Artificial intelligence (AI) is changing the internal communications landscape. The sci-fi revolution is upon us and AI isn't just a scary threat in Hollywood movies any more – it's already embedded in digital tools we use every single day. But if it's not all Big Brother menace, how can we harness this exciting technology to benefit our work in internal communications? I was recently invited to join the #commschat team online, alongside IBM's AI Watson Ecosystem lead Silvia Cambie and other IC pros, to share ideas and insights into how we're teetering on the brink of an AI transformation in employee engagement. Here are my five must-know takeaways from our discussion.

Over the summer, streaming giant and industry up-ender Netflix reported its first domestic subscriber loss since 2011 and its lowest quarterly subscriber growth in three years. Within hours, its stock value tanked $17 billion in a single day. You read that right: $17 BILLION. Clearly, no one is immune from disruption and this is especially true in the media and entertainment business--even those who helped create and spur them forward. Last year, we looked at digital transformation trends for media and entertainment focusing on things like the increase in video ads, a clamor for digital experience, and a rise in mobile data usage due to such high demand. All of these predictions have become a reality and heading into 2020, all of those things will likely to continue.

As consumers are going on their shopping frenzy for Cyber Monday, tech enthusiasts are spending their time in Las Vegas at the AWS re:Invent conference, where Amazon unveils the latest gadgets and gizmos it has in the works. Excitingly enough, for day one on Monday, Amazon Web Services (AWS) and Julien Simon announced the world's first machine-learning-enabled musical keyboard for developers--AWS DeepComposer. Powered by machine learning, AWS DeepComposer allows developers of all skill levels to learn "Generative A.I." while creating original music outputs. In the world of artificial intelligence (A.I.), the most rapidly growing areas include computer vision, natural language processing, and of course, Generative AI. Generative A.I. is one of the biggest recent advancements in A.I. technology because of its ability to create something new by utilizing "generative adversarial networks."

The modern deep learning approaches to natural language processing are voracious in their demands for large corpora to train on. Folk wisdom estimates used to be around 100k documents were required for effective training. The availability of broadly trained, general-purpose models like BERT has made it possible to do transfer learning to achieve novel results on much smaller corpora. Thanks to these advancements, an NLP researcher might get value out of fewer examples since they can use the transfer learning to get a head start and focus on learning the nuances of the language specifically relevant to the task at hand. Thus, small specialized corpora are both useful and practical to create.

Ironically, algorithms are telling us that machines will soon be able to do most of our jobs, but those conclusions perfectly illustrate what's non-scientific about turning human reasoning over to computers. Barely a month passes without a news story about how robots and artificial intelligence (AI) are going to devastate a significant number of the jobs in the workplace, sweeping away solid salary paying employment for factory workers and white-collar clerks alike. Just this month, the UK Parliament reported on the future of work in the face of automation, declaring that over 70% of jobs were at medium to high risk of displacement. While the report draws on a "more optimistic" study by the ONS to arrive at this prediction, the ONS used methods inspired by the even-more-frightening results in a 2013 paper by Oxford economist Carl Frey and machine learning expert Michael Osbourne, which found that almost half of jobs were at high risk, and two-thirds at medium risk. The paper was so important that in addition to shaping the methodologies of later reports (like those of the ONS, the OECD, and others), it informed a speech of the Bank of England's Chief Economist to the Trades Union Congress in 2015, prompted the "Fourth Industrial Revolution" theme of the 2016 Davos Forum, provided the basis of the WEF "Future of Jobs" report, and generated a subsequent sea of articles by journalists who rarely questioned the numbers.

More Governments Employ Artificial Intelligence in Government and Law Enforcement Artificial intelligence is developing at a rapid rate and is already changing the way businesses and governments run, but how the algorithms they use work isn't clear. More governments are implementing machine learning and artificial intelligence to increase efficiency, cut costs, enforce laws, and combat the spread of fake news.

Technology leads podcast is a podcast with three hosts Tom, Daniel, and Rik. Each episode has a guest that will be interviewed. The podcast starts with a couple of interesting tech updates. We question whether these are still podcasts or more leaning towards the audiobook genre. Remote controlling your car with an app is nice, but what if you rent a car and a previous customer can still control it!

--Scientists have used many different classification methods to solve the problem of music classification. But the efficiency of each classification is different. In this paper, we propose two compared methods on the task of music style classification. More specifically, feature extraction for representing timbral texture, rhythmic content and pitch content are proposed. Comparative evaluations on performances of two classifiers were conducted for music classification with different composers' styles.

China has issued new rules banning online video and audio providers from using artificial intelligence (AI) and virtual reality technologies to produce "fake news." The regulation published Friday by China's cyberspace authority said that both providers and users of online video news and audio services are "not allowed" to use new technologies such as deep learning and virtual reality to create, distribute and broadcast "fake news." "Fake news" has been generalised to mean anything from a mistake to a parody or a deliberate misinterpretation of facts. The rules come into effect on January 1, 2020. Failure to follow them could be considered a criminal offence, the Cyberspace Administration of China (CAC) said, without offering details on punishments.

Artificial intelligence is expected to reshape the future workplace - drastically changing or replacing entire jobs. In fact, companies are already employing AI-based technologies to recruit talent and evaluate workers' performance. The central question has emerged: To what extent will AI and automation continue to change the workforce and what does it mean for both blue-collar and white-collar workers? On Wednesday, November 20, POLITICO held a deep-dive conversation on how AI is transforming the American workplace and what legislative and policy solutions should be implemented to address this shift.