"Alexa" was just another female name. Uber hadn't taken anyone for a ride yet. And the buzz around Facebook had more to do with the fact that seemingly everyone you once knew was turning up on "The Social Network," and less about the numerous data and privacy scandals that would tarnish the company's reputation later on. The year was 2010, the dawn of a new decade. And while 10 years is a long time for most every industry, in consumer tech it might as well be a lifetime.
Every 18 – 24 months, the world is doubling the quantum of data available. In other words, we are generating as much data produced by all of human race, every 2 years. This is not because we have suddenly turned interesting and everyone is documenting their lives! Rather, a couple of other factors have come together in the past decade. One, we are using many data formats today.
SAN FRANCISCO: Facebook's artificial intelligence (AI) research team has developed a tool that tricks the facial recognition system to wrongly identify a person in a video, the media reported. The "de-identification" system, which also works in live videos, uses machine learning to change key facial features of a subject in a video, according to a report in VentureBeat on Friday. "Face recognition can lead to loss of privacy and face replacement technology may be misused to create misleading videos," reads a paper explaining the company's approach, as cited by VentureBeat. This de-identification technology earlier worked mostly for still images, The Verge reported. "Recent world events concerning advances in, and abuse of face recognition technology invoke the need to understand methods that deals with de-identification. Our contribution is the only one suitable for video, including live video, and presents quality that far surpasses the literature methods," said the paper.
The way we do Artificial Intelligence has emerged over the years, as the result of various shortcuts we took, to bypass difficult problems. The behaviour of the current AI systems, including some concerning aspects, is due to those choices. And if we answer no, what other method should we use? Read the story of how we ended up in this situation: https://philpapers.org/rec/CRISTA-3
Climate change is a conversation we need to be having in Intensive Care circles. If the environmental catastrophe that is unfolding around us continues unabated there may no longer even be Intensive Care Units. The rising global temperatures, the melting ice, the extreme weather events, and their impact on agricultural crops and human habitation may well lead to such a fall in the economy that our healthcare system may not have the financial resources it does now. And given ICUs are the most expensive part of our hospitals, have a guess what might disappear first. So who is there better to listen to about the climate crisis than British intensivist, Professor Hugh Montgomery, a deeply passionate and highly intelligent man, who was a founding member of the UK Climate and Health Council, and who has helped raise awareness about climate change for over 2 decades.
All the world's tech giants from Alibaba to Amazon are in a race to become the world's leaders in artificial intelligence (AI). These companies are AI trailblazers and embrace AI to provide next-level products and services. Here are 10 of the best examples of how these companies are using artificial intelligence in practice. Chinese company Alibaba is the world's largest e-commerce platform that sells more than Amazon and eBay combined. Artificial intelligence (AI) is integral in Alibaba's daily operations and is used to predict what customers might want to buy.
Some attacks may still slip "under the radar" though, which is why tools that leverage machine-learning, like User and Entity Behavior Analytics (UEBA), are an important support to your SIEM as they will detect more unusual threats as well as greatly increase the overall fidelity of your security alerts. SIEM and UEBA are further supported by threat hunting tools that enable your hunt teams to track down any other threats that may still be lurking in your system. All three approaches are important to your threat detection and response ecosystem. Micro Focus is a global software company with 40 years of experience in delivering and supporting enterprise software solutions that help customers innovate faster with lower risk. Our portfolio enables our 20,000 customers to build, operate, and secure the applications and IT systems that meet the challenges of change.
Keeping abreast of shopping trends online is straightforward enough -- whole categories of startups achieve this with predictive modeling. But what about when that shopping takes place in-store? Tracking the behaviors of mall, outlet, and department store shoppers is of critical importance to physical store brands, particularly considering that the percentage of brick-and-mortar sales increased by 2% from $2.99 trillion in 2016 to $3.04 trillion in 2017. To meet this need, Miron Mironiuk founded Cosmose AI, a Shanghai-based analytics software provider that anticipates how people shop offline. Brands like Subway, Samsung, Walmart, Airbnb, Tencent, Burberry, Omnicom, Mercedes-Benz, Anheuser-Busch InBev, LVMH, Kering, L'Oréal, Gucci, Cartier, P&G, Nestle, and Coca-Cola use its tool suite to granularly track offline visitors' purchasing habits and target them with online ads via WeChat, Weibo, Facebook, Google, and over 100 other internet platforms.