Tech News - Data

On 8th November, Google updated its sexual misconduct policy in response to the #GoogleWalkout that protested the discrimination, racism, and sexual harassment that employees encountered at Google’s workplace. Following this, Sundar Pichai announced a ‘comprehensive’ plan to incorporate transparency into how employees raise concerns and how Google will handle them. One of the main points publicized to a great extent was that Google eliminated forced arbitration in cases of sexual harassment. Now, fresh reports have emerged that Richard Hoyer, a lawyer for Loretta Lee, the ex-Google software engineer who filed a sexual harassment, gender discrimination, and wrongful termination suit against her former employer earlier this year, told BuzzFeed News that a Google attorney stated the policy change would not apply to her ongoing case. Google lawyer Brian Johnsrud sent an email (reviewed by Buzzfeed) to Hoyer last Friday which stated, “Google announced a prospective policy change which applies going forward to individual sex harassment as well as sex assault claims. This kind of policy change does not apply retroactively to claims already compelled to arbitration.” In response to this claim, Hoyer told Buzzfeed that “Google says, ‘We will not force employees into arbitration,’ and [the] response to me taking them up on that is, ‘Oh, we didn’t say when.’ It was a shock to see Google renege on the announcement that [the company] went through a lot of effort to publicize.” Loretta Lee’s suit, filed in February 2018, alleges she was “ routinely sexually harassed”  without any intervention on Google’s part to stop the harassment. The suit further states that male coworkers spiked her drinks with alcohol, one male co-worker messaged her to ask for a “horizontal hug”; and that at a holiday party, a drunk male coworker slapped her. According to the lawsuit, she found a male coworker hiding under her desk and “believed he may have installed some type of camera or similar device under her desk”. Post the complaint filed in the HR department of Google, the lawsuit states that Lee’s male co-workers retaliated against her. They refused to approve her code and stalled her projects, thus making it more difficult for her to succeed at work. In September 2018, the Lee case was compelled into arbitration. Hoyer, told BuzzFeed News that there still would have been time to appeal the court’s order compelling arbitration. On the day of Google’s announcement to end forced arbitration, Hoyer contacted Google's lawyer to say Lee elected not to arbitrate her claims. According to emails reviewed by BuzzFeed News, Google’s lawyer delayed the reply for a week and finally stated that the company would still force arbitration for her case. Apparently, the reply was received on the very last day that Lee could have appealed. According to Buzzfeed, the email exchange between Hoyer and Johnsrud showed that in October, Lee sought to negotiate a monetary settlement with Google. The reply received from Johnsrud was not befitting at all:  “I was surprised to receive your voicemail making a settlement demand after Ms. Lee has tried to trash Google in the press and avoid arbitration.” He further added that unless Lee substantially reduced her settlement demand, Google would prefer to proceed with arbitration. Private arbitration often shields a firm from workers airing their grievances in open court, and also results in lower-cost settlements between the oppressed worker and the employer. In mandated arbitration, there are no rules of evidence and there is no public access to what happens as compared to a traditional court settling. Many cases of mandated arbitration have not lead to a fair settlement between the employer and employee. Google’s roll back on its policy statement in Lee’s case looks like a massive discouragement for workers suffering from sexual harassment at other workplaces. Head over to BuzzFeed for an entire coverage of this news. 90% Google Play apps contain third-party trackers, share user data with Alphabet, Facebook, Twitter, etc: Oxford University Study OK Google, why are you ok with mut(at)ing your ethos for Project DragonFly? Google now requires you to enable JavaScript to sign-in as part of its enhanced security features

It has not been long since the Logan Paul controversy hit the internet and people criticized YouTube algorithms and complained that they were still seeing recommendations of Logan Paul’s videos, even when it was brought down. Earlier this week, a “Flat Earth Conference” was held at Denver, Colorado where some attendees talked about how Youtube has persuaded them to believe the flat earth theory. In fact, Logan Paul was also one of the conference’s keynote speakers, despite not believing that the Earth is flat. The attendees were interviewed by Daily Beast. In the conference, many participants told Daily Beast that they have come to believe in the Flat Earth theory based on YouTube videos. “It came on autoplay,” said Joshua Swift, a conference attendee. “So I didn’t actively search for Flat Earth. Even months before, I was listening to Alex Jones.” Recently, NBA star Kyrie Irving also spoke about his obsession with flat earth theory blaming YouTube videos for it. Irving spoke of having wandered deep down a “rabbit hole” on YouTube. This has brought the emphasis back on the recommendation system that YouTube uses. In a blog post, Guillaume Chaslot, and ex-googler who helped build the YouTube algorithm explains, “Flat Earth is not a ’small bug’. It reveals that there is a structural problem in Google's AIs and they exploit weaknesses of the most vulnerable people, to make them believe the darnedest things.” He mentions a list of Flat Earth videos which were promoted on Youtube. https://www.youtube.com/watch?v=1McqA9ChCnA   https://www.youtube.com/watch?v=XFSH5fnqda4 This makes one question whether the YouTube algorithm is evil? The YouTube algorithm recommends videos based on watch time. More watch time means more revenue and more scope for targeted ads. What this changes, is the fundamental concept of choice and the exercising of user discretion. The moment the YouTube Algorithm considers watch time as the most important metric to recommend videos to you, less importance goes into the organic interactions on YouTube, which includes liking, commenting and subscribing to videos and channels. Chaslot was fired by Google in 2013 over performance issues. His claim was that he wanted to bring about a change in the approach of the YouTube algorithm to make it more aligned with democratic values instead of being devoted to just increasing the watch time. Chaslot has created Algotransparency, a site that scans and monitors YouTube recommendations daily. Other Twitter users have also supported Chaslot’s article. https://twitter.com/tristanharris/status/1064973499540869121 https://twitter.com/technollama/status/1064573492329365504 https://twitter.com/sivavaid/status/1064527872667369473 Is YouTube’s AI Algorithm evil? YouTube has a $25 million plan to counter fake news and misinformation YouTube went down, Twitter flooded with deep questions, YouTube back and everyone is back to watching cat videos

In a paper published earlier this month, a team of AI researchers at Facebook have been looking closely at how AI agents ‘understand’ images and the extent to which they can be said to develop a shared conceptual language. Building on earlier research that indicates “(AI) agents are now developing conceptual symbol meanings,” the Facebook research team attempted to dive deeper and look closely at how AI agents develop representations of visual inputs. What they found was intriguing - the conceptual ‘language’ that the AI agents seemed to share wasn’t in any way related to the input data, but instead what the researchers describe as a ‘shared conceptual pact’. This research is significant as it opens the lid on how agents in deep learning systems, and opens up new possibilities for understanding how they work. Background Researchers take their cue from current research into AI agents. This research runs visual ‘games’..“This… allows us to address the exciting issue of whether the needs of goal-directed communication will lead agents to associate visually-grounded conceptual representations to discrete symbols, developing natural language-like word meanings” reads the paper. However, most of the existing studies present only the analysis of the agents’ symbol usage. Very little attention is given to the representation of the visual input developed by the agents during the interaction process.  Researchers have made use of the referential games of Angeliki Lazaridou, a research scientist at Deepmind, where a pair of agents communicates about images using a fixed-size vocabulary. “Unlike in those previous studies, which suggested that the agents developed a shared understanding of what the images represented, our researchers found that they extracted no concept-level information”, reads the research paper. The paired AI agents would arrive at an image-based decision depending only on the low-level feature similarities. How does it work? Researchers implemented Lazaridou’s, same-image game and the different image game. In the same image game, the Sender and Receiver are shown the same two images (that are always of different concepts). In the different-image game, the Receiver is shown different images than the Sender’s every time. The experiments were repeated using 100 random initialization seeds. Researchers first looked at how playing the game affects the way agents “see” the input data. This involves figuring out which of the image embeddings differ from the input image representations, and from each other. Researchers then further predicted that as the training continues, Sender and Receiver representations become quite similar to each other, as well as the input ones. To finally compare the similarity structure of the input, Sender and the Receiver spaces, representational similarity analysis (RSA) from computational neuroscience is used by the researchers. AI agents reach an image-based consensus The paired agents in the game arrived at an ‘image-based consensus’ depending solely on low-level feature similarities, without determining, for instance, that pictures of a Boston terrier and a Chihuahua both represent dogs. In fact, the agents were able to reach this consensus despite being presented with similar patterns of visual noise, which included no recognizable objects. This confirmed the hypothesis that the Sender and Receiver are capable of communicating about the input data with no conceptual content at all. This, in turn, suggests that no concept-level information (e.g., features that would allow to identify the instances of the dog or chair category) has been extracted by the agents during the training process. For more information, check out the official research paper. UK researchers have developed a new PyTorch framework for preserving privacy in deep learning Researchers show that randomly initialized gradient descent can achieve zero training loss in deep learning UK researchers build the world’s first quantum compass to overthrow GPS

RedisGraph was released in beta mode six months ago. On the 14th of November, RedisLabs announced the general availability of RedisGraph v1.0. RedisGraph is a Redis module that adds a graph database functionality to Redis. RedisGraph delivers a fast and efficient way to store, manage and process graphs, around 6 to 600 times faster than existing graph databases. RedisGraph represents connected data as adjacency matrices and employs the power of GraphBLAS which is a highly optimized library for sparse matrix operations. How does RedisGraph Work? Redis is a single-threaded process by default. RedisGraph is bound to the single thread of Redis and supports all incoming queries while including a threadpool that takes a configurable number of threads at the module’s loading time to handle higher throughputs. The queries are calculated in one of the threads of the threadpool. This means reads can scale and handle large throughput easily. Each query only runs in one thread. This is what separates RedisGraph from other graph database implementations—which typically execute each query on all available cores of the machine. This makes RedisGraph more suitable for real-time and real-world use cases where high throughput and low latency under concurrent operations are important. In RedisGraph, a write query ( that modifies the graph in any way ) must be executed in complete isolation. RedisGraph also ensures write/readers separation by using a read/write (R/W) lock. This means that either multiple readers can acquire the lock or just a single writer can write a query.  The lock ensures that as long as a writer is executing, no one can acquire the lock, and as long as there’s a reader executing, no writer can obtain the lock. Benchmarking RedisGraph The team conducted a benchmark test on RedisGraph that proved the latter’s speed was more than other graph databases. They used a simple benchmark released by TigerGraph that covered the following: Data loading time Storage size of loaded data Query response time for k-hop neighborhood count Query response time for weakly connected components and page rank The TigerGraph benchmark compared all other graph databases and reported TigerGraph to be 2-8000 times faster than any other graph database. The Redis team compared RedisGraph using the exact same setup. The test focused mainly on the k-hop neighborhood count query. To test the result of concurrent operations, parallel requests were added to the TigerGraph benchmark. RedisGraph utilized just a single core and other graph databases were using up to 32 cores. ReddisGraph was faster in response times than any other graph database (with the exception of TigerGraph in the single request k-hop queries tests on the Twitter dataset). The single request benchmark test and parallel request benchmark test also returned positive results for RedisGraph. In all the tests conducted, RedisGraph never timed out or generated out of memory exceptions. RedisGraph shows performance improvements under load of 6 to 60 times faster than existing graph solutions for a large dataset (twitter dataset) and 20 to 65 times faster on a normal data set (graph500 dataset). The benchmark also proves that RedisGraph outperforms Neo4j, Neptune, JanusGraph and ArangoDB on a single request response time with improvements almost 36 to 15,000 times faster. There were 2X and 0.8X faster single request response times as compared to TigerGraph. Future improvements as listed by the team include: Performance improvements for aggregations and large result sets A faster version of GraphBLAS More Cypher clauses/functionality to support even more diverse queries Integration for graph visualization software LDBC benchmarking tests You can head over to RedisLabs official Blog to know more about the benchmarking tests conducted. Introducing Web High Level Shading Language (WHLSL): A graphics shading language for WebGPU Facebook’s GraphQL moved to a new GraphQL Foundation, backed by The Linux Foundation 2018 is the year of graph databases. Here’s why.

On 14th and 15th November, Verizon hosted the Ericsson’s 2018 OSS/BSS (Operations Support Systems/ Business Support Systems) user Group conference. The theme of the conference was ‘Quest for easy.’ The conference included presentations, demos, panels discussions and meetings with service providers from all over the world. This year the conference was held in New York, USA and was a two-day long event. The participants got some wonderful insights from the customers who shared their OSS/BSS experiences. The attendees also got a chance to go through around ten demos across Ericsson’s OSS/BSS portfolio. They got enlightened by the idea of what ‘Quest For Easy’ can mean for consumers and enterprises, operations and businesses. They got some information on how can ‘Quest For Easy’ create an impact on service providers and the products and services they offer. Highlights from the speakers Experts from Ericsson made the event more interesting. Emanuele Iannetti, Head of Solution Area BSS gave some useful and latest information to the audience about the Ericsson BSS portfolio. Marton Sabli, Head of Solution and Service Readiness for Solution Area OSS, Rick Mallon, Head of BSS Catalog and Order Management and Mats Karlsson, Head of Solution Area OSS also gave talks. Marton Sabli spoke about the orchestration of network slices and service assurance in a multi-vendor environment. Mats Karlsson gave his insight on 5G, right from enablers to monetization and Rick Mallon explained how Catalog and Order Care help in achieving simplicity and automation. Mohit Gupta, Director of Product Management at Ericsson, explained the audience the importance of insight-driven automation. Insights from the panel discussions The panel discussions were interesting as the customers got a chance to speak about the challenges, opportunities and their overall point of view. These panel discussions were divided into two tracks. The first one was based on revenue management while the other one covered service management, orchestration, and analytics. Arthur D. Little led one of the panels in which the customers including Verizon, Sprint and T-Mobile shared their views on the challenges and opportunities related to 5G and IoT. They also shared their experiences with digital transformation and monetization. Gary G Fujinami, Director of Performance Analytics Development / Operations at Verizon, threw some light on challenges of management and orchestration in an NFV (Network Functions Platform) enabled multi-operator world. Read more about this news on Ericsson. OpenStack Foundation to tackle open source infrastructure problems, will conduct conferences under the name ‘Open Infrastructure Summit’ Tableau 2019.1 beta announced at Tableau Conference 2018 “We call on the UN to invest in data-driven predictive methods for promoting peace”, Nature researchers on the eve of ViEWS conference

Yesterday, EuclidesDB, a multi-model machine learning feature database released its v0.1. EuclidesDB 0.1 is tightly coupled with PyTorch and provides a backend for including and querying data on the model feature space. EuclidesDB provides a simple standalone server that stores, builds indexes, and serves requests using efficient serialization and protocols with an easy API. It provides APIs for including new data into the database and querying it later. Since it uses gRPC (gRPC Remote Procedure Call) for communication, the API can be consumed in many different languages. As mentioned earlier, it comes with a very tight integration with PyTorch, where libtorch is used as the backend to run traced models. And, thus provides a very easy pipeline to integrate new models into the Euclides DB C++ backend. The concept behind EuclidesDB EuclidesDB is based on two main concepts: Module/Model are terms used interchangeably to represent every computation. Model Space represents a space of features generated by a model. When a user adds a new image or other kinds of data into the database, they need to specify which model should be used to index this data. This data is then forwarded into the specified models and their features are saved into a local key-value database. Similarly, when a user queries for similar items on a model space, they need to make a request with a new image and specify on which model spaces they want to find similar items. Then similar items for each model space is returned together with their relevance. Features of EuclidesDB v0.1 Euclides v0.1: Uses gRPC as protocol communication and protobuf as a serialization mechanism for its communication with client APIs. Uses LevelDB for database serialization. Uses LSH (Locality Sensitive Hashing) for approximate nearest neighbors. Comes with PyTorch integration through libtorch. Provides easy integration for new custom fine-tuned models. EuclidesDB is currently in its initial release and many new features will be introduced in the future versions. The client API is also expected to change in the upcoming releases before a robust API design is stabilized. To know more in detail, check out EuclidesDB’s official website. FoundationDB 6.0.15 releases with multi-region support and seamless failover management ScyllaDB announces Scylla 3.0, a NoSQL database surpassing Apache Cassandra in features Redbird, a modern reverse proxy for node

In September, Goldman Sachs estimated that almost $9 billion dollar revenue is coming to Apple from Google for being the built-in search engine on Apple’s Safari web browsers. Till then, Apple had never talked about its revenue stream from Google. However, last week, Tim Cook, CEO, Apple participated in an interview by Axios on HBO. In the interview, he was asked if he agreed of taking billion dollars from Google. He casually replied to the question stating, “I think their (Google’s) search engine is the best”. He also admitted that Apple-Google partnership was not "perfect." He further defended Apple’s multi-billion dollar deal with Google search by talking about the additional security measures that Apple has added to Safari to "help" users better navigate the Google search engine. These include private web browsing and an intelligent tracker prevention. He stated in the interview, "Look at what we've done with the controls we've built in. We have private web browsing. We have an intelligent tracker prevention, What we've tried to do is come up with ways to help our users through their course of the day. It's not a perfect thing. I'd be the very first person to say that. But it goes a long way to helping." Apple has been quite vocal about not selling targeted advertisements based on user information. Cook has criticized Google, Facebook, and other social media platforms for mishandling user privacy. He has claimed that Apple’s business model depends on selling hardware such as smartphones and tablets and that they are very particular about user privacy. Last month, Cook had also given a speech at a privacy conference in Brussels where he mentioned his concerns on privacy in various social media platforms. He had also called for new digital privacy laws in the United States. His concerns involved, users' personal data collection by companies, data manipulation, and lack of surveillance. People on the internet are not much in favor of this news. Twitter users are raising eyebrows on Cook’s casual statement and the fact they are taking millions of dollars from Google even if they disagree with its policies in the first place. https://twitter.com/b_fung/status/1064552025864765441   https://twitter.com/christianring/status/1064614295395282947 Apple was previously using Bing as its default browser in 2017. However, the company switched to Google because it faced consistency issues with Bing. It’s still not sure if the main reason to switch to Google was the company’s expectations of consistent results or the multi-billion deal! You can see a snippet of Tim Cook’s interview on Axios. Newer Apple maps is greener and has more details A kernel vulnerability in Apple devices gives access to remote code execution Gaël Duval, creator of the ethical mobile OS, /e/, calls out Tim Cook for being an ‘opportunist’ in the ongoing digital privacy debate

The FoundationDB team released version 6.0.15 of its distributed, NoSQL database, yesterday. FoundationDB 6.0.15 explores new features such as multi-region support, seamless failover management, along with performance changes, and bug fixes. FoundationDB is an open source, multi-model datastore by Apple that lets you store multiple data types in a single database. All data in FoundationDB is safely stored, distributed, and replicated in the Key-Value Store component. FoundationDB offers high performance on commodity hardware, helping you support very heavy loads at a low cost. Let’s have a look at what’s new in FoundationDB 6.0.15. New features FoundationDB 6.0.15 offers native multi-region support that dramatically increases your database's global availability. This also offers greater control over how failover scenarios are managed. Seamless failover is now possible in FoundationDB 6.9.15, allowing your cluster to survive the loss of an entire region without any service interruption. These features can be further deployed so that clients experience low-latency, single-region writes. Support has been added for asynchronous replication to a remote DC with processes in a single cluster. This improves the asynchronous replication provided by fdbdr as servers can fetch data from the remote DC in case all the other replicas have been lost in one DC. Additional support has been added for synchronous replication of the transaction log to a remote DC. This makes sure that the remote DC need not contain any storage servers. The TLS plugin has been statically linked into the client and server binaries. There is no longer a need for a separate library. The fileconfigure command has been added to fdbcli which configures a database from a JSON document. Performance changes The master recovery time for clusters with large amounts of data has been significantly reduced. Recovery time has been significantly reduced for cases where rollbacks are executed on the memory storage engine. Clients can now update their key location cache much more efficiently after the reboots of storage servers. Multiple resolver configurations have been tuned to carry out the job balancing work more efficiently between each resolver. Bug Fixes Clusters that been configured to use TLS would get stuck, leading to all their CPUs getting used for opening new connections. This issue has been fixed now. The issue of TLS certificate reloading causing the TLS connections to drop until the processes were restarted has been fixed. The issue of Watches registered on a lagging storage server taking a long time to trigger has been fixed. Other Changes The capitalization of trace event names and attributes has been normalized. Memory requirements of the transaction log have been increased by 400MB. The replication factor in status JSON has been stored under redundancy_mode instead of redundancy.factor. The metric data_version_lag is replaced by data_lag.versions and data_lag.seconds. Several additional metrics have been added for the number of watches and mutation count and are exposed through status. For more information on FoundationDB 6.0.15, check out the official release notes. MongoDB switches to Server Side Public License (SSPL) to prevent cloud providers from exploiting its open source code BlazingDB announces BlazingSQL , a GPU SQL Engine for NVIDIA’s open source RAPIDS MongoDB acquires mLab to transform the global cloud database market and scale MongoDB Atlas

Microsoft had planned to bring ads to the Mail App in Windows 10. It also has an entire support page dedicated to ads on mail. But last week after the backlash from the people, Frank X. Shaw, the Head of Communications at Microsoft claimed on Twitter that ads on the Mail app were not intended to be tested broadly. Though it has been turned off now. https://twitter.com/fxshaw/status/1063518403036557312 According to Microsoft, the ads will appear for all users. Even if one doesn’t use a Microsoft email service like Outlook and only have Gmail, Yahoo, G Suite, or other third-party accounts, the ad will still be visible until one purchases an Office 365 subscription. The team at Microsoft is having a pilot running in Brazil, Canada, Australia, and India to get user feedback on ads in Mail. These ads will be visible on Windows Home and Windows Pro but not on Windows EDU or Windows Enterprise. Microsoft chooses Interest-based advertising for its users Windows generates an advertising ID for each user on the device. When the advertising ID is enabled, both Microsoft apps and third-party apps can access and use the advertising ID. It is similar to the websites that access and use a unique identifier stored in a cookie. Mail app uses this ID to provide more relevant advertising to users. Also, the Mail app may use the demographic information to make ads more relevant to the users. This is possible for the users who have logged into Windows with a Microsoft Account. Users can turn off interest-based advertising at any time. If a user turns off the interest-based advertising, the user will still see ads but they won’t be relevant to the interests. As per the Support page of Microsoft, these interest-based ads do not check the user’s emails to display ads. Microsoft does not use personal information, like the content of the email, calendar, or contacts, to target the users for ads. Microsoft doesn’t use the content in the mailbox or in the Mail app. But privacy is still a concern while referring to Microsoft. As per a report by Privacy Company, Microsoft collects and stores users personal without any public documentation. Microsoft systematically collects data about the individual use of Word, Excel, Outlook, and PowerPoint without letting users know. Since the data stream is encoded, Microsoft does not offer any choice to switch off the data collection, or ability to see what data has been collected. For example, Microsoft collects information about events in Word, when you use the backspace key a number of times in a row, which probably means you do not know the correct spelling. But also the sentence before and after a word that you look up in the online spelling checker or translation service. Microsoft‘s use of the telemetry data is one of the biggest concerns of the report as Microsoft is regularly pushing more and more services off-premise. Data Protection Impact Assessment (DPIA) show that the new methods like Microsoft cloud, in SharePoint, OneDrive, Office 365 come with high data protection risks for data subjects. The blog states that Microsoft has already made commitments to make adjustments to its software to accommodate privacy concerns, e.g. a telemetry data viewer tool and a new “zero-exhaust setting.” Privacy Company outlines six high risks for data subjects The unlawful storage of classified/sensitive/special categories of data, both in metadata and in subject lines of the e-mail. The incorrect qualification of Microsoft as a data processor, instead of a joint controller. Insufficient control over factual data processing and sub-processors. The lack of purpose limitation, both for the processing of historically collected data and the possibility to dynamically add new types of events The transfer of diagnostic data outside of the European Economic Area (EEA), while the current legal ground for Office ProPlus is the Privacy Shield and the validity of this agreement is subject of a procedure at the European Court of Justice. The indefinite retention period of diagnostic data and also the lack of a tool to delete historical, diagnostic data. The Privacy Company recommends admins of the enterprise few measures to lower the privacy risk for employees and other users. It suggests to not use SharePoint Online / OneDrive. It advises to not use the web-only version of Office 365. The company also suggests using a stand-alone deployment without Microsoft account for confidential/sensitive data. Read more about the news on the DPIA’s pdf. Microsoft amplifies focus on conversational AI: Acquires XOXCO; shares guide to developing responsible bots Microsoft fixes 62 security flaws on Patch Tuesday and re-releases Windows 10 version 1809 and Windows Server 2019 Microsoft announces container support for Azure Cognitive Services to build intelligent applications that span the cloud and the edge

On Friday, Blackberry announced its plans to acquire Cylance on Friday for $1.4 billion in cash to help expand its QNX unit, which makes software for next-generation autonomous cars. According to Blackberry, “Cylance will operate as a separate business unit within BlackBerry Limited”. This deal is expected to close by February 2019. Describing the Cylance acquisition, BlackBerry CEO John Chen said, “Cylance’s leadership in artificial intelligence and cybersecurity will immediately complement our entire portfolio, UEM, and QNX in particular. We are very excited to onboard their team and leverage our newly combined expertise. We believe adding Cylance’s capabilities to our trusted advantages in privacy, secure mobility, and embedded systems will make BlackBerry Spark indispensable to realizing the Enterprise of Things.” Technology from Cylance will be leveraged in critical areas of Blackberry’s Spark Platform. This Spark Platform is a next-generation secure chip-to-edge communications platform for the EoT (Enterprise of Things) that will create and leverage trusted connections between any endpoint. It enables organizations to comply with stringent multi-national regulatory requirements. Cylance’s CEO Stuart McClure, said, “Our highly skilled cybersecurity workforce and market leadership in next-generation endpoint solutions will be a perfect fit within BlackBerry where our customers, teams, and technologies will gain immediate benefits from BlackBerry’s global reach. We are eager to leverage BlackBerry’s mobility and security strengths to adapt our advanced AI technology to deliver a single platform.” To know more about this acquisition head over to the official press release. A decade of Android: Slayer of Blackberry, challenger of iPhone, mother of the modern mobile ecosystem IBM acquired Red Hat for $34 billion making it the biggest open-source acquisition ever

Last week, hackers attempted to extort ProtonMail by alleging a data breach with no evidence. One of the alleged hackers named, AmFearLiathMor has written in the message that, “We hacked Protonmail and have a significant amount of their data from the past few months. We are offering it back to Protonmail for a small fee if they decline then we will publish or sell user data to the world.” ProtonMail is one of the largest secure email services developed by CERN and MIT. The team at ProtonMail clarified, “We have no indications of any breach from our internal infrastructure monitoring.” Though, with further investigation, the team traced the source of the rumors on 4chan, a simple image-based bulletin board, where anyone can post comments and share images anonymously. The claims there included: CNN employees use ProtonMail and refer to the American people as prostitutes. Michael Avenatti uses ProtonMail and has a BDSM fetish. Private military contractors used ProtonMail to discuss circumventing the Geneva convention, underwater drone activities in the Pacific Ocean, and possible international treaty violations in Antarctica. Rampant pedophilia among high ranking government officials who use ProtonMail. ProtonMail's team said, “We believe that this is a hoax and failed extortion attempt, and there is zero evidence to suggest otherwise.”  For example, the criminals claimed that ProtonMail is vulnerable because the company doesn’t use SRI (Subresource Integrity), but this claim is baseless because it doesn't use any third party CDNs (content delivery networks) to serve the web app. ProtonMail only uses web servers that specifically eliminate the potential attack vector. The team said, “We are aware of a small number of ProtonMail accounts which have been compromised as a result of those individual users falling for phishing attacks (this is why we encourage using 2FA). However, we currently have zero evidence of a breach of our infrastructure.” As per the report by BleepingComputer, the hackers might send $20 in bitcoin to the one who would spread the word about this hack using #Protonmail on Twitter. People have given a mixed reaction to this news. Many are just scared and do not wish to take any risks and suggest to change the password. https://twitter.com/ProtonMail/status/1063392853014048768   https://twitter.com/crytorekt1/status/1063452592792051713 The team said, “The best way to ensure that they (criminals) do not succeed is to ignore them.” As a lot of users find this platform secure, this alleged hacking news, which is probably false, has still managed to create some impact on the users. The latest announcement on the Read recipients feature by the company could be a small distraction but is it enough to move the attention from the hacking news? https://twitter.com/ProtonMail/status/1063485043660734464 Read more about this news on Reddit. A new data breach on Facebook due to malicious browser extensions allowed almost 81,000 users’ private data up for sale, reports BBC News Cathay Pacific, a major Hong Kong based airlines, suffer data breach affecting 9.4 million passengers Timehop suffers data breach; 21 million users’ data compromised

Spotify announced, last week, that it has come out with Chartify, a new open source Python data visualization library, making it easy for data scientists to create charts. It comes with features such as concise and user-friendly syntax and consistent data formatting among others. Let’s have a look at these features in this new library. Concise and user-friendly syntax Despite the abundance of tools such as Seaborn, Matplotlib, Plotly, Bokeh, etc, used by data scientists at Spotify, chart creation has always been a major issue in the data science workflow. Chartify solves that problem as the syntax in it is considerably more concise and user-friendly, as compared to the other tools. There are suggestions added in the docstrings, allowing users to recall the most common formatting options. This, in turn, saves time, allowing data scientists to spend less time on configuring chart aesthetics, and more on actually creating charts. Consistent data formatting Another common problem faced by data scientists is that different plotting methods need different input data formats, requiring users to completely reformat their input data. This leads to data scientists spending a lot of time manipulating data frames into the right state for their charts. Chartify’s consistent input data formatting allows you to quickly create and iterate on charts since less time is spent on data munging. Chartify Other features Since a majority of the problems could be solved by just a few chart types, Chartify focuses mainly on these use cases and comes with a complete example notebook that presents the full list of chart types that Chartify is capable of generating. Moreover, adding color into charts greatly help simplify the charting process, which is why Chartify has different palette types aligned to the different use cases for color. Additionally, Chartify offers support for Bokeh, an interactive python library for data visualization, providing users the option to fall back on manipulating Chartify charts with Bokeh if they need more control. For more information, check out the official Chartify blog post. cstar: Spotify’s Cassandra orchestration tool is now open source! Spotify has “one of the most intricate uses of JavaScript in the world,” says former engineer 8 ways to improve your data visualizations

The ‘Neural Information Processing Systems’, or ‘NIPS’, a well-known machine learning and computational neuroscience conference adopted ‘NeurIPS’ as an alternative acronym for the conference, last week. The acronym ‘NIPS’ had been under the spotlight worldwide over the past few years as some members of the community thought of the acronym as “sexist” and pointed out that it is offensive towards women. “Something remarkable has happened in our community. The name NeurIPS has sprung up organically as an alternative acronym, and we’re delighted to see it being adopted”, mentioned the NeurIPS team. NIPS team also added that they have taken a couple of measures to support the new acronym. This is why all signage and the program booklet for the 2018 meeting will have either the full conference name or NeurIPS mentioned to refer to the conference. Sponsors have also been asked to make sure that they make the required changes within their document materials. A branding company has also been hired to get a new logo designed for the conference. Moreover, the conference site has been moved to neurips.cc. “one forward-thinking member of the community purchased neurips.com and described the site’s purpose as ‘host[ing] the conference content under a different acronym... until the board catches up,” as mentioned on NeurIPS news page. NIPS organizers had conducted a  poll, back in August, on the NIPS website asking people if they agree or disagree with the name change. Around 30% of the respondents had answered that they support the name change (28% males and about 44% females) while 31% ‘strongly disagreed’ with the name change proposal (31% male and 25% female). This had led to NIPS keeping the name as it is. However, many people were upset by the board’s decision, and when the emphasis on a name change within the community became evident, the name got revised. One such person who was greatly dissatisfied with the decision was Anima Anandkumar, director of Machine Learning at Nvidia, who had started a petition on change.org last month. The petition managed to gather 1500 supporters as of today. “The acronym of the conference is prone to unwelcome puns, such as the perhaps subversively named pre-conference “TITS” event and juvenile t-shirts such as “my NIPS are NP-hard”, that add to the hostile environment that many ML researchers have unfortunately been experiencing” reads the petition. Anima pointed out that some of these incidents trigger uncomfortable memories for many researchers who have faced harassing behavior in the past. Moreover, Anandkumar tweeted out with #ProtestNIPS in support of the conference changing its name, which received over 300 retweets. https://twitter.com/AnimaAnandkumar/status/1055262867501412352 After the board’s decision to rebrand the name, Anandkumar tweeted out thanking everyone for their support for #protestNIPS. “ I wish we could have started with a clean slate and done away with problematic legacy, but this is a compromise. I hope we can all continue to work towards better inclusion in #ml”. Other than Anandkumar, many other people had been equally active in amplifying the support for #protestNIPS. People in support of #protestNIPS Jeff Dean, head of Google AI Dean had tweeted in support of Anandkumar, saying that NIPS should take the issue of name change seriously: https://twitter.com/JeffDean/status/1055289282930176000 https://twitter.com/JeffDean/status/1063679694283857920 Dr. Elana J Fertig, Associate Professor of Applied Mathematics, Johns Hopkins Elana had also tweeted in support of #protestNIPS. “These type of attitudes cannot be allowed to prevail in ML. Women need to be welcome to these communities. #WomenInSTEM” https://twitter.com/FertigLab/status/1063908809574354944 Daniela Witten, professor of (bio)statistics, University of Washington Witten tweeted saying: “I am so disappointed in @NipsConference for missing the opportunity to join the 21st century and change the name of this conference. But maybe the worst part is that their purported justification is based on a shoddy analysis of their survey results”. https://twitter.com/daniela_witten/status/1054800517421924352 https://twitter.com/daniela_witten/status/1054800519607181312 https://twitter.com/daniela_witten/status/1054800521582731264 “Thanks to everyone who has taken the time to share thoughts and concerns regarding this important issue. We were considering alternative acronyms when the community support for NeurIPS became apparent. We ask all attendees this year to respect this solution from the community and to use the new acronym in order that the conference focus can be on science and ideas”, mentioned the NeurIPS team. NIPS 2017 Special: Decoding the Human Brain for Artificial Intelligence to make smarter decisions NIPS 2017 Special: A deep dive into Deep Bayesian and Bayesian Deep Learning with Yee Whye Teh NIPS 2017 Special: How machine learning for genomics is bridging the gap between research and clinical trial success by Brendan Frey

Google will soon roll out a new feature on Google Maps that will let users, message business profiles in nearby locations. This will help them with the opportunity to ask questions while looking for things to do and places to go or shop. Last year Google enabled users in selected countries to message businesses from the Business Profiles on Google. On Wednesday, Aditya Tendulkar, Product Manager at Google Maps, wrote in a blog post, “You’ll see your messages with the businesses you connect with via ‘Business Profiles’ in the side menu, within the Google Maps app on both, Android as well as iOS devices.” https://lh6.googleusercontent.com/xo1gT3uII6iLenY3z8kh7_iv-FD3cnfTBmAYFm2mXksJQvpheSEti51Tonhf7I8xXJtAUwfuldDD7BoaDpMHdFUnLfmaF78thSzrqsp0bl45nILcCh-YGKy-JA32dKckq09wHJvV In order to accept messages from users, the local businesses will have to install the My Business App and enable messages. If one tries to reach out to a shop for some questions which the website isn’t answering, then one can simply message. It’s always easy to drop a message while traveling. Users just need to look for the “message” button on Business Profiles on Search and Maps to message. Also, users in countries worldwide would be able to chat with businesses for the very first time. The other advantage of My Business App is that it is a free tool. It will also help small business owners reach more people online and connect with their customers through Google. This will, in turn, help them in escalating the growth of their ventures. It could possibly work like the Facebook page where it is easy to message businesses. Integrating My Business app within Maps is better as there is no need for a separate messaging app. https://twitter.com/verge/status/1055489488858869761 Google’s messaging platforms haven’t really worked well in past. Hangouts and Allo are not much used by people. Also, the RCS Chat hasn’t launched in the US across all major carriers. It would be interesting to see the fate of My Business App. Read more about this new on Google’s official blog. Google’s Pixel camera app introduces Night Sight to help click clear pictures with HDR+ Google makes major inroads into healthcare tech by absorbing DeepMind Health Monday’s Google outage was a BGP route leak: traffic redirected through Nigeria, China, and Russia

Yesterday, Airtable, a cloud collaboration service, has raised $100 million in funding. The company has raised the funds to expand its business with more talent and offices outside the US. The company has also catapulted to a $1.1 billion valuation. According to PitchBook, the company was only valued at $152 million, eight months ago in its last round. Airtable, the maker of a coding platform for non-techies was founded by Howie Liu, Emmett Nicholas and Andrew Ofstad. It uses a simple interface as a frontend to produce apps and other web-based experiences. This interface is built on spreadsheets and other tools familiar to knowledge workers. Airtable just had 30,000 customers, eight months back. But Airtable’s tools are now used by approximately, 80,000 businesses. One of the major advantages of Airtable is its Slack-like approach to the task of buildings things. Airtable make it easy for non-developers to code There are many tools for building apps and other products but usually, they are very technical and complicated. It becomes difficult for those who aren’t well versed with programming. Also, it’s equally difficult and expensive to build apps that solve this problem. Airtable identified this problem and has built powerful macros under the hood of standard-looking database interfaces. It has made things easy for people who aren’t good at coding. With Airtable, one can customize their own database as per their requirements without relying on someone’s DB model The competition and the market scenario Airtable is not the only organization working on this issue. Companies like DashDash and Microsoft and partners are also working in the same direction. Microsoft’s Excel is known to all, Microsoft and partners are now working towards enhancing the functionalities of the spreadsheets. It seems the competition is going to be tough in near future! Airtable also has a platform called Blocks. Blocks help its users to bring in data from a number of sources. It also lets users select different kinds of outputs. Users can decide how and where the data is to be used, whether it be a marketing campaign across text messaging, an AI-based bot, or a VR experience. Read more about this news on TechCrunch. Python, Tensorflow, Excel and more – Data professionals reveal their top tools Is Microsoft planning to make Python an official Scripting Language for its Excel package? Manage Security in Excel