Tags “This is one of the most extraordinary black hole systems I’ve ever come across,” explained Associate Professor James Miller-Jones, lead author of a study recently published in Nature.”Like many black holes, it’s feeding on a nearby star, pulling gas away from the star and forming a disk of material that encircles the black hole and spirals towards it under gravity.”What’s different in V404 Cygni is that we think the disk of material and the black hole are misaligned.”This appears to be causing the inner part of the disk to wobble like a spinning top and fire jets out in different directions as it changes orientation.” Think of the black hole in V404 Cygni as a gigantic, light consuming Beyblade that’s starting to run out of juice. It’s no longer spinning straight, it’s wobbling all over the place.You can read more about the ground breaking discovery here, at ICRAR’s official website. Post a comment 14 genius Stephen Hawking quotes that will make you question your place in the universe (pictures) Trippy. ICRAR The year 2019 has been a big one for black holes. To begin with, we saw one for the first time. We also discovered 83 of them at the edge of our universe. No big deal.Now recent research is uncovering more about the insanely dense, spacetime bending bad boys of the universe. Get this: while most black holes are thought to “spin” (thanks to the space dust and gas in orbital motion around the black hole) scientists have discovered a black hole that does things a little differently.V404 Cygni is a binary system in the constellation of Cygnus. At its center is a black hole that is currently in the process of absorbing a low mass nearby star. Astronomers from the International Centre for Radio Astronomy Research in Perth, Western Australia noticed that the black hole in V404 Cygni was spitting out bright jet beams of matter into space. That’s relatively normal, what wasn’t normal was the direction the matter was being sprayed. As a result of the way black holes normally spin, the matter tends to spray out in the same direction. This time it was being sprayed out at different angles. The jets appear to be rapidly rotating.You can see this visualized in the below animation. The conclusion: this black hole is spinning a little differently than the rest. 0 Share your voice 14 Photos Sci-Tech
People chant slogans and hold signs to condemn the rape and killing of 7-year-old girl Zainab Ansari in Kasur, during a protest in Peshawar, Pakistan. Photo: ReutersTwo civilians were killed when officers fired live rounds to disburse crowds that attacked a police station in Pakistan on Wednesday in a protest over the rape and murder of a 7-year-old girl.Police recovered the body of Zainab Ansari on Tuesday from a garbage dumpster in the town of Kasur in eastern Pakistan, four days after she was reported missing.It was the twelfth incident of a girl being adducted, raped, and killed in the past year in Kasur district, police say. Residents have been furious at the authorities for what they see as a failure to investigate such cases.The spokesman for Pakistan’s Punjab province, Malik Muhammad Ahmad Khan, told Reuters that protesters turned violent and attacked a local police office.”They started throwing stones at the office and some of armed protesters shot bullets at police. In order to stop them, police resorted to aerial firing,” Khan said, adding that two people were killed and one wounded as a result.Locals said police responded with undue force.”A peaceful protest was taking place, some students threw stones and police responded by firing at the crowd,” Saleem ur Rehman, a resident who was at the protest, told Reuters. “The law and order situation here is really bad and there have been many such incidents. That is what the protest was about.”Ansari’s parents, who were not in the country when their daughter was kidnapped, returned on Wednesday.”I want justice! I want justice!” Zainab’s mother cried, surrounded by reporters at the international airport in the capital Islamabad.Ansari’s case has attracted the attention of the country’s civilian and military leadership, with Punjab Chief Minister Shahbaz Sharif calling for immediate action.Police in Kasur deny they have been lax in investigating child abductions in the town. Regional police officer Zulfiqar Hameed told Reuters that four kidnappers had been arrested and another killed during an arrest attempt.”Investigations reveal that in each case a paedophile kidnaps little girls, rapes them and kills them,” he said.The case of Ansari would soon be solved, he said: “We have got CCTV footage that shows a young man taking her along. We will catch him very soon,” he said, adding that 95 DNA samples had been taken from suspects.A number of police officials have been transferred out of the region for failing to investigate complaints of missing children since 2015, when authorities uncovered what they called a paedophile ring linked to a prominent local family. At least two people have been convicted in the case, in which authorities say hundreds of children in the district were abused.
X Share Al OrtizHouston Mayor Sylvester Turner (center) announces the results of an investigation by the Houston Police Department about the sale of Kush on the city. Houston Police DepartmentKush is typically packaged in shiny and visually appealing bags. Houston Police DepartmentRafeeq Panjvany is one of the two men HPD arrested as a result of this investigation. Houston Police DepartmentNaushad Pradhan is the other man HPD arrested as a result of this investigation.Houston Mayor Sylvester Turner announced Monday the results of an investigation about the sale of synthetic marijuana, which has become an ongoing mission for the Houston Police Department, HPD.Accompanied by HPD’s acting chief Martha Montalvo and Harris County District Attorney Devon Anderson, Turner held a press conference at HPD’s headquarters to inform about the arrest of two men, Naushad Ramzan-AliPradhan (58 years-old) and Rafeeq Panjvany (54 years-old), who have been charged with delivery of synthetic cannabinoids in the 208th State District Court.The investigation began in early July through an anonymous tip and culminated with the arrest of the two men on September 14th.HPD recovered more than 4,000 packages of Kush—the common name of the drug— with a street value of over 400,000 dollars.HPD Sergeant Marsha Todd said they are making progress in the fight against Kush and detailed that “the Narcotics Division right now has made approximately 46 total arrests from various stores and other locations since our Kush initiative began in late June.”“We’ve seized hundreds of pounds of Kush, along with various assets of the proceeds from the sale of these synthetic drugs,” Todd added.Kush has been in the news recently after an incident at Hermann Park, when about ten individuals were taken to local hospitals for overdoses of synthetic marijuana.Turner said Kush has become a national epidemic and Houston is no stranger to its effects.“In the four months since it was created,” the Mayor noted “HPD’s public intoxication team has responded to approximately 600 calls, resulting in nearly 500 individuals taken off the streets and admitted to the City’s sobering centers.”HPD officials emphasize they are trying to go after the suppliers to have a long term effect in their fight against this drug.The public can submit anonymous tips through the website www.stopdrugshouston.org. 00:00 /01:19 Listen To embed this piece of audio in your site, please use this code:
In a paper published on February 4, Google engineers drafted out plans to forward federated learning at a scale. It showcases the high-level plans, challenges, solutions, and applications. Federated learning was first introduced in 2017 by Google. The idea is to use data from a number of computing devices like smartphones instead of a centralized data source. Federated learning can help with privacy Federated learning can be beneficial as it addresses the privacy concern. Android phones are used for the system where the data is only used but never uploaded to any server. A deep neural network is trained by using TensorFlow on the data stored in the Android phone. The Federated averaging algorithm by Brendan McMahan uses a similar approach as synchronous training. The weights of the neural network are combined in the cloud using Federated Averaging. This creates a global model which is then pushed back to the phones as results/desirable actions. To enhance privacy approaches like differential privacy and Secure aggregation are taken. The paper addresses challenges like time zone differences, connectivity issues, interrupted execution etc,. Their work is mature enough to deploy the system in production for tens of millions of devices. They are working towards supporting billions of devices now. The training protocol The system involves devices and the Federated Learning server communicating availability and the server selecting devices to run a task. A subset of the available devices are selected for a task. The Federated Learning server instructs the devices what computing task to run with a plan. A plan would consist a TensorFlow graph and instructions to execute it. There are three phases for the training to take place: Selection of the devices that meet eligibility criteria Configuring the server with simple or Secure Aggregation Reporting from the devices where reaching a certain number would get the training round started Source: Towards Federated Learning at Scale: System Design The devices are supposed to maintain a repository of the collected data and the applications are responsible to provide data to the Federated Learning runtime as an example store. The Federated Learning server is designed to operate on orders of many magnitudes. Each round can mean updates from devices in the range of KBs to tens of MBs coming going the server. Data collection To avoid harming the phone’s battery life and performance, various analytics are collected in the cloud. The logs don’t contain any personally identifiable information. Secure aggregation Secure aggregation uses encryption to make individual device updates uninspectable. They plant to use it for protection against threats in data centers. Secure aggregation would ensure data encryption even when it is in-memory. Challenges of federated learning Compared to a centralized dataset, federated learning poses a number of challenges. The training data is not inspectable, tooling is required to work with proxy data. Models cannot be run interactively and must be compiled to be deployed in the Federated Learning server. Model resource consumption and runtime compatibility also come into the picture when working with many devices in real-time. Applications of Federated Learning It is best for cases where the data on devices is more relevant than data on servers. Ranking items for better navigation, suggestions for on-device keyboard, and next word prediction. This has already been implemented on Google pixel and Gboard. Future work is to eliminate bias caused be restrictions in device selection, algorithms to support better parallelism (more devices in one round), avoiding retraining already trained tasks on devices, and compression to save bandwidth. Federated computation, not federated learning The authors do no mention machine learning explicitly anywhere in the paper. They believe that the applications of such a model are not limited to machine learning. Federated Computation is the term they want to use for this concept. Federated computation and edge computing Federated learning and edge computing are very similar, there are but subtle differences in the purpose of these two. Federated learning is used to solve problems with specific tasks assigned to endpoint smartphones. Edge computing is for predefined tasks to be processed at end nodes, for example, IoT cameras. Federated learning decentralizes the data used while edge computing decentralizes the task computation to various devices. For more details on the architecture and its working, you can check out the research paper. Read next Technical and hidden debts in machine learning – Google engineers’ give their perspective Researchers introduce a machine learning model where the learning cannot be proved What if AIs could collaborate using human-like values? DeepMind researchers propose a Hanabi platform.