In a café on the Upper East Side of Manhattan, a one-time videogame developer turned political theorist named Santiago Siri is trying to explain to me how his nonprofit startup, Democracy.Earth, aims to fix the world's broken politics with the help of the blockchain. The conversation has already covered a dizzying amount of ground. We've discussed the emergence of the Westphalian order of nation-states in the 17th century, Russia's interference in the 2016 US election, the total collapse of Venezuelan society, and Siri's own experience of political corruption in his native Argentina. But he finally boils it all down to one short sentence. "We want to tokenize the like," Siri says.

Though many industries have fully embraced technology, the oil and gas industry has come later to the party. However, the industry has not been left out when it comes to innovation. Thanks to rising oil prices and better profit margins, oil and gas companies have the capital to invest in the future. Digital technologies are currently upending the way things are being done in this industry. While companies are slow to adopt them all, soon every part of the industry will embrace these digital technologies.

Hot on the heels of a report that Apple might be developing a coprocessor for health data analysis, news broke this afternoon of Google Coach, a rumored Google wellness product powered by artificial intelligence (AI). Fitness will be Google Coach's bread and butter, Android Police reports. But unlike Google Fit, Google's activity-tracking platform, it'll deliver insights proactively, informed in part by calendar appointments, reminders, and logged activities. If you skip a scheduled gym day, for example, it might nudge you to find another time. And if you're falling short of a fitness goal, it could suggest workouts and routines that would help you achieve it.

Mixtures of Mallows models are a popular generative model for ranking data coming from a heterogeneous population. They have a variety of applications including social choice, recommendation systems and natural language processing. Here we give the first polynomial time algorithm for provably learning the parameters of a mixture of Mallows models with any constant number of components. Prior to our work, only the two component case had been settled. Our analysis revolves around a determinantal identity of Zagier which was proven in the context of mathematical physics, which we use to show polynomial identifiability and ultimately to construct test functions to peel off one component at a time. To complement our upper bounds, we show information-theoretic lower bounds on the sample complexity as well as lower bounds against restricted families of algorithms that make only local queries. Together, these results demonstrate various impediments to improving the dependence on the number of components. They also motivate the study of learning mixtures of Mallows models from the perspective of beyond worst-case analysis. In this direction, we show that when the scaling parameters of the Mallows models have separation, there are much faster learning algorithms.

A year after Microsoft and Amazon first announced skills to bring Amazon's personal assistant to Windows users and the Microsoft assistant Cortana to the Amazon Echo connected speaker, the new features are available to consumers. The idea is that from Windows, users will be able to voice shop on Amazon, and on the Amazon Echo speaker, users will be able to hear e-mails and set up calendar appointments from the Microsoft Outlook program. "The goal is to have two integrated digital assistants who can carry out tasks across different dimensions of daily life -- at home or work, and on whatever device is most convenient," Microsoft's Jennifer Langston wrote on a company blog. But before you can get them to work, first you'll need to "enable" their skills. Amazon sends customers to the Alexa smartphone app to add skills, while Microsoft sends people to the web.

All online travel agencies are scrambling to meet the AI driven personalization standard set by Amazon and Netflix. In addition, the world of online travel has become a highly competitive space where brands try to capture our attention (and wallet) with recommending, comparing, matching and sharing. In this post, we aim to create the optimal hotel recommendations for Expedia's users that are searching for a hotel to book. We will model this problem as a multi-class classification problem and build SVM and decision tree in ensemble method to predict which "hotel cluster" the user is likely to book, given his (or her) search details. The data is anonymized and almost all the fields are in numeric format.

More and more technology and digital services are built upon, and driven, by AI and machine learning. But as we are beginning to see, these programmes are starting to replicate the biases which are fed into them, notably biases around gender. It is therefore imperative that the machine learning process is managed from input to output – including data, algorithms, models, training, testing and predictions – to assure that this bias is not perpetuated. Bahar Gholipour notes this bias as AI's so-called'black box' problem -- our inability to see the inside of an algorithm and therefore understand how it arrives at a decision. He claims that'left unsolved, it can devastate our societies by ensuring that historical discrimination, which many have worked hard to leave behind, is hard-coded into our future.'

An integration between Amazon's Alexa and Microsoft's Cortana is now in public preview, according to a Wednesday blog post from Microsoft. The collaboration between two of the most well known digital assistants was first announced in August 2017 and later demoed in early 2018. Relying on two digital assistants, and having them work together, could make it easier for users to stay on top of their work and personal lives, the post noted. For now, Cortana and Alexa can be enabled as a skill on each other, the post said. Cortana can be summoned on Echo devices, and Alexa can be called on Windows 10 PCs and Harman Kardon Invoke speakers.

More people will be able to access the Alexa-Cortana collaboration their companies unveiled last year, now that the team-up is available as a public preview. Unfortunately, you can only take it for a spin if you're in the US, but this is still a much wider release than the limited beta Microsoft and Amazon rolled out a few months ago. So long as you're a customer based in the country, you'll now be able to summon Alexa through Windows 10 devices and Harman Kardon's Invoke speakers and Cortana through Amazon's Echo devices. The two tech giants are working together to bring the experience to more devices. If you want to access Cortana on an Echo speaker, just say "Alexa, open Cortana" to use the assistant to check your emails, schedule and to-do lists.

A year ago, Amazon and Microsoft pledged that their digital assistants, Alexa and Cortana, would become friends. That future has now arrived: Beginning today, you'll be able to invoke Alexa from Windows 10's Cortana, and Cortana from an Alexa device like the Echo. Today (or possibly tomorrow, according to a Microsoft representative) Alexa and Cortana will become skills in their respective devices. Put another way, you'll be able to say "Hey Cortana, open Alexa" on a Windows 10 PC or Harman Kardon Invoke. On an Amazon Echo, you can say "Alexa, open Cortana."