Artificial Intelligence and COVID-19: How Technology Can Understand, Track, and Improve Health Outcomes – Stanford University News

On April 1, nearly 30 artificial intelligence (AI) researchers and experts met virtually to discuss ways AI can help understand COVID-19 and potentially mitigate the disease and developing public health crisis.

COVID-19 and AI: A Virtual Conference, hosted by the Stanford Institute for Human-Centered Artificial Intelligence, brought together Stanford faculty across medicine, computer science, and humanities; politicians, startup founders, and researchers from universities across the United States.

In these trying times, I am especially inspired by the eagerness and diligence of scientists, clinicians, mathematicians, engineers, and social scientists around the world that are coming together to combat this pandemic, Fei-Fei Li, Denning Family Co-Director of Stanford HAI, told the live audience.

COVID-19: What is Working?

As the virus envelops the world, South Korea, China, Hong Kong, and Singapore have been able to drastically flatten their curves, says Michele Barry, Stanford University professor of medicine. To begin, these countries were quick to enact strong containment, social-distancing or quarantine rules, rigorous and free testing and tracking, and far-reaching communication strategies. Why else were they so successful? All were highly prepared to meet this health crisis as a result of prior experience confronting the 2002 SARS epidemic, she notes.

Jason Wang, director of Stanfords Center for Policy, Outcomes, and Prevention, pointed to Taiwan as another leader in this space. Taiwan focused on tracking health supplies, coordinating government agencies, regulating transportation, and amending laws for violating quarantine. Both Taiwan and South Korea implemented aggressive technologies, including thermal imaging. If your temperature reading was too high, for example, you were denied entry to an office building or restaurant.

In the United States, early focus has shifted from containment to quarantine and testing. Were paying attention to Korea, China, and Singapore and other places that are a month ahead of us, says U.S. Rep. Ami Bera. Serological testing used to diagnose the presence of antibodies in the blood will help us understand who has immunity and when we can reopen parts of the community, he adds.

The Fight Against Misinformation

Managing the scope of this global pandemic has been made more difficult and complicated by the spread of disinformation, misinformation, and conspiracy theories.

In times of crisis, University of Washington associate professor Kate Starbird explains, people come together to seek information and take psychological comfort. But sensemaking can also lead to false rumors. Disinformation false information thats spread intentionally causes confusion and even panic and can divert resources to the wrong areas, says Stanford Health Communication Initiative director Seema Yasmin. Both disinformation and misinformation (any information thats inaccurate) can breed xenophobia. Eram Alam, Harvard University assistant professor, notes a recent uptick in hate crimes and racist incidents as references to the Chinese virus or Wuhan virus peppered articles and government news conferences.

To maintain trust, says Starbird, political leaders must be mindful that their statements not contribute to the spread of misinformation or cast doubt on science; crisis communicators must be transparent about the rationale for their actions (while acknowledging that facts may change as we learn more).

Researchers Roles in Fighting COVID-19

Across disciplines, researchers are finding ways to fight COVID-19, by sharing data and building new tools. Infectious diseases data scientist Lucy Li of the Chan Zuckerberg Biohub says her organization is developing a tool to estimate unreported infections. At Stanford, associate professor of medicine Nigam Shah and colleagues are honing in on ways data science can respond both operationally (How many patients will our region have? How many ICU beds do we need?) and clinically (Whom do we test?), while pointing to critical areas for further research (What drugs can help us?). Harvard Medical School pediatrician John Brownstein and his team are tracking all coronavirus infections worldwide and partnering with organizations designing tools around the information together with the CDC, for example, they are working to analyze the efficacy of various social-distancing policies.

At Carnegie Mellon, statistics and machine learning associate professor Ryan Tibshiranis epidemiological forecasting team has shifted from studying flu to COVID-19 to predict short-term forecasts that will inform public health officials in making policy decisions. Meanwhile, Tina White, a Stanford mechanical engineering PhD candidate, designed an open-source app to track the spread of COVID-19, using anonymized Bluetooth data. HAI co-director Fei-Fei Lis research offers an AI approach to helping senior citizens stay in their homes: sensors and cameras could send valuable information about sleep or dietary patterns, for instance, to clinicians in a secure and ethical way.

Meanwhile, startups are playing a role. Curai co-founder Xavier Amatriain says his companys machine learning tools create personalized diagnostic assessments, while Anthony Goldblooms company, Kaggle, offers the machine-learning community ways to share data and review each others work.

Finding a Cure

Tools are essential weapons for tracking and better understanding the disease, but vaccines and drugs are the pathway to an eventual cure. Binbin Chen, Stanford genetics MD and PhD student, says vaccines are among the most powerful ways to curb a pandemic and prevent its recurrence. His team uses artificial intelligence to examine fragments of SARS-CoV-2 to determine how they might apply to COVID-19 vaccines. These tools, says Chen, can give us a better educated guess and increase our chances of finding an effective vaccine. Meanwhile, Stanford bioengineering research engineer Stefano Rensi is examining existing drugs that can be repurposed to combat the disease. He and his team use natural language processing, protein structure prediction, and biophysics to identify potential drugs. According to preliminary results, the team has classified several candidates, including one undergoing clinical testing in Japan.

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IBM Research releases a new set of cloud- and artificial intelligence-based COVID-19 resources – TechRepublic

Access to the online databases is free to qualified researchers and medical experts to help them identify a potential treatment for the novel coronavirus.

IBM Research is making multiple free resources available to help healthcare researchers, doctors, and scientists around the world accelerate COVID-19 drug discovery. The resources can help with gathering insights, to applying the latest virus genomic information and identifying potential targets for treatments, to creating new drug molecule candidates, the company said in a statement.Though some of the resources are still in exploratory stages, IBM is giving access to qualified researchers at no charge to aid the international scientific investigation of COVID-19.The announcement follows IBM's launch of the US COVID-19 High Performance Computing Consortium, which is harnessing massive computing power in the effort to help confront the coronavirus, the company said.

Healthcare agencies and governments around the world have quickly amassed medical and other relevant data about the pandemic. And, there are already vast troves of medical research that could prove relevant to COVID-19, IBM said."Yet, as with any large volume of disparate data sources, it is difficult to efficiently aggregate and analyze that data in ways that can yield scientific insights," the company said.SEE: How tech companies are fighting COVID-19 with AI, data and ingenuity (TechRepublic)

To help researchers access structured and unstructured data quickly, IBM has offered a cloud-based AI research resource that the company said has been trained on a corpus of thousands of scientific papers contained in the COVID-19 Open Research Dataset (CORD-19), prepared by the White House and a coalition of research groups, and licensed databases from the DrugBank, Clinicaltrials.gov and GenBank.

"This tool uses our advanced AI and allows researchers to pose specific queries to the collections of papers and to extract critical COVID-19 knowledge quickly," the company said. However, access to this resource will be granted only to qualified researchers, IBM said.

The traditional drug discovery pipeline relies on a library of compounds that are screened, improved, and tested to determine safety and efficacy, IBM noted.

"In dealing with new pathogens such as SARS-CoV-2, there is the potential to enhance the compound libraries with additional novel compounds," the company said. "To help address this need, IBM Research has recently created a new, AI-generative framework which can rapidly identify novel peptides, proteins, drug candidates and materials."

This AI technology has been applied against three COVID-19 targets to identify 3,000 new small molecules as potential COVID-19 therapeutic candidates, the company said. IBM is releasing these molecules under an open license, and researchers can study them via a new interactive molecular explorer tool to understand their characteristics and relationship to COVID-19 and identify candidates that might have desirable properties to be further pursued in drug development.To streamline efforts to identify new treatments for COVID-19, IBM said it is also making the IBM Functional Genomics Platform available for free for the duration of the pandemic."Built to discover the molecular features in viral and bacterial genomes, this cloud-based repository and research tool includes genes, proteins and other molecular targets from sequenced viral and bacterial organisms in one place with connections pre-computed to help accelerate discovery of molecular targets required for drug design, test development and treatment," IBM said.

Select IBM collaborators from government agencies, academic institutions and other organizations already use this platform for bacterial genomic study, according to IBM. Now, those working on COVID-19 can request the IBM Functional Genomics Platform interface to explore the genomic features of the virus.

Clinicians and healthcare professionals on the frontlines of care will also have free access to hundreds of pieces of evidence-based, curated COVID-19 and infectious disease content from IBM Micromedex and EBSCO DynaMed, the company said.

These two decision support solutions will give users access to drug and disease information in a single and comprehensive search, according to IBM. Clinicians can also provide patients with consumer-friendly education handouts with relevant, actionable medical information, the company said.IBM's Micromedex online reference databases provide medication information that is used by more than 4,500 hospitals and health systems worldwide, according to IBM."The scientific community is working hard to make important new discoveries relevant to the treatment of COVID-19, and we're hopeful that releasing these novel tools will help accelerate this global effort," the company said."This work also outlines our long-term vision for the future of accelerated discovery, where multi-disciplinary scientists and clinicians work together to rapidly and effectively create next generation therapeutics, aided by novel AI-powered technologies."

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Leveraging Artificial Intelligence to Enhance the Radiologist and Patient Experience – Imaging Technology News

Arecent study earlier this year in the journal Nature, which included researchers from Google Health London, demonstrated that artificial intelligence (AI) technology outperformed radiologists in diagnosing breast cancer on mammograms. This study is the latest to fuel ongoing speculation in the radiology industry that AI could potentially replace radiologists. However, this notion is simply sensational.

Consider the invention of autopilot. Despite its existence, passengers still rely on pilots, in conjunction with autopilot technology, to travel. Similarly, radiologists can combine their years of medical knowledge and personal patient relationships with AI technology to improve the patient and clinician experience. To examine this in greater detail, consider the scenarios in which AI is making, or can make, a positive impact.

Measuring a womans breast density is critical in assessing her risk for developing breast cancer, as women with very dense breasts are four to five times more likely to develop breast cancer than women with less dense breasts.1,2 However, as radiologists know, very dense breast tissue can create a masking effect on a traditional 2-D image, since the glandular tissue color matches that of cancer. As a result, a womans breast density classification can influence the type of breast screening exam she should get. For example, digital breast tomosynthesis (DBT) technology has proven as superior for all women, including those with dense breasts.

Categorizing density, though, can traditionally be a subjective process radiologists must manually view the breast images and make a determination, and in some cases two radiologists may disagree on a classification. This is where AI technology can make a positive impact. Through a collection of images in a database and consistent algorithms, AI technology can help unify breast density classification, especially for images teetering between a B and C BI-RADS score.

While AI technology may offer the potential to provide more consistent BI-RAD scores, the role of the radiologist is still very necessary its the radiologist who would know the patients full profile that could impact clinical care. For example, this can include other risk factors their patient may have, such as family history of breast cancer, to personal beliefs about various screening options and beyond all of which are external factors that could influence how to manage a particular patients journey of care.

In addition to helping assist with breast density classification, AI technology can also help improve workflow for radiologists which can, in turn, impact patient care. Although it is clinically proven to detect more invasive breast cancers, DBT technology produces a much larger amount of data and larger data files compared to 2-D mammography, creating workflow challenges for radiologists. However, AI technology now exists that can help reduce reading time for radiologists by identifying the critical parts of 3-D data worth preserving. The technology can then cut down on the number of images to read while maintaining image quality. The AI technology does not take over the radiologists entire role of reading the images and providing a diagnosis to patients it simply calls to their attention the higher risk images and cases that require urgent attention, allowing radiologists to prioritize cases in need of more serious and immediate scrutiny.

There are many more challenges that radiologists face today in which AI technology can potentially make an impact in the future. For example the length of time between a womans screening and the delivery of her results could use improvement, especially since that waiting period can elicit very high emotions. The important thing to realize for now, though, is that AI technology plays an important and positive role in radiology today, and the best outcomes will occur when radiologists and AI technology are not mutually exclusive but rather work in practice together.

Samir Parikh is the global vice president of research and development for Hologic. In this role, he is responsible for leading and driving innovative advanced solutions across the continuum of care to drive sustainable growth of the breast and skeletal health division.

References:

1.Boyd NF, Guo H, Martin LJ, et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med. 356(3):227-36, 2007.

2. Yaghjyan L, Colditz GA, Collins LC, et al. Mammographic breast density and subsequent risk of breast cancer in postmenopausal women according to tumor characteristics. J Natl Cancer Inst. 103(15):1179-89, 2011.

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Artificial intelligence used to predict which coronavirus patients are at greater risk of ARDS – Euronews

An artificial intelligence tool is being developed which researchers hope could be used to predict which coronavirus patients will suffer life-threatening lung damage.

The team behind the initial study reported 80% accuracy in its predictions of which patients would develop acute respiratory distress syndrome (ARDS) - which can be fatal in severe COVID-19 cases.

The aim of the research is to provide hospitals with a tool to help decide which patients cans safely be sent home and which will need beds and potentially breathing equipment allocated to them.

The AI tool used data on 53 patients from two hospitals in China, who all tested positive for coronavirus in January.

ARDS is a condition where the lungs, inflamed by serious infection such as pneumonia, cannot provide the body's vital organs with enough oxygen. The condition causes fluid to to leak into the air sacs in the lungs, making it difficult to breath.

It is the cause of death in many fatal coronavirus cases, with severe cases of pneumonia damaging the lungs of patients. In one study published earlier this month, of 201 patients with pneumonia in a hospital in China, 84 developed ARDS, 67 received mechanical ventilation and 44 died. All those who died developed ARDS and received mechanical ventilation.

The AI study, conducted by researchers at NYU Grossman School of Medicine and the Courant Institute of Mathematical Sciences at New York University, looked at demographic, laboratory and radiological findings of patients with COVID-19.

The paper, published online in the journal Computers, Materials & Continua, found the best indicators of future severity were not as expected.

Instead of factors such as certain patterns in lung imaging, fever, and even age and gender, it found changes in three features gave the most accurate prediction of future deterioration:

The small sample size of the study limits its current utility, but the researchers think it holds promise as another tool to predict the patients most vulnerable to the virus, according to one of the authors, Megan Coffee MD.

"We hope that the tool, when fully developed, will be useful to physicians as they assess which moderately ill patients really need beds, and who can safely go home, with hospital resources stretched thin," said co-author Anasse Bari.

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‘Magic toilet’ could monitor users’ health, say researchers – The Guardian

A smart toilet boasting pressure sensors, artificial intelligence and a camera has been unveiled by researchers who say it could provide a valuable way to keep tabs on our health.

The model is the latest version of an idea that has been around for several years: a system that examines our daily movements in an effort to spot the emergence of diseases. Such an approach, experts say, has an advantage over wearable devices, since individuals do not need to remember to use the system.

We have developed a passive human health monitoring system that can be easily incorporated into a normal daily routine, requiring minimal or even no human intervention, the team behind the new toilet report.

They hope it will eventually become a daily clinic, helping in the prevention and early detection of problems from diabetes to urinary tract infections and inflammatory bowel diseases.

Writing in the journal Nature Biomedical Engineering, the international team of researchers note that previous attempts at such a toilet have been expensive and have provided limited information. However, their new system can be fitted on to existing toilets and incorporates a suite of sensors and detectors.

The future will be either a magic toilet paper or these magic toilets

These include test strips that detect telltale health markers within urine, such as glucose and red blood cells, as well as video recordings of the flow to spot changes that may be related to disease.

We believe that inconsistencies can provide valuable information about the prostate and bladder functions, the authors write.

In addition, the system incorporates cameras that take images of users stool. These images are then classified using a machine-learning system a type of artificial intelligence into the different categories on the Bristol stool scale that reflect problems such as constipation or diarrhoea.

The toilet has further features. It was also able to collect additional information, such as first stool dropping time and total seating time, which can potentially be acted on by clinicians to help to manage constipation and haemorrhoids, the authors write.

Perhaps most inventively, the team report that the system detects who is using the toilet from a fingerprint scanner on the flush handle, and analprints distinctive creases in the lining of the anus, captured by video frames.

However the team say there is more to do, not least in testing the device in large clinical studies so far a total of 21 participants have tested the toilet. They also stress the need to develop self-cleaning mechanisms to avoid false positives in the tests, adapt the system to squatting toilets, and redesign the urine analysis system for women, as it is currently designed for users who stand up while having a pee. They also hope to expand the range of tests to screen for illicit drug use, sexually transmitted infections and the makeup of microbes in the gut.

But whether the system will prove popular is another matter. In a survey of 300 individuals near Stanford University who were asked to rate what they thought of the proposed toilet, 30% said they felt uncomfortable with it, primarily citing privacy concerns, with the analprint the most disliked component.

Prof Tim Spector, an expert on the gut microbiome from Kings College London, who was not involved in the research, welcomed the work, but said the teams future plans to analyse chemicals and microbes were important.

We know that your stool sample is probably the best snapshot of your current health that we have, he said.

Spector said the new toilet was a sign of things to come, predicting that regular monitoring would become commonplace.

The future will be either a magic toilet paper that gives you this result or these magic toilets that will give you a chemical analysis basically of the chemicals your microbes are producing, to give a snapshot of your inner health, he said.

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Analysis on Impact of COVID-19-Artificial Intelligence (AI) in Construction Market 2019-2023 | Demand for Data Integration to Boost Growth | Technavio…

Technavio has been monitoring the artificial intelligence (AI) in construction market and it is poised to grow by USD 1.13 billion during 2019-2023. The report offers an up-to-date analysis regarding the current market scenario, latest trends and drivers, and the overall market environment.

This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20200403005386/en/

Technavio has announced its latest market research report titled Global Artificial Intelligence (AI) in Construction Market 2019-2023 (Graphic: Business Wire)

Technavio suggests three forecast scenarios (optimistic, probable, and pessimistic) considering the impact of COVID-19. Please Request Latest Free Sample Report on COVID-19 Impact

The market is concentrated, and the degree of concentration will decelerate during the forecast period. Autodesk, IBM, Microsoft, Oracle, and SAP are some of the major market participants. The demand for data integration will offer immense growth opportunities. To make the most of the opportunities, market vendors should focus more on the growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments.

Demand for data integration has been instrumental in driving the growth of the market.

Artificial Intelligence (AI) in Construction Market 2019-2023: Segmentation

Artificial Intelligence (AI) in Construction Market is segmented as below:

To learn more about the global trends impacting the future of market research, download latest free sample report of 2020-2024: https://www.technavio.com/talk-to-us?report=IRTNTR30539

Artificial Intelligence (AI) in Construction Market 2019-2023: Scope

Technavio presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources. Our artificial intelligence (AI) in construction market report covers the following areas:

This study identifies investment in AI startups as one of the prime reasons driving the artificial intelligence (AI) in construction market growth during the next few years.

Artificial Intelligence (AI) in Construction Market 2019-2023: Vendor Analysis

We provide a detailed analysis of vendors operating in the artificial intelligence (AI) in construction market, including some of the vendors such as Autodesk, IBM, Microsoft, Oracle, and SAP. Backed with competitive intelligence and benchmarking, our research reports on the Artificial Intelligence (AI) in construction market are designed to provide entry support, customer profile and M&As as well as go-to-market strategy support.

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Artificial Intelligence (AI) in Construction Market 2019-2023: Key Highlights

Table Of Contents:

PART 01: EXECUTIVE SUMMARY

PART 02: SCOPE OF THE REPORT

PART 03: MARKET LANDSCAPE

PART 04: MARKET SIZING

PART 05: FIVE FORCES ANALYSIS

PART 06: MARKET SEGMENTATION BY SOLUTION

PART 07: CUSTOMER LANDSCAPE

PART 08: MARKET SEGMENTATION BY APPLICATION

PART 09: GEOGRAPHIC LANDSCAPE

PART 10: DRIVERS AND CHALLENGES

PART 11: MARKET TRENDS

PART 12: VENDOR LANDSCAPE

PART 13: VENDOR ANALYSIS

PART 14: APPENDIX

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Technavio is a leading global technology research and advisory company. Their research and analysis focus on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions. With over 500 specialized analysts, Technavios report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavios comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

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Artificial Intelligence (AI) Market is projected to garner $169411.8 million in 2025 with a booming CAGR 55.6% – WhaTech Technology and Markets News

Increase in investment in AI technologies, rise in demand for analyzing and interpreting large amount of data, and surge in adoption of AI in emerging market are expected to propel the global AI market.

Rise in investment in AI technologies, increased demand for analyzing and interpreting large amount of data, and surge in customer satisfaction coupled with increase in adoption of reliable cloud application have boosted the growth of the global artificial intelligence (AI) market. However, dearth of trained and experienced staff hampers the market growth.

On the contrary, rise in adoption of AI in emerging markets and rapid development of smarter robots are expected to create lucrative opportunities in the near future.

The global AI market is divided on the basis of technology, industry vertical, and geography. Based on technology, the market is segmented into machine learning, natural language processing, image processing, and speech recognition.

The machine learning segment held the largest share in 2016, contributing more than half of the market and expected to maintain its dominance throughout the study period. Moreover, the segment is projected to register the fastest CAGR of 56.4% during the forecast period.

The artificial intelligence market accounted for$4,065.0 millionin 2016, and is expected to reach$169,411.8 millionby 2025, growing at a CAGR of 55.6% from 2018 to 2025.

The market report provides an in-depth analysis of the major market players such asApple Inc., Alphabet (Google Inc.), IBM Corporation, Baidu, Microsoft Corporation, IPsoft, NVIDIA, MicroStrategy, Inc., Verint Systems Inc (Next IT Corp), and Qlik Technologies Inc.

Based on industry vertical, the market is divided into media & advertising, BFSI, it & telecom, retail, healthcare, automotive & transportation, and others. The IT & telecom segment dominated the market in 2016, contributing more than one-fifth of the market.

Moreover, the segment is projected to register the fastest CAGR of 56.8% during the forecast period.

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The global AI market is analyzed across various regions such as North America, Europe, Asia-Pacific, and LAMEA. The market across North America held the largest share in 2018, contributing nearly half of the market.

However, the market across Asia-Pacific is projected to manifest the fastest CAGR of 59.4% during the forecast period.

Top Impacting Factors Such as -

1.Increase in investment in AI technologies

2.Growth in demand for analyzing and interpreting large amounts of data

3.Increased customer satisfaction and increased adoption of reliable cloud applications

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Holocaust survivors will be able to share their stories after death thanks to a new project – 60 Minutes – CBS News

Tonight, as the world struggles to contain and recover from the novel coronavirus, we offer a story we completed just before life changed so dramatically. It is a story of history, hope, survival and resilience, which has its roots in another time when the world was convulsed by crisis World War II.

This year marks the 75th anniversary of the end of that war and of the liberation of concentration camps across Europe. Most of the survivors who remain are now in their 80s and 90s. Soon there will be no one left who experienced the horrors of the Holocaust firsthand, no one to answer questions or bear witness to future generations. But a new and dramatic effort is underway to change that. Harnessing the technologies of the present and the future, it keeps alive the ability to talk to, and get answers from, the past.

Correspondent Lesley Stahl's interview with Holocaust survivor Aaron Elster, who spent two years of his childhood hidden in a neighbor's attic, was unlike any interview she had ever done.

"Aaron, tell us what your parents did before the war," Stahl asked Elster.

"They owned and operated a butcher shop," Elster said.

It wasn't the content of the interview that was so unusual.

"Where did you live?" Stahl asked.

"I was born in a small town in Poland called Sokolw Podlaski," Elster said.

It's the fact that this interview was with a man who was no longer alive. Aaron Elster died two years ago.

"What's the weather like today?" Stahl asked.

"I'm actually a recording," Elster said. "I cannot answer that question."

Heather Maio came up with the idea for this project. She had worked on exhibits featuring Holocaust survivors for years and wanted future generations to have the same opportunity to interact with them as she'd had.

"I wanted to talk to a Holocaust survivor like I would today," Maio said. "With that person sitting right in front of me and we were having a conversation."

She knew that back in the 90s, after making the film "Schindler's List," Steven Spielberg created a foundation named for the Hebrew word for the Holocaust Shoah to film and collect testimonies from as many survivors as possible. They have interviewed nearly 55,000 of them so far and have stored them at the University of Southern California. But Maio dreamed of something more dynamic, being able to actively converse with survivors after they're gone. And she figured, in the age of artificial intelligence tools like Siri and Alexa, the technology had to be creatable.

She brought the idea to Stephen Smith, executive director of the USC Shoah Foundation, and now her husband. He loved it, but some of his colleagues weren't so sure.

"One of them looked at me," Maio said. "She was, like, 'You wanna talk to dead people?'"

"And you said, '"Yes, because that's the point,'" Stahl said.

"That's the point," Maio said.

"Well maybe people thought you're turning the Holocaust into something maybe hokey?" Stahl asked.

"Yeah," Maio said. "They said that, 'You're gonna Disney-fy the Holocaust.'"

"We had a lot of pushback on this project," Smith said. "'Is it the right thing to do? What about the wellbeing of the survivors? Are we trying to keep them alive beyond their deaths?' Everyone had questions except for one group of people, the survivors themselves, who said, 'Where do I sign up? I would like to participate in this project.' No barriers to entry."

The first survivor they signed up to do a trial run was a man named Pinchas Gutter, who was born in Poland and deported to the Majdanek concentration camp with his parents and twin sister Sabina at the age of 11. He is the only one who survived. They flew Gutter from his home in Toronto to Los Angeles, and asked him to sit inside a giant lattice-like dome.

"Yeah, I call it a sphere," Gutter said. "They call it a dome. And then eventually, it was called a bubble."

A bubble surrounding him with lights and more than 20 cameras. The goal was to future-proof the interviews so that as technology advances and 3D, hologram-like projection becomes the norm, they'll have all the necessary angles.

"So the very first day we went to film Pinchas, we had these ultra high speed cameras," Smith said. "They were all linked together and synced together to make this video of him. So we sit down and they press record. Nothing happens. So Pinchas is sitting there with 6,000 LED lights on him and cameras that don't work."

Sunglasses shielded his eyes.

"I was bored sitting in that chair, So I started singing to myself," Gutter said. "So suddenly, Steven had this idea, 'Oh, he's singing. We're gonna record some songs of his.'"

Both Smith and Maio said Gutter was a good sport. Eventually the cameras rolled and Gutter was asked to come back to the bubble for the real thing.

"How long were you in that chair?" Stahl asked him.

"A whole week from 9:00 to 5:00," Gutter said. "We were there with breaks for lunch. And-- but I was there from 9:00 to 5:00 answering questions."

It took so long because they asked him nearly 2000 questions. The idea was to cover every conceivable question anyone might ever want to ask him.

"Did you have to look exactly the same?" Stahl asked.

"I had to wear the same clothes and I had three pairs of the same jackets, the same shirts, the same trousers, the same shoes," Gutter said.

Gutter can now be seen -- in those shirts, trousers, and shoes -- at Holocaust museums in Dallas, Indiana, and at the Illinois Holocaust Museum in Skokie, outside Chicago, where visitors can ask him their own questions.

"What kept you going," one girl asked, "or what gave you hope while you were experiencing hardship in the camps?"

"We did hope that the Nazis would lose the war," Gutter's digital image responded.

Gutter's image is projected onto an 11-foot high screen. Smith explained how the technology works.

"So what's happening is all of the answers to the questions that Pinchas gave go into a database," Smith said. "And when you ask a question, the algorithm is looking through all of the database, 'Do I have an answer to that.' And then it'll bring back what it thinks is the closest answer to your question."

Stahl then asked Gutter's digital image a question.

"Did you have a happy childhood?" Stahl asked.

"I had a very happy childhood," Gutter's digital image said. "My parents were winemakers. My father started teaching me to become a winemaker when I was 3-and-a-half years old. By the age of 5, I could already read and I could already write."

"Wow," Stahl said. "You're very smart."

"Thank you," Gutter's digital image said with a laugh.

"I've noticed there's a little jiggle right before Pinchas starts to talk," Stahl said. "What is that?""What you're seeing here isn't a human being," Smith said. "It's video clips that are-- that are being butted up to each other and played. And as it searches and brings the clip in, you just-- you're seeing a little bit of a jump cut."

The jump cuts stopped being distracting once Stahl asked about the fate of Gutter's family.

"Tell us what happened when you got to the camp," Stahl said.

"As soon as we arrived there, we were being separated into different groups," Gutter's digital image said. "And my sister was somehow pushed towards the children. And I saw her, she must have spotted my mother. So she ran towards my mother. I saw my mother. And she hugged her. And since that time, all I can remember whenever I think of my sister is her long-- big, long, blonde braid."

That was the last time he saw his twin sister, Sabina. He learned later that day that she and both his parents had been killed in the gas chambers. Pinchas Gutter was alone at age 11, put to work as a slave laborer.

"Did you ever see anybody killed?" Stahl asked.

"Unfortunately, I saw many people die in front of my eyes," Gutter's digital image said.

Stahl wasn't sure how a recording would handle what she wanted to ask him next.

"How can you still have faith in God?" Stahl asked.

"How can you possibly not believe in God?" Gutter's digital image said.

"Well," Stahl said, "how did he let this happen?"

"God gave human beings the knowledge of right and wrong and he allowed them to do what they wished on this earth, to find their own way," Gutter's digital image said. "To my mind, when God sees what human beings are up to, especially things like genocide, he weeps."

"Wow. Stephen, I could ask him questions for ten hours," Stahl said.

Since Pinchas Gutter was filmed, the Shoah Foundation has recorded interviews with 21 more Holocaust survivors, each for a full week. And they've shrunk the set-up required, so they can take a mobile rig on the road to record survivors close to where they live. They've deliberately chosen interview subjects with all different wartime experiences. Survivors of Auschwitz, hidden children, and as we saw last fall in New Jersey, 93-year-old Alan Moskin, who isn't a holocaust survivor. He was a liberator.

"Entering that camp was the most horrific sight I've ever seen or ever hope to see the rest of my life," Moskin said.

Moskin was an 18-year-old private when his Army unit liberated a little-known concentration camp called Gunskirchen.

"There was a pile of skeleton-like bodies on the left," Moskin said. "There was another pile of skeleton-like bodies on the right. 'Those poor souls.' That's the term my lieutenant kept screaming, 'Oh my God, look at these poor souls.'"

"I remember the expression and the attitude of all of us," Moskin continued. "'What in the freak? What is this? God almighty'"

Each of Alan Moskin's answers is then isolated by a team of researchers at the Shoah Foundation Office. They add into the system a variety of questions people might ask to trigger that response.

"For every question that we asked, there are 15 different ways of asking the same question," Maio said. "And that's all manual."

Editors rotate the image, turn the green screen background into black and then a long process of testing begins, some of it in schools.

Students are asked to try it out. Ask whatever questions they want and see if the system calls up the correct answer.

"How did you find out that your city was getting invaded by Germany?" One student asked.

"How did you feel about your family?" Another asked.

Pinchas Gutter's digital image responded to one student by asking, "Can you rephrase that, please?"

Every question and response is then reviewed.

"We log every single question that's asked of the system," Maio said. "And see if there is a better response that addresses that question more directly."

As Stahl's crew discovered, it's still a work in progress.

"Tell us about your family when you were a little boy," Stahl asked Gutter's digital image.

"How about you ask me about life after the war?" The digital image answered back.

"So, couple of things about artificial intelligence," Smith said. "It is mainly artificial and not so intelligent."

"Just yet, for now," Maio said.

"But the beauty of artificial intelligence is it develops over time," Smith said. "So we aren't changing the content. All the answers remain the same. But over time, the range of questions that you can ask will be enhanced considerably."

Questions to draw out what it was like for Aaron Elster hiding in that attic 75 years ago.

"I used to pray to God to let me live 'til I was 25," Elster's digital image said. "I wanted to taste what adulthood would be like. So, am I a lucky guy? Yes I am."

Of more than 20 men and women who have participated so far in the project, three have already passed away. Stahl had conversations with two of them, conversations that at times felt so normal, she said she could almost forget she was talking with the digital image of someone no longer living.

First, a spunky 4'9" woman named Eva Kor, an identical twin who, together with her sister, survived Auschwitz and the notorious experiments of Dr. Josef Mengele. Kor spent her life after the war in Terre Haute, Indiana. She died last summer at the age of 85.

"Hi, Eva. How are you today?" Stahl asked.

"I'm fine, and how are you?" Kor's digital image said back.

"I'm good," Stahl asked.

Stahl said it felt natural to answer Kor's question before posing her own.

"So how old were you when you went to Auschwitz?" Stahl asked.

"When I arrived in Auschwitz, I was ten years old," Kor's digital image said. "And I stayed in Auschwitz until liberation, which was about nine months later when we were liberated."

"So we made a little announcement about the fact we were starting this project," Smith said. "I get a call the next day from a lady called Eva Kor. I didn't know her at that point in time. And she says, 'I want to be one of those 3D interviews.'"

"'I wanna be a hologram,'" Maio recalled Kor saying.

"I said, 'Well, I'm traveling, I'm very sorry,'" Smith said. "'Where're you going?' 'Oh, well, I've got to go to New York. I'm going to D.C.' 'When are you gonna go to D.C.? I'm going to D.C.' Turns out we were going to the same event in D.C. I arrive at my hotel, she's sitting in the lobby, waiting for me."

When Eva, on the right, and her twin sister, Miriam arrived at Auschwitz, they were pulled away from their parents and older sisters and taken to a barrack full of twins. They never saw their family again.

60 Minutes reported on Mengele's twin experiments in a story back in 1992, and Stahl actually interviewed the living Eva Kor at her home in Terre Haute. Eva told Stahl then about becoming extremely sick after an injection.

"Mengele came in every morning and every evening, with four other doctors," Kor said in 1992. "And he declared, very sarcastically, laughing, 'Too bad. She's so young. She has only 2 weeks to live.'"

"When I heard that, I knew he was right and I immediately made a silent pledge that I would prove you, Dr. Mengele, wrong," Kor's digital image said in the present.

Imagine, picking up a conversation almost 30 years later -- and after Eva Kor's death.

"Eva, tell us about Dr. Mengele," Stahl asked. "What was he like?"

"He had a gorgeous face, a movie star face, and very pleasant, actually. Dark hair, dark eyes," Kor's digital image said. "When I looked into his eyes, I could see nothing but evil. People say that the eyes are the center of the soul, and in Mengele's case, that was correct."

Eva and Miriam are visible in footage taken by the Soviet forces that liberated Auschwitz 75 years ago.

They went back to the camp many times, Eva continuing to go even after Miriam's death in 1993. It was on one of those visits that Eva made a stunning announcement that she had decided to forgive her Nazi captors.

"I, Eva Moses Kor, hereby give amnesty to all Nazis who participated," Kor said at the time.

She came under blistering attack from other survivors.

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Holocaust survivors will be able to share their stories after death thanks to a new project - 60 Minutes - CBS News

Artificial intelligence trialled in search and rescue missions – Defence Connect

An artificial intelligenceproject run by Defence personnel in search and rescue (SAR) trials has the potential to save lives.

An artificial intelligenceproject run by Defence personnel in search and rescue (SAR) trials has the potential to save lives.

The project, dubbed AI-Search, aims to apply modern AI to help detect small and difficult-to-spot targets, such as life rafts and individual survivors.

Plan Jerichos AI lead, Wing Commander Michael Gan, said his team recognised the potential for the technology to augment and enhance SAR.

The idea was to train a machine-learning algorithm and AI sensors to complement existing visual search techniques, hesaid.

Our vision was to give any aircraft and other Defence platforms, including unmanned aerial systems, a low-cost, improvised SAR capability.

His team approached Lieutenant Harry Hubbert of Warfare Innovation Navy Branch, who was prominent in developing AI-enabled autonomous maritime vehicles for the Five Eyes Exercise Autonomous Warrior in Jervis Bay in late 2018.

LEUT Hubbert was given a month to develop the new algorithms and completed the work in a fortnight.

The AI comprises a series of machine-learning algorithms alongside other deterministic processes to analyse the imagery collected by camera sensors and aid human observers.

AI-Search was first trialled successfully aboard a RAAF C-27J Spartan last year. The second trial took place in March this year near Stradbroke Island, Queensland. During these trials, AI-Search detected a range of small targets in a wide sea area while training the algorithm.

Using commercial off-the-shelf components with custom software and programming by LEUTHubbert, the trials highlighted the feasibility of the technology, which can be applied easily to other ADF airborne platforms.

There is a lot of discussion about AI in Defence but the sheer processing power of machine-learning applied to SAR has the potential to save lives and transform it, LEUT Hubbert said.

The project is a collaboration between Warfare Innovation Navy Branch, Plan Jericho, RAAF Air Mobility Groups No. 35 Squadron and the University of Tasmanias Australian Maritime College.

The projectstemmed froma challenge from the Director-General Air Combat Capability, AIRCDRE Darren Goldie, to find a way of enhancing SAR using improved sensors.

Artificial intelligence trialled in search and rescue missions

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Artificial intelligence trialled in search and rescue missions - Defence Connect

The Growing Role of Artificial Intelligence in the Pharmaceutical Industry – BBN Times

object(stdClass)#31465 (59) { ["id"]=> string(4) "5792" ["title"]=> string(69) "How Blockchain Improves Logistics: Benefits, Drawbacks, and Use Cases" ["alias"]=> string(66) "how-blockchain-improves-logistics-benefits-drawbacks-and-use-cases" ["introtext"]=> string(177) "

The blockchain technology and logistics industry tend to be quite profitable for each other. Additionally, this collaboration brings benefits to carriers and customers.

In this article, well discuss all you need to know about blockchain in the logistics sector.

Blockchain allows optimizing logistic processes in the real-time mode. This technology tends to improve the relationship between shippers and carriers.

We've singled out six main advantages of using blockchain in the logistics sector. Lets discuss them more precisely.

There are a lot of documents required for the transportation process. For example, a bill of lading or B/L. It stands for an agreement that consists of transportation terms, conditions, and other issues.

Blockchain allows recording all the steps. As a result, any participant can look through the delivery chain. If something happens, recorded information will report a problem.

Blockchain allows optimizing routes and delivering faster. In this case, smaller companies can compete with bigger ones, offering faster routes.

As a result, its possible to reduce expenses on the shipping process.

Blockchain simplified the process of goods certification. The combination of IoT and blockchain allows creating smart contracts.

Transactions made on blockchain are secure. Its impossible to change something in the transaction. It leads to decreasing fraudulent operations.

Intermediaries stand for agents that take part in the transportation chain. However, withlogistics software development, the industry doesnt need such specialists.

Weve already mentioned smart contracts. They tend to reduce time and expenses. Also, both parties have an opportunity to automate the validation process, manage obligations, and so on.

There were main blockchain advantages. As you can see, this technology can be quite profitable for the logistics industry.

Of course, there are some disadvantages of using blockchain technology. Lets discuss them more precisely.

Blockchain allows automating supply processes. As a result, there is no need for various specialists. The number of unemployed workers will rise.

Businesses that use blockchain technology should have a standard process. Unfortunately, these days, businesses dont have one.

Its required to create a standard process on the government level. So, businesses can follow it to avoid some common problems.

Its evident that blockchain development is expensive and time-consuming. Additionally, its required to have powerful hardware.

Also, there are expenses on specialists that are experienced in blockchain integration.

So, blockchain is a quite expensive technology that requires additional preparation before using it. However, some companies have already integrated blockchain and got some profit.

Blockchain makes it easy to track goods during shipment. Additionally, the companies have an opportunity to monitor the conditions of the packages.

As a result, its possible to detect broken goods, spoilt products, and so on.

Of course, such opportunities lead to decreasing unnecessary expenditures.

Successful story. Walmart cooperates with IBM to use the blockchain technology in the logistics. The system allows seeing what products are sold. Also, its possible to know the location of the product (the particular warehouse). The company claims that the supply process becomes more transparent.

Blockchain allows reducing the number of documents required for transportation. Additionally, the number of mistakes will also decrease due to automatization. The shipping terms fulfill more precisely.

Let's face it payments are important for any business. Blockchain makes this process secure. For example, its possible to make transactions with such cryptocurrencies as Bitcoin. As a result, the payment process is secure and transparent. Also, such solutions improve international processes.

Successful story. Tallysticks has made a platform that simplified payment processes using blockchain. The solution offers smart contracts that can be customized depending on the business needs and requirements.

Blockchain gives end consumers an opportunity to simplify the authenticity of the goods. There are platforms with data about product origin, quality, fineness, and others.

This technology gives clients transparency. As a result, people trust companies more.

Blockchain makes cooperation easier. For example, enterprises can cooperate with small companies to deliver goods faster. Such a solution is profitable for both parties.

These days, companies can cooperate with each other without intermediaries. It leads to cost reduction and improved delivery processes.

Successful story. ShipChain platform uses blockchain to improve cooperation. For instance, the service allows tracking the delivery from the warehouse to the buyer's door. It leads to better customer experience and satisfaction.

The delivery process is long and expensive. Also, there can occur various delays due to weather conditions and other issues.

Usually, to manage such issues, companies hire lawyers. However, blockchain changes the situation. The transportation process is tracked from the beginning to the end. So, both parties can see any changes in the route.

Also, the parties can monitor any issues connected to the delivery and decide whose fault they were.

Blockchain technology innovates the logistics sector. The companies can simplify the delivery process, making routes shorter.

All these solutions lead to customer satisfaction. As a result, the clients trust companies and order goods or services more often.

The main advantage of blockchain is transparency. Business owners, as well as end consumers, have an opportunity to track the delivery process. Also, customers can ensure that during the delivery the storing conditions were followed.

However, developing blockchain-based solutions is an expensive and time-consuming process. Companies have to prepare beforehand and single out the requirements of the final product.

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The Growing Role of Artificial Intelligence in the Pharmaceutical Industry - BBN Times