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;-).

That was the repeated response from Magic Leap founder Rony Abovitz when Reed Albergotti of The Information asked about the technology behind the startup's augmented-reality glasses. For months, as Albergotti recently reported, Magic Leap has wooed investors and journalists by strapping them into a bulky helmet that augments their world with Star Wars-like spaceships and other digital creations. But this helmet is too big and too expensive for the mass market, so the company is working to squeeze its technology into a sleek pair of wire-rim glasses. The rub, according to ex-employees speaking with The Information, is that the company is having trouble actually making that happen. Abovitz wouldn't let Albergotti try the glasses on, and when asked how they work, all he would say was: "Squirrels and sea monkeys."

When the general public first learned about drones, the context was largely related to military applications and spy tactics, so the unmanned aircraft were cast with a bad rap. Years later, a number of creative technologists have found ways to use drones to help people, animals, and the environment. Drones are being used to protect endangered animals from poachers in Africa, to beam internet access to parts of the world never before served, and even as remote flying builders. Drones are helping humans work on projects - from the curious to the comical - that wouldn't have been possible without the small autonomous aircraft. Read on to learn about some of the most amazing ways drones are helping people and the planet.

The following is the text of a talk I gave in San Francisco on December 1st, 2016. The audience was readers of my newsletter, Exponential View. You can sign up here. This is a long (7,500 word) transcript of the talk. You can scan it to see the slides and accompanying exhibits if that is easier. Or even read it in more than one sitting…. Exponential View has a purpose. In between all the emojis and all the spelling mistakes, this is what it's about: This is me on my first day at school back when I was in Zambia in sub-Saharan Africa. On the right is my friend Rehan, who I reconnected recently through Facebook. He is now known as Dr. Freeze and he does non-invasive body sculpting in Orange County. So I can get you a good rate. But I think it's important, this starting point is important. We often are inspired from where we come from and what the hell was I doing in Zambia? My dad was trained as economist and accountant, well he is retired now, but then he was an economist and was down in Zambia building the kind of institutions that we take for granted in countries like the U.S. and the U.K. to make the country function. Zambia had just got independence from the U.K. It needed a deeper civil service, it was having to build its legal system, create its system of distribution and so on. So I got an early exposure to the importance of economic institutions for making societies wealthier and making them work. While I was down in Zambia, which is a land-locked country and doesn't have great access to the sea and this is the 1970s, so we didn't have a vast range of toys.

Internet of Things (IoT) has brought everything connected through internet. Increase application of smart devices are enabling us to collect big data on a regular basis. The data gathered are becoming more complex and uncertain and therefore artificial intelligence (AI) came into picture. AI can efficiently deal with the difficulties created by big data. Artificial Intelligence is basically the simulation of logical human thinking using computer technology.

Factorizing low-rank matrices has many applications in machine learning and statistics. For probabilistic models in the Bayes optimal setting, a general expression for the mutual information has been proposed using heuristic statistical physics computations, and proven in few specific cases. Here, we show how to rigorously prove the conjectured formula for the symmetric rank-one case. This allows to express the minimal mean-square-error and to characterize the detectability phase transitions in a large set of estimation problems ranging from community detection to sparse PCA. We also show that for a large set of parameters, an iterative algorithm called approximate message-passing is Bayes optimal. There exists, however, a gap between what currently known polynomial algorithms can do and what is expected information theoretically. Additionally, the proof technique has an interest of its own and exploits three essential ingredients: the interpolation method introduced in statistical physics by Guerra, the analysis of the approximate message-passing algorithm and the theory of spatial coupling and threshold saturation in coding. Our approach is generic and applicable to other open problems in statistical estimation where heuristic statistical physics predictions are available.

Missing records are a perennial problem in analysis of complex data of all types, when the target of inference is some function of the full data law. In simple cases, where data is missing at random or completely at random (Rubin, 1976), well-known adjustments exist that result in consistent estimators of target quantities. Assumptions underlying these estimators are generally not realistic in practical missing data problems. Unfortunately, consistent estimators in more complex cases where data is missing not at random, and where no ordering on variables induces monotonicity of missingness status are not known in general, with some notable exceptions (Robins, 1997), (Tchetgen Tchetgen et al, 2016), (Sadinle and Reiter, 2016). In this paper, we propose a general class of consistent estimators for cases where data is missing not at random, and missingness status is non-monotonic. Our estimators, which are generalized inverse probability weighting estimators, make no assumptions on the underlying full data law, but instead place independence restrictions, and certain other fairly mild assumptions, on the distribution of missingness status conditional on the data. The assumptions we place on the distribution of missingness status conditional on the data can be viewed as a version of a conditional Markov random field (MRF) corresponding to a chain graph. Assumptions embedded in our model permit identification from the observed data law, and admit a natural fitting procedure based on the pseudo likelihood approach of (Besag, 1975). We illustrate our approach with a simple simulation study, and an analysis of risk of premature birth in women in Botswana exposed to highly active anti-retroviral therapy.

LONDON – Drones delivering blood and medicine to rural areas of Tanzania could help to save the lives of many mothers and newborn babies in a country where one of the biggest causes of maternal deaths is blood loss during childbirth, the U.K. aid department said. The Department for International Development (DFID), which has given funding for the trial due to start early next year, said the drone deliveries could assist more than 50,000 births a year in the East African country. The drones will be able to carry up to 1 kg (2 pounds) of medical supplies and reduce delivery times to 19 minutes from the 110 minutes it takes on average by vehicle. "The U.K. is at the forefront of investing in cutting-edge technology to tackle the global challenges of today such as disease pandemics, medical emergencies and disaster responses," said Priti Patel, U.K.'s international development secretary. "This innovative, modern approach ensures we are achieving the best results for the world's poorest people and delivering value for money for British taxpayers," she said in a statement Thursday.