Dramatic drone footage showing an previous unknown and uncontacted indigenous tribe living deep in the Brazilian jungle has been seen for the first time. The video was shot from above a vast area of dense Amazon rainforest in the far west of northern Brazil. The images show a group of 16 indigenous people from a tribe which, according to the Brazilian agency for native tribes, Funai, has never had any contact with the outside world. The photos, as well as the drone footage, were taken in 2017, and has now been released. The video and photographs were taken during an expedition in 2017, but have only been released now.

Artificial intelligence has swept the board with humans in games like chess and Go, but taking on e-sports might be a step too far -- for now. At The International tournament last night in Vancouver, a team of human pro gamers defeated a team of AI bots at the battle arena game Dota 2. The victory for team human was decisive but by no means inevitable, with the AI players putting up a valiant fight. And with two more games to play this week, machine might yet triumph over humanity. The bots were the creation of OpenAI, a non-profit research lab founded by tech luminaries such as SpaceX CEO Elon Musk. The lab's main goal is to develop artificial intelligence that "benefits all of humanity," but teaching bots to play Dota has been an important research task for some time now.

One way to measure progress in artificial intelligence is to chart victories by algorithms over champions of increasingly challenging games--checkers, chess, and, in 2016, Go. On Wednesday, five bots sought to extend AI's mastery to e-sports, in the fantasy battle game Dota 2. They failed, as a team of pro gamers from Brazil called paiN defended humanity's honor--for now. A crowd of thousands in Vancouver's hockey arena watched the bots battle paiN over 52 tense minutes packed with spells and firebolts. The human-machine contest was a side event to The International, a Dota 2 tournament that boasts the biggest purse in e-sports, at $25 million. The five bots that lost Wednesday were created by OpenAI, a research institute cofounded by Tesla CEO Elon Musk to work towards human-level artificial intelligence, and make the technology safe.

The International In the past hour, OpenAI's artificially intelligent bots lost their first match against professional players at smash-hit computer game Dota 2 at The International – the video game's annual championship tournament. It's the first bout in a best-of-three competition between human professional players versus OpenAI's code, the other two rounds will take place over the next two days, each day a different human team. Thousands of hardcore Dota fans lit up by glowing bracelets sat down at the Rogers Arena in Vancouver, Canada, to watch pros battle against a machine running OpenAI's software in this first round. The humans – dubbed Team paiN – were five players from Brazil, while OpenAI Five is made up five long-short-term memory neural-network-based agents. Dota 2 is a popular battle strategy game played online.

RIO DE JANEIRO – New aerial images give a rare glimpse of an isolated tribe in Brazil's Amazon, showing 16 people walking through jungle as well as a deforested area with a crop. In a clip released Tuesday night, one of the tribespeople appears to be carrying a bow and arrow. Brazil's agency for indigenous affairs, Funai, said it captured the drone shots during an expedition last year to monitor isolated communities, but only released them now to protect their study. Researchers monitored the tribe in Vale do Javari, an indigenous territory in the southwestern part of the state of Amazonas. There are 11 confirmed isolated groups in the area -- more than anywhere else in Brazil.

Bruno Pereira, who coordinates Funai's study of isolated groups in the region, said these documentations also help researchers study their culture. The agency has not yet been able to identify the name of the tribe, though it has guesses about its ethnicity and what language it speaks.

This paper addresses the problem of mapping natural language text to knowledge base entities. The mapping process is approached as a composition of a phrase or a sentence into a point in a multi-dimensional entity space obtained from a knowledge graph. The compositional model is an LSTM equipped with a dynamic disambiguation mechanism on the input word embeddings (a Multi-Sense LSTM), addressing polysemy issues. Further, the knowledge base space is prepared by collecting random walks from a graph enhanced with textual features, which act as a set of semantic bridges between text and knowledge base entities. The ideas of this work are demonstrated on large-scale text-to-entity mapping and entity classification tasks, with state of the art results.

Technology experts have uncovered a vast misinformation campaign attempting to spread stories on a hugescale. Facebook, and Twitter have found and removed hundreds of accounts that were apparently set up to target users in the US, UK, Latin America and the Middle East. But it is not clear what the campaign was being used for. The accounts appear to have been tied to Iranian actors and cybersecurity firms said they had appeared to be promoting Iran's geopolitical agenda around the world. But whether the campaign was being set up to launch any more specific or targeted attack remains unclear.

LIMA – Small, camera-carrying robots helped archaeologists in Peru discover three new underground passageways holding ceramics, tools and human remains at the more than 3,000 year-old Chavin de Huantar temple in the Andes, Peru's culture ministry said. The robots, remote-controlled all-terrain vehicles carrying lights and cameras, were designed by engineers at the University of Stanford and helped explore narrow passageways at the ancient site, the ministry added. One of the passageways contained the remains of three people, including one who appears to have been sacrificed, John Rick, an archaeologist with the University of Stanford, told journalists at Chavin de Huantar on Monday. Chavin de Huantar was once a religious and administrative center for people across the Andes. It was named after the Chavin people who grew crops in Peru's central Andes more than 2,000 years ago.

In this paper, we study how to make clustering benefiting from differentiable programming whose basic idea is treating the neural network as a language instead of a machine learning method. To this end, we recast the vanilla $k$-means as a novel feedforward neural network in an elegant way. Our contribution is two-fold. On the one hand, the proposed \textit{k}-meansNet is a neural network implementation of the vanilla \textit{k}-means, which enjoys four advantages highly desired, i.e., robustness to initialization, fast inference speed, the capability of handling new coming data, and provable convergence. On the other hand, this work may provide novel insights into differentiable programming. More specifically, most existing differentiable programming works unroll an \textbf{optimizer} as a \textbf{recurrent neural network}, namely, the neural network is employed to solve an existing optimization problem. In contrast, we reformulate the \textbf{objective function} of \textit{k}-means as a \textbf{feedforward neural network}, namely, we employ the neural network to describe a problem. In such a way, we advance the boundary of differentiable programming by treating the neural network as from an alternative optimization approach to the problem formulation. Extensive experimental studies show that our method achieves promising performance comparing with 12 clustering methods on some challenging datasets.