Category Archives: Artificial Intelligence
Preventing hospital readmissions with the help of artificial intelligence – University of Virginia The Cavalier Daily
The University Health Systems data science team recently advanced to the next stage of a nationwide competition to apply artificial intelligence to hospital readmissions, a persistent and costly issue. Sponsored by the Centers for Medicare and Medicaid Services, the inaugural Artificial Intelligence Health Outcomes Challenge initially received hundreds of applications. CMS chose only 25 submissions, the Universitys among them, to execute their proposed strategies.
A few years ago, in order to significantly reduce unplanned readmissions to the hospital, the University initiated efforts to develop a cutting-edge yet easily accessible solution to this widespread problem. Bommae Kim, senior data scientist for the University Health System, began pursuing remedies for the epidemic of readmissions in 2018.
Usually, after a patient was discharged, they couldnt manage their disease for some reason, so were trying to figure out what that reason is and help, Kim said.
The University Health Systems data science team found that three percent of patients at the University constitute 30 percent of readmissions within the first 30 days following release from the hospital, while the majority of the remaining 70 percent return within a year. After identifying the need to decrease such adverse events, data scientists in the Universitys Health System, such as Jason Adams, turned to artificial intelligence to target key factors that contribute to a patient returning unnecessarily to the hospital.
The purpose is to take this amount of information and in an automated way to tell that a person is at risk and what is the course of action that can best help that patient, Adams said.
Kim acts as project leader alongside a team of data scientists and information technology personnel. Overseen by Jon Michel, director of data science for the University Health System, the researchers produce models that help predict the likelihood of readmission and subsequently provide actionable advice for physicians.
Only a year or so later in 2019, CMS announced a competition to tackle the same challenge. CMS directed participants to employ the computing power of artificial intelligence to construct a model that accurately and efficiently flags patients at risk of returning to the hospital for non-routine treatments. More than 300 applicants submitted proposals during the launch stage of the challenge.
The University was one of only 25 groups selected to advance to the next stage, vying with organizations such as IBM, Deloitte and the Mayo Clinic for the $1 million grand prize and utilization by the CMS Innovation Center to determine payment and service delivery strategies.
Were doing this for our U.Va. patients, but it would be nice to win the competition because then we can deploy our approach at the national level, Kim said. We believe in our approach.
For this phase of the competition, CMS distributed Medicare claims data to the remaining teams. Claims from all across the country provide the opportunity to fine-tune the Universitys model with data outside of the University Health System. According to Application Systems Analyst Programmer Angela Saunders, the supplemental details will prove beneficial for the Universitys models.
Saunders did point out challenges with the millions of rows of data, which require extensive resources to simply store in an environment suitable for manipulation. Furthermore, inconsistencies lingered in the dataset from year to year, requiring the feature engineering team to sift and sort through the tables, standardizing entries and column headers, which detail the traits associated with each claimant.
Its not just a little data, Saunders said. We have exhausted a lot of resources just to get the data to consistency. Each year, things change just a little bit and so just getting it into a consistent format is a lot of the battle.
Based on the teams assessments, much of the feature engineering portion of the project at least the preliminary round of it has been completed. The next step involves transporting data to Rivanna, the Universitys high performance computing system, and fitting predictive models to the data. Data scientist Rupesh Silwal, who helps design and evaluate multiple iterations of the modeling architecture, noted the importance of not only systemizing the entries, but also of ensuring sensitive medical data remains anonymous.
The feature engineering team has cleaned the data, made sure everything makes sense from year to year and that all of the sensitive information is scrubbed so we can move the data to this other computing infrastructure, Silwal said. Part of our effort has been focused on getting the data in there and using it to set up a modeling environment to see if we can make predictions.
Specifics regarding modeling techniques and factors employed in creating the Universitys unique solution could not be revealed at this time, due to the proprietary nature of the ongoing competition. In broad terms, factors such as past utilization of certain hospital services like the Emergency Department or chronic conditions contribute to the initial formulation of the model, as they are indicators of high potential for readmission, data scientist Adis Ljubovic said.
Those are fairly well-known and were using that as the baseline, but we also have the secret sauce ones that are preventable, Ljubovic said.
Other variables intended to capture financial, transportation and lifestyle information for patients also augment the standard determinants of readmission, while electronic medical records from the University provide documentation of trends in the Universitys own health system.
Another distinctive aspect of the Universitys proposal is its commitment to a solution that clinicians accept. Senior data scientist John Ainsworth and Ljubovic, along with other members of the Universitys project, assert that the healthcare industry generally adopts a conservative mindset with regards to artificial intelligence modeling in hospitals. However, the University Health Systems data scientists have consulted with doctors at the University hospital about introducing tools physicians trust and can easily adopt.
Data science techniques bring with them the potential for accuracy, for bringing in and ingesting larger datasets, Ainsworth said. The richness of the data gets recorded and putting up the information in front of clinicians that can help them take meaningful action is what were going for. If we can ... give them some sense of where preventative strategies might lie, that can support them in their goal of caring for patients.
Several members of the team agreed a complex issue like hospital readmission calls for a collective approach. In the University Health Systems data science department, that can be a rare occurrence, several data scientists remarked, as their separate assignments often occupy most of their time. Senior Business Intelligence Developer Manikesh Iruku expressed appreciation for the chance to learn more about data science techniques, and others shared similar experiences when it came to exploring different subfields of data science.
Saunders and data scientist Valentina Baljak emphasized the confidence this collaboration has given the group to tackle new tasks.
Frequently for us, we have our own projects and its a one-person project, Baljak said. Occasionally you collaborate with someone, but I dont really think we had a project that involved all of us at the same time. That has been a great experience.
Currently, competitors are finalizing their project packages to submit to CMS in February. CMS plans to winnow the field down to the seven best proposals by April. Regardless of the outcome, the Universitys team plans to put their results and newly developed models into practice within the Universitys Health System.
In particular for healthcare, in some ways the best is yet to come in the data science world, Ainsworth said. The future is bright for data science in healthcare.
As Cyber Fraud Increases, Its Artificial Intelligence to The Rescue – ETF Trends
As technology continues to advance, it gives cybercriminals more tools to defraud consumers and in turn, companies are fighting back with artificial intelligence (AI). This gives disruptive-focused ETFs more prominence as AI sets out to fight the good fight.
In response, many financial sector companies are adopting AI to combat both staff and customer fraud, wrote Jeff Palmer in IT Pro Portal. Banks already use AI to detect and prevent payment fraud and employ image-recognition systems for security. What is less widely known is that some companies are also now successfully using AI to comb call records for GDPR breaches or even monitor live calls to flag mis-selling and rogue trading in real-time.
Among the variety of applications of AI in the financial sector is speech recognition, which offers numerous possibilities, including voice-based account servicing, robo-advice, autonomous analysis of audio archives and live sentiment analysis of customer calls as well as the real-time transcription of any audio feed to allow instant decisions to be made, Palmer added. Giants such as Deloitte are now using AI to help enforce compliance and mine their audio data for additional business insights. For instance, automated speech recognition (ASR) technology in audio monitoring can set live triggers on chosen keywords, which can include major financial announcements and other announcements that can have an impact on share prices. This monitoring capability can also detect potential issues, signs of insider trading and patterns of misconduct such as rogue trading.
As AI continues to become a major component of the intelligence community, security-focused ETFs can benefit further, such as theFirst Trust NASDAQ Cybersecurity ETF (NYSEArca: CIBR)and theETFMG Prime Cyber Security ETF (NYSEArca: HACK).
First up, CIBR seeks investment results that correspond generally to the price and yield f an equity index known as the Nasdaq CTA Cybersecurity IndexSM. The index is comprised of securities of companies classified as cybersecurity companies by the CTA.
Next, HACK seeks investment results that correspond generally to the price and yield performance of the Prime Cyber Defense Index. The index tracks the performance of the exchange-listed equity securities of companies across the globe that (i) engage in providing cybersecurity applications or services as a vital component of its overall business or (ii) provide hardware or software for cybersecurity activities as a vital component of its overall business.
For a broad play in disruptive tech, investors can look at theGlobal X Robotics & Artificial Intelligence Thematic ETF (NasdaqGM: BOTZ). BOTZ seeks to invest in companies that potentially stand to benefit from increased adoption and utilization of robotics and artificial intelligence (AI), including those involved with industrial robotics and automation, non-industrial robots, and autonomous vehicles.
For more market trends, visit ETF Trends.
Continue reading here:
As Cyber Fraud Increases, Its Artificial Intelligence to The Rescue - ETF Trends
Lead singer of Moist has created an artificial intelligence named Ophelia – CTV News
WINNIPEG -- The lead singer of the Canadian rock group Moist and four-time Juno winner David Usher was a in Winnipeg Thursday, but not for his music.
The rocker is also a tech entrepreneur in the area of artificial intelligence and he was showing off his new artificial being.
"I was born six months ago. I'm a child really," said Ophelia, an artificial intelligence created by Usher.
Ophelia isn't much different from other artificial intelligence systems like Siri or Alexa, but her purpose is.
Usher said while other AI is used to collect data, Ophelia is used to have a conversation. Every time she talks with someone, she learns more about how to communicate.
"We're really concerned about the conversation cloud that really is much more about human emotions and human contact. Those kind of things, life and death and love and feeling and birth," said Usher, who is the founder of Reimagine AI.
Usher said this sort of tech can be used for thing such as greeting guests at hotels, acting as a host at museums or helping people in hospitals.
In collaboration with Sheldon Memory Lab at McGill University, Usher is helping develop a companion bot for Alzheimer patients.
"Our AIs can come on and recognize them by name and initiate engagement to do some of those things that they've forgotten that they like to do."
Kathy Knight, CEO of Tech Manitoba, said the use of AI is growing in Manitoba and with it, so is automation.
That's a one of the topics of conversation going on at a tech conference at the RBC Convention Centre Thursday and Friday, which is entitled, Disrupted.
"To actually get people to think about the human side of tech and think about how all of this change is affecting the people we live with and work with everyday, and how do we bring them along," said Knight.
While Usher said there are concerns about what people will do with AI in the future, he chooses to look at the good instead.
"You don't have to build the smartest AI, you just have to build something that can help," said Usher.
Visit link:
Lead singer of Moist has created an artificial intelligence named Ophelia - CTV News
If a novel was good, would you care if it was created by artificial intelligence? – The Guardian
Roland Barthes was speaking metaphorically when he suggested in 1967 that the birth of the reader must be ransomed by the death of the author. But as artificial intelligence takes its first steps in fiction writing, it seems technology may one day start to make Barthes metaphor all too real.
AI is still some way off writing a coherent novel, as surreal experiments with Harry Potter show, but the future isnt so far away in Hollywood. According to Nadira Azermai, whose company ScriptBook is developing a screenwriting AI: Within five years well have scripts written by AI that you would think are better than human writing.
Self-promotion aside, if there is the possibility of a decent screenplay from ScriptBooks AI within five years, then a novel composed by machines cant be far behind. But its hard to shake the impression that, even if such novels eventually turn out to be better than human writing, something would be lost.
Perhaps the feeling comes from an idea that would be anathema to Barthes: the idea of literature as communication.
If a book is a heart that only beats in the chest of another, as Rebecca Solnit suggests, then it seems two parties are required: someone to write and someone to read. So when AI writes fiction there seems to be a missing piece, a void at the heart of the text where meaning should reside.
Barthes would have none of this, of course, insisting that it is language which speaks, not the author. In terms which strikingly anticipate the workings of software currently at the cutting edge of artificial writing, such as OpenAIs GPT-2, he argues that a text is not a line of words releasing a single meaning (the message of the Author-God), but instead a tissue of citations, resulting from the thousand sources of culture. The writer can only imitate a gesture forever anterior, never original, Barthes continues. If he wants to express himself the internal thing he claims to translate is itself only a readymade dictionary whose words can be explained (defined) only by other words, and so on ad infinitum.
And he must be on to something. Imagine yourself, some years in the future, pulling a novel by an unknown author off the shelves and finding that it is really good. Would you be any less moved by the story if you were then told it had been produced using groundbreaking AI? If all you had were the words in front of you on the page, how would you even know? Those who scoff at the idea that AI could ever pass this literary Turing test havent been paying attention for the past 50 years. Computers can now drive cars, recognise faces, translate between languages, fill in as your personal assistant, even beat the world champion at Go achievements that are often dismissed as just computation even though an expert of the 1970s would have classed any one of them as a signature ability of human intelligence.
Should publishers decide the future of literature is written in code, there may still be some hope for authors. A shift to AI-generated novels could only ever be a short-term strategy. As Barthes intuited and OpenAIs latest algorithm demonstrates, its certainly possible to assemble writing from other writing. But even if this patchwork prose becomes better than human writing, it would be only drawing on a finite well of inspiration. Train your AI on the sum total of human literature thus far and all youll get is a mass of references: a gesture forever anterior, never original. No one who witnessed the phenomenon that was the Fifty Shades of Grey series could doubt that imitation can be lucrative for a while. But when even an imitator as skilful or as lucky as EL James finds her sales on a downward curve its clear that no matter how feisty your stallion at first appears, flogging it will only get you so far.
Barthes belief in the primacy of the word, his dogged insistence that life can only imitate the book, leaves his recipe for literature missing a vital ingredient: the individual experience that any human writer facing the blank page cannot avoid. Without the raw input of the complicated business that is life, even the most talented AI can only rearrange the books it ingested in its training enough for a few good years in publishing, perhaps, but hardly a sustainable model for literary culture.
Maybe Im thinking too small. Maybe any publisher looking forward to the death of the author would only need to expand the training programme for their writing machines. Perhaps they could hook their AIs up to the daily news, wire them into Spotify, encourage them to make new friends on Twitter and feed it all back into the work. The resulting algorithms would be very different to human beings, of course. But perhaps they would be enough like thinking, feeling beings that their fiction would be communicating something rather marvellous after all.
Richard Lea writes for Guardian books
The rest is here:
If a novel was good, would you care if it was created by artificial intelligence? - The Guardian
Joint Research on Applying Artificial Intelligence to Industrial Cybersecurity – Novus Light Technologies Today
Radiflow, a provider of cybersecurity solutions for industrial automation networks, and the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (Fraunhofer IOSB), a prominent research institute for applied science in Germany, today announced the launch of a joint research project for applying advanced machine learning and artificial intelligence to cybersecurity for industrial automation networks.
For this research project, Radiflow and Fraunhofer IOSB will collaborate on developing machine learning methods and artificial intelligence techniques for allowing the autonomous detection of non-compliant and anomalous behaviors on industrial automation networks. This applied research will involve evaluating graph-based and semantic approaches for event correlation and context awareness in order to develop these new machine learning and artificial intelligence capabilities.
The outcome of this research will be the development of a prototype for an Autonomous Industrial Cybersecurity Assistance System (AICAS) that expands on existing approaches for detecting deviations and anomalies to a baseline of network behaviors on OT networks. This prototype will be designed to self learn the underlying behaviors an of industrial automation networks and the functions of the connected assets in order to dynamically detect new and unknown cyberthreats.
The question of how AI can enhance industrial cybersecurity to better respond to changing OT environments and new attack techniques is timely and essential, said Dr.-Ing. Christian Haas, Group Manager at Fraunhofer IOSB. Radiflow and its extensive experience working with industrial enterprises and critical infrastructure operators make the company the ideal research partner for applying AI to the industrial cybersecurity domain.
The funding for this research project, which is scheduled to last two years, was granted by the Innovation Authority in Israel and the Federal Ministry of Education and Research in Germany.
At the conclusion of this research project, Radiflow intends to incorporate the new capabilities of this AICAS prototype into itsiSID industrial threat detection system.
Determining if abnormal behavior has been caused by normal operational activities or by cyber-attackers is critical for understanding and securing an OT network, explained Yehonatan Kfir, CTO of Radiflow. AI holds the potential to improve the situational awareness of OT networks by efficiently distinguishing between abnormal behavior that was caused by normal operations and abnormal behavior that is connected to a cyberattack.
Original post:
Joint Research on Applying Artificial Intelligence to Industrial Cybersecurity - Novus Light Technologies Today
Heres how Compass uses artificial intelligence to support its agents – Inman
The vast majority of what we do will disappear into the regular tools agents use every day, Compass CTO Joseph Sirosh said on stage at Inman Connect New York.
Amid all the market place disruption, news-making acquisitions and lawsuits Joseph Sirosh, the chief technology officer at the well-funded brokerage Compass, believes the companys goal and mission are pretty straightforward.
Joseph Sirosh | Photo credit: Compass
Compass, to me, is an idea, Sirosh said at Inman Connect in New York on Thursday. Agents grow their business and we invest as much as possible in agents growing their business with technology.
Compass has grown its technology team massively in the past year, nearly tripling it since Sirosh took the role. The company has pulled in talent from some of the worlds top technology companies like Amazon, Microsoft, Facebook and Google.
Among the key areas Compass has focused is artificial intelligence (AI), Sirosh, the former CTO of AI at Microsoft and the CTO of consumer at Amazon, told Clelia Peters, the president of Warburg Realty and Inmans editor-at-large, atInman Connectat the Marriott Marquis in New York City.
AI in real estate, according to Sirosh, is going to empower both the consumer and the agent. Compass, right now, is incorporating predictive AI into its search tools.
With even a few letters being typed, you pick the right search query, Sirosh said.
Eventually, the search will be smarter, thanks to AI. Consumers will be able to search by picture, like throwing a photo of a craftsman-style home into a reverse image search to bring up photos of other craftsman homes on the market, whereas right now, most home searches are limited to geographical locations, and numbers of beds or bathrooms.
Compass is also powering its customer relationship management tool (CRM) with artificial intelligence, by helping agents stay on top of their sphere.
Staying in touch with your sphere of influence is hard work, you have thousands of contacts, Sirosh said. Lots of agents tell me they have lost hundreds of thousands of dollars because they didnt follow up. Consistency of follow up is one of the most challenging things.
Eventually, artificial intelligence will power the platform experience in real estate, Sirosh explained, where the entire ecosystem of what the agent and consumer needs will be connected in one place. The platform begins with listings, where the agents can acquire a listing, make it searchable, price it and market it. Then on the other side, the agent can organize listings for consumers, schedule tours and the consumer can even make an offer.
It sounds all obvious but the reality is, this is done in a fragmented way, Sirosh said.
Sirosh compared it to the experience of listening to music. It used to be recorded in an analog way from a guitar, then pressed into a record and youd go to the record store and buy a physical record by word of mouth or someone elses recommendation. Now, AI pushes recommendations right to an app on your phone and your music listening and discovery journey is guided by AI.
Getting agents to adopt technology is always a challenge, of course, but Sirosh explained that the best technology is the technology you dont even know is there.
The vast majority of what we do will disappear into the regular tools agents use every day, Sirosh said. [Those tools] will become more simple and effective.
Email Patrick Kearns
Read more here:
Heres how Compass uses artificial intelligence to support its agents - Inman
University to Help Society Wrap Their Minds Around Artificial Intelligence – Governing
(TNS) Researchers at the University of Michigan have been exploring the need to set ethics standards and policies when it comes to the use of artificial intelligence, and they now have their own place to do so.
The university has created a new Center of Ethics, Society and Computing (ESC) that will focus on AI, data usage, augmented and virtual reality, privacy, open data and identity.
According to thecenters website, the name and abbreviation alludes to the ESC key on a computer keyboard, which was added to interrupt a program when it produced unwanted results.
In the same way, the Center for Ethics, Society and Computing (ESC pronounced escape) is dedicated to intervening when digital media and computing technologies reproduce inequality, exclusion, corruption, deception, racism or sexism, the centers mission statement reads.
The center will bring together scholars who are committed to feminist, justice-focused, inclusive and interdisciplinary approaches to computing, the university said in a news release.
Associate Director Silvia Lindtner said the center has been in a soft launch phase since March 2019. The idea for ESC was born out of making a critical engagement with the politics and ethics of computing a central aspect of technology research and design, she said.
We established ESC to build on and give legitimacy to the long-term scholarship and activism in technology, engineering and design, and to create an interdisciplinary space to explore and apply critical, justice-oriented and feminist approaches to computing and technology research, Lindtner said.
Director Christian Sandvig said the center is hosting a visiting artist working on robotics this term, and that the center includes faculty from computer science, architecture, music and business schools.
We are fairly unique because we are aggressively pursuing research approaches and topics beyond what people normally think about as computing, Sandvig said.
Lindtner said the universitys public nature allows the center to engage deeply with the broader public, policy experts and actors in the social justice movement.
This is a topic that used to be on the fringes, but more recently has gotten broader attention as we have experienced many unintended consequences of technology, Lindtner said.
Some of the concerns the center will be tackling include gender and racial stereotyping in AI and data-based algorithms, as well as an overall lack of accountability and digital justice.
Sandvig said a lot of companies are now rushing to nominal ethics conversations as a solution to the negative perceptions of their products, but ESC is not interested in ethics-washing.
Were looking ahead to difficult debates about the future path we are steering with technology in society, Sandvig said. We need to make it normal that there is an extensive program of research about this topic ethics, justice, technology, people and the future and it must be central to the enterprise of developing technology and training students.
The center is sponsored by the School of Information; the Center for Political Studies at the Institute for Social Research, and the Department of Communication Studies in the College of Literature, Sciences and the Arts at UM.
2020 MLive.com, Walker, Mich..Distributed byTribune Content Agency, LLC.
See the rest here:
University to Help Society Wrap Their Minds Around Artificial Intelligence - Governing
Google CEO: ‘Artificial intelligence needs to be regulated’ | TheHill – The Hill
Google CEO Sundar Pichaiis calling for governments around the world to regulate artificial intelligence, saying the sensitive technology should not be used to "support mass surveillance or violate human rights."
However, Pichai the top executive at Google as well as its parent company Alphabet also argued that governments should not go too far as they work to rein in high-stakes technologies like facial recognition and self-driving vehicles.
His speech inEurope and companion op-edcome as Europe weighs newethics rules for artificial intelligence and the White House urges a light-touch approach to regulating technology.
"There is no question in my mind that artificial intelligence needs to be regulated," Pichai wrote in theFinancial Times. "It is too important not to. The only question is how to approach it."
Since 2018 Google has touted its AI principles as a potential framework for government regulation. The guidelines urge tech companies to ensure artificial intelligence technologies incorporateprivacy features, contribute to the greater social good and do not reflect "unfair" human biases.
Critics have pushed back onthe tech industry's stated support for AI regulation,claiming the companies are trying to dictate the terms of regulation in their own favor.
"Sensible regulation must also take a proportionate approach, balancing potential harms, especially in high-risk areas, with social opportunities," Pichai wrote.
Governments around the world have found themselves behind the curve as artificial intelligence advances at lightning speed, opening up new frontiers for potential regulation. Several cities in the U.S. have taken the lead by imposing all-out bans on facial recognition technology,which oftenmisidentifies people of color at higher rates.
Pichai has thrown his support behind a temporary ban onfacial recognition technology, which he says can be used for "nefarious" purposes.
"I think it is important that governments and regulations tackle it sooner rather than later and give a framework for it, Pichai said at a conference in Brussels this week.It can be immediate, but maybe theres a waiting period before we really think about how its being used. ... Its up to governments to chart the course.
Microsoft has also released its own ideas around how to regulatefacial recognition tech, and says it abides by a strict set of AI ethics standards.
In 2018, Pichai spent his speech in Davos, Switzerland, toutingthe enormous potential of artificial intelligence, presenting a rosier view of the technologybefore it experienced an intense backlash over the past several years.
Now, as Europe and the U.S. creep closer to instituting rules around many of the products that Google creates, Pichai is raising his voice around what he sees as the best approach to AI.
"Googles role starts with recognizing the need for a principled and regulated approach to applying AI, but it doesnt end there," Pichai wrote. "We want to be a helpful and engaged partner to regulators as they grapple with the inevitable tensions and trade-offs. We offer our expertise, experience and tools as we navigate these issues together."
Read the original post:
Google CEO: 'Artificial intelligence needs to be regulated' | TheHill - The Hill
How the Pentagon’s JAIC Picks Its Artificial Intelligence-Driven Projects – Nextgov
The Pentagon launched its Joint Artificial Intelligence Center in 2018 to strategically unify and accelerate AI applications across the nations defense and military enterprise. Insiders at the center have now spent about nine months executing that defense driven AI-support.
At an ACT-IAC forum in Washington Wednesday, Rachael Martin, the JAICs mission chief of Intelligent Business Automation Augmentation and Analytics, highlighted insiders early approach to automation and innovation.
Our mission is to transform the [Defense] business process through AI technologies, to improve efficiency and accuracybut really to do all those things so that we can improve our overall warfighter support, Martin said.
Within her specific mission area, Martin and the team explore and develop automated applications that support a range of efforts across the Pentagon, such as business administration, human capital management, acquisitions, finance and budget training, and beyond. Because the enterprise is vast, the center is selective in determining the projects and programs best fit to be taken under its wing.
For the JAIC, there are a couple of key principles that we want to go by, or that we're going to adhere to when we're looking at a project and whether we support it, Martin explained.
The first principle to be evaluated is mission impact. In this review, insiders pose questions like who cares? she said. They assess the user-base that would most benefit from the project and what the ultimate outcome would be across Defense if the JAIC opted to support it. Next, according to Martin, officials review data-readiness. In this light, insiders address factors like where the data to be used is storedand whether its actually prepped for AI, or more advanced analysis and modeling to run on top of it.
The third factor thats assessed is technology maturity. Martin said that contrary to what many seem to think, the JAIC is not a research organization but instead seeks to apply and accelerate their adoption of already-existing solutions across the department and where those improvements are needed most. Insiders are therefore not at all interested in spending heaps of time researching new, emerging AI and automation applications. Instead, they aim to identify what already exists and is ready to be deployed at this moment.
So that's a big one for us that we like to emphasize, Martin said.
The final assessment is whether the JAIC can identify Defense insiders who will actually use whatever they are set to build. When developing something new, Martin said insiders want to those itll eventually touch to weigh in on the development every step of the way.
We're not in the business of coming up with good ideas and then creating something and trying to hoist it on somebody else, Martin said. We really believe in a very user-centric approach.
Read the original here:
How the Pentagon's JAIC Picks Its Artificial Intelligence-Driven Projects - Nextgov
Artificial Intelligence (AI) in Retail Market to Reach USD 23,426.3 Million by 2026; Rising Awareness About the Advantages of AI in Retail Operations…
PUNE, India, Jan. 23, 2020 /PRNewswire/ -- The global artificial intelligent (AI) in retail market size is estimated to reach USD 23,426.3 million by 2026, exhibiting a CAGR of 33.7% during the forecast period. The ongoing shift by retailers from traditional retail experience to AI-driven business solutions is one of the crucial factors enabling the growth of the AI in retail market. According to an article published by Forbes, 83% believe AI is a strategic priority for their businesses today and 84% of respondents say AI will enable them to obtain or sustain a competitive advantage. The growing awareness about the advantages of AI in retail operations such as quality improvement, paced up decision making, strong operational agility and enhanced customer experience will boost the AI in retail market growth in the forthcoming years. In addition, exceptional benefits of AI-powered data analytics will further spur demand for AI in retail market in the foreseeable future.
According to the report, published by Fortune Business Insights in a report, titled "Artificial Intelligence (AI) in Retail MarketSize, Share & Industry Analysis, By Offering (Solutions, Services), By Function (Operations-Focused, Customer-Facing), By Technology (Computer Vision, Machine Learning, Natural Language Processing, and Others), and Regional Forecast, 2019-2026" the AI in retail market size was valued at USD 2,306.8 million in 2018. The report is aimed at delivering a comprehensive view of the AI in retail market dynamics, structure by identifying and providing information regarding the key market segments. It also focuses on an all-encompassing analysis of leading market players by financial position, product, product portfolio, price, growth strategies, and regional presence. It offers porter's analysis and SWOT analysis to record the question of shareholders and highlights the investment potential in the upcoming future. It also showcases different procedures and strategies of companies currently operating in the market. It further examines the components convincing market expansion, growth patterns, restricting factors and market strategies.
To gain more insights into the market with detailed table of content and figures, click here: https://www.fortunebusinessinsights.com/artificial-intelligence-ai-in-retail-market-101968
Disposition to AI-powered Chat Bots by Retailers Will Encourage Market Expansion
The growing inclination of retail brands for the deployment of AI-powered chatbots for customer engagement will augment healthy growth of the market in the forthcoming years. Retail brands are able to handle several queries simultaneously with the help of chatbots, without the need to employ a large workforce. The positive impact of artificial intelligence on customer relations and sales will spur demand for AI in retail. Furthermore, close-ended chatbots are configured to answer shopping-related questions, provide quick support and suggestions besides offering a better resolution to their problem. Customers are more likely to engage with AI-powered chatbots, which, in turns enhances customer loyalty. These factors combined will accelerate the AI in retail market share in the foreseeable future.
Emergence of Virtual Trial Rooms to Bolster Healthy Growth
The increasing popularity of virtual trial rooms and ongoing development across retail supply chains will aid the AI in retail market trend during the forecast period. For instance, virtual trial rooms enable buyers to try different dresses without actually having to wear them with the help of digital mirrors. Further, AI allows shoppers to experiment with their outfit by means of a touch-based interface. In addition, the launch of virtual rooms by major companies to create growth opportunities for the market. For instance, Fitiquette, a fashion Web site uses a ground-breaking technology that allows customers to try on outfits in a virtual 3D world based on the user's exact body dimensions. The trial room gives a 360-degree view of the fit and drape of a garment on the actual body dimensions of the consumer.
Request a Sample Copy: https://www.fortunebusinessinsights.com/enquiry/request-sample-pdf/artificial-intelligence-ai-in-retail-market-101968
Introduction of AI Integrated Products and Solutions to Foster Growth in Asia Pacific
North America was valued at USD 1,102.0 million and is expected to remain dominant during the forecast period. The rising deployment of AI-based solutions by retailers to improve the supply chain operations and product portfolio will contribute positively to the AI in retail market revenue. Asia Pacific is expected to grow rapidly during the forecast period owing to the launch of various AI integrated products and solutions. For instance, China is expected to be a world-leading AI center by 2030.
List of the Major Companies in the Global Artificial Intelligence (AI) in Retail Market include:
Have Any Query? Ask Our Experts:https://www.fortunebusinessinsights.com/enquiry/speak-to-analyst/artificial-intelligence-ai-in-retail-market-101968
Table of Content:
o Definition, By Segment
o Research Approach
o Sources
o Drivers, Restraints and Opportunities
o Emerging Trends
o Macro and Micro Economic Indicators
o Consolidated SWOT Analysis of Key Players
o Porter's Five Forces Analysis
o Key Findings / Summary
o Market Size Estimates and Forecasts
Continued..!!!
Request for Customization:https://www.fortunebusinessinsights.com/enquiry/customization/artificial-intelligence-ai-in-retail-market-101968
(Have a Look at Reports Trending inInformation & TechnologyIndustry)
Browse Related Reports:
Internet of Things (IoT) MarketSize, Share and Industry Analysis By Platform (Device Management, Application Management, Network Management), By Software & Services (Software Solution, Services), By End-Use Industry (BFSI, Retail, Governments, Healthcare, Others) And Regional Forecast, 2019 2026
Artificial Intelligence (AI) MarketSize, Share and Global Trend by Component (Hardware, Software, Services), By Technology (Computer Vision, Machine Learning, Natural Language Processing, Others), By Industry Vertical (BFSI, Healthcare, Manufacturing, Retail, IT & Telecom, Government, Others) and Geography Forecast till 2026
Big Data Technology Market Size, Share & Industry Analysis, By Offering (Solution, Services), By Deployment (On-Premise, Cloud, Hybrid), By Application (Customer Analytics, Operational Analytics, Fraud Detection and Compliance, Enterprise Data Warehouse Optimization, Others), By End Use Industry (BFSI, Retail, Manufacturing, IT and Telecom, Government, Healthcare, Utility, Others) and Regional Forecast, 2019-2026
Retail Cloud MarketSize, Share & Industry Analysis, By Model Type (Infrastructure as a Service, Platform as a Service and Software as a Service), By Deployment (Public, Private and Hybrid Cloud), By Solution (Supply Chain Management, Workforce Management, Customer Management, Reporting & Analytics, Data Security, Omni-Channel), By Enterprise Size (Small & Medium and Large Enterprise) and Regional Forecast, 2019-2026
Natural Language Processing (NLP) MarketSize, Share & Industry Analysis, By Deployment (On-Premises, Cloud, and Hybrid), By Technology (Interactive Voice Response (IVR), Text Analytics, Speech Analytics, Pattern and Image Recognition, and Others), By Industry Vertical (Healthcare, Retail, BFSI, Automotive & Transportation, Advertising & Media, Manufacturing, and Others) and Regional Forecast, 2019-2026
Unified Communication as a Service (UCaaS) MarketSize, Share & Industry Analysis, By Component (Telephony, Unified Messaging, Collaboration Platforms, Conferencing, and Reporting and Analytics), By Organization Size (SMEs, Large Enterprises), By End-User (Banking, Financial Services, and Insurance (BFSI), IT and Telecommunications, Healthcare, Public Sector and Utilities, and Others) and Regional Forecast, 2019-2026
3D Printing MarketSize, Share & Industry Analysis, By Component (Hardware, Software, and Services), By Technology (Fused Deposition Modeling, Selective Laser Sintering, Stereolithography, Direct Metal Laser Sintering, PolyJet, Multi Jet Fusion (MJF), Others) By Applications (Prototyping, Production, Proof of Concept, and Others), By End-Use (Automotive, Aerospace and Defense, Healthcare, Others) and Regional Forecast, 2019-2026
Internet of Things (IoT) in Manufacturing MarketSize, Share & Industry Analysis, By Platform (Device Management, Application Management, Network Management), By Software & Services (Software Solution and Services), By Application (Predictive Maintenance, Asset Tracking and Management, Logistics and Supply Chain Management, Real-Time Workforce Tracking and Management, Emergency and Incident Management and Others) and Regional Forecast, 2019-2026
Cyber Security MarketSize, Share & Industry Analysis, By Component (Solutions, Services), By Deployment (On-Premises, Cloud), By Organization Size (SMEs, Large Enterprises), By End-User (BFSI, IT and Telecommunications, Retail, Healthcare, Government, Manufacturing, Travel and Transportation, Energy and Utilities and Others) and Regional Forecast, 2019 2026
Virtual Reality MarketSize, Share & Industry Analysis, By Offering (Hardware, Software), By Technology (Nonimmersive, Semi-Immersive), By Industry Vertical (Gaming & Entertainment Media, Healthcare, Education, Automotive, Aerospace & Defense, Manufacturing), By Application (Training & Simulation, Educational, Attraction, Research & Development) and Regional Forecast, 2019 2026
Endpoint Security MarketSize, Share and Global Trend By Component (Software, Services), By Deployment (On-Premise, Cloud), By Enterprise Size (Large Enterprises, Small & Medium Enterprises), By End-Use Industry (BFSI, Telecom & IT, Retail, Healthcare, Government & Public Sector, Transportation, and Others) and Geography Forecast, 2019-2026
Fraud Detection and Prevention MarketSize, Share and Industry Analysis By Component (Solutions, Services), By Application area (Insurance Claims, Services, Money Laundering), By Deployment (Cloud & On-premise), By Organization Size (Large, Small & Medium Enterprises), By Vertical (BFSI, IT and Telecommunication, Government,Travel and Transportation, Manufacturing, Healthcare and Life Sciences) and Geography Forecast, 2019 2026
Identity And Access Management MarketSize, Share and Industry Analysis By Component (Provisioning, Directory Services, Single Sign-On, Others), By Deployment Model (Cloud, On-Premises), By Enterprise Size (Large Enterprises, Small and Medium Enterprises), By Industry Vertical (BFSI, IT and Telecom, Retail and Consumer Packed Goods, Others) And Regional Forecast 2019-2026
About us:
Fortune Business Insights offers expert corporate analysis and accurate data, helping organizations of all sizes make timely decisions. We tailor innovative solutions for our clients, assisting them address challenges distinct to their businesses. Our goal is to empower our clients with holistic market intelligence, giving a granular overview of the market they are operating in.
Our reports contain a unique mix of tangible insights and qualitative analysis to help companies achieve sustainable growth. Our team of experienced analysts and consultants use industry-leading research tools and techniques to compile comprehensive market studies, interspersed with relevant data.
At Fortune Business Insights we aim at highlighting the most lucrative growth opportunities for our clients. We therefore offer recommendations, making it easier for them to navigate through technological and market-related changes. Our consulting services are designed to help organizations identify hidden opportunities and understand prevailing competitive challenges.
Contact Us:
Fortune Business Insights Pvt. Ltd. 308, Supreme Headquarters, Survey No. 36, Baner, Pune-Bangalore Highway, Pune - 411045, Maharashtra, India.Phone:US: +1-424-253-0390 UK: +44-2071-939123 APAC: +91-744-740-1245 Email: sales@fortunebusinessinsights.com Fortune Business Insights
LinkedIn| Twitter| Blogs
Press Release-https://www.fortunebusinessinsights.com/press-release/artificial-intelligence-ai-in-retail-market-9527
SOURCE Fortune Business Insights