BOGOTA/CARACAS – A former Venezuelan municipal police chief and anti-government activist says he helped organize an operation to launch armed drones over a military rally on Saturday that President Nicolas Maduro has called an assassination attempt. In an interview, Salvatore Lucchese, a Venezuelan activist who was previously imprisoned for his role in past protests, told Reuters he orchestrated the attack with a loose association of anti-Maduro militants known generally in Venezuela as the "resistance." The "resistance" referred to by Lucchese is a diffuse collection of street activists, student organizers and former military officers. It has little formal structure, but is known in the country mostly for organizing protests in recent years in which demonstrators have clashed with police and soldiers. Reuters could not independently verify Lucchese's claims about the attack, in which drones flew over the rally in central Caracas.

Drone industry and law-enforcement officials are struggling to find common ground over expanding flights and protecting public safety, a debate thrust into the public spotlight by a reported assassination attempt on Venezuelan President Nicolás Maduro. The Federal Aviation Administration is projecting a fourfold increase, from more than 110,000 currently, in the number of commercial drones flying in U.S. skies in the next five years. U.S. law-enforcement officials, however, want to delay widespread operations until reliable defensive systems are developed. Saturday's attack with unmanned aircraft in Caracas was a reminder for the drone industry and U.S. government officials over the potential security threats even readily available commercial drones can pose. Venezuelan authorities said a pair of explosive-laden drones carrying a total of about 4 pounds of plastic explosives were part of an unsuccessful assassination attempt during an outdoor ceremony in Caracas, with one of the vehicles detonating after government jamming devices knocked it off course.

The 2020 Summer Olympics in Tokyo will deploy a facial recognition system to identify more than 300,000 athletes, staff, volunteers, and journalists at the games. It's the first time that facial recognition technology will be used for security at the Olympics. The planned system is supposed to address several unique security considerations for the upcoming games. Unlike many previous Olympics, Tokyo will not have a centralized Olympic Park in which athletes and others can travel freely between the main facilities--instead, the 2020 Games will be spread out across the Tokyo metropolitan area. Given that setup, people will need to authenticate their identities at more than 40 venues across the city, which could potentially lead to longer wait times to enter the facilities.

The world of an 80s teenager was one of arcade machines, LPs and Nintendo game consoles. And now you can step back in time and enter that world thanks to a computer museum that has recreated it using a series of fascinating exhibitions. They include an 80s classroom with'state-of-the-art' Apple IIe computers, a'friend's basement' that contains wood-panelled walls and a classic Nintendo Entertainment System (NES) console, and a videogame arcade. A typical basement from the 1980s has been recreated at the Living Computers: Museum Labs in Seattle. There is also a 1980s classroom packed with Apple IIe computers.

Artificial intelligence is being credited for helping Hong Kong customs officials increase seizures of fake goods sold online by about one-third in the first six months of this year, resulting in a haul of counterfeit items worth HK$1.96 million (US$247,000). A new supercomputer they began using last December scoured websites 24 hours a day and detected close to 2,000 of the 5,200 items seized by the Customs & Excise Department. Over the same period last year, officers netted 11,800 pieces of counterfeit goods worth HK$1.47 million. A source said the department might look into expanding the capacity of the computer, which gathers important information during investigations, but he stressed it would complement rather than replace manual enforcement work by customs officers. "The analytics tool saves us a lot of time screening online platforms manually," the source said.

Stories of how students and developers get started in applied machine learning are an inspiration. In this post, you will hear about Álvaro Lemos story and his transition from student to getting a machine learning internship. I'm from Salvador, Bahia (Brazil), but currently, I live in Belo Horizonte, Minas Gerais (also in Brazil). I am studying Electrical Engineering at the Federal University of Minas Gerais and since the beginning of my undergraduation course, I've been involved with software development in some way. On my first week as a freshman, I joined a research group called LabCOM to help a colleague on his master's degree project.

In automatic speech recognition (ASR) what a user says depends on the particular context she is in. Typically, this context is represented as a set of word n-grams. In this work, we present a novel, all-neural, end-to-end (E2E) ASR sys- tem that utilizes such context. Our approach, which we re- fer to as Contextual Listen, Attend and Spell (CLAS) jointly- optimizes the ASR components along with embeddings of the context n-grams. During inference, the CLAS system can be presented with context phrases which might contain out-of- vocabulary (OOV) terms not seen during training. We com- pare our proposed system to a more traditional contextualiza- tion approach, which performs shallow-fusion between inde- pendently trained LAS and contextual n-gram models during beam search. Across a number of tasks, we find that the pro- posed CLAS system outperforms the baseline method by as much as 68% relative WER, indicating the advantage of joint optimization over individually trained components. Index Terms: speech recognition, sequence-to-sequence models, listen attend and spell, LAS, attention, embedded speech recognition.

This work focuses on support vector machine (SVM) with feature selection. A MILP formulation is proposed for the problem. The choice of suitable features to construct the separating hyperplanes has been modelled in this formulation by including a budget constraint that sets in advance a limit on the number of features to be used in the classification process. We propose both an exact and a heuristic procedure to solve this formulation in an efficient way. Finally, the validation of the model is done by checking it with some well-known data sets and comparing it with classical classification methods.

The Venezuelan government's account of Saturday's attempted assassination-by-drone of President Nicolás Maduro has raised more questions than it has answered. Here's what we know: A video of the event shows the chaos that ensued when the drones exploded, with Maduro abruptly stopping his speech and soldiers in the crowd fleeing. The president was unharmed, but seven National Guard soldiers were injured. Hours later, Maduro appeared on national television to accuse the outgoing Colombian president, Juan Manuel Santos, and far-right elements in the U.S. of plotting the alleged attack. A little-known group called "Soldados de Franelas" claimed responsibility for the attack on Twitter. The group regularly posts anti-Maduro content but little else is known about them.

Maduro, whose approval ratings hover around 25 percent, with opponents blaming his policies for worsening an economic meltdown, has called government supporters to unite in the face of what he described as right-wing plots led by the neighboring Colombian government and exiles in the United States.