Artificial Intelligence (more commonly known as AI) has successfully permeated our lives in the truest sense. From making a business decision to completely changing your profession, AI is rapidly transforming today's business industry. On one hand, it can lead you to a life of professional growth and prosperity if you accept it or it can make you cry tears of frustration. The trick is to understand AI because it is here to stay. Photography is subjective while artificial intelligence (AI) is objective.

This week, Gov. Doug Ducey and the Arizona Commerce Authority partnered to host a roundtable with more than a dozen local entrepreneurs to discuss the successes and challenges of being a startup leader in the state.

Netflix's famous algorithm challenge awarded a million dollars to the best algorithm for predicting user ratings for films. But did you know that the winning algorithm was never implemented into a functional model? Netflix reported that the results of the algorithm just didn't seem to justify the engineering effort needed to bring them to a production environment. At your company, you can create the most elegant machine learning model anyone has ever seen. That's no easy feat, which is why we're presenting you with seven machine learning best practices.

Despite over 40 years of research, the role of artificial intelligence and machine learning (ML) for clinical applications remains in evolution.

Deep learning, a form of artificial intelligence, uses artificial neural networks that mimic the function of the human brain.

Artificial Intelligence is apparently ready to get to work.

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.