Alibaba has gone from an ecommerce company to its own economy. The Tmall Global Shopping day, Alibaba's Single's Day event, recorded 120.7 billion RMB (17.8 billion USD) in sales in one day. They also revealed some interesting plans for the coming future. Robotics, AI, AR, and VR will be adopted across sectors like ecommerce, logistics, service sector, and finance to make user's daily life smarter. YunOS, a cloud-based data and service oriented operating system for the Internet of Things, will power a wide range of smart devices including smartphones, wearables, Internet cars, robots, and smart household appliances.

Food and agribusiness comprise a $5 trillion industry that accounts for 10 percent of global consumer spending, 40 percent of employment and 30 percent of greenhouse-gas emissions. This massive industry does not change easily, but change – transformative innovation – is precisely what's needed. We collected some examples of artificial intelligence techniques that can help farmers to save thousands of dollars. Three years ago Belarusian startup OneSoil was created. It's an online service to monitor the status of sown areas, which can increase productivity and save resources with the help of artificial intelligence.

SINGAPORE – A boom in consumer drone sales has spawned a counter-industry of startups aiming to stop drones flying where they shouldn't, by disabling them or knocking them out of the sky. Dozens of startup firms are developing techniques -- from deploying birds of prey to firing gas through a bazooka -- to take on unmanned aerial vehicles (UAVs) that are being used to smuggle drugs, drop bombs, spy on enemy lines or buzz public spaces. The arms race is fed in part by the slow pace of government regulation for drones. In Australia, for example, different agencies regulate drones and counter-drone technologies. "There are potential privacy issues in operating remotely piloted aircraft, but the Civil Aviation Safety Authority's role is restricted to safety. Privacy is not in our remit," a CASA official said.

This is the 2-part blog version of a talk I've given at DOAG Conference this week. I've also uploaded the slides (no ppt; just pretty R presentation;-)) to the articles section, but if you'd like a little text I'm encouraging you to read on. That is, if you're in the target group for this post/talk. For this post, let me assume you're a SQL girl (or guy). With SQL you're comfortable (an expert, probably), you know how to get and manipulate your data, no nesting of subselects has you scared;-).

Develop and tune a suite deep learning models on a range of projects. The most advanced machine learning platform used by professionals.

This is the second installment in a three-part review of 2016 in machine learning and deep learning. Part One, here, covered general trends. In Part Two, we review the year in open source machine learning and deep learning projects. Part Three will cover commercial machine learning and deep learning software and services. There are thousands of open source projects on the market today, and we cannot cover them all. We've selected the most relevant projects based on usage reported in surveys of data scientists, as well as development activity recorded in OpenHub. In this post, we limit the scope to projects with a non-profit governance structure, and those offered by commercial ventures that do not also provide licensed software. Part Three will include software vendors who offer open source "community" editions together with commercially licensed software.

This algorithm forms the basis for many modern day ML algorithms, most notably neural networks. In addition, we'll discuss the perceptron algorithm's cousin, logistic regression. And then we'll conclude with an introduction to SVMs, or support vector machines, which are perhaps one of the most flexible algorithms used today. In machine learning, there are two general classes of algorithms. You'll remember that in our last post we discussed regression and classification.

Autonomous vehicles are already making profound choices about whose lives matter, according to experts, so we might want to pay attention. "Every time the car makes a complex manoeuvre, it is implicitly making trade-off in terms of risks to different parties," Iyad Rahwan, an MIT cognitive scientist, wrote in an email. The most well-known issues in AV ethics are trolly problems -- moral questions dating back to the era of trollies that ask whose lives should be sacrificed in an unavoidable crash. For instance, if a person falls onto the road in front of a fast-moving AV, and the car can either swerve into a traffic barrier, potentially killing the passenger, or go straight, potentially killing the pedestrian, what should it do? Rahwan and colleagues have studied what humans consider the moral action in no-win scenarios (you can judge your own cases at their crowd-sourced project, Moral Machine).

Autoregression is a time series model that uses observations from previous time steps as input to a regression equation to predict the value at the next time step. It is a very simple idea that can result in accurate forecasts on a range of time series problems. In this tutorial, you will discover how to implement an autoregressive model for time series forecasting with Python. Autoregression Models for Time Series Forecasting With Python Photo by Umberto Salvagnin, some rights reserved. A regression model, such as linear regression, models an output value based on a linear combination of input values.

On the west coast of Australia, Amanda Hodgson is launching drones out towards the Indian Ocean so that they can photograph the water from above. The photos are a way of locating dugongs, or sea cows, in the bay near Perth--part of an effort to prevent the extinction of these endangered marine mammals. The trouble is that Hodgson and her team don't have the time needed to examine all those aerial photos. There are too many of them--about 45,000--and spotting the dugongs is far too difficult for the untrained eye. Deep learning is remaking Google, Facebook, Microsoft, and Amazon.