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We often hear big (and unrealistic) promises about the potential of AI to solve the world’s ills, and I was skeptical when I first learned that AI might be starting to aid disaster response, including following the earthquake that has devastated Turkey and Syria.
But one effort from the US Department of Defense does seem to be effective: xView2. Though it’s still in its early phases of deployment, this visual computing project has already helped with disaster logistics and on the ground rescue missions in Turkey.
An open-source project that was sponsored and developed by the Pentagon’s Defense Innovation Unit and Carnegie Mellon University’s Software Engineering Institute in 2019, xView2 has collaborated with many research partners, including Microsoft and the University of California, Berkeley. It uses machine-learning algorithms in conjunction with satellite imagery from other providers to identify building and infrastructure damage in the disaster area and categorize its severity much faster than is possible with current methods.
Ritwik Gupta, the principal AI scientist at the Defense Innovation Unit and a researcher at Berkeley, tells me this means the program can directly help first responders and recovery experts on the ground quickly get an assessment that can aid in finding survivors and help coordinate reconstruction efforts over time.
In this process, Gupta often works with big international organizations like the US National Guard, the United Nations, and the World Bank. Over the past five years, xView2 has been deployed by the California National Guard and the Australian Geospatial-Intelligence Organisation in response to wildfires, and more recently during recovery efforts after flooding in Nepal, where it helped identify damage created by subsequent landslides.
In Turkey, Gupta says xView2 has been used by at least two different ground teams of search and rescue personnel from the UN’s International Search and Rescue Advisory Group in Adiyaman, Turkey, which has been devastated by the earthquake and where residents have been frustrated by the delayed arrival of search and rescue. xView2 has also been utilized elsewhere in the disaster zone, and was able to successfully help workers on the ground be “able to find areas that were damaged that they were unaware of,” he says, noting Turkey’s Disaster and Emergency Management Presidency, the World Bank, the International Federation of the Red Cross, and the United Nations World Food Programme have all used the platform in response to the earthquake.
“If we can save one life, that’s a good use of the technology,” Gupta tells me.
How AI can help
The algorithms employ a technique similar to object recognition, called “semantic segmentation,” which evaluates each individual pixel of an image and its relationship to adjacent pixels to draw conclusions.
Below, you can see snapshots of how this looks on the platform, with satellite images of the damage on the left and the model’s assessment on the right—the darker the red, the worse the wreckage. Atishay Abbhi, a disaster risk management specialist at the World Bank, tells me that this same degree of assessment would typically take weeks and now takes hours or minutes.
Marash, Turkey: Satellite imagery (left) from earth imaging company Planet Labs PBC and the output from xView2 (right) attributed to UC Berkeley, the Defense Innovation Unit, and Microsoft.
This is an improvement over more traditional disaster assessment systems, in which rescue and emergency responders rely on eyewitness reports and calls to identify where help is needed quickly. In some more recent cases, fixed-wing aircrafts like drones have flown over disaster areas with cameras and sensors to provide data reviewed by humans, but this can stilltake days, if not longer. The typical response is further slowed by the fact that different responding organizations often have their own siloed data catalogues, making it challenging to create a standardized, shared picture of which areas need help. xView2 can create a shared map of the affected area in minutes, which helps organizations coordinate and prioritize responses—saving time and lives.
This technology, of course, is far from a cure-all for disaster response. There are several big challenges to xView2 that currently consume much of Gupta’s research attention.
First and most important is how reliant the
By: Tate Ryan-Mosley
Title: How AI can actually be helpful in disaster response
Sourced From: www.technologyreview.com/2023/02/20/1068824/ai-actually-helpful-disaster-response-turkey-syria-earthquake/
Published Date: Mon, 20 Feb 2023 10:00:00 +0000
Procurement in the age of AI
Procurement professionals face challenges more daunting than ever. Recent years’ supply chain disruptions and rising costs, deeply familiar to consumers, have had an outsize impact on business buying. At the same time, procurement teams are under increasing pressure to supply their businesses while also contributing to business growth and profitability.
Deloitte’s 2023 Global Chief Procurement Officer Survey reveals that procurement teams are now being called upon to address a broader range of enterprise priorities. These range from driving operational efficiency (74% of respondents) and enhancing corporate social responsibility (72%) to improving margins via cost reduction (71%).
To meet these rising expectations, many procurement teams are turning to advanced analytics, AI, and machine learning (ML) to transform the way they make smart business buying decisions and create value for the organization.
New procurement capabilities unlocked by AI
AI and ML tools have long helped procurement teams automate mundane and manual procurement processes, allowing them to focus on more strategic initiatives. But recent advances in natural language processing (NLP), pattern recognition, cognitive analytics, and large language models (LLMs) are “opening up opportunities to make procurement more efficient and effective,” says Julie Scully, director of software development at Amazon Business.
The good news is procurement teams are already well-positioned to capitalize on these technological advances. Their access to rich data sources, ranging from contracts to invoices, enables AI/ML solutions that can illuminate the insights contained within this data. Acting on these insights unlocks new capabilities that can enhance decision-making and improve spending patterns across the organization.
Predicting supply chain disruptions. In an era of constant supply chain disruptions, procurement teams are often faced with inconsistent item availability, which can negatively impact employee and customer experience. Indeed, the Deloitte 2023 Global Chief Procurement Officer survey finds that only 25% of firms are able to identify supply disruptions promptly “to a large extent.”
AI tools can help address this issue by recognizing patterns that indicate an emerging supply shortage and automatically recommending two or three product alternatives to business buyers, thereby preventing supply disruptions. These predictive capabilities also empower procurement teams to establish buying policies that proactively account for items that are more likely to go out of stock.
Answering pressing questions quickly. Sifting through data to understand the cause of a supply chain disruption, product defect, or other risk is time-consuming for a procurement professional. LLM-powered chatbots can streamline these processes by understanding complex queries about orders and “putting together a nuanced answer,” says Scully. “AI can query a wide variety of sources to fully answer a question quickly and in a way that feels natural and understandable.” In addition to providing fast and accurate answers to pressing questions, AI promises to reduce the need to explain procurement issues eventually. Instead, it will proactively analyze orders, buying patterns, and the current situation to provide instant support.
Offering customized recommendations. As business buyers increasingly demand personalized experiences, procurement officers seek ways to customize their interactions with business procurement systems. Scully provides the example of an employee tasked with hosting a holiday party for 150 employees who needs help deciding what to order. An AI-based procurement tool posed that scenario, she says, could generate a proposed shopping cart, sifting through “millions and billions of data points to recommend and suggest items that the employee may not have even thought of.”
Better yet, she adds, “as we get into really large language models, AI/ML can help answer questions or help buy items you didn’t even know you needed by understanding your particular situation in a much more detailed way.”
Influencing compliance spend. Procurement professionals aim to balance employees’ freedom to purchase the items they need with minimal intervention. However, self-sufficiency should not come at the cost of proper spend
By: MIT Technology Review Insights
Title: Procurement in the age of AI
Sourced From: www.technologyreview.com/2023/11/28/1083628/procurement-in-the-age-of-ai/
Published Date: Tue, 28 Nov 2023 16:00:00 +0000
Did you miss our previous article…
The Download: COP28 controversy and the future of families
This is today’s edition of The Download our weekday newsletter that provides a daily dose of what’s going on in the world of technology.
Why the UN climate talks are a moment of reckoning for oil and gas companies
The United Arab Emirates is one of the world’s largest oil producers. It’s also the site of this year’s UN COP28 climate summit, which kicks off later this week in Dubai.
It’s a controversial host, but the truth is that there’s massive potential for oil and gas companies to help address climate change, both by cleaning up their operations and by investing their considerable wealth and expertise into new technologies.
The problem is that these companies also have a vested interest in preserving the status quo. If they want to be part of a net-zero future, something will need to change—and soon. Read the full story.
How reproductive technology can reverse population decline
Birth rates have been plummeting in wealthy countries, well below the “replacement” rate. Even in China, a dramatic downturn in the number of babies has officials scrambling, as its population growth turns negative.
So, what’s behind the baby bust and can new reproductive technology reverse the trend? MIT Technology Review is hosting a subscriber-only Roundtables discussion on how innovations from the lab could affect the future of families at 11am ET this morning, featuring Antonio Regalado, our biotechnology editor, and entrepreneur Martín Varsavsky, founder of fertility clinic Prelude Fertility. Don’t miss out—make sure you register now.
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 Instagram recommends sexual content to adults that follow kids
Test accounts were served risqué posts and disturbing videos. (WSJ $)
Meta was aware it had millions of underage users, a complaint alleges. (NYT $)
2 The first transatlantic flight powered by alternative fuels has taken off
Waste fats and corn leftovers are fueling the flight between London and New York. (BBC)
Here are the key phrases you need to know to understand climate change. (Vox)
Everything you need to know about the wild world of alternative jet fuels. (MIT Technology Review)
3 The United Arab Emirates planned to strike oil deals during COP28
Which doesn’t seem terribly climate-friendly. (BBC)
AUAE AI firm is believed to have covertly worked with Chinese companies. (NYT $)
China’s own carbon emissions are on course to peak soon. (Economist $)
4 Starlink can only operate in Gaza with Israel’s approval
That’s according to Elon Musk, who is visiting Israel currently. (FT $)
5 Foxconn is struggling to build iPhones in India
So the manufacturer started shipping over skilled workers from China. (Rest of World)
6 The world’s banana supply is in serious trouble
A deadly fungus is sweeping through crops—and there’s no known cure. (Bloomberg $)
7 Digital car keys don’t always work the way they’re supposed to
Which is a major problem if you can’t guarantee your vehicle is secure. (The Verge)
8 It’s not just you—dating is tough
But these tips can help to make it a less harrowing experience. (WP $)
Here’s how the net’s newest matchmakers help you find love. (MIT Technology Review)
9 Big dogs don’t live that long
But biotech company Loyal is hoping to change that with an experimental drug. (Wired $)
These scientists are working to extend the life span of pet dogs—and their owners. (MIT Technology Review)
10 The quiet bliss of living in an internet-free home
And how you can achieve it, too. (The Atlantic $)
How to log off. (MIT Technology Review)
Quote of the day
“He ignored me royally, which is his privilege. And he lost almost all the money that he had invested.”
—Christine Lagarde, president of the European Central Bank, explains to students in Frankfurt how one of her sons lost his money on crypto, despite her repeated warnings, Reuters reports.
The big story
Are you ready to be a techno-optimist again?
Back in 2001, MIT Technology Review picked 10 emerging areas of innovation that we promised would “change the world.” It was a time of peak techno-optimism.
By: Rhiannon Williams
Title: The Download: COP28 controversy and the future of families
Sourced From: www.technologyreview.com/2023/11/28/1083923/the-download-cop28-controversy-and-the-future-of-families/
Published Date: Tue, 28 Nov 2023 13:10:00 +0000
Finding value in generative AI for financial services
With tools such as ChatGPT, DALLE-2, and CodeStarter, generative AI has captured the public imagination in 2023. Unlike past technologies that have come and gone—think metaverse—this latest one looks set to stay. OpenAI’s chatbot, ChatGPT, is perhaps the best-known generative AI tool. It reached 100 million monthly active users in just two months after launch, surpassing even TikTok and Instagram in adoption speed, becoming the fastest-growing consumer application in history.
According to a McKinsey report, generative AI could add $2.6 trillion to $4.4 trillion annually in value to the global economy. The banking industry was highlighted as among sectors that could see the biggest impact (as a percentage of their revenues) from generative AI. The technology “could deliver value equal to an additional $200 billion to $340 billion annually if the use cases were fully implemented,” says the report.
For businesses from every sector, the current challenge is to separate the hype that accompanies any new technology from the real and lasting value it may bring. This is a pressing issue for firms in financial services. The industry’s already extensive—and growing—use of digital tools makes it particularly likely to be affected by technology advances. This MIT Technology Review Insights report examines the early impact of generative AI within the financial sector, where it is starting to be applied, and the barriers that need to be overcome in the long run for its successful deployment.
DOWNLOAD THE REPORT
The main findings of this report are as follows:
Corporate deployment of generative AI in financial services is still largely nascent. The most active use cases revolve around cutting costs by freeing employees from low-value, repetitive work. Companies have begun deploying generative AI tools to automate time-consuming, tedious jobs, which previously required humans to assess unstructured information.
There is extensive experimentation on potentially more disruptive tools, but signs of commercial deployment remain rare. Academics and banks are examining how generative AI could help in impactful areas including asset selection, improved simulations, and better understanding of asset correlation and tail risk—the probability that the asset performs far below or far above its average past performance. So far, however, a range of practical and regulatory challenges are impeding their commercial use.Legacy technology and talent shortages may slow adoption of generative AI tools, but only temporarily. Many financial services companies, especially large banks and insurers, still have substantial, aging information technology and data structures, potentially unfit for the use of modern applications. In recent years, however, the problem has eased with widespread digitalization and may continue to do so. As is the case with any new technology, talent with expertise specifically in generative AI is in short supply across the economy. For now, financial services companies appear to be training staff rather than bidding to recruit from a sparse specialist pool. That said, the difficulty in finding AI talent is already starting to ebb, a process that would mirror those seen with the rise of cloud and other new technologies.
More difficult to overcome may be weaknesses in the technology
By: MIT Technology Review Insights
Title: Finding value in generative AI for financial services
Sourced From: www.technologyreview.com/2023/11/26/1083841/finding-value-in-generative-ai-for-financial-services/
Published Date: Mon, 27 Nov 2023 01:00:00 +0000
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