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2020 IoT Trends and Predictions: Be prepared for the IoT Tsu-nami

#artificialintelligence

We must be prepared for the Internet of Things (IoT) Tsunami, but it will not be in 2020 as many of us believed. The good news is that it is approaching but now more quietly than a few years ago. For the most pessimistic or unconvinced of the IoT, I must say that much of the hype around the Internet of Things is not really hype anymore. I will say one more time: "IoT's here to stay". In Ten Trends of IoT in 2020, Ahmed Banafa considers that in the year 2020 we will hit all 4 components of IoT Model: Sensors, Networks (Communications), Analytics (Cloud), and Applications, with different degrees of impact.


Embedding Inference for Structured Multilabel Prediction

Neural Information Processing Systems

A key bottleneck in structured output prediction is the need for inference during training and testing, usually requiring some form of dynamic programming. Rather than using approximate inference or tailoring a specialized inference method for a particular structure---standard responses to the scaling challenge---we propose to embed prediction constraints directly into the learned representation. By eliminating the need for explicit inference a more scalable approach to structured output prediction can be achieved, particularly at test time. We demonstrate the idea for multi-label prediction under subsumption and mutual exclusion constraints, where a relationship to maximum margin structured output prediction can be established. Experiments demonstrate that the benefits of structured output training can still be realized even after inference has been eliminated.


Zipari How can you make smart predictions about data you don't have?

#artificialintelligence

You've heard the term, and you probably nod in agreement when someone tells you how important it is. But secretly you may not be sure what it is or how it works. Ask your data scientists to explain, and you may get lost in a sea of specialist talk about forks, leaf nodes, split points, and recursions. The only thing you need to know is that machine learning applies statistical models to the data you have in order to make smart predictions about data you don't have. Those predictions can help you find signals in the noise and extract value from all the data you're collecting.


Email marketing trends and predictions

#artificialintelligence

Earlier this year, Litmus consulted with industry experts to determine their predictions on'how the most crucial elements of email marketing will change in the next decade.' Although this article was published before the COVID-19 'tornado' ripped through the entire world, the email marketing trends mentioned (extracted from the ebook'The Future of Email in 2020 and Beyond') are still very relevant. And they will most likely play a role in shaping the future email marketing landscape as well. There is an option to download the ebook, from which you will learn how email teams and email strategy could change, as well as why there is a need to prioritize subscriber privacy and understand the critical need for seamless integrations. Refer to the article for more on the highlights, which are displayed in an infographic, titled '5 predictions for the future of email marketing' – they are:


Oscar Nomination Predictions and Filmmaker Charles Burnett

Slate

On this episode of Represent, Aisha is joined by Mark Harris, a Vulture writer and author of Pictures at a Revolution and Five Came Back, to help predict this year's Oscar nominees. Then, Aisha talks to revered director Charles Burnett, who emerged from the period of groundbreaking black independent filmmaking known as the L.A. Rebellion.