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Tinder starts using artificial intelligence to check users' profile photos are real

Daily Mail - Science & tech

Tinder is to'swipe left' on catfishing as the popular dating app starts using artificial intelligence to check that profile photos uploaded by users are genuine. The photo verification feature will allow members to get their images authenticated by posing for a series of real-time selfies. Human-assisted artificial intelligence technology will then compare these submission to existing profile photos to confirm that they do match up. Once a person's photos have been verified, their profile will be granted a blue checkmark icon so that other users can trust their appearance is genuine. The verification feature is one of a number of dating safety features being added to Tinder, which will also gain a dedicated in-app safety centre and panic button.

AI, digital skills and data growth will dominate the analytical agenda in 2020 - Mag Viral News


We are entering a new decade that is defined by data. Organizations will either succeed or fail because of the way they collect, use, and democratize data analytics across their organization. At this crucial turning point in business transformation, companies must embrace change and invest in it. In the recently released 10 Enterprise Analytics Trends for 2020, MicroStrategy consulted leading industry experts to identify the key trends that will impact the analysis of corporate data for 2020 and beyond. Three key themes were identified: the crucial role of artificial intelligence (AI), the focus on digital skills and the growth of data.

AppSec California 2020: Machine Learning and Application Securit...


In this talk, we will take an in-depth look at various mechanisms of attack detection, from signatures and regular expressions to machine learning. Attack detection is critical for most security solutions, whether we are talking about a load balancer-based (NIDS, WAF), host-based or in-application solutions (HIDS, RASP). Interestingly, regardless of the differences in architecture and data flow, most solutions use similar detection principles and techniques. We will explore how the detection architecture evolved over time and how the new generation of detection logic, such as the architecture implemented by some of the advanced application security tools, are principally different from that of the legacy solutions.

State of the Art Survey of Deep Learning and Machine Learning Models for Smart Cities and Urban Sustainability


Deep learning (DL) and machine learning (ML) methods have recently contributed to the advancement of models in the various aspects of prediction, planning, and uncertainty analysis of smart cities and urban development. This paper presents the state of the art of DL and ML methods used in this realm. Through a novel taxonomy, the advances in model development and new application domains in urban sustainability and smart cities are presented. Findings reveal that five DL and ML methods have been most applied to address the different aspects of smart cities. These are artificial neural networks; support vector machines; decision trees; ensembles, Bayesians, hybrids, and neuro-fuzzy; and deep learning.

Arkansas' First AI and Machine Learning Accelerator to Launch with Cohort of 14 Companies -- Startup Junkie


Cohort of 14 U.S. and international startups to relocate to Bentonville for 12 weeks PRESS RELEASE – The first-ever Arkansas-based artificial intelligence and machine learning accelerator will launch later this month, with the goal of helping a cohort of startups within these fields connect to regional enterprise partners. The Fuel Accelerator, in its second iteration, will provide regular, hands-on education and workshops to a cohort of 14 companies from across the United States, Europe and Asia. These 14 companies will make their way to Northwest Arkansas, at the foot of the Ozark Mountains, for a 12-week, enterprise-ready accelerator that will provide them with access to other startup founders, industry experts, institutions of higher education, and public policy officials. Fuel launched in late 2018 with eight startups participating in a supply chain-focused, 16-week program. The program helped its first cohort nurture relationships with key Fortune 500 companies through feedback sessions, training, pilots and demos.

VA's AI Tech Sprint yields a tool for matching patients with clinical trials, and more - FedScoop


A group of high school students was one of the top teams to emerge from the recent AI Tech Sprint by the Department of Veterans Affairs, delivering a web application that could help match cancer patients to clinical trials. The three students from Northern Virginia entered their work in a competition that included software companies like Oracle Healthcare and MyCancerDB. Digital consulting company Composite App took the $20,000 first place prize for its solution -- a tool for helping patients stay on track with their care plan -- but the clinical trials team got an honorable mention. The tech sprint was organized by the VA's new AI institute, and it focused on partnering with outside organizations and companies interested in applying artificial intelligence tools and techniques to VA data. The high school team's members -- Shreeja Kikkisetti, Ethan Ocasio and Neeyanth Kopparapu -- met as part of the Northern Virginia-based nonprofit Girls Computing League.

Investorideas.com Newswire - Special Edition AI Eye Featuring (OTC PINK: GTCH) : Healthcare and Medical - Prominent Segment in Rapidly Growing and Broadening AI Market


No longer relegated to the ranks of science fiction, AI is rapidly becoming ubiquitous as one the most dynamic new fields in technology. But just as it cannot be consigned to fiction, AI cannot be reducible to any particular tech category, as it demonstrates applicability in an increasing array of different industries. Its core technologies - such as machine learning, deep learning, natural language processing (NLP) and computer vision - have enabled AI to penetrate and become indispensable in everything from autonomous vehicles, virtual assistants, energy, voice and text translation, retail, healthcare and more. And this is all happening fast. A report from Grand View Research, for instance, projects a compound annual growth rate (CAGR) for the global AI market of 46.2 percent from 2019 to 2025.

Deepfakes: A threat to democracy or a bit of fun?


"We are already at the point where you can't tell the difference between deepfakes and the real thing," Professor Hao Li of the University of Southern California tells the BBC. We are at the computer scientist's deepfake installation at the World Economic Forum in Davos which gives a hint of what he means. Like other deepfake tools, his software creates computer-manipulated videos of people - often politicians or celebrities - that are designed to look real. Most often this involves "face swapping", whereby the face of a celebrity is overlaid onto the likeness of someone else. As I sit, a camera films my face and projects it onto a screen in front of me; my features are then digitally mapped.

Moving from AI awareness to meaningful implementation


While most executives at financial institutions agree that artificial intelligence (AI) is important to their organization's success, few have fully implemented AI projects. In a recent Cognizant survey of 230 financial services executives, three-quarters said AI is extremely or very important to the success of their organizations. However, only 61% of those were aware of an AI project at their company. Even more telling, only 29% were aware of a project that had been fully implemented. Clearly, AI is quickly becoming a competitive requirement, creating the risk that those who are not implementing or updating AI capabilities will fall behind.

Guiding the Ethics of Artificial Intelligence


This blog post is adapted from our June 10 response to the National Institute of Standards and Technology's (NIST) request for information (RFI) 2019-08818: Developing a Federal AI Standards Engagement Plan. This RFI was released in response to an Executive Order directing NIST to create a plan for the development of a set of standards for the acceptable use of AI technologies. Given the wide adoption of AI technologies and the lag in commensurate laws and regulations, this post aims to help NIST by highlighting the current state, plans, challenges, and opportunities in ethics and AI. In 2016 the European Union (EU) created the General Data Protection Regulation (GDPR) that would expand protections around EU citizens' personal data beginning in 2018. Meanwhile, China has extensively integrated AI technologies into their government and social structure via the China Social Credit System.