If you use such social media websites as Facebook and Twitter, you may have come across posts flagged with warnings about misinformation. So far, most misinformation – flagged and unflagged – has been aimed at the general public. Imagine the possibility of misinformation – information that is false or misleading – in scientific and technical fields like cybersecurity, public safety and medicine. There is growing concern about misinformation spreading in these critical fields as a result of common biases and practices in publishing scientific literature, even in peer-reviewed research papers. As a graduate student and as faculty members doing research in cybersecurity, we studied a new avenue of misinformation in the scientific community.
In the years since the ubiquitous dating app Tinder launched in 2012, its interface has stayed largely the same. Today Tinder is launching a slew of new features to serve Gen Z, which accounts for more than half of their users according to their press release. With the introduction of video and an Explore page, the app is going to look a lot more like TikTok and Snapchat. Tinder wants to "bring the main character energy" to the app, invoking a popular TikTok meme, by adding the ability for users to put videos on their profiles. They say this is part of making Tinder a "multi-dimensional experience."
Humans use technology to travel, communicate, learn, operate a business, and live comfortably. Our lives have been made easier by advances in technology. Communication, transportation, education and learning, healthcare, and many other infrastructure business areas have benefited from technological advancements. Technology has an impact on how people communicate, learn, and think. It contributes to society and influences how individuals interact daily.
Facebook's new Artificial Intelligence technology not only identifies Deepfakes, it can also gives hints about their origin Artificial intelligence (AI) created videos and pictures have become much popular and that can create some serious problems as well, because you can create fake videos, and manipulated images of any type to put anyone in trouble. Deepfakes use deep learning models to create fictitious photos, videos, and events. These days, deepfakes look so realistic that it becomes very difficult to identify the real picture from the fake one with a normal human eye, therefore, Facebook's AI team has created a model in collaboration with a group of Michigan State University that has the ability to identify not only the fabricated picture or videos, but it can even trace the origin. The latest technology of Facebook checks the resemblances from a compilation of deepfakes datasets to find out if they have a common basis, looking for a distinctive model such as small specks of noise or minor quirks in the color range of a photo. By spotting the small finger impressions in the photo, the new AI model is capable to distinguish particulars of how the impartial network that produced the photo was invented, such as how large the prototype is and how it was prepared.
The spread of misinformation and hate speech is increasing on multiple social media platforms affecting a certain group of people. Celebrities and politicians are experiencing the most as primary targets but that is affecting the minds of common people as well. The malicious digital content also contains hate speech regarding different ethnicity and minorities like LGBTQ. Hate speech travels faster than light on social media platforms. This can develop violence, riots, or other dangerous impacts in society. It is seen that AI models and deep learning algorithms are advancing as per time but it is still struggling in moderating hate speech.
In a 2017 Deloitte survey, only 42% of respondents considered their institutions to be extremely or very effective at managing cybersecurity risk. The pandemic has certainly done nothing to alleviate these concerns. Despite increased IT security investments companies made in 2020 to deal with distributed IT and work-from-home challenges, nearly 80% of senior IT workers and IT security leaders believe their organizations lack sufficient defenses against cyberattacks, according to IDG. Unfortunately, the cybersecurity landscape is poised to become more treacherous with the emergence of AI-powered cyberattacks, which could enable cybercriminals to fly under the radar of conventional, rules-based detection tools. For example, when AI is thrown into the mix, "fake email" could become nearly indistinguishable from trusted contact messages.
The annual production of data follows an exponential curve, the assimilation by a person or even by a group of persons of this data is no longer possible. To get the most out of it, it is necessary to be helped by computers. But as this data is mostly unstructured, classical algorithms are unable to do this job. Only Artificial Intelligence and in particular NLP with Sentiment Analysis can do it. We created ElligencIA with the aim of giving meaning to this ocean of data and taking advantage of this collective intelligence. ElligencIA, operational since January 1st 2021, is an AI consulting and solutions company for the BFSI.
If you're into the market and investment side of things, how does a Series F funding round as part of a $325 million investment led by Eurazeo and GV (formerly Google Ventures), bringing Neo4j's valuation to over $2 billion sound? If you're into the technology and applications side of things, how does a Neo4j demo of a social network application with 3 billion people, running queries designed to test the limits of graph query languages and databases across a 1000 node cluster sound? Graph database vendor Neo4j CEO and co-founder Emil Eifrem is announcing the funding and showcasing the demo today at the company's annual virtual conference NODES. We caught up with Eifrem to get a taste of things to come. Truth be told, we were not entirely surprised to learn about Neo4j's funding round.
Facebook has developed an artificial intelligence that it claims can detect deepfake images and even reverse-engineer them to figure out how they were made and perhaps trace their creators. Deepfakes are wholly artificial images created by an AI. Facebook's new AI looks at similarities among a collection of deepfakes to see if they have a shared origin, looking for unique patterns such as small speckles of noise or slight oddities in the colour spectrum of an image. By identifying the minor fingerprints in an image, Facebook's AI is able to discern details of how the neural network that created the image was designed, such as how large the model is or how it was trained. "I thought there's no way this is going to work," says Tal Hassner at Facebook.