Category Archives: Artificial Intelligence
Regulators Are Killing The Banking Industry. Artificial Intelligence Can Save It. – Government, Public Sector – United States – Mondaq News Alerts
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Money laundering is the oxygen that criminal networks breathe tosurvive. And in doing so, they'll creatively bypass regulatorybarriers that are both watered down and arrive years-too-late. Theimplementation of the EU's 5th Money LaunderingDirective (5MLD) is the latest in a global march of regulatoryguidelines that attempt to play catch-up with increasingly adeptmoney launderers and the criminals they support. Since the GlobalFinancial Crisis, regulations like 5MLD attempt to tighten thenoose around money laundering funnels with stricter definitions ofclient risk and lowering the threshold for the application ofenhanced due diligence.
But for many financial institutions, providing a higher level ofinvestigation on their Clients is not a means to an end, but an endin itself, as long as it narrowly satisfies that compliancecheckbox of "doing more."
For some financial institutions, applying these checks, even inthe narrowest terms, can backfire easily, and waste key businessopportunities. Screening solutions are most commonly applied methodfor high risk clients, but offer little protection against bothfalse positives or black and white interpretations of whatconstitutes a risky hit.
For example, a legitimate businessman in South Africa can berejected by a bank because he was appointed by Malta as an honorarycouncil, thereby earning himself a profile on a risk database. Buta local municipal official in Taipei accused by local media ofaccepting bribes from construction companies can get away scot-freeunder those same checks, and put the financial institution atrisk.
It's no wonder that criminals of all shapes and sizes resortto sophisticated networks of front-men and shell companies to cleandirty money, beating out the screening processes they know will beused by banks and other financial institutions on the beneficiariesof new accounts.
Take the whopping 200 billion-plus money laundering scandal thatcontinues to rock Europe's Nordic banks. There, dirty cash fromRussia found its way into the EU's most reputable bankinginstitutions via a handful of insider bank employees and severaldozen front-men.
Eventually, it took investigative journalists and lawenforcement in numerous countries to detect these schemes. In doingso, they demonstrated a dangerous paradigm; that today, we expectbankers and other financial professionals to carry outlaw-enforcement level investigations to shield against dirty cash,but have few answers for how they are supposed to get the trainingand tools to do so all in a manner that doesn't changetheir pro-business DNA.
By implementing Artificial Intelligence and other newtechnologies, it's up to the private sector to providepractical solutions that translate crude regulatory directives intoactionable defensive measures, while remaining sensitive to thecommercial goals of those using them.
According to numerous surveys, and circulars put out byregulators themselves, static screening databases are no longersufficient, as money launderers are able to easily bypass them,while powerful, corrupt businessmen and politicians use legalaction to simply remove themselves from these lists. To properlyidentify risk in today's world, huge amounts of data must beretrieved and analyzed from local news, social media, corporateregistries found in the "deep" web of sources not indexedby Google and other search engines even the dark net.
Even the most cunning investigators cannot possibly processthese huge amounts of data, even if they know where to find it. Butby deploying artificial intelligence to detect negative sentiments,analyze networks, and identify anomalies, researchers at financialinstitutions can focus on matching the intelligence insights theyreceive with their own risk policies.
Failure to adapt and implement artificial intelligence in aworld where clients look for the fastest, smoothest onboardingprocess will result in loss of business to the competition, greaterrisk in clients being accepted, or both.
Governments and regulators shouldn't reinvent the wheel, butin each jurisdiction they should actively promote and encourage thedevelopment of artificial intelligence in the financial sector. IfFinancial Institutions are going to be placed on the front lines inthe fight against money laundering, they should have the righttools to win.
Daniel Nisman is the Head of Financial InvestigationsSolutions at Cobwebs Technologies. He is a career financial crimeintelligence analyst and AML specialist.
The content of this article is intended to provide a generalguide to the subject matter. Specialist advice should be soughtabout your specific circumstances.
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Regulators Are Killing The Banking Industry. Artificial Intelligence Can Save It. - Government, Public Sector - United States - Mondaq News Alerts
Cleveland Clinic’s Center for Clinical Artificial Intelligence looks for real answers in the future of health care – Crain’s Cleveland Business
The Museum of Contemporary Art Cleveland and Jo-Ann Stores Inc. are teaming up for a series of interactive activities around moCa's current exhibition, "Margaret Kilgallen: that's where the beauty is." (Hudson-based Jo-Ann is the lead sponsor of the show, which moCa says "evokes the vitality of American street and folk life, as well as vintage signage and typography.) On Saturday, Feb. 29, and on two other Saturdays, March 7 and 21, from noon to 4 p.m., guests can design and print their own T-shirts. On April 4 and May 2, Jo-Ann facilitators will lead tutorials featuring one of Kilgallen's passions, handlettering. Through May, moCa said, the museum's first floor will be home to an interactive installation "in which visitors are invited into a unique Art Stories booth, where they are prompted to record stories of items they would create with their hands, hearts and minds for loved ones." The activities will culminate on May 16, with artmaking opportunities throughout the day.
Bloomberg reports that the Senate could vote next week on a piece of legislation that "aims to boost energy storage technology as well as nuclear and renewable power," and includes a measure from U.S. Sen. Rob Portman, R-Cincinnati. The bill, unveiled Thursday, Feb. 27,"represents the latest Republican approach of promoting clean energy while steering clear of mandates to cut emissions of climate-warming gases or stop fossil fuel development on public lands," the news service reports. It "seeks to spur carbon capture, grid modernization and security and also includes a measure championed by Susan Collins of Maine ... that would fund an Energy Department research program to reduce the cost of grid-scale energy storage. The technology could transform the wind and solar industries by allowing, for example, solar power made during the day to be used at night," according to the article. Bloomberg says the bill also includes "a long-stalled measure" from Portman "that would increase energy efficiency in residential and federal buildings and a separate measure aimed at helping the development of new nuclear reactor technology."
It's a busy week for Portman, who also has an op-ed piece in Barron's with Sen. Ben Cardin, D-Maryland, that highlights what they call "the next big legislative step forward to ensure hard-working Americans achieve a safe and secure retirement." They write that the Retirement Security & Savings Act "includes a broad set of reforms designed to strengthen Americans' retirement security by addressing four major opportunities in the existing retirement system: (1) allowing people who have saved too little to set more aside for their retirement; (2) helping small businesses offer 401(k)s and other retirement plans; (3) expanding access to retirement savings plans for low-income Americans without coverage; and (4) providing more certainty and flexibility during Americans' retirement years." Portman and Cardin argue that the measure "will build upon the success of the SECURE Act legislation to strengthen our private retirement system and help more Americans save for their retirement which was signed into law late last year."
The Wall Street Journal runs a letter from an emeritus professor at Case Western Reserve University that takes issue with former Republican National Committee chairman Michael Steele's defense of the National Popular Vote Interstate Compact. From Erik M. Jensen's letter: Under the compact, signatory states would have to allocate their electoral votes to the candidate who wins a plurality (not a majority) of the national popular vote. Even so, the compact is a recipe for disaster. Compact supporters seem to assume that presidential races will continue to be dominated by two candidates, one of whom will get, if not a popular majority, at least a plurality above 40% thus showing some national support. But the Electoral College, as it now works (with a winner-take-all system in all but two states), is one reason we've had two dominant parties. If the national popular vote controls the outcome, we can expect several candidates with a chance of winning to be on the November ballot. We could have a "winner" with only, say, 30% (and maybe even less) of the popular vote, and he or she could be someone unacceptable to the rest of the electorate. That's crazy. It's like being declared the "winner" of a presidential primary with 25% of the vote. Jensen concludes, "Another problem with the compact is that when the popular vote is close, a national recount would be necessary. With the Electoral College, recounts are typically required in at most a few states; the college generally provides a clear winner. With the compact, however, the ballots in every precinct in the country would require rechecking. Does Mr. Steele really want Bush v. Gore on steroids?"
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ECSL Practitioners’ Forum on Artificial Intelligence and the Space Sector: Legal And Regulatory Aspects – SpaceWatch.Global
The European Centre for Space Law (ECSL) has been organising a one-day Practitioners Forum every year since 1992. The aim of the Forum is to provide those working across all areas of the space sector an opportunity to network and discuss topical areas of space law and policy relevant to the sector.
The next Practitioners Forum will take place at ESA ESOC in Darmstadt, Germany on 23 of April 2020, and will gather high-level experts to address Artificial Intelligence and the Space Sector: legal and regulatory aspects.
The programme of the event is available here.
Registration is open until the 10th of April and limited to 100 participants. To register, please click here.
ABOUT THE EUROPEAN CENTRE FOR SPACE LAW (ESCL)
The European Centre for Space Law (ESCL) was established in 1989 under the auspices of the European Space Agency (ESA) and with the support of a number of pioneers in this field.
Current members of the ECSL include professionals working in a wide range of areas within the space sector, lawyers, university professors and students.
Among other things, one of the main objectives of the Centre is to provide a forum for all those wishing to participate in constructive dialogue related to space law and space policy, and to encourage interdisciplinary exchange among members.
ESCL members include professionals working in different areas within the space sector. Citizens of ESA Member States or countries with cooperative agreements with ESA can become members of ECSL upon payment of a small annual fee.
Membership gives the right to participate in ECSL activities, to vote at the General Meeting of Members and to receive certain ECSL publications.
Josh Swamidass on Artificial Intelligence at the University of Washington – Discovery Institute
Josh Swamidass is the Washington University computational biologist and intelligent design critic who debated with biochemist Michael Behe last week at Texas A&M. Their exchange is now up on YouTube. Jonathan Witt reported on the contents here.
Dr. Swamidass then headed to Seattle where he spoke last night at the University of Washington on Human Identity and the Meaning of Artificial Intelligence: A Conversation with a Secular Humanist and a Scientist Christian. It was good to see Josh in the flesh. The sponsor, Veritas Forum, is a Christian group that says it is committed to courageous conversations. We place the historic Christian faith in dialogue with other beliefs and invite participants from all backgrounds to pursue Truth together.
I have to admit the event was kind of dull compared with the Behe debate. But Josh gave a nice presentation with AI/consciousness basics about Alan Turing, John Searles Chinese Room, etc. The most interesting thing I heard was his passing mention of Alfred Wallace, co-founder with Charles Darwin of the theory of evolution by natural selection, and Wallaces Doubt about whether human consciousness could have evolved in a Darwinian manner. Actually, this is a question on which Wallace broke with Darwin, becoming arguably a forerunner of ID.
For the discussion, Josh was then paired with a law professor who seemed totalka lot without saying quite as much. To join in the courageous conversation, you could submit questions through a website. I asked, under my first name only, Where do you think Alfred Russel Wallaces doubt about the unguided evolution of human consciousness stands today? Sounds a bit like intelligent design.
I didnt stay till the end but when I left I counted 30 approved questions in the queue while a lone question languished, unapproved to be asked and still Waiting for review. Guess which one?
[I updated this post for clarity and because I may have been a little hard on the law professor. DK]
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Josh Swamidass on Artificial Intelligence at the University of Washington - Discovery Institute
Computer Scientist Develops the Art of Artificial Intelligence – University of Texas at Dallas
Dr. Kang Zhang
It took years for Pablo Picasso to perfect his style. Now, a University of Texas at Dallas computer science professor is developing algorithms to generate unique images that mimic the cubist pioneers paintings in seconds.
Dr. Kang Zhang uses artificial intelligence (AI) to teach computers to create illustrations in the style of the famous masters: Jackson Pollock and his paint splatters or Joan Mir and his curved shapes and sharp lines. The process involves feeding computers examples of colors, abstract shapes and layouts so they can learn to produce their own versions of masterpieces.
Zhang, a professor of computer science and director of the Visual Computing Lab in the Erik Jonsson School of Engineering and Computer Science, uses computer science to study fine art and he uses fine art to find ways to make better computer visuals.
He recently returned from the Czech Republic, where he spent last fall lecturing and conducting research at Charles University in Prague as a Fulbright Distinguished Chair. Zhang also traveled to Poland, Germany and Serbia to give presentations on his project, Design and Experiment of Multi-Dimensional Information Visualization and Aesthetic Representations.
The computer can be a tool to develop beautiful and user-friendly designs for just about everything we see on our screens, Zhang said. The goal is to have art and design help computing. User interfaces, for example, are supposed to be friendly and beautiful, but they are often created by computer scientists with only function in mind.
Zhang used deep learning and image processing techniques to transform photographs into Picassos cubist style.
Zhang, who has written textbooks on the subject and lectured across the globe, is an expert in computational aesthetics, a subfield of AI that involves applying mathematical formulas to represent and analyze aesthetic features. He said the technology can help software and web developers produce better computer-generated graphics, user interfaces and visualizations of big data.
Generating visuals in the style of abstract artists involves an AI function called deep learning, which teaches the machine to process information and recognize patterns the way a human brain does and perform tasks without explicit instructions.
Zhangs process involves splicing images, building computer models of irregular shapes, encoding the designs and writing algorithms to let the computer take over and weave the colors, layouts and shapes into new creations. For example, he and his colleagues and students have published articles in the journal The Visual Computer describing how they transformed portraits into Picassos cubist style and modeled Pollocks dripping style of painting. They have also delivered conference presentations detailing a method for generating Mirs surrealism.
The Fulbright Distinguished Chairs Program comprises approximately 40 distinguished lecturing, distinguished research and distinguished lecturing/research awards ranging from three to 12 months. Awards in the Fulbright Distinguished Chairs Program are viewed as among the most prestigious appointments in the Fulbright Scholar Program. Candidates should be eminent scholars and have a significant publication and teaching record. Learn how to apply.
In addition to generating better visuals, computational aesthetics increasingly is being used to analyze art in new ways. For example, Zhangs study in the April 2019 edition of the journal Leonardo examined the white space in artist Wu Guanzhongs paintings. Leaving white space by not painting over the white rice paper is typical in Chinese painting. When Zhang and the studys co-authors collected data on viewers eye movements and asked viewers to rate the artwork based on various features, the researchers found that the white space in Wus work had a significant effect on viewers aesthetic experiences.
Zhang developed a passion for art while growing up in China and has won awards for his oil paintings and Chinese calligraphy. Throughout his career, he has incorporated art into his research, which, he emphasized, explores how computers can serve as tools not replacements for creativity.
Computer science will not replace artists and designers, Zhang said. Rather, it can help both groups extend their imaginations and capability in making creative works.
University of Texas at Dallas alumna Caryn Voskuil MA96, PhD00 spent two weeks last fall in France as part of the Fulbright U.S. Scholar Program.
Voskuil, associate dean of humanities, fine and performing arts at Richland College in Dallas, was part of a group of 12 college administrators who traveled to France to see firsthand how international education is managed.
Caryn Voskuil MA96, PhD00
I felt as if I had taken an entire course in two weeks, she said. Frances attitude toward education is very inclusive; anyone who earns a baccalaureate degree there is promised a place at a university or in higher education. Its quite different from the way we do it, but its really a wonderful system.
Voskuils travel grant was part of the Fulbright International Education Administrators program. Recipients are chosen based on academic and professional achievement, as well as a record of service and demonstrated leadership in their particular fields.
After earning her doctoral degree from UT Dallas, Voskuil served in education roles in a number of developing and post-conflict countries, including Afghanistan, Cambodia and Bosnia-Herzegovina. She began her appointment at Richland in 2015.
Voskuil said it is important for educators, as well as students, to learn from each other.
Global learning and cross-cultural understanding are very important for student success in the workplace and for the success of our country and our world. Unfortunately, most people from developing countries or post-conflict countries cant really afford to go abroad and only about 1% of American students actually study abroad, she said. So to really encourage diversity and a global perspective, we need to find better ways to make international education available to everyone.
Phil Roth
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Computer Scientist Develops the Art of Artificial Intelligence - University of Texas at Dallas
Artificial intelligence | MIT News
Weathers a problem for autonomous cars. MITs new system shows promise by using ground-penetrating radar instead of cameras or lasers.
Tech-based solutions sought for challenges in work environments, education for girls and women, maternal and newborn health, and sustainable food.
MIT duo uses music, videos, and real-world examples to teach students the foundations of artificial intelligence.
PatternEx merges human and machine expertise to spot and respond to hacks.
In a Starr Forum talk, Luis Videgaray, director of MITs AI Policy for the World Project, outlines key facets of regulating new technologies.
A deep-learning model identifies a powerful new drug that can kill many species of antibiotic-resistant bacteria.
MIT graduate student is assessing the impacts of artificial intelligence on military power, with a focus on the US and China.
The mission of SENSE.nano is to foster the development and use of novel sensors, sensing systems, and sensing solutions.
By organizing performance data and predicting problems, Tagup helps energy companies keep their equipment running.
Researchers develop a more robust machine-vision architecture by studying how human vision responds to changing viewpoints of objects.
Three-day hackathon explores methods for making artificial intelligence faster and more sustainable.
MITs new system TextFooler can trick the types of natural-language-processing systems that Google uses to help power its search results, including audio for Google Home.
Starting with higher-value niche markets and then expanding could help perovskite-based solar panels become competitive with silicon.
With the initial organizational structure in place, the MIT Schwarzman College of Computing moves forward with implementation.
Doctoral candidate Natalie Lao wants to show that anyone can learn to use AI to make a better world.
Device developed within the Department of Civil and Environmental Engineering has the potential to replace damaged organs with lab-grown ones.
Computer scientists new method could help doctors avoid ineffective or unnecessarily risky treatments.
Model tags road features based on satellite images, to improve GPS navigation in places with limited map data.
A new method determines whether circuits are accurately executing complex operations that classical computers cant tackle.
MIT researchers and collaborators have developed an open-source curriculum to teach young students about ethics and artificial intelligence.
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Artificial intelligence | MIT News
32 Artificial Intelligence Companies You Should Know | Built In
From Google and Amazon to Apple and Microsoft, every major tech companyis dedicating resources to breakthroughs in artificial intelligence. Personal assistants like Siri and Alexa have made AI a part of our daily lives. Meanwhile, revolutionary breakthroughs like self-driving cars may not be the norm, but are certainly within reach.
As the big guys scramble to infuse their products with artificial intelligence, other companies are hard at work developing their own intelligent technology and services. Here are 32artificial intelligence companies and AI startupsyou may not know today, but you will tomorrow.
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See all jobs at top tech companies & startups
Industry: Healthtech, Biotech, Big Data
Location: Chicago, Illinois
What it does: Tempus uses AI to gather and analyze massive pools of medical and clinical data at scale. The company, with the assistance of AI, provides precision medicine that personalizes and optimizes treatments to each individuals specific health needs; relying on everything from genetic makeup to past medical history to diagnose and treat. Tempus is currently focusing on using AI to create breakthroughs in cancer research.
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Industry: Big Data, Software
Location: Boston, Massachusetts
What itdoes:DataRobot provides data scientists with a platform for building and deploying machine learning models. The softwarehelps companies solve challenges by finding the best predictive model for their data. DataRobot's techis used inhealthcare, fintech, insurance, manufacturing and even sports analytics.
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Industry: Big Data, Software
Location: Chicago, Illinois
What itdoes:Narrative Science creates natural language generation (NLG) technology that can translatedata into stories. By highlightingonly the most relevant and interesting information, businesses canmake quicker decisions regardless of the staff's experience with data or analytics.
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Industry: Fintech
Location: New York, New York
What itdoes:AlphaSense is an AI-powered search engine designed to helpinvestment firms, banks and Fortune 500 companies find important information within transcripts, filings, news and research.The technologyuses artificial intelligencetoexpandkeyword searches for relevant content.
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Industry: Software
Location: New York, New York
What itdoes:Clarifai is an image recognition platform that helps users organize, curate, filter and search their media. Within the platform, images and videos are tagged, teachingthe intelligent technology to learn which objects are displayed in a piece of media.
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Industry: Machine Learning, Software
Location: Boston, Massachusetts
What itdoes:Neurala is developing "The Neurala Brain," a deep learning neural network software that makesdevices like cameras, phones and drones smarter and easier to use. Neuralas solutions are currently usedon more than amillion devices. Additionally, companies and organizations like NASA, Huawei, Motorola and the Defense Advanced Research Projects Agency (DARPA) are also using the technology.
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Industry: Automotive, Transportation
Location: Boston, Massachusetts
What itdoes:With a mission to provide safe efficient driverless vehicles,nuTonomy is developing software thatpowers autonomous vehicles in cities around the world. The company uses AItocombinemapping, perception, motion planning, control and decision making into software designed toeliminate driver-error accidents.
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Industry: Adtech, Software
Location: New York, New York
What itdoes:Persado is a marketing language cloud that usesAI-generated language to craft advertising for targeted audiences. With functionality across all channels, Persado helps businessesincrease acquisitions, boost retention and buildbetter relationships with their customers.
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Industry: Machine Learning
Location: New York, New York
What itdoes:x.ai creates autonomous personal assistants powered by intelligent technology. The assistants, simply named Amy and Andrew Ingram, integrate with programs like Outlook, Google, Office 365 and Slack,schedule or update meetings, and continually learnfrom everyinteraction.
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Industry: Software, Cloud
Location: Austin, Texas
What itdoes:CognitiveScale builds augmented intelligence for thehealthcare, insurance, financial services and digital commerce industries. Its technology helpsbusinesses increase customer acquisition and engagement, while improving processes like billing and claims. CognitiveScales products are used by such heavy hitters asP&G, Exxon, JP Morgan & Chase, Macys and NBC.
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Industry: Biotech, Healthtech
Location: San Francisco, California
What itdoes:Freenome uses artificial intelligence to conduct innovative cancer screenings and diagnostic tests. Using non-invasive blood tests, the companys AI technology recognizes disease-associated patterns, providingearlier cancer detection and better treatment options.
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See all jobs at top tech companies & startups
Industry: Robotics
Location: Pleasanton, California
What itdoes:AEyebuilds the vision algorithms, software and hardware that ultimately become the eyes of autonomous vehicles. ItsLiDAR technology focuses on the most important information in a vehicles sightline such as people, other cars and animals, while putting less emphasis on things like the sky, buildings and surrounding vegetation.
Industry: Machine Learning, Robotics
Location: Menlo Park, California
What itdoes:AIBrainis working to create fully autonomous artificial intelligence. By fusingproblem solving, learning and memory technologies together, the company can build systems thatlearn and adapt without human assistance.
Industry: Agriculture, Robotics, Software
Location: Sunnyvale, California
What itdoes:Blue River Tech combines artificial intelligence and computer vision to build smarter farm tech. The companys See & Spray machine learning technology, for example, can detectindividual plants and applyherbicide to the weeds only. The solution not only prevents herbicide-resistant weeds but reduces 90% of the chemicalscurrently sprayed.
Industry: Software
Location: Oakland, California
What it does:Vidado can pulldata from virtually any channel, including handwritten documents, dramatically increasingpaper to digital workflow speeds and accuracy. The cloud-based platform is utilized by leading organizations and companies like New York Life, the FDA, Metlife and MassMutual.
Industry: Legal, Software
Location: San Francisco
What itdoes:Casetext is an AI-powered legal search engine with a database of more than10 million statutes, cases and regulations. Called CARA A.I., the company's techcan search within the language, jurisdiction and citations of a user's uploaded documents and return relevant searches from the database.
Industry: Cloud, Robotics
Location: Santa Clara, California
What itdoes:CloudMinds provides cloud robot services for the finance, healthcare, manufacturing, power utilities, public sector and enterprise mobility industries. Its cloud-based AI usesadvanced algorithms, large-scale neural networks and training data to make smarter robots for image and object recognition, natural language processing, speech recognition and more.
Industry: Software
Location: San Francisco, California
What itdoes:Figure EightprovidesAI training software to machine learning and data science teams. The company's"human-in-the-loop" platform uses human intelligence to train and test machine learning, and has powered AI projects for major companies like Oracle, Ebay SAP and Adobe.
Industry: Big Data, Software
Location: Mountain View, California
What itdoes:H2O.ai is the creator of H2O, an open source platform for data science and machine learning that is utilized by thousands of organizations worldwide. H2O.ai supplies companies in a variety of industries predictive analytics and machine learning tools thataidein solvingcriticalbusiness challenges.
Industry: Biotech
Location: Bethesda, Maryland
What itdoes:Insilico Medicine is using artificial intelligence for anti-aging and drug discovery research. The company'sdrug discovery engine contains millions of samples forfinding disease identifiers. Insilicois used byacademic institutions, pharmaceutical and cosmetic companies.
Industry: Software, Automotive
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32 Artificial Intelligence Companies You Should Know | Built In
Can Machines And Artificial Intelligence Be Creative? – Forbes
We know machines and artificial intelligence (AI) can be many things, but can they ever really be creative? When I interviewed Professor Marcus du Sautoy, the author of The Creativity Code, he shared that the role of AI is a kind of catalyst to push our human creativity. Its the machine and human collaboration that produces exciting resultsnovel approaches and combinations that likely wouldnt develop if either were working alone.
Can Machines And Artificial Intelligence Be Creative?
Instead of thinking about AI as replacing human creativity, it's beneficial to examine ways that AI can be used as a tool to augment human creativity. Here are several examples of how AI boosts the creativity of humans in art, music, dance, design, recipe building, and publishing.
Art
In the world of visual art, AI is making an impact in many ways. It can alter existing art such as the case when it made the Mona Lisa a living portrait a la Harry Potter, create likenesses that appear to be real humans that can be found on the website ThisPersonDoesNotExist.com and even create original works of art.
When Christies auctioned off a piece of AI artwork titled the Portrait of Edmond de Belamy for $432,500, it became the first auction house to do so. The AI algorithm, a generative adversarial network (GAN) developed by a Paris-based collective, that created the art, was fed a data set of 15,000 portraits covering six centuries to inform its creativity.
Another development that blurs the boundaries of what it means to be an artist is Ai-Da, the worlds first robot artist, who recently held her first solo exhibition. She is equipped with facial recognition technology and a robotic arm system thats powered by artificial intelligence.
More eccentric art is also a capability of artificial intelligence. Algorithms can read recipes and create images of what the final dish will look like. Dreamscope by Google uses traditional images of people, places and things and runs them through a series of filters. The output is truly original, albeit sometimes the stuff of nightmares.
Music
If AI can enhance creativity in visual art, can it do the same for musicians? David Cope has spent the last 30 years working on Experiments in Musical Intelligence or EMI. Cope is a traditional musician and composer but turned to computers to help get past composers block back in 1982. Since that time, his algorithms have produced numerous original compositions in a variety of genres as well as created Emily Howell, an AI that can compose music based on her own style rather than just replicate the styles of yesterdays composers.
In many cases, AI is a new collaborator for todays popular musicians. Sony's Flow Machine and IBM's Watson are just two of the tools music producers, YouTubers, and other artists are relying on to churn out today's hits. Alex Da Kid, a Grammy-nominated producer, used IBMs Watson to inform his creative process. The AI analyzed the "emotional temperature" of the time by scraping conversations, newspapers, and headlines over a five-year period. Then Alex used the analytics to determine the theme for his next single.
Another tool that embraces human and machine collaboration, AIVA bills itself as a creative assistant for creative people and uses AI and deep learning algorithms to help compose music.
In addition to composing music, artificial intelligence is transforming the music industry in a variety of ways from distribution to audio mastering and even creating virtual pop stars. An auxuman singer called Yona, developed by Iranian electronica composer Ash Koosha, creates and performs music such as the song Oblivious through AI algorithms.
Dance and Choreography
A powerful way dance choreographers have been able to break out of their regular patterns is to use artificial intelligence as a collaborator. Wayne McGregor, the award-winning British choreographer and director, is known for using technology in his work and is particularly fascinated by how AI could enhance what is done with the choreography in a project with Google Arts & Culture Lab. Hundreds of hours of video footage of dancers representing individual styles were fed into the algorithm. The AI then went to work and "learned how to dance. The goal is not to replace the choreographer but to efficiently iterate and develop different choreography options.
AI Augmented Design
Another creative endeavor AI is proving to be adept at is commercial design. In a collaboration between French designer Philippe Starck, Kartell, and Autodesk, a 3D software company, the first chair designed using artificial intelligence and put into production was presented at Milan Design Week. The Chair Project is another collaboration that explores co-creativity between people and machines.
Recipes
The creativity of AI is also transforming the kitchen not only by altering longstanding recipes but also creating entirely new food combinations in collaborations with some of the biggest names in the food industry. Our favorite libations might also get an AI makeover. You can now pre-order AI-developed whiskey. Brewmasters decisions are also being informed by artificial intelligence. MITs Computer Science and Artificial Intelligence Laboratory (CSAIL) is making use of all those photos of the food that we post on social media. By using computer vision, these food photos are being analyzed to better understand peoples eating habits as well as to suggest recipes with the food that is pictured.
Write Novels and Articles
Even though the amount of written material to inform artificial intelligence algorithms is voluminous, writing has been a challenging skill for AI to acquire. Although AI has been most successful in generating short-form formulaic content such as journalism "who, what, where, and when stories," its skills continue to grow. AI has now written a novel, and although neural networks created what many might find a weird read, it was still able to do it. And, with the announcement a Japanese AI programs short-form novel almost won a national literary prize, its easy to see how it wont be long before AI can compete with humans to write compelling pieces of content. Kopan Page published Superhuman Innovation, a book not only about artificial intelligence but was co-written by AI. PoemPortraits is another example of AI and human collaboration where you can provide the algorithm with a single word that it will use to generate a short poem.
As the world of AI and human creativity continue to expand, its time to stop worrying about if AI can be creative, but how the human and machine world can intersect for creative collaborations that have never been dreamt of before.
You can watch the full interview with Marcus du Sautoy here:
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Can Machines And Artificial Intelligence Be Creative? - Forbes
Parasoft introduces Artificial Intelligence (AI) and Machine Learning (ML) into Software Test Automation for the Safety-critical Market at Embedded…
Parasoft C/C++test's new functionality offers teams the ability to link test cases to requirements and code coverage enhancements, improving productivity instantly
MONROVIA, Calif. andNUREMBERG, Germany, Feb. 27, 2020 /PRNewswire/ -- Parasoft, the global automated software testing authority since 1987,announced todayat Embedded World, thenew release ofParasoftC/C++test, aunified C and C++ development testing solution forreal-time safety- and security-criticalembedded applicationsand enterprise IT.With this new release,Parasoftappliesa new approachtoexpeditesoftware code analysis findings andincreasetheproductivity ofautomatedsoftware testing, allowing teams to achieveindustrycompliance standardseasily.
To learn more aboutParasoftC/C++test, visit:https://www.parasoft.com/products/ctest.
"With the new release of C/C++test,we are bringing unique AIandMLcapabilities to help organizations with the adoption of static analysis forsecure safety-critical applicationsdevelopment.With these innovations, organizations can immediately reduce manual effort in their software quality processes,"statedMiroslawZielinski,ParasoftProduct Manager."Organization serious intheirapproach to safety, security, and quality of software, will soon need to include AI-based tools into their development process to keep pace with competition and stay relevantinthe market. This is only our first step in the application of AIandML to the safety-critical market."
Embedded devicesarecomplex,and with increasingsafety and securityconcerns, it is crucial that automated software testing solutions stay up to date on the ever-expanding compliance standards.Hence,Parasoftcontinues to leadtheenforcementof the latestguidelines.Additionally, withindustry-standard prerequisites toestablishtraceability of software requirements to test cases,Parasofthas built integrations with some of the most popular application lifecycle management(ALM)solutions.The integrationsestablishtraceabilityfromsoftware requirements to test cases.
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"The market for functional safety (FuSa)Testtoolssales will grow at the quickest CAGR of 9.3% to reach $539.6M in revenue in 2023. The need to establish bi-directional traceability to meet FUSA certification requirements is fueling interest in using integrated application lifecycle management (ALM)and product lifecycle management (PLM) solutions to manage the entire product development process,"states Chris Rommel, EVP,VDC ResearchGroup.
What's new?
Aninnovativetechnique forincreasingstructural coverage fromunittestingthroughadvanced code analysis for C/C++ and Java. This now significantly reduces the burden of testing efforts required by standards such as ISO 26262 (Automotive), DO-178B/C(Aerospace), IEC 62304 (Medical Devices) and IEC 61508 (Functional Safety)
Parasoftleaps forward beyond the rest of the market, withaunique application of AI/Machine Learning to help organizations with the adoption of Static Analysis. Parasoft'sAI-solution reviews new static analysis findings in the context of both historical interactions with the code base and prior static analysis findings to predict relevance and prioritize the new findings.
Parasoftcontinues to provide leading support for automated enforcement of industry coding guidelines with expanded coverage for updated security standards (e.g. the 2019 CWE Top 25 and 'on the cusp'),AUTOSARC++14 and the new MISRA C 2012 Amendment2, ensuringParasoft'stools continue to meet the changing needs of the industry by keeping pace with guideline requirements.
Parasoftannounces new integrations withPolarion,codeBeamer,andJira, for enhanced requirements traceability. The bi-directional data exchange bridges the gap between requirements and the tests that validate them, to offer full traceability down to the code being developed, helping fulfill compliance to developing process standards such as ISO 26262 (Automotive), DO-178B/C(Aerospace), IEC 62304 (Medical Devices) and IEC 61508 (Functional Safety).
AboutParasoft
Parasoft, the global automated software testing authorityfor over 30+ years,provides innovative tools that automate time-consuming testing tasks and provide management with intelligent analytics necessary to focus on what matters.Parasoftsupports software organizations as they develop and deploy applicationsforthe embedded, enterprise, and IoT markets.Parasoft'stechnologies reduce the time, effort, and cost of delivering secure, reliable, and compliant software, by integrating static and runtime analysis; unit, functional, and API testing; and service virtualization.Withourdeveloper testing tools, manager reporting/analytics, and executivedashboarding,Parasoftenables organizations to succeed in today's most strategicecosystems anddevelopment initiatives real-time, safety-critical, secure,agile, continuous testing,andDevOps.www.parasoft.com; https://www.parasoft.com/products/ctest
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Parasoft introduces Artificial Intelligence (AI) and Machine Learning (ML) into Software Test Automation for the Safety-critical Market at Embedded...
Artificial Intelligence Crowdsourcing Competition for Injury Surveillance – EC&M
By Sydney Webb, PhD; Carlos Siordia, PhD; Stephen Bertke, PhD; Diana Bartlett, MPH, MPP; and Dan Reitz
In 2018, NIOSH, the Bureau of Labor Statistics (BLS), and the Occupational Safety and Health Administration (OSHA) contracted the National Academies of Science (NAS) to conduct a consensus study on improving the cost-effectiveness and coordination of occupational safety and health (OSH) surveillance systems. NASs report recommended that the federal government use recent advancements in machine learning and artificial intelligence (AI) to automate the processing of data in OSH surveillance systems.
The main source of OSH information on fatal and non-fatal workplace incidents comes from the unstructured free-text injury narratives recorded in surveillance systems. For example, an employer may report an injury as worker fell from the ladder after reaching out for a box. For decades, humans have read these injury narratives to assign standardized codes using the U.S. Bureau of Labor Statistics (BLS) Occupational Injury and Illness Classification System (OIICS). Coding these injury narratives to analyze data is expensive, time consuming, and fraught with coding errors.
AI, namely machine learning text classification, offers a solution to this problem. If algorithms can be developed to read the injury narratives, data can be pulled from these surveillance systems in a fraction of the time of hand coding.
NIOSH developed an AI algorithm to apply OIICS codes based on injury narratives from a hospital emergency department surveillance system. However, the efficiency of this algorithm was not clear. To see if better coding algorithms could be developed, NIOSH turned to crowdsourcing.
While not unique to AI, crowdsourcing involves asking the crowd or people in the public with a variety of skill sets to provide their unique solution to a problem. The approach results in a large number of potential solutions that can be assessed to identify those that work best. Generally, the best crowd solutions are better than the original solution. In this case, NIOSH worked with two crowds one internal to CDC and one external to CDC to propose better solutions to NIOSHs initial coding algorithm.
Courtesy of NIOSH
Before conducting an external competition, a team of 17 researchers from NIOSH, the Centers for Disease Control and Prevention (CDC), BLS, OSHA, the Federal Emergency Management Administration (FEMA), the Census Bureau, the National Institutes of Health (NIH)7, and the Consumer Products Safety Commission hosted a competition for staff at CDC. A total of 19 employees competed to develop the best algorithm to code worker injury narratives. The team received nine algorithms, five of which outperformed the NIOSH baseline script, which had an accuracy of 81%. The internal crowdsourcing competition winning algorithm was 87% a 6% improvement.
In October 2019, NIOSH, together with National Aeronautics and Space Administration (NASA), hired a Tournament Lab vendor, Topcoder, to host the external crowdsourcing competition. This was the first-ever external crowdsourcing competition from CDC and NIOSH, which was partially funded through the CDC Innovation Fund Challenge. The competition accessed Topcoders global community of data science experts to develop a Natural Language Processing (NLP) algorithm to classify occupational work-related injury records according to OIICS.
Like the internal competition, the external competition was also a success. There were 961 submissions from 388 registrants representing over 26 countries (32% United States, 21% India). Those participating self-identified as having degrees in computer science and engineering, chemistry, computer engineering, computer science, data science, and economics to name a few. This competition produced 21% more registrants and 66% more submissions than the average Topcoder competition. The high-quality submissions achieved nearly 90% accuracy, which surpassed the 87% accuracy goal achieved during the internal competition.
The 1st place external crowdsource winner was Raymond van Veneti, who is a doctoral student in numerical mathematics at the University of Amsterdam. Second place was awarded to a senior data scientist at Sherbank AI lab in Russia; 3rd place was awarded to a developer and data scientist from China; 4th place was awarded to a biostatistician at the School of Medicine at Emory University in Atlanta, GA; and 5th place was awarded to a full stack engineer from Bangalore, India.
External crowdsource 1st place winner Raymond van Veneti.Courtesy of NIOSH
The external competition and the resulting algorithm support improving efficiency and reducing costs associated with coding occupational safety and health surveillance data. Ultimately, it is hoped that the improved algorithm will contribute to greater worker safety and health. The NIOSH project team will work with the 1st prize winners script to make an easy-to-use web tool for public use. In the interim, the top 5 winning solutions are available on GitHub.
For more information, visit https://blogs.cdc.gov.
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Artificial Intelligence Crowdsourcing Competition for Injury Surveillance - EC&M