According to statistics, over 1.9 billion users log into YouTube every single month watching more than a billion hours of video daily, which is half the internet. Organizations are integrating video creation and video sharing with their marketing strategies. As on date, YouTube supports 80 different languages, which also adds to its popularity. Cisco predicts that by 2022, video will consume 82 percent of all internet traffic. Considering the massive number of users, high volume of activities and richness of content, it makes sense for YouTube to take advantage of artificial intelligence (AI) and machine learning (ML) to add efficiency to its operations.

We contribute the largest publicly available dataset of naturally occurring factual claims for the purpose of automatic claim verification. It is collected from 26 fact checking websites in English, paired with textual sources and rich metadata, and labelled for veracity by human expert journalists. We present an in-depth analysis of the dataset, highlighting characteristics and challenges. Further, we present results for automatic veracity prediction, both with established baselines and with a novel method for joint ranking of evidence pages and predicting veracity that outperforms all baselines. Significant performance increases are achieved by encoding evidence, and by modelling metadata. Our best-performing model achieves a Macro F1 of 49.2%, showing that this is a challenging testbed for claim veracity prediction.

Most research on lifelong learning (LLL) applies to images or games, but not language. Here, we introduce LAMAL, a simple yet effective method for LLL based on language modeling. LAMAL replays pseudo samples of previous tasks while requiring no extra memory or model capacity. To be specific, LAMAL is a language model learning to solve the task and generate training samples at the same time. At the beginning of training a new task, the model generates some pseudo samples of previous tasks to train alongside the data of the new task. The results show that LAMAL prevents catastrophic forgetting without any sign of intransigence and can solve up to five very different language tasks sequentially with only one model. Overall, LAMAL outperforms previous methods by a considerable margin and is only 2-3\% worse than multitasking which is usually considered as the upper bound of LLL. Our source code is available at https://github.com/xxx.

Steve Jobs once said, "A lot of times, people don't know what they want until you show it to them'. This makes sense, especially in this era of constant choice overload. Consumers today have access to a plethora of products just at the click of their mouse. These innumerable choices can sometimes turn out to be confusing and hampering and do more harm than good. For instance, a company may offer millions of products on its website, but how does a consumer find a new and appealing product from amongst those?

Machine learning (ML) is another emerging technology where machines can learn on their own.

Over the past year, AI systems have made huge strides in their ability to generate convincing text, churning out everything from song lyrics to short stories. Experts have warned that these tools could be used to spread political disinformation, but there's another target that's equally plausible and potentially more lucrative: gaming Google. Instead of being used to create fake news, AI could churn out infinite blogs, websites, and marketing spam. The content would be cheap to produce and stuffed full of relevant keywords. But like most AI-generated text, it would only have surface meaning, with little correspondence to the real world.

Fox News Flash top headlines for Sept. 6 are here. Check out what's clicking on Foxnews.com An Apple project to rewrite how the Siri voice assistant handles sensitive topics like feminism and the #MeToo movement told developers to either not engage, deflect or inform. According to leaked documents obtained by The Guardian, the project saw Siri's responses rewritten to never explicitly say the word "feminism" -- although it was OK for the AI-powered assistant to say it was in favor of equality. Apple's guidelines explain that "Siri should be guarded when dealing with potentially controversial content," and that when questions are directed at the voice assistant, they can be "deflected. However, care must be taken here to be neutral."

When people think of tech in media, their first thoughts are likely around digital platforms that bring more content to our fingertips. Now, leading innovations -– namely, AI and blockchain -- are enabling media companies to take this a step further by delivering even more compelling content to broader audiences. AI is being used to watch and understand live video in real-time to provide insights that enhance the viewer experience. Technologies such as computer vision and image recognition can tag video based on different characteristics. There is no better example of using AI to create dynamic experiences than in sports, where AI can identify exciting plays by evaluating players' actions or an audience's reaction.

On Tuesday, the company said it raised $72.5 million in a round led by Goldman Sachs Group Inc. and Ping An Global Voyager Fund, with continued investments from Wells Fargo & Co., Nvidia Corp. and Nexus Venture Partners. H2O.ai, based in Mountain View, Calif., has raised a total of $147 million since it was founded in 2012. The company sells software that helps businesses incorporate machine learning into their applications to make them more predictive. Its machine-learning platform is used by more than 18,000 companies, including Walgreens Boots Alliance Inc., which uses it to price retail goods, and Capital One Financial Corp., which uses it to help detect fraud, Mr. Ambati said. The platform offers a set of tools that are designed to simplify AI for nonexperts, and can be used for a range of applications.

One of the primary benefits of AI today, whether you develop AI software, shoot video, or take photos, is that AI can accelerate the process and bring your product to reality quicker. Specifically, for software developers, the AI tools at their disposal for edge devices like smartphones are opening the way for new cutting-edge features and applications. "As a developer or as a creative, would you rather spend your time on the mundane challenges of programming or getting right to the creative side?" says Gary Brotman, senior director and head of AI strategy and product planning at Qualcomm Technologies. "AI, using neural networks, which means today's smartphone features produce photos as good as those you'd expect from a high-end DSLR camera." Plus, as technology evolves, all those familiar features like scene recognition, night mode photography, super resolution, and more can be applied in real time rather than during post-processing as they are today.