Take the latest VB Survey to share how your company is implementing AI today.

To say that the speed of technological change in AI is fast-firing is an understatement. As engineers and data scientists unlock more of the potential of AI and machine learning, ever-more innovative solutions continue to advance the goals of business leaders.

At Transform 2020 next week, youll have a chance to see those solutions for yourself. Transform 2020 Expo (July 15-17) will showcase some of the most cutting edge AI companies, from large tech giants like Intel and Dell to some of the most innovative growth companies and startups like Dataiku, Cloudera, and Modzy.

This means youll be able to get an up-close look at some of the most advanced solutions spanning AI security, automation, conversational AI, explainable AI, training data, as well as solutions for specialized areas, such as customer experience, and specific industries, such as wealth management.

Each exhibitor will host a virtual expo booth, where you can interact, engage in live Q&A and chat, as well as book private meetings in order to have more in-depth discussions about your needs and how they can be met.

Once the event begins, just click on the Expo Booths icon in the menu displayed on the event platform. From there, youll be able to earmark and select all those youd like to follow up with.

And if you happen to be a company thats disrupting the AI space? We may still be able to slip you in, if you get in touch asap. Just head to our registration page and select the Digital Expo Booth option.

This, combined with our special 1-1 meeting feature for business decision makers, will make Transform one of the best networking events of the year for business executives looking to implement AI.

See you there!

See the article here:

Visit the cutting edge in AI: Transform 2020 Expo (July 15-17) - VentureBeat

The University of PennsylvaniasWharton Schoolof Business June 30 announced the establishment of WhartonAI for Business, an initiative led by AI expert and Wharton professor Kartik Hosanagar.

The initiative boasts that it will inspire cutting-edge teaching and research in artificial intelligence, while joining with global business leaders to set a course for better understanding of this nascent discipline.

The advances made possible by artificial intelligence hold the potential to vastly improve lives and business processes, outgoing Wharton DeanGeoff Garrett in a statement. Our students, faculty, and industry partners are eager to join in our AI knowledge creation efforts to more deeply explore how machine learning will impact the future for everyone.

Operating withinAnalytics at Whartonand led by Hosanagar, the John C. Hower Professor of Operations, Information and Decisions, AI for Business will explore artificial intelligences applications and impact across industries, the university notes.

Hosanagar is renowned for his AI research and instruction. He is the author of the book, A Humans Guide to Machine Intelligence: How Algorithms Are Shaping Our Lives and How We Can Stay in Control, and created the first Wharton online courses on AI, Artificial Intelligence for Business.

The Indian American entrepreneur has also founded or advised numerous startups in online marketing and retail, including Yodle and Milo, it said.

Our students and professors are energized by the idea that AI is influencing nearly every aspect of humanity, and our efforts to understand it can make a difference for years to come, he said in the university report.

Im very excited to help lead AI for Business since the future of machine learning is happening nowthere are unlimited entry points for experiential learning to explore the topic, the professor added.

The launch of AI for Business is made possible by a $5 million gift from Tao Zhang and his wife Selina Chin, the Wharton alumni couple who founded the food delivery app Dianping and run the Singapore-based Blue Hill Foundation.

Earlier this year, Hosanagar launched one of the leading online courses in the AI space, the highly popular Artificial Intelligence for Business, offered by Wharton Online, according to the university.

Hosanagar spoke tothe university media outlet, Penn Today,about what he sees happening with AI in business, especially in light of the coronavirus pandemic.

He noted that AI for Business will support students, faculty and industry.

The professor said in the report that real gains in AI lie in using it for high-risk opportunities that revolve around customer satisfaction or other revenue generating activities.

Also, what separates the AI projects that succeed from the ones that dont often has to do with the business strategies organizations follow when applying AI, he said.

Streaming platforms such as Netflix and other entertainment companies face a dilemma because social distancing has disrupted their content creation pipelines, he noted.

When asked how students will benefit from AI for Business, Hosanagar said that, in addition to having access to new AI-focused courses, students will be able to apply classroom learning to real life business challenges through an analytics accelerator project, AI focused datathon, Whartons Venture Lab Business Challenge, Industry speaker series, and AI focused business treks.

As for the future of AI, he said, The future is very bright, including innovative methods for data collection, content creation, and large-scale automation that are opening new opportunities for business with the use of AI applications.

Excerpt from:

Wharton School's Kartik Hosanagar Launches AI for Business Initiative - India West

Add to favorites

You can use API, CLI, or Console

AWS has released a new tool that allows customers of its AI services to more easily stop sharing their datasets with Amazon for product improvement purposes: something that is currently a default opt-in for many AWS AI services.

Until this week, AWS users had to actively raise a support ticket to opt-out of content sharing. (The default opt-in can see AWS take customers AI workload datasets and store them for its own product development purposes, including outside of the region that end-users had explicitly selected for their own use.)

AWS AI services affected include facial recognition service Amazon Rekognition, voice recording transcription service Amazon Transcribe, natural language processing service Amazon Comprehend and more, listed below.

(AWS users can otherwise choose where data and workloads reside; something that is vital for many for compliance and data sovereignty reasons).

Opting in to sharing is still the default setting for customers: something that appears to have surprised many, as Computer Business Review reported this week.

The company has, however, now updated its opt-out options to make it easier for customers to set opting out as a group-wide policy.

Users can do this in the console, by API or command line.

Users will permission to run organizations:CreatePolicy

Console:

Command Line Interface (CLI) and API

Editors note: AWS has been keen to emphasise a difference between content and data following our initial report, asking us to correct our claim that AI customer data was being shared by default with Amazon, including sometimes outside selected geographical regions. It is, arguably, a curious distinction. The company appears to want to emphasise that the opt-in is only for AI datasets, which it calls content.

(As one tech CEO puts it to us: Only a lawyer that never touched a computer might feel smart enough to venture into content, not data wonderland.)

AWSs own new opt-out page initially read disputed that characterisation.

It read: AWS artificial intelligence (AI) services collect and store data as part of operating and supporting the continuous improvement life cycle of each service.

As an AWS customer, you can choose to opt out of this process to ensure that your data is not persisted within AWS AI service data stores. [Our italics].

AWS has since changed the wording on this page to the more anodyne: You can choose to opt out of having your content stored or used for service improvements and asked us to reflect this.For AWSs full new guide to creating, updating, and deleting AI services opt-out policies, meanwhile, see here.

Go here to see the original:

How to Stop Sharing Sensitive Content with AWS AI Services - Computer Business Review

The artificial intelligence community needs to begin developing the vocabulary to define and clearly explain the harms the technology can cause, in order to reign in abuses with facial biometrics, AI Now Institute Technology Fellow Deb Raji argues in a TWIML AI podcast.

The podcast on How External Auditing is Changing the Facial Recognition Landscape with Deb Raji, hosted by Sam Charrington, who asks about the genesis of the audits Raji and colleagues have performed of biometric facial recognition systems, industry response, and the ethical way forward.

Raji describes her journey through academia and an internship with Clarifaito taking up the cause of algorithmic bias and connecting with Joy Buolamwini after watching her TedTalk. The work Raji did with others in the community gained prominence with Gender Shades, and concepts that emerged from that and similar projects have been built into engineering practices at Google.

Facial recognition is characterized as very immature technology, which was exposed as not working by the Gender Shades study.

It really sort of stemmed from this desire toidentify the problem in a consistent way and communicate it in a consistent way, Raji says of the early work delineating the problem of demographic differentials in facial recognition.

Raji won an AI Innovation Award, along with Buolamwini and Timnit Gebru, for their work in 2019.

The problem was hardly understood at all when Raji first began bringing it up, and even know seems to be fully comprehended by few in the community, as Raji says is demonstrated by a recent Twitter argument between Yann Lecun and Gebru. Raji comments that the connection between research efforts like Lecuns and products should be very clear to him. Raji also pans his downplaying of what she calls procedural negligence by not including people of color in the testing.

Representation does not necessarily mean that the training dataset demographics mirror the society the model is being deployed in. Raji notes that if 10 percent of the people in a certain area have dark skin, then models used there need to be trained with enough images of people with dark skin to ensure that the model works for that 10 percent, which may be a much higher ratio.

Raji also talks during the podcast about how the results of the follow-up testing shows the need for targeted pressure to force companies to address the gaps in their demographic performance. The limits of auditing are also explored in the conversation.

The need to have information specific to implementations is discussed in the context of facial recognition for law enforcement uses, and suggests it should be taken off the market in the absence of that information.

Raji says that as some facial recognition systems have reduced or practically eliminated demographic disparities and other accuracy issues, the problem of its weaponization has become more pressing. She notes that people are careful with their fingerprint data much more than facial images. In addition to misuse by law enforcement, sometimes out of ignorance about the technology and sometimes deliberate, Raji says the weaponization of the technology in deployments like the Atlantic Plaza Towers in Brooklyn.

The bias issue exposes the complexity of the issue, and the myth that facial recognition is like magic, Raji suggests. While the necessary conversations are held, the technology should not be used, according to Raji. To make it safe, Raji suggests that technical standards like those supplied by NIST need to be supplemented with others that include considerations of ethics like those produced or discussed by ISO, IEEE, and the WEF.

Though Raji presents the problems she is concerned with as systematic, she acknowledges the benevolence of some facial recognition algorithms.

No-ones threatening your Snapchat filter, Raji states.

accuracy | AI | AI Now Institute | artificial intelligence | biometric identification | biometrics | biometrics research | ethics | facial recognition

View post:

Facial recognition needs auditing and ethics standards to be safe, AI Now bias critic argues - Biometric Update

BOSTON--(BUSINESS WIRE)--Avrio now provides recruiters the first fully automated end-to-end recruiting technology, leveraging AI to increase recruiter efficiency while eliminating non-strategic manual tasks. To Avrio Eftase! It means Tomorrow has Arrived! in Greek, and with this version, the world of tomorrow is here today for employers. The whole process takes minutes and hours, not days and weeks to get top candidates.

Now, employers have a fully-scalable AI recruiter that requires no upfront integrations, no messy data replication and no ATS tracking codes and source-of-hire reports to reconcile. You post a job on the system and get hires. You pay for hires, when you acquire a new employee.

The AI engine can find candidates via job postings and across resume databases, contact them directly, confirm both job skills and fit criteria and find a time that works for them to connect with a human decision maker. Avrio is pre-integrated with Nexxt to publish jobs across 50 career sites with access to a diversified talent network of more than 75 million candidates from the Nexxt database. Machine learning and semantic matching is used to drive efficiency throughout the entire process for candidates and for employers.

With Avrio, customers can take advantage of the HR Tech industrys first and only risk free business model to make their lives easier. Customers only pay for actual hires. There are no upfront user licenses, no lock-ins, no CPC, PPC, PPV or CPA to worry about. You pay to hire an employee.

Alex Knowles, Talent Manager at Copenhagen Capacity, an early Avrio customer said, Avrio is a proven solution, not just for employers but also talent attraction agencies looking to create growth in their cities. As the official organisation for investment promotion and economic development in Greater Copenhagen, we are excited to use the new capabilities to further our mission to recruit top talent from all across the world to work in Denmark.

Avrio has taken a very unique and innovative approach when it comes to AI for hiring, said Nikos Livadas, Vice President of Strategic Alliances at Nexxt. We are very excited to be partnering with Avrio to help create a compelling recipe for talent acquisition leaders, enabling them to increase candidate engagement while also decreasing time to hire. With Nexxts more than 27 million resumes and 75 million candidates fueling Avrios conversational AI sourcing and ranking platform we cant wait to see how this new offering exceeds customer expectations in todays challenging environment.

Job applicants have long been stymied by the black hole of hiring processes, said Javid Muhammedali, Head of Product at Avrio AI. A responsive, scalable AI recruiter that can review resumes, ask personalized questions, have a full conversation and answer candidates questions is a compelling solution given all the uncertainty in the hiring process. HR leaders can have peace of mind in being able to scale up when called upon, and yet have a consistent process.

Were excited to bring to market a revolutionary solution that accelerates hiring, said Nachi Junankar, CEO. Recruiters and managers face a massive increase in applicants with a smaller team. At the same time, applicants are looking for employers to be more responsive. Avrio ensures that the right candidate gets to the front of the line and that both recruiters and applicants get the speed and effectiveness they deserve.

About Avrio AI Inc.Avrio, a leader in AI for recruiting helps employers and staffing firms match, engage and hire top talent. To see how AI is making breakthrough changes in recruiting, visit https://www.goavrio.com or book a demo at https://www.goavrio.com/chatbot

See the article here:

Workers Can Be Hired Back by Employers Using a Fully Automated AI Recruiter From Avrio - Business Wire

Machine intelligence must go hand-in-hand with human wisdom, Alibaba Group founder Jack Ma said Thursday.

Speaking at the World Artificial Intelligence Conference, Ma said that humans should strive to better understand themselves and the Earth, especially in the face of a global crisis like the Covid-19 outbreak.

This pandemic has shown us how little we know about ourselves and how little we know about the Earth. Because we dont know ourselves, dont know the world we are living in, dont understand the Earth and dont know how to cherish and preserve the Earth, we have created many troubles and disasters, Ma said via video message. He added that, despite the resources, wealth, knowledge and technological prowess enjoyed by society today, human wisdom was still the key to addressing the worlds challenges and was needed to enhance communication and cooperation to find impactful and long-lasting solutions.

With the theme of Intelligent World, Indivisible Community, the three-day conference features presentations, keynote speeches and panel discussions with prominent global figures from the realm of science and technology, including Turing Award winners Yoshua Bengio and Andrew Yao, Director General of the United Nations Industrial Development Organization Li Yong and Tesla CEO Elon Musk.

In his speech during the opening ceremony, Ma said that while the technologies of the past improved our way of living, the technologies of today and tomorrow should help humankind survive better.

During the pandemic, people have used internet technology to survive, not just for themselves, but also for others, he said. There are many cases: going to school, having a meeting, shopping, visiting a doctor all of these activities rely on digital technology. To innovate in order to survive is the strongest and most irresistible force.

He also pointed to an AI algorithm that Alibabas research and innovation institute DAMO Academy developed to help diagnose Covid-19. Informed by data from thousands of computed-tomography scans and trained by deep learning, the algorithm can accurately detect the virus in 20 seconds, vastly shortening the time it takes for doctors to review CT scans, confirm cases and move on to treatment and supportive measures.

Ma said that such innovations were indicative of the quickening pace of digitalization in the world.

Technological transformation will come earlier and its speed will accelerate. We need to be ready, he said.

Sign up for our newsletterto receive the latest Alibaba updates in your inbox every week.

View original post here:

Jack Ma Calls for Wisdom and Innovation at World AI... - Alizila

The firms that sell AI tools to automate recruiting have started to work the pandemic into their pitches to prospective clients: As the economy tanks and the hiring process moves almost entirely online, AI recruiting tools offer a chance to save some money and make use of new troves of digital data on prospective candidates.

In fact, the field is expected to expand during the crisis and has been attracting new investment. Its not just automated resume-sifting: There are firms competing to automate every stage of the hiring process. And while the machines seldom make hiring decisions on their own, critics say their use can perpetuate discrimination and inequality.

AI firm Textio claims it can optimize every word of a job posting, using a machine learning model that correlates certain turns of phrase with better hiring outcomes. Companies hiring in California, for example, are advised to describe things as awesome to appeal to local job seekers, while New York employers are counseled to avoid the adjective.

Big name firms like LinkedIn and ZipRecruiter use matchmaking algorithms to comb through hundreds of millions of job postings to connect candidates with compatible companies. Smaller competitors, like GoArya, seek to differentiate themselves by scraping data from the internetincluding social media profilesto inform recruiting decisions.

Firms like Mya promise to automate the task of reaching out to candidates via email, text, WhatsApp, or Facebook Messenger, using natural language processing to have open-ended, natural, and dynamic conversations. The companys chatbots even conduct basic screening interviews, filtering out early-stage applicants who dont meet the employers qualifications. Other companies, like XOR and Paradox, sell chatbots designed to schedule interviews and field applicants questions.

Some AI vendorsincluding Ideal, CVViZ, Skillate, and SniperAIpromise to cut the drudgery of hiring by automatically comparing applicants resumes with those of current employees. Tools like these have faced criticism for recreating existing inequalities: Even if the algorithms are programmed to ignore traits like race or gender, they might learn from past hiring data to pick up on proxies for these traitsfor example, prioritizing candidates who played lacrosse or are named Jared. Amazon developed its own screener and quickly scrapped it in 2018 after finding it was biased against women.

Recruiting firm HireVue, which boasts 700 corporate clients including Hilton and Goldman Sachs, sells an AI tool that analyzes interviewees facial movements, word choice, and speaking voices to assign them an employability score. The platform is so ubiquitous in industries like finance and hospitality that some colleges have taken to coaching interviewees on how to speak and move to appeal to the platforms algorithms.

AI firm Humantic offers to understand every individual without spending your time or theirs by using AI to create psychological profiles of applicants based on the words they use in resumes, cover letters, LinkedIn profiles, and any other piece of text they submit.

Meanwhile, Pymetrics puts current and prospective employees through a series of 12 games to glean data about their personalities. Its algorithms use the data to to find applicants that fit company culture. In a 2017 presentation, a Pymetrics representative demonstrated a game that required users to react when a red circle appears, but do nothing when they see a green circle. That game was actually looking at your levels of impulsivity, it was looking at your attention span, and it was looking at how you learn from your mistakes, she told the crowd. Critics suggest the games might just measure which candidates are good at puzzles.

Read the original here:

AI hiring tools aim to automate every step of recruiting - Quartz

July 10, 2020Infervision announced U.S. Food and Drug Administration (FDA) 510(K) clearance of the InferRead Lung CT.AI product, which uses the state-of-the-art artificial intelligence and deep learning technology to automatically perform lung segmentation, along with accurately identifying and labeling nodules of different types. InferRead Lung CT.AI is designed to support concurrent reading and can aid radiologists in pulmonary nodule detection during the review of chest computed tomography (CT) scans, increasing accuracy and efficiency. With five years of international clinical use, Infervision's InferRead Lung CT.AI application is a robust and powerful tool to assist the radiologist.

InferRead Lung CT.AI is currently in use at over 380 hospitals and imaging centers globally. More than 55,000 cases daily are being processed by the system and over 19 million patients have already benefited from this advanced AI technology. "Fast, workflow friendly, and accurate are the three key areas we have emphasized during product development. We're very excited to be able to make our InferRead Lung CT.AI solution available to the North American market. Our clients tell us it has great potential to help provide improved outcomes for providers and patients alike," saidMatt Deng, Ph.D., Director of Infervision North America. The Company offers the system under a number of pricing models to make it easy to acquire.

The company predicts the system may also be of great benefit to lung cancer screening (LCS) programs across the nation. Lung cancer is the second most common cancer in both men and women in the U.S. Survival rates are 60% in five years if discovered at an early stage. However, the survival rate is lower than 10% if the disease progresses to later stages without timely follow-up and treatment. The Lung Cancer Screening program has been designed to encourage the early diagnosis and treatment of the high-risk population meeting certain criteria. The screening process involves Low-dose CT (LDCT) scans to determine any presence of lung nodules or early-stage lung disease. However small nodules can be very difficult to detect and missed diagnoses are not uncommon.

"The tremendous potential for lung cancer screening to reduce mortality in the U.S. is very much unrealized due to a combination of reasons. Based on our experience reviewing the algorithm for the past several months and my observations of its extensive use and testing internationally, I believe that Infervision's InferRead Lung CT.AI application can serve as a robust lung nodule "spell-checker" with the potential to improve diagnostic accuracy, reduce reading times, and integrate with the image review workflow," saidEliot Siegel, M.D., Professor and Vice Chair of research information systems in radiology at theUniversity of Maryland School of Medicine.

InferRead Lung CT.AI is now FDA cleared, and has also received the CE mark inEurope. "This is the first FDA clearance for our deep-learning-based chest CT algorithm and it will lead the way to better integration of advanced A.I. solutions to help the healthcare clinical workflow in the region," according to Deng. "This marks a great start in the North American market, and we are expecting to provide more high-performance AI tools in the near future."

For more information:global.infervision.com

View original post here:

Infervision Receives FDA Clearance for the InferRead Lung CT.AI - Imaging Technology News