Artificial intelligence will humanize recommendation engines, improve the accuracy of logistics engines, and represent a monumental change in the friendliness of chatbot engines. Learning new languages (Duolingo), finding new dinner plans (Replika) and making photography exciting again (Prisma) is how our business partners will be introduced to the potential of artificial intelligence. If I asked you how to build a house, you'd have a series of steps in mind. When asked how to validate a company's technology security perimeter, other action steps come immediately to the forefront. And when booking a vacation to Brazil, a clear approach to get you on the beach fast rushes to the mind.

Here is a very real and true thing: 2017 is making it really hard to be a science fiction writer. To be sure, these times -- by which I mean the Trump era to date, let's go ahead and avoid cutesy winking allusions -- are making it hard for lots of writers, not just the ones who write science fiction. It's difficult to focus on writing, particularly fiction, when the world feels like it's on fire and everyone you know is trying to decide between hiding in a hole or taking up recreational alcoholism to get by. The rapid-fire pace of events is such that you (or at least I) end up sitting at the computer sort of paralyzed. In the last few weeks we've had (in no particular order) the healthcare vote, hurricane Scaramucci, North Korea and racists marching with Tiki torches like the domestic terrorists they are.

Google has turned to an unusual source to train its high-tech AI: chocolate chip cookie recipes. Tasking programmers with helping an AI learn from data through trial-and-error is tedious and time-consuming, so the company has employed a neural network called Vizier to help another neural networks learn via a type of training automation called hyperparameter tuning. To teach Vizier, Google tasked it with formatting the perfect chocolate chip cookie recipe, considering taste-tester feedback until it for the recipe just right. Google has turned to an unusual source to train its high-tech AI: chocolate chip cookie recipes. The company gave chefs recipes to bake for taste-testers, who then provided feedback via a survey.

Google's computer scientists have created an AI to tweak the company's other AIs. The advanced machine learning system, which goes by the faintly sinister name of Google Vizier, automatically tunes algorithms right across Google's parent company Alphabet. But to test it, the researchers used an old-fashioned metric: cookie quality in the canteen. Modern machine learning systems are the algorithmic equivalent of Formula 1 racing cars. The systems have tremendous power, but they are extremely sensitive: to function effectively they need to be finely tuned, usually by hand.

Recommender systems (RS) help users navigate large sets of items in the search for "interesting" ones. One approach to RS is Collaborative Filtering (CF), which is based on the idea that similar users are interested in similar items. Most model-based approaches to CF seek to train a machine-learning/data-mining model based on sparse data; the model is then used to provide recommendations. While most of the proposed approaches are effective for small-size situations, the combinatorial nature of the problem makes it impractical for medium-to-large instances. In this work we present a novel approach to CF that works by training a Denoising Auto-Encoder (DAE) on corrupted baskets, i.e., baskets from which one or more items have been removed. The DAE is then forced to learn to reconstruct the original basket given its corrupted input. Due to recent advancements in optimization and other technologies for training neural-network models (such as DAE), the proposed method results in a scalable and practical approach to CF. The contribution of this work is twofold: (1) to identify missing items in observed baskets and, thus, directly providing a CF model; and, (2) to construct a generative model of baskets which may be used, for instance, in simulation analysis or as part of a more complex analytical method.

The explosive growth of structured and unstructured data, along with the availability of new technologies such as cloud computing and machine learning algorithms, have made the expanded use of artificial intelligence (AI) in banking possible. According to Goldman Sachs, AI will enable $34 billion to $43 billion in annual "cost savings and new revenue opportunities" within the financial services sector by 2025. With more data accessible than ever before, banks are actively working on opportunities to better integrate machine learning into their businesses. However, this does not have to mean a less personalized experience for customers. Rather, it is crucial for customer loyalty that, even with decreasing face-to-face interactions, customized interactions are the norm.

The Bios Urn mixes cremains with soil and seedlings. It automatically waters and cares for the memorial sapling, sending updates to a smartphone app. The Bios Urn mixes cremains with soil and seedlings. It automatically waters and cares for the memorial sapling, sending updates to a smartphone app. Earlier this summer, a modest little startup in Barcelona, Spain, unveiled its newest product -- a biodegradable, Internet-connected funeral urn that turns the ashes of departed loved ones into an indoor tree.

TSG 1899 Hoffenheim is a Bundesliga football club that has made a 17-year journey from Germany's fifth division. Think Sutton United becoming Arsenal. You forgot to provide an Email Address. This email address doesn't appear to be valid. This email address is already registered.

A company can have the best technology in the world. It can have the strongest talent. It can have the coolest product ideas. But to train the algorithms that will deliver the intelligence to transform our cities, it needs data. Sign up to get Backchannel's weekly newsletter. That's why earlier this year, after leaving Microsoft the previous fall, legendary engineer Qi Lu headed to Beijing to become Baidu's chief operating officer. At his former job, he was, among other things, CEO Satya Nadella's top deputy in helping to lead the company's AI strategy. Clearly, he saw more opportunity across the Pacific: In China, 731 million people--nearly twice the entire population of the United States--are online.

Indium, rhodium, platinum, tellurium and gold: these are some of the rarest elements in the world. From smartphones (which contain a whopping 60 to 64 elements) to hybrid cars, wind turbines and medical equipment, much of the technology we depend upon contains a rich list of elemental ingredients. Meanwhile, demand for traditional metals such as copper and aluminium is rocketing, driven by the rapid growth of emerging economies in Asia and South America. If our voracious appetite for these minerals continues at the current rate then rare earth metals may be mined out in 15 to 20 years, and indium may only have another decade of supplies remaining. Even aluminium could run dry within the next century.