As the Chief Revenue Officer at HungerRush, Olivier Thierry is influencing customer expectations with AI as the restaurant industry has begun experimenting with it, he tells Spiceworks News & Insights' Technology Editor, Neha Kulkarni. Restaurants have realized taking on new technology will help them not only survive the challenges but achieve results, he notes. From labor shortages to improving customer experience, in this edition of Tech Talk, Olivier discusses how AI can overcome these challenges and allow restaurants to reduce human error. He also shares how natural language processing can interpret customer attitudes in phone orders and have a real place in understanding customer experience. Olivier: The pandemic turned the restaurant industry upside down, and many of its setbacks are still being felt today.

In the field of machine learning, semi-supervised learning (SSL) occupies the middle ground, between supervised learning (in which all training examples are labeled) and unsupervised learning (in which no label data are given). Interest in SSL has increased in recent years, particularly because of application domains in which unlabeled data are plentiful, such as images, text, and bioinformatics. This first comprehensive overview of SSL presents state-of-the-art algorithms, a taxonomy of the field, selected applications, benchmark experiments, and perspectives on ongoing and future research.Semi-Supervised Learning first presents the key assumptions and ideas underlying the field: smoothness, cluster or low-density separation, manifold structure, and transduction. The core of the book is the presentation of SSL methods, organized according to algorithmic strategies. After an examination of generative models, the book describes algorithms that implement the low-density separation assumption, graph-based methods, and algorithms that perform two-step learning.

L'olivier - assurance auto, an auto insurer and French subsidiary of the English group Admiral, a European leader in automobile insurance, is joining InsurTech Shift Technology to fight against car insurance fraud. According to insurance magazine l'Argus de l'Assurance, in 2014 fraud represented 2.5 billion Euros in damages, only €219M of which have been recovered by insurers. Faced with such high figures, which are also on the increase, the aim of L'olivier is to rely on artificial intelligence and data science to automate and optimize the detection of suspicious claim files. For L'olivier, a direct insurer created in 2011, it was important to reinforce its plan to fight against fraud by establishing a dedicated unit: "Shift will help us in building out our capabilities. Their solution improves our ability to detect fraud by reducing the number of irrelevant cases, at the same time as it enhances our ability to prove fraud by providing administrators with avenues of investigation, enabling us to avoid payment of fraudulent claims," explains Janny Druon, head of the Claims Analytics team at L'olivier.

I use a variety of tools for advanced analytics, most recently I've been using Spark (and MLlib), R, scikit-learn, and GraphLab. When I need to get something done quickly, I've been turning to scikit-learn for my first pass analysis. For access to high-quality, easy-to-use, implementations1 of popular algorithms, scikit-learn is a great place to start. So much so that I often encourage new and seasoned data scientists to try it whenever they're faced with analytics projects that have short deadlines. I recently spent a few hours with one of scikit-learn's core contributors Olivier Grisel. We had a free flowing discussion were we talked about machine-learning, data science, programming languages, big data, Paris, and … scikit-learn!

Whether you're partial to Netflix, Hulu, Amazon Prime, one of the others, or all of the above, new and old movies are yours for the watching. Witness Christian Bale's turn as a serial killer in the sardonic American Psycho. Or get your horror on with Final Destination 3. Read on to learn about all 12 movies now available online. Given that it's based on one of the most popular books of all time (Antoine de Saint-Exupery's 1943 novella), fans may rule that Mark Osborne's movie version of The Little Prince (2016) is somewhere between an insult and a disaster. But taken on its own, it's a wonderfully creative, soul-soothing work.