Tech News

Google has notified users in a support note that they are taking down the Hire by Google service on September 1, 2020. In the vague note, no particular reason has been specified by Google. It simply states, “While Hire has been successful, we’re focusing our resources on other products in the Google Cloud portfolio.” Launched in 2017, the Hire by Google service is an applicant tracking system aimed to assist small to medium businesses (SMBs) for candidate sourcing. Its integrated software (Google Search, Gmail, Google Calendar, Google Docs, Google Sheets and Google Hangouts) makes activities like applicant search, interview scheduling and feedback simpler. A profile on Google Hire, can make a candidate more trackable as recruiters and hiring managers can get more information about the candidate from web sites such as LinkedIn, GitHub, and others. Even an email communication with the candidate is tracked on the candidate profile available on Google Hire. Until now, Hire was only available to companies in the United States, United Kingdom and Canada. In the FAQs following the note, Google has said that no new functionalities will be added in the Hire product. It also states that until September 1, 2020, customers under contract will be provided support in accordance with the Technical Support Services Guidelines (TSS) of Hire. “After your next bill, there will be no additional charges for your standard usage of Hire up until the end of your contract term or September 1, 2020, whichever comes first”, adds the note. It also specifies that closing down of Hire will have no impact on user’s G Suite agreement. Which other Google products have been shut down Google’s decision to shut down its own projects is not new. Two months ago, Google announced that it was shutting down the Trips app which was a substitute for Inbox's trip bundling functionality. This news came after the community favorite Google Inbox was discontinued in March 2019. In April this year, Google also ceased and deleted all user accounts on its Google+ social network platform. Per Verge, the reason behind the closure of Google+ was the security liabilities the social network posed. It suffered two significant data leaks causing millions of Google+ users’ data at risk. Though Google stated that Google+ failed to meet the company’s expectations of user growth and mainstream pickup as the reason for its packup. In May, another popular Google product, Works with Nest was given an end date of August 30, 2019. This was the result of Google’s plan of action to bring all the Nest and Google Home products under one brand ‘Google Nest’. With an aim to make its smart home experience more secure and unified for users, all the Nest account users were asked to migrate to Google Accounts, as it is the only serving front-end for using products across Nest and Google. This decision of phasing out Works with Nest had made many Nest products users’ infuriated back then. Read Also: Turbo: Google’s new color palette for data visualization addresses shortcomings of the common rainbow palette, ‘Jet’ With this trend of killing its own products, Google is gaining a lot of negative campaigning. Many people are of the opinion that Google’s side projects cannot be trusted for long term adoption. A user on Hacker News comments, “What is humorous to me is that Google is hurting users who typically have the most influence over SaaS integrations at their company (managers) by taking away a tool that helped them deal with the part of their job most of them hate the most (hiring/recruiting). If it hasn't been obvious yet to managers watching this, Google's software is not a safe investment for you to make for your company. It is only a matter of time until you will suddenly have to divert your time to figuring out how to migrate away from a Good Tool to a Less Good Tool because Google built it well then took it away.  Swapping a tool like this is an abysmal resource sink for you and your company. This is not the first, second, third, fourth or even fifth time this has happened, but this one should hit close to home. Google's software is not a safe investment for you to make for your company.” Many are wondering if Hire was really successful as stated by Google, then what could be the reason behind its shut down. Another comment on Hacker News reads, “Why do they cancel this product? Are they losing profit over this? Were they working on any new features? If no new features are required, would it be such a hassle to just keep the product working without assigning engineers to it? Only support?” Interested users can read the FAQs in the Google support page to know more information. Google Chrome 76 now supports native lazy-loading Google confirms and fixes 193 security vulnerabilities in Android Q Cisco Talos researchers disclose eight vulnerabilities in Google’s Nest Cam IQ indoor camera

At the MariaDB OpenWorks held earlier this week, MariaDB CEO Michael Howard took a stab at big proprietary cloud vendors and accused them of "strip-mining open-source technologies and companies," and “abusing the license and privilege, not giving back to the community." His keynote at the event described his plans for MariaDB, the future of MariaDB, and how he plans for MariaDB on becoming an ‘heir to Oracle and much more’. Furthermore, the entire keynote saw instances of Howard targeting his rivals- namely Amazon and Oracle- and comparing MariaDB mottos to its rivals. "We believe proprietary and closed licenses are dead. We believe you have to be a general-purpose database and not a relegated niche one, like--and nothing against it--time series. That's not going to be a general purpose database that will drive applications worldwide." MariaDB is an example of such a database. Accusations on Oracle and Amazon AWS Targeting Oracle, Howard said, "Now, you can migrate complex operational Oracle systems to MariaDB. Last year, we had one of the largest banks--Development Bank of Singapore--in the world forklift from Oracle to MariaDB. Since then, MariaDB has seen five times the number of Oracle migrations happening over the last year." Howard has also accused Amazon’s AWS of promoting its brand and making MariaDB instances on AWS look incompetent in the process. When Austin Rutherford, MariaDB's VP of Customer Success, showed the audience the result of a HammerDB benchmark on AWS EC2, AWS's default MariaDB instances did poorly. The AWS homebrew Aurora, which is built on top of MySQL, consistently beat the former database. The top-performing DBMS was MariaDB Managed Services on AWS. While these results initially were not a major cause of concern, Howard observed that one of the biggest retail drug companies in the world-and a MariaDB customer-had told MariaDB that "Amazon offers the most vanilla MariaDB around. There's nothing enterprise about it. We could just install MariaDB from source on EC2 and do as well." It was then that he "began to wonder, Is there something that they're deliberately crippling?" Further adding “There is something not kosher happening." Comparing MariaDB to Aurora, Howard said, "The best Aurora can do in a failover is 12 seconds. MariaDB can do it less than a second." ‘Heir to Oracle’ In his keynote, he speaks about making MariaDB the 'heir apparent' to Oracle, even including a checklist of what needs to be achieved to be that 'drop-in' replacement for the market-leading database. Source: Computerworld UK According to The Register, just last year, MariaDB released an Oracle compatibility layer, which allows customers to migrate their applications from Oracle to MariaDB, and also use their internal skills. “All these Oracle application developers and people familiar with Oracle – you can’t just say ‘jump off a cliff onto new ground’; you have to give them a bridge. Sometimes that’s emotional, sometimes it’s technical.” “It was so jarring to the proprietary vendors who pride themselves on secrecy, on taking advantage – at least monetarily, in the margins sense – from customers,” he said. “Open-source destroys these artificial definitions and boundaries that have been so, so much a part of the software industry.” Speaking to Computerworld UK , Howard further explained his views on the big cloud vendors. "Oracle as the example of on-premise lock-in and Amazon being the example of cloud lock-in. You could interchange the names, you can honestly say now that Amazon should just be called Oracle Prime, they have gone so aggressive. Fortunately or unfortunately, depending on whose position you want to take, it's all good for MariaDB because we can act as consumer protection. We are going to protect the brand quality and technical quality of our product no matter where it sits." Red Hat Satellite to drop MongoDB and will support only PostgreSQL backend Red Hat drops MongoDB over concerns related to its Server Side Public License (SSPL) GNU Health Federation message and authentication server drops MongoDB and adopts PostgreSQL

Last month, the Guardian reported that Apple contractors regularly listen to confidential medical information, drug deals, and personal recordings of couples, as part of their job via Siri’s recordings. The contractors are responsible for grading Siri’s responses on a variety of factors such as checking if the activation of the voice assistant was deliberate or accidental,  if the query was something Siri was expected to help with and whether Siri’s response was appropriate. As per the report by the Guardian, one of the Apple contractors explained the grading process. In the grading process, the audio snippets are taken which are not connected to names or IDs of individuals and contractors are made to listen to them in order to check whether Siri is accurately hearing them or Siri may have been invoked by mistake. In a statement to the Guardian, Apple said, “A small portion of Siri requests are analysed to improve Siri and dictation. User requests are not associated with the user’s Apple ID. Siri responses are analysed in secure facilities and all reviewers are under the obligation to adhere to Apple’s strict confidentiality requirements.”  Additionally, Apple said that the data “is used to help Siri and dictation … understand you better and recognise what you say.” Siri can also accidentally get activated when it by mistakenly hears the word ‘wake’ or the phrase “Hey Siri”. The Apple contractor explained, “The sound of a zip, Siri often hears as a trigger.” This month, Apple has planned to suspend Siri’s response grading and review the process, this might be the company’s counter move against this report by the Guardian. Apple will also be issuing a software update in the future that will give Siri users a choice to choose whether they participate in the grading process or not.  In a statement to TechCrunch, Apple said, “We are committed to delivering a great Siri experience while protecting user privacy.” The company further added, “While we conduct a thorough review, we are suspending Siri grading globally. Additionally, as part of a future software update, users will have the ability to choose to participate in grading.” Companies like Amazon and Google have also come into the radar because of involving humans for monitoring their automatic voice assistants. There were reports that stated that Amazon’s staff was listening to some of Alexa’s recordings. And there was a similar incident that happened with Google Assistant. This month, Amazon came up with an option to disable the human review of Alexa recordings. It seems users might appreciate if they are asked for their consent before their personal recordings get monitored. Also, these recordings get stored on the server and if any incident of data breach takes place or if a malicious attacker targets the server or datacenter, there is a high possibility of such data getting into the wrong hands. And this might make us think if our personal data is really secure? In a recent Threatpost Podcast on voice assistant privacy issues, Tim Mackey, principal security strategist at cybersecurity research center at Synopsys said, “The biggest concern that I have is actually around data retention policies and disclosure.”  Mackey further added, “So we have an expectation that these are connected devices, and that perhaps short of the Alexa-then-perform-action activity, that the communication, the actual processing of our request is going to occur on an Amazon server, Google server or so forth…. And what we’re learning is that the providers tend to keep this data for an indeterminate amount of time. And that’s a significant risk, because the volume of data itself means that it’s potentially very interesting to a malicious actor someplace who wishes to say, target an individual.” Apple acquires Pullstring to possibly help Apple improve Siri and other IoT-enabled gadgets Apple joins the Thread Group, signaling its Smart Home ambitions with HomeKit, Siri and other IoT products Apple previews macOS Catalina 10.15 beta, featuring Apple music, TV apps, security, zsh shell, driveKit, and much more!        

In what could mark a major leap in cancer detection by artificial intelligence, researchers at Showa University in Yokohama, Japan, have developed an AI software that they claim can spot bowel cancer in less than a second. In a recently conducted trial, the AI system was successfully able to pinpoint potentially dangerous tumours from endoscopy images with clinical accuracy. Led by Dr. Yuichi Mori, the study involved 250 men and women in whom colorectal polyps had been detected using endocytoscopy. In total 306 polyps were assessed, and scientists used the AI program to predict the pathology of each polyp. The predictions were then compared with the final pathological report, and it was found that the system correctly detected 94% of cancers by matching each growth against over 30,000 images that were used for machine learning. What is remarkable is that it took the program less than a second to review each magnified endoscopic image and determine whether or not the polyp was malignant. “The most remarkable breakthrough with this system is that artificial intelligence enables real-time optical biopsy of colorectal polyps during colonoscopy, regardless of the endoscopists' skill,” Mori said. While the diagnostic system is yet to obtain the regulatory approval, Mori believes it could really help patients do away with needless surgeries. “This allows the complete resection of adenomatous (cancerous) polyps and prevents unnecessary polypectomy (removal) of non-neoplastic polyps,” he said. The findings were also presented at the ongoing United European Gastroenterology (UEG) Week in Barcelona, Spain. The research team is now working full throttle on this project, and they plan to take the study to a new level by developing an automatic polyp detection system. "Precise on-site identification of adenomas during colonoscopy contributes to the complete resection of neoplastic lesions" Mori added. "This is thought to decrease the risk of colorectal cancer and, ultimately, cancer-related death."

Back in June, OpenAI Five, the artificial intelligence bot team, had smashed amateur humans in the video game Dota 2.  But, this time it set a completely different standard by beating semi-professional players at the Dota 2 game, yesterday. This was part of an effort to benchmark the progress of the bots so far as the openAI team plans to beat a team of top professionals at The International Dota 2 championship, taking place from August 20 to 25. As mentioned in the OpenAI blog, “Dota 2 is one of the most popular and complex esports games in the world, with creative and motivated professionals who train year-round to earn part of Dota’s annual $40M prize pool (the largest of any esports game)”. It requires its players to have fast-twitch reflexes, strong knowledge of game strategies, along with solid teamwork. OpenAI Five fight as a group and consists of five neural networks. The game started off with OpenAI Five playing warm-up games with the audience. Later, the OpenAI Five team played a three-game series, against a group of humans, that included former Dota 2 professionals and casters, Merlini, Fogged, Cap, and Blitz. The OpenAI Five performed really well in the first two games. For the final game, the OpenAI team let the audience select their team of five heroes, which handicapped the bots’ chances of winning. Humans won the last round, finishing the series with a score of 2-1. According to the OpenAI blog, “OpenAI Five plays 180 years worth of games against itself every day, learning via self-play. It trains using a scaled-up version of Proximal Policy Optimization running on 256 GPUs and 128,000 CPU cores”. Proximal Policy Optimization ( PPO ) refers to a new class of reinforcement learning algorithms. It has become the default algorithm of choice for OpenAI as it is easy to implement and performs well. It involves “computing an update at each step that minimizes the cost function”. The OpenAI team had made small changes to their neural network bot last month. This included increasing its reaction time and using new strategies. This is not the first time when a computer has beaten human beings in games. From computers beating humans at chess to computers winning debates against humans, the chances of OpenAI Five beating professionals at The International does not seem that low. But what has set apart OpenAI Five’s achievement from the rest is its ability to optimize strategies well in a team as opposed to simply learn to master strategies as individual players. If you enjoyed reading this, be sure to check out the entire account on twitch, Dota 2 game: OpenAI Five vs Humans. Alibaba introduces AI copywriter AI beats Chinese doctors in a tumor diagnosis competition Meet CIMON, the first AI robot to join the astronauts aboard ISS

An announcement post yesterday said that Rust 2018 beta is now in the final phase before release. A new beta has just been released with updates. After bug fixes, the final release will take place on December 6. In comparison to the Rust 2018 Edition Preview 2, the new Rust 1.31.0 beta includes all of the features stabilized in v1.31.0 207 and many bug fixes. Those new features are as follows. Changes in Rust Beta The new lifetime elision rules now allow eliding lifetimes in functions and impl headers. Lifetimes are still needed to be defined in structs. const functions can now be defined and used. These const functions right now are a strict minimal subset of the const fn RFC. Tool lints can now be used, which allow scoping lints from external tools by using attributes. With this release, the #[no_mangle] and #[export_name] attributes can be located anywhere in a crate. Previously they could only be located in exported functions. Parentheses can now be used in pattern matches. The compiler change includes updating musl to 1.1.20. There are some library changes and API stabilizations. Now, cargo will download crates in parallel using HTTP/2 protocol. The packages in Cargo.toml can also be renamed now. You can know more about these changes on GitHub. Changes in tooling Rust Beta 2018 also includes a number of improvements in the area of tooling. Rustfmt is now at version 1.0. RLS and Clippy will no longer be installed via “preview” components after a rustup update. The developers have listed two focus areas to find the bugs, namely the module system implementation and the RLS. Work for next release In Rust Preview 2, two variants for the module system were evaluated—“anchored paths” vs “uniform paths”. This evaluation continues in this beta release. This means that the compiler accepts only code that both variants would accept. You can read the announcement post for more details. Rust 2018 RC1 now released with Raw identifiers, better path clarity, and other changes GitHub Octoverse: The top programming languages of 2018 Red Hat announces full support for Clang/LLVM, Go, and Rust

On 1st October, Neo4j was rewarded with an $80 million Series E to bring their products to a wider market. This could possibly be the companies last private fundraise. In 2016, the company got a $36 million Series D investment. Neo4j has been successful with around 200 enterprise customers to their credit including Walmart, UBS, IBM and NASA with customers from 20 of the top 25 banks and 7 of the top 10 retailers. The round for series E was led by One Peak Partners and Morgan Stanley Expansion Capital with participation from existing investors Creandum, Eight Roads and Greenbridge Partners. As reported in Techcrunch, this is what he has to say: “If your mental framework is around building a great company, you’re going to have all kinds of options along the way. So that’s what I’m completely focused on,” Eifrem explained. This year, the company was focussed on expanding into artificial intelligence. Since Graph databases help companies understand connections in large datasets and AI involves large amounts of data to drive the learning models, both of them used hand-in-hand will benefit the organization. Eifrem has expressed intentions to use the money to expand the company internationally. He also plans to provide localized service in terms of language and culture wherever their customers happen to be. This news seems to have gone down well with Neo4j users: Source: y combinator Head over to Techcrunch to know more about this news. Why Neo4j is the most popular graph database Neo4j 3.4 aims to make connected data even more accessible From Graph Database to Graph Company: Neo4j’s Native Graph Platform addresses evolving needs of customers

Facebook has been in news in recent years for its data leaks and data privacy concerns. This time the company is on the radar because of the deplorable working conditions of content moderators. The reviewers are so much affected by the content on the platform that they are trying to overcome their PTSD by having sex and getting into drugs at work, reports The Verge in a compelling and horrifying insight into the lives of content moderators who work as contract workers at Facebook’s Arizona office. Last year there was a similar report against Facebook. An ex-employee had filed a lawsuit against Facebook, in September for not providing enough protection to the content moderators who are responsible for reviewing disturbing content on the platform. The platform has millions of videos, images of child sexual abuse, rape, torture, bestiality, beheadings, suicide, and murder. The platform relies on machine learning augmented by human content moderators to keep the platform safe for the users. This means any image that violates the corporation’s terms of use is removed from the platform. In a statement to CNBC, a Facebook spokesperson said, "We value the hard work of content reviewers and have certain standards around their well-being and support. We work with only highly reputable global partners that have standards for their workforce, and we jointly enforce these standards with regular touch points to ensure the work environment is safe and supportive, and that the most appropriate resources are in place." The company has also posted a blog post about its work with its partners like Cognizant and its steps towards ensuring a healthy working environment for content reviewers. As reported by The Verge, the contracted moderators get one 30-minute lunch, two 15-minute breaks, and nine minutes of "wellness time" per day. But much of this time is spent waiting in queues for the bathroom where three stalls per restroom serve hundreds of employees. Facebook’s environment is such that workers cope with stress by telling dark jokes about committing suicide, then smoke weed during breaks to numb their emotions. According to the report, it’s a place where employees can be fired for making just a few errors a week. Even the team leaders give a hard time to the content moderators by micromanaging their bathroom and prayer break. The moderators are paid $15 per hour for moderating content that could range from offensive jokes to potential threats to videos depicting murder. A Cognizant spokesperson said, “The company has investigated the issues raised by The Verge and previously taken action where necessary and have steps in place to continue to address these concerns and any others raised by our employees. In addition to offering a comprehensive wellness program at Cognizant, including a safe and supportive work culture, 24x7 phone support and onsite counselor support to employees, Cognizant has partnered with leading HR and Wellness consultants to develop the next generation of wellness practices." Public reaction to this news is mostly negative with users complaining and condemning how the company is being run. https://twitter.com/waltmossberg/status/1100245569451237376 https://twitter.com/HawksNest/status/1100068105336774656 https://twitter.com/likalaruku/status/1100194103902523393 https://twitter.com/blakereid/status/1100094391241170944 People are angry with the fact that the content moderators at Facebook endure such trauma in their role. Some believe some compensation should be given to those suffering from PTSD as a result of working in certain high-stress roles in companies across industries. https://twitter.com/hypatiadotca/status/1100206605356851200 According to Kevin Collier, a Cyber reporter, Facebook is underpaying and making content moderators overwork in a desperate attempt to reign in abuse of the platform it created. https://twitter.com/kevincollier/status/1100077425357176834 One of the users tweeted, “And I've concluded that FB is run by sociopaths.” Youtube has rolled out a feature in the US that displays notices below videos uploaded by news broadcasters which receive government or public money. Alex Stamos, former Chief Security Officer at Facebook, highlighted something similar but with reference to Facebook. According to him, Facebook needs a state-sponsored label and people should know the human cost of policing online humanity. https://twitter.com/alexstamos/status/1100157296527589376 To know more about this news, check out the report by The Verge. Ex-employee on contract sues Facebook for not protecting content moderators from mental trauma NIPS 2017 Special: Decoding the Human Brain for Artificial Intelligence to make smarter decisions Facebook and Google pressurized to work against ‘Anti-Vaccine’ trends after Pinterest blocks anti-vaccination content from its pinboards  

A few days ago, Alibaba Cloud announced the release of Mars, its tensor-based framework for large-scale data computation. Mars tensor provides a familiar interface like Numpy, which is a popular tool for most of the Python users such as mathematicians, engineers, etc. and the ones working in core scientific computing. Mars can also scale into a single machine, and scale out to a cluster with hundreds of machines. Users can simply install Mars tensor with the following code: import mars.tensor as mta = mt.random.rand(1000, 2000)(a + 1).sum(axis=1).execute() According to a Medium post by Synced, “Mars can simply tile a large tensor into small chunks and describe the inner computation with a directed graph, enabling the running of parallel computation on a wide range of distributed environments, from a single machine to a cluster comprising thousands of machines.” Xuye Qin, Alibaba Cloud Senior Engineer, bragged about Mars’ performance by stating, “Mars can complete the computation on a 2.25T-size matrix and a 2.25T-size matrix multiplication in two hours.” Unlike NumPy, Mars provides users with the ability to run matrix computation at a very large-scale. Alibaba developers carried out a simple experiment to test Mars’ performance. According to the graph below where NumPy (represented by a red cross at the upper left) lags far behind Mars tensors, which is successful in achieving ideal performance values. Source: Medium Mars supports a subset of NumPy interfaces, which include: Arithmetic and mathematics: +, -, *, /, exp, log, etc. Reduction along axes (sum, max, argmax, etc). Most of the array creation routines (empty, ones_like, diag, etc). Mars not only supports create array/tensor on GPU, but also supports create sparse tensor. Most of the array manipulation routines such as reshape, rollaxis, concatenate, etc. Basic indexing (indexing by ints, slices, newaxes, and Ellipsis) Fancy indexing along a single axis with lists or NumPy arrays, e.g. x[[1, 4, 8],:5] Universal functions for elementwise operations. Linear algebra functions including product (dot, matmul, etc.) and decomposition (cholesky, svd, etc.). To know more about Mars in detail, visit its official GitHub page. NumPy drops Python 2 support. Now you need Python 3.5 or later Google researchers introduce JAX: A TensorFlow-like framework for generating high-performance code from Python and NumPy machine learning programs Introducing numpywren, a system for linear algebra built on a serverless architecture

Slack has become a mainstay of many industries - when it goes down, you can be sure you'll know about it. However, for a number of users, Slack access appears to have been revoked. Most of these users have an Iranian background. Mahdi Saleh, a PhD student at the Technical University of Munich, explained on Twitter how Slack had terminated his account "in order to comply with export control and economic sanctions laws and regulations promulgated by the U.S. Department of Commerce and the U.S. Department of Treasury." https://twitter.com/mahdimax2010/status/1075524107847000064 Slack responded quickly on Twitter, explaining that "our systems may have detected an account on our platform with an IP address originating from a designated embargoed country." The company then offered to investigate the issue in detail for Saleh. Saleh said that following the exchange he got in touch with Slack, but has not, at the time of writing, heard back from the company. Other Slack users have had their accounts terminated Saleh says that he does not believe his case is unique: "Apparently I am not the only person outside Iran that this happened to" he said. "A lot researchers [sic] and emigrants got the same email from Slack." A quick Twitter search indicates that this is the case, with a number of users sharing the same message from Slack as the one received by Saleh. "I’m a PhD student in Canada with no teammates from Iran!" said Twitter user @a_h_a. "Is Slack shutting down accounts of those ethnically associated with Iran?! And what’s their source of info on my ethnicity?" https://twitter.com/a_h_a/status/1075510422617219077 The same user also called into question whether the reasons given by Slack are true or accurate. "I’m in Canada. No ties to Iran. No teammates in Iran!" "I wonder how my account was associated with my ethnicity and how/where they digged [sic] this info from," he said. Amir Odidi, a software developer at ipinfo.io said that there was "no way to appeal this decision. No way to prove that I'm not living in Iran and not working with Iranians on slack. Nope. Just hello we're banning your account." https://twitter.com/aaomidi/status/1075621119028314112 These aren't the only cases - there are a huge range of other examples of Iranians based in the U.S. and Canada having their accounts terminated. https://twitter.com/nv_rahimi/status/1075695124561125377 https://twitter.com/bamaro_ir/status/1075667601878061056 "Filter coffee, not people", said one user. Slack responds It's hard to say exactly what's going on. We approached Slack to get their perspective; the company provided us with a statement very similar to the one sent to those users who have had their accounts terminated. It reads: “Slack complies with the U.S. regulations related to embargoed countries and regions. As such, we prohibit unauthorized Slack use in Cuba, Iran, North Korea, Syria and the Crimea region of Ukraine. For more information, please see the US Department of Commerce Sanctioned Destinations, The U.S. Department of Treasury website, and the Bureau of Industry and Security website. “Our systems may have detected an account and/or a workspace owner on our platform with an IP address originating from a designated embargoed country. If our systems indicate a workspace primary owner has an IP address originating from a designated embargoed country, the entire workspace will be deactivated. If someone thinks any actions we took were done in error, we will review further.” What does this tell us about how Slack handles user data? With no clear response from Slack, it isn't exactly clear how this happened. You could take Slack at their word, but given the information given by users on Twitter, there does appear to be a piece missing in this puzzle. However, we probably can say that Slack does have an extensive record that allows them to link accounts to specific countries - whether that's via IP address or something else. As one Twitter user wrote, the story suggests that Slack has "more data than some customs and border agencies." https://twitter.com/rakyll/status/1075691304896606208 This article was updated 12.10.2018 10.25am EST to include Slack's response.

Last week one of the Google Walkout organizers, Claire Stapleton resigned from the company after facing continuous retaliation from the management. Last year in November, a global Google Walkout for Real Change was organized by Claire Stapleton, Meredith Whittaker and six other employees at the company. It prompted 20,000 Google employees and contractors in 50 cities to walk off the job on November 1, 2018, to oppose the company’s handling of sexual harassment allegations. Employees had put together a list of six demands for executives to address what they considered as rampant sexism and racism at the company. Google CEO, Sundar Pichai did agree to make one of the demanded policy changes, to make the workplace conditions stable. Google agreed to get rid of forced arbitration for their employees. On Friday, Google Walkout for Real Change group published a letter on Medium which Stapleton had shared internally to her coworkers. The letter explained her reasons for quitting Google. https://twitter.com/clairewaves/status/1137002800053985280 “These past few months have been unbearably stressful and confusing,” the post said. “But they’ve been eye-opening, too: the more I spoke up about what I was experiencing, the more I heard, and the more I understood how universal these issues are. That’s why I find it so depressing that leadership has chosen to just bluntly refute my story. They have a different version of what happened; that’s how this works.” When the news broke of payouts to executives accused of sexual harassment, Stapleton was inspired to call for the walkout. And since then, Stapleton and other Google employees say supervisors have retaliated against them for speaking out. In the month of April this year they shared stories of retaliation they had been facing. https://twitter.com/GoogleWalkout/status/1136997345416101893 According to The Guardian, Stapleton was a marketing manager who spent 12 years at Google and YouTube. She wrote in an email to coworkers announcing her departure “I made the choice after the heads of my department branded me with a kind of scarlet letter that makes it difficult to do my job or find another one. If I stayed, I didn’t just worry that there’d be more public flogging, shunning, and stress, I expected it.” “The message that was sent [to others] was: ‘You’re going to compromise your career if you make the same choices that Claire made,” she told the Guardian by phone. “It was designed to have a chilling effect on employees who raise issues or speak out.” Stapleton said she was demoted and asked to take medical leave, even though she wasn’t sick. Meredith Whittaker, said she was reassigned and told to stop her well-known research on AI ethics in her capacity as co-founder of AI Now Institute. Both women detailed their experiences in an email to coworkers in April, which was then shared with journalists at Wired. “My manager started ignoring me, my work was given to other people, and I was told to go on medical leave, even though I’m not sick,” Stapleton wrote. “Only after I hired a lawyer and had her contact Google did management conduct an investigation and walked back my demotion, at least on paper. While my work has been restored, the environment remains hostile and I consider quitting nearly every day.” Stapleton believes the treatment and the alleged attempt to push her out of the company were designed to dissuade other employees from taking similar actions. In the Medium post, Stapleton says she was inspired and motivated by Google’s culture during her initial years, but after 2017, she saw the difference in culture and leadership. “Google’s always had controversies and internal debates, but the ‘hard things’ had intensified, and the way leadership was addressing them suddenly felt different, cagier, less satisfying,” she writes. Google has denied the retaliation allegations, saying that any changes to positions were not retaliatory. Stapleton says in her post that the response from management to her story has been “depressing.” “We thank Claire for her work at Google and wish her all the best,” a Google spokesperson said in a statement. “To reiterate, we don’t tolerate retaliation. Our employee relations team did a thorough investigation of her claims and found no evidence of retaliation. They found that Claire’s management team supported her contributions to our workplace, including awarding her their team Culture Award for her role in the Walkout.” Meredith Whittaker said in a tweet that “Google’s trying to stop a movement. But that’s not how it works — badge or no, Claire isn’t going away, nor are the 1000s organizing across the company.” https://twitter.com/mer__edith/status/1137006840313548801 Stapleton said that despite her decision to leave the company, she was optimistic about the future of worker organizing at Google. “I’ve paid a huge personal cost in a way that is not easy to ask anyone else to do,” she said. “There’s a lot of exhaustion and there’s a lot of fear, but I think that speaking up in whatever way people are comfortable with is having an absolutely tremendous impact.” “It’s not going away,” she said. Stapleton’s departure comes amid considerable turmoil for Google and YouTube, which are facing increased antitrust scrutiny from the US government. Google faces increasing criticism over inconsistent and controversial decisions related to content moderation, and growing activism from employees over issues including the company’s treatment of temps, vendors and contractors(TVCs) and choice of controversial projects to work on including Project Maven and Project Dragonfly. An ex-Googler Vida Vakil who was present when the scandal broke at Google last year weighed in saying the head of HR (Eileen Naughton) defended her handling sexual harassment and paying out millions to the offender at the TGIF meeting by rationalising  that things like that happen because it is in human nature. https://twitter.com/VidaVakil/status/1137046293778317313 Ex-Google employee advocate, Liz Fong-Jones, who quit Google earlier this year on ethical grounds, also tweeted that Google is systematically driving out people who care for the company, which is sad for the company. https://twitter.com/lizthegrey/status/1137009160971796481 US regulators plan to probe Google on anti-trust issues; Facebook, Amazon & Apple also under legal scrutiny Google Cloud went offline taking with it YouTube, Snapchat, Gmail, and a number of other web services Is it time to ditch Chrome? Ad blocking extensions will now only be for enterprise users

Yesterday, Google launched the beta version of its Cloud Source Repositories. Claiming to provide its users with a better search experience, Google Cloud Source Repositories is a Git-based source code repository built on Google Cloud. The Cloud Source Repositories introduce a powerful code search feature, which uses the document index and retrieval methods similar to Google Search. These Cloud source repositories can pose a major comeback for Google after Google Code, began shutting down in 2015. This could be a very strategic move for Google, as many coders have been looking for an alternative to GitHub, after its acquisition by Microsoft. How does Google code search work? Code search in Cloud Source Repositories optimizes the indexing, algorithms, and result types for searching code. On submitting a query, the query is sent to a root machine and sharded to hundreds of secondary machines. The machines look for matches by file names, classes, functions and other symbols, and matches the context and namespace of the symbols. A single query can search across thousands of different repositories. Cloud Source Repositories also has a semantic understanding of the code. For Java, JavaScript, Go, C++, Python, TypeScript and Proto files, the tools will also return information on whether the match is a class, method, enum or field. Solution to common code search challenges #1 To execute searches across all the code at ones’ company If a company has repositories storing different versions of the code, executing searches across all the code is exhaustive and ttime-consuming While using Cloud Source Repositories, the default branches of all repositories are always indexed and up-to-date. Hence, searching across all the code is faster. #2 To search for code that performs a common operation Cloud Source Repositories enables users to perform quick searches. Users can also save time by discovering and using the existing solution while avoiding bugs in their code. #3 If a developer cannot remember the right way to use a common code component Developers can enter a query and search across all of their company’s code for examples of how the common piece of code has been used successfully by other developers. #4 Issues with production application  If a developer encounters a specific error message to the server logs that reads ‘User ID 123 not found in PaymentDatabase’, they can perform a regular expression search for ‘User ID .* not found in PaymentDatabase’ and instantly find the location in the code where this error was triggered. All repositories that are either mirrored or added to Cloud Source Repositories can be searched in a single query. Cloud Source Repositories has a limited free tier that supports projects up to 50GB with a maximum of 5 users. You can read more about Cloud Source Repositories in the official documentation. Google announces Flutter Release Preview 2 with extended support for Cupertino themed controls and more! Google to allegedly launch a new Smart home device Google’s prototype Chinese search engine ‘Dragonfly’ reportedly links searches to phone numbers

(2020-Dec-21) While working with Azure Functions that provide a serverless environment to run my computer program code, I’m still struggling to understand how it actually works. Yes, I admit, there is no bravado in my conversation about Function Apps, I really don’t understand what happens behind a scene, when a front-end application submits a request to execute my function code in a cloud environment, and how this request is processed via a durable function framework (starter => orchestrator => activity).  Azure Data Factory provides an interface to execute your Azure Function, and if you wish, then the output result of your function code can be further processed in your Data Factory workflow. The more I work with this couple, the more I trust how a function app can work differently under various Azure Service Plans available for me. The more parallel Azure Function requests I submit from my Data Factory, the more trust I put into my Azure Function App that it will properly and gracefully scale out from “Always Ready instances”, to “Pre-warmed instances”, and to “Maximum instances” available for my Function App. Supported runtime version for PowerShell durable functions, along with data exchange possibilities between orchestrator function and activity function requires a lot of trust too because the latter is still not well documented. My current journey of using Azure Functions in Data Factory has been marked with two milestones so far: Initial overview of what is possible - http://datanrg.blogspot.com/2020/04/using-azure-functions-in-azure-data.html Further advancement to enable long-running function processes and keep data factory from failing - http://datanrg.blogspot.com/2020/10/using-durable-functions-in-azure-data.html Photo by Jesse Dodds on Unsplash Recently I realized that the initially proposed HTTP Polling of long-running function process in a data factory can be simplified even further. An early version (please check the 2nd blog post listed above) suggested that I can execute a durable function orchestrator, which eventually will execute a function activity. Then I would check the status of my function app execution by polling the statusQueryGetUri URI from my data factory pipeline, if its status is not Completed, then I would poll it again.  In reality, the combination of Until loop container along with Wait and Web call activities can just be replaced by a single Web call activity. The reason for this is that simple: when you initially execute your durable Azure Function (even if it will take minutes, hours, or days to finish), it will almost instantly provide you with an execution HTTP status code 202 (Accepted). Then Azure Data Factory Web activity will poll the statusQueryGetUri URI of your Azure Function on its own until the HTTP status code becomes 200 (OK). Web activity will run this step as long as necessary or unless the Azure Function timeout is reached; this can vary for different pricing tiers - https://docs.microsoft.com/en-us/azure/azure-functions/functions-scale#timeout The structure of statusQueryGetUri URI is simple: it has a reference to your azure function app along with the execution instance GUID. And how Azure Data Factory polls this URI, is unknown to me, it's all about trust, please see the beginning of this blog post https://<your-function-app>.azurewebsites.net/runtime/webhooks/durabletask/instances/<GUID>?taskHub=DurableFunctionsHub&connection=Storage&code=<code-value> This has been an introduction, now the real blog post begins. Naturally, you can execute multiple instances of your Azure Function at the same time (event-driven processes or front-end parallel execution steps) and the Azure Function App will handle them. My recent work project requirement indicated that when a parallel execution happens, a certain operation still needed to be throttled and artificially sequenced, again, it was a special use case, and it may not happen in your projects. I tried to put such throttling logic inside of my durable azure function activity, however, with many concurrent requests to execute this one particular operation, my function had app used all of the available instances, while the instances were active and running, my function became not available to the existing data factory workflows. There is a good wiki page about Writing Tasks Orchestrators that states, “Code should be non-blocking i.e. no thread sleep or Task.WaitXXX() methods.” So, that was my aha moment to remove the throttling logic from my azure function activity to the data factory. Now, when an instance of my Azure Function finds itself that it can’t proceed further due to other operation running, it completes with HTTP status code 200 (OK), releases the azure function instance, and also provides an additional execution output status that it’s not really “OK” and needs to re-executed. The Until loop container now will handle two types of scenario: HTTP Status Code 200 (OK) and custom output Status "OK", then it exits the loop container and proceeds further with the "Get Function App Output" activity. HTTP Status Code 200 (OK) and custom output Status is not "OK" (you can provide more descriptive info of what your not OK scenario might be), then execution continues with another round of "Call Durable Azure Function" & "Get Current Function Status". This new approach for gracefully handling conflicts in functions required some changes in Azure Function Activity: (1) to run regular operation and completes with the custom "OK" status or identify another running instance, completes the current function instance and proved "Conflict" custom status, (2) Data Factory adjustments to check the custom Status output and decides what to do next. Azure Function HTTP long polling mission was accomplished, however, now it has two layers of HTTP polling: natural webhook status collection and data factory custom logic to check if my webhook received OK status was really OK. The post Using Azure Durable Functions with Azure Data Factory - HTTP Long Polling appeared first on SQLServerCentral.

We recently asked whether Dart programming was dead, but news of its death might well have been exaggerated. Version 2 of the programming language has just been released, with a range of updates and changes that should cement its popularity with admirers and win new users too. With Dart playing a big part in Google's much-anticipated Flutter and Fuchsia projects, there's a possibility that version 2.0 represents a brand new chapter in Dart's life. News of a Dart 'reboot' first emerged in February 2018. Anders Thorhauge Sandholm said at the time that “with Dart 2, we’ve dramatically strengthened and streamlined the type system, cleaned up the syntax, and rebuilt much of the developer tool chain from the ground up to make mobile and web development more enjoyable and productive.” It would appear that six months later the team have finally delivered on their promise. They'll be hoping it makes a positive impact on the language's wider adoption. What's new in Dart 2.0? There's a whole host of changes that Dart developers will love, all of which can be found in the changelog on GitHub. Most notable is a stronger typed system, which includes runtime checks that will capture errors more effectively, and, for those developers working on Flutter, you can now create an instance of a class without using the "new" keyword. Among other updates, other key changes to Dart include: "Functions marked async now run synchronously until the first await statement. Previously, they would return to the event loop once at the top of the function body before any code runs." "Constants in the core libraries have been renamed from SCREAMING_CAPS to lowerCamelCase." "...New methods have been added to core library classes. If you implement the interfaces of these classes, you will need to implement the new methods." All the changes you'll find in Dart 2.0 amount to the same thing: improving the developer experience and making the code more readable. The obvious context to all this 'reboot' is that Google is betting on the growth of Flutter and Fuchsia over the next few years. With these improvements, it's possible that we'll begin to see Dart's fortunes changing. CodeMentor may have called Dart the 'worst programming language to learn in 2018' at the start of the year, but it will be interesting to see if it's popularity has grown by the time we hit 2019. You can download Dart 2.0.0 for Windows, Mac, and Linux here.

Up-and-coming cryptocurrency startup IOTA has partnered with more than 20 corporate behemoths such as Deutsche Telekom, Bosch, Microsoft, PricewaterhouseCoopers, Accenture and Fujitsu to build a reliable Data Marketplace for data sharing and monetizing. Several research groups from universities around the world are also involved in the project. According to IOTA, over 2.5 quintillion bytes of information are generated on a daily basis, but almost 99% is lost because there is no safe place to exchange and share this data securely. “Any kind of data can be monetized,” said David Sønstebø, who co-founded the Internet-of-Things based cryptocurrency, “If you have a weather station collecting wind, temperature, humidity, and barometric data, for instance, you can sell that to an entity that is doing climatic research.” The marketplace aims to give connected devices the ability to securely transfer, buy and sell datasets using a “tangle” based distributed ledger technology. Other cryptocurrencies such as Bitcoin and Ether use blockchain technology in contrast. “IOTA is kind of the first distributed ledger that goes beyond the blockchain,” Sønstebø said, “We got rid of the blocks and we got rid of the chains, which has resulted in getting rid of the major pain points or limitations of the blockchain such as fees, scalability, and centralization.” As soon as data is put onto IOTA’s decentralized ledger, it is distributed to countless nodes or the computers that connect to the blockchain network, ensuring that it is impossible to tamper with the data, Sønstebø claimed. Basically, Tangle is a form of Directed Acyclic Graph (DAG), a complex data structure where the devices on the network build consensus through the web of connections between transactions, as they randomly verify each other’s transactions. This method of verification means there’s no central ledger, and there’s no need for miners to power the network. It is this decentralized permissionless ledger, where the data will be hosted, that may possibly ensure that the data being sold on IOTA’s marketplace is tamper-proof. Since computing power in the Tangle grows as the network grows, IOTA is promising free, fast transactions. The marketplace demo will run until January, IOTA stated, adding that they will release a series of blog posts and case studies to highlight how companies can use the technology and benefit from it. While the technology is still new, it may act as a catalyst for a whole new paradigm of research, artificial intelligence, and democratization of data. In tangle, IOTA has used an interesting technique to distribute and decentralize its ledger while addressing the core drawbacks of blockchain system. In their white paper released in October, IOTA had even said the tangle “naturally succeeds the blockchain as its next evolutionary step.”