behaviour has drawn the attention of many astronomers hoping to pin down the cause and the extreme physics involved in fast radio bursts.

The AI algorithms dredged up the radio signals from data were recorded over a five-hour period in 2017, by the Green Bank Telescope in West Virginia in the US.

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The researchers developed the new, powerful machine-learning algorithm and reanalysed the 2017 data, finding an additional 72 bursts not detected originally. (IANS)

An earlier analysis of the 400 terabytes of data employed standard computer algorithms to identify 21 bursts during that period.

“All were seen within one hour, suggesting that the source alternates between periods of quiescence and frenzied activity,” said Berkeley postdoctoral researcher Vishal Gajjar.

Also Read: HCL Launches AI Based ‘HCL Turbo’

The researchers developed the new, powerful machine-learning algorithm and reanalysed the 2017 data, finding an additional 72 bursts not detected originally.

This brings the total number of detected bursts from FRB 121102 to around 300 since it was discovered in 2012, researchers said. (IANS)