Tech News - Data

On Thursday, the team at Facebook open sourced F14, an algorithm for faster and memory-efficient hash tables. F14 helps the hash tables provide a faster way for maintaining a set of keys or map keys to values, even if the keys are objects, like strings. The team at Facebook aimed at simplifying the process of selecting the right hash table with the help of F14. The algorithm F14 focuses on the 14-way probing hash table within Folly, Facebook’s open source library of C++ components. These F14 hash tables are better in performance as compared to the previous tools the team had. According to Facebook F14 is can be used as default for all sorts of use cases. There are many factors that need to be considered while choosing a C++ hash table. These factors could be about keeping long-lived references or pointers to the entries, the size of the keys, the size of the tables, etc. The team at Facebook suggests if the developers aren’t planning to keep long-lived references to entries then they may start with the option- folly::F14FastMap/Set or, they can opt for folly::F14NodeMap/Set. Challenges with the existing hash table algorithms Usually the hash tables start by computing a numeric hash code for each key and uses that number for indexing into an array. The hash code for a key remains the same but the hash codes for different keys are different. These keys in a hash table are distributed randomly across the slots in the array. So there are chances of collisions between the keys that map to the same array. Using Chaining method Most of the hash table algorithms handle these collisions by using the chaining method. The chaining method uses a secondary data structure such as a linked list for storing all the keys for a slot. This helps in storing the keys directly in the main array and further checking new slots if there is a collision. If the number of keys are divided by the size of the main array, we get a number called the load factor which the measure of the hash table’s fullness. By decreasing the load factor and making the main array larger, it’s possible to reduce the number of collisions. The problem with this method is that it will waste memory. Using STL method The next method is using the standard template library (STL) for C++ that provides hash tables via std::unordered_map and std::unordered_set. The method does guarantee reference stability which means the references and pointers to the keys and values in the hash table remains valid until the corresponding key is removed. Thus the entries must be indirect and individually allocated but that would add a substantial CPU overhead. Folly comes with a fast C++ class without reference stability and a slower C++ class that allocates each entry in a separate node. According to Facebook, the node-based version is not fully standard compliant, but it is still compatible with the standard version for all the codes. F14 reduces collisions with vector instructions F14 provide practical improvements for both performance and memory by using the vector instructions available on modern CPUs. F14 uses the hash code for mapping the keys to a block of slots instead of to a single slot and then searches within the chunk in parallel. For this intra-chunk search, F14 uses vector instructions (SSE2 or NEON) that filters all the slots of the chunk at the same time. The team at Facebook has named this algorithm as F14 because it filters 14 slots at once. This F14  algorithm performs collision resolution in case a chunk overflows or if two keys both pass the filtering step. With F14 there is a low probability of collision taking place within instruction pipelining. The team used Chunking strategy for lowering the collision rate. To explain this better, the chance that 15 of the table’s keys would map to a chunk with 14 slots is quite lower than the chance that two keys would map to one slot. For instance, imagine you are in a room with 180 people. The chance that one other person has the same birthday as you is about 50 percent, but the chance that there are 14 people who were born in the same fortnight as you is much lower than 1 percent. Chunking keeps the collision rate low even for load factors above 80 percent. Even if there were 300 people in the room, the chance of a fortnight “overflow” is still less than 5 percent. F14 uses reference-counted tombstones for empty slots Most of the strategies for reducing the collisions keep looking for an empty slot until they find one but that is a little difficult to execute. In this case, the algorithm should either leave a tombstone, an empty slot that doesn’t terminate the probe search or it has to slide down the later keys in the probe sequence. This is again very complex and difficult to execute. In workloads that mix insert and erase, the tombstones can get accumulated. And accumulated tombstones increase the load factor from the performance perspective. F14 uses a strategy that acts similar to reference-counted tombstones. This strategy is based on an auxiliary bit for each slot suggested by Amble and Knuth in their 1974 article “Ordered hash tables.” A bit is set whenever their insertion routine passes a slot that is already full and the bit records that a slot has overflowed. A tombstone corresponds to an empty slot with the overflow bit set. The overflow bit makes searches faster as the search for a key can be stopped at a full slot where the overflow bit is clear, even if the following slot is not empty. The team at Facebook has worked towards having the count the number of active overflows. The overflow bits are set when a displaced key is inserted rather than when the key that did the displacing is removed. This makes it easy to keep track of the number of keys relying on an overflow bit. Each of the F14 chunks uses 1 byte of metadata for counting the number of keys that wanted to be placed in the chunk but are currently stored in a different chunk. And when a key gets erased, it decrements the overflow counter on all the chunks that are on its probe sequence by cleaning them up. F14 optimizes memory effectively It is important to reduce memory waste for improving performance and allowing more of a program’s data to fit in the cache. The two common strategies used for hash table memory layouts are indirect which uses a pointer stored in the main array and direct which uses a memory of the keys and values incorporated directly into the main hash array. F14 uses pointer-indirect (F14Node) and direct storage (F14Value) versions, and index-indirect (F14Vector). The Facebook team uses STL container std::unordered_set that never wastes any data space as it waits until the last moment to allocate nodes. The F14NodeSet executes a separate memory allocation for every value, like std::unordered_set. It also stores pointers to the values in chunks and uses F14’s probing collision resolution to ensure that there are no chaining pointers and no per-insert metadata. The  F14ValueSet stores the values inline and has lesser data waste due to using a higher maximum load factor. F14ValueSet hence achieves memory-efficiency easily. While testing, the team encountered unit test failures and production crashes. Though the team has randomized the code for debug builds. F14 now randomly chooses among all the empty slots in a chunk when inserting a new key. Also, the entry order isn’t completely randomized and according to the team, the shuffle is good enough to catch a regressing test with only a few runs. To know more about this news, check out Facebook’s post. New York AG opens investigation against Facebook as Canada decides to take Facebook to Federal Court for repeated user privacy violations Facebook shareholders back a proposal to oust Mark Zuckerberg as the board’s chairperson Facebook sets aside $5 billion in anticipation of an FTC penalty for its “user data practices”

Earlier this month, AKQA, a global innovation agency, introduced a new outdoor sport called Speedgate, which is created by an AI system built by them. This AI system was trained on more than 400 sports including Rugby, Soccer, and football to form the rules and regulations for Speedgate. In Speedgate, each team has six players consisting of forwards and defenders. The teams playing the game have to score goals by kicking through two consecutive gates. When a player kicks the ball through an X gate, the center gate will unlock the goal gate. After the center gate is unlocked, the team in possession can score by kicking the ball through the end gate in any direction. Here’s a video showing how this game actually works: https://www.youtube.com/watch?v=Uj4CQiuX8GM&feature=youtu.be Developers at AKQA trained a recurrent neural network and a deep convolutional generative adversarial network on over 400 sports. It uses NVIDIA Tesla GPUs for training the neural networks as well as for inferencing. Additionally, the neural network was also trained on 10,400 logos to generate the official Speedgate logo. The model was able to generate over 1,000 different sport concepts. Though many of them were interesting, the team wanted the AI system to come up with a game that was in addition to being fun and easy to understand was also active and accessible. And, Speedgate checked all the boxes for them. Kathryn Webb, AI Practice Lead at AKQA, said, “GPU technology helped us to condense training and generation phases down to a fraction of what they would’ve been. We would not have been able to achieve so many unique ML contributions in the project without that speed. It gave us more time to test, learn and adapt, and ultimately helped to produce the best final result.” Read more in detail, visit AKQA’s official website. OpenAI Five beats pro Dota 2 players; wins 2-1 against the gamers Google announces Stadia, a cloud-based game streaming service, at GDC 2019 Microsoft announces Game stack with Xbox Live integration to Android and iOS  

OpenAI has built a new deep neural network called MuseNet for composing music, the details of which it shared in a blog post yesterday. The research organization has made a prototype of MuseNet-powered co-composer available for users to try till May 12th. https://twitter.com/OpenAI/status/1121457782312460288 What is MuseNet? MuseNet uses the same general-purpose unsupervised technology as OpenAI’s GPT-2 language model, Sparse Transformer. This transformer allows MuseNet to predict the next note based on the given set of notes. To enable this behavior, Sparse Transformer uses something called “Sparse Attention”, where each of the output position computes weightings from a subset of input positions. For audio pieces, a 72-layer network with 24 attention heads is trained using the recompute and optimized kernels of Sparse Transformer. This provides the model long context that enables it to remember long term structure in a piece. For training the model, the researchers have collected training data from various sources. The dataset includes the MIDI files donated by ClassicalArchives and BitMidi. The dataset also includes data from online collections, including Jazz, Pop, African, Indian, and Arabic styles. The model is capable of generating 4-minute musical compositions with 10 different instruments and is aware of different music styles from composers like Bach, Mozart, Beatles, and more. It can also convincingly blend different music styles to create a completely new music piece. The MuseNet prototype, which is made available for users to try, only comes with a small subset of options. It supports two modes: In simple mode, users can listen to the uncurated samples generated by OpenAI. To generate a music piece yourself, you just need to choose a composer or style and an optional start of a famous piece. In advanced mode, users can directly interact with the model. Generating music in this mode will take much longer but will give an entirely new piece. Here’s how the advanced mode looks like: Source: OpenAI What are its limitations? The music generation tool is still a prototype so it does has some limitations: To generate each note, MuseNet calculates the probabilities across all possible notes and instruments. Though the model gives more priority to your instrument choices, there is a possibility that it will choose something else. MuseNet finds it difficult to generate a music piece in case of odd pairings of styles and instruments. The generated music will sound more natural if you pick instruments closest to the composer or band’s usual style. Many users have already started testing out the model. While some users are pretty impressed by the AI-generated music, some think that it is quite evident that the music is machine generated and lacks the emotional factor. Here’s an opinion shared by a Redditor for different music styles: “My take on the classical parts of it, as a classical pianist. Overall: stylistic coherency on the scale of ~15 seconds. Better than anything I've heard so far. Seems to have an attachment to pedal notes. Mozart: I would say Mozart's distinguishing characteristic as a composer is that every measure "sounds right". Even without knowing the piece, you can usually tell when a performer has made a mistake and deviated from the score. The Mozart samples sound... wrong. There are parallel 5ths everywhere. Bach: (I heard a bach sample in the live concert) - It had roughly the right consistency in the melody, but zero counterpoint, which is Bach's defining feature. Conditioning maybe not strong enough? Rachmaninoff: Known for lush musical textures and hauntingly beautiful melodies. The samples got the texture approximately right, although I would describe them more as murky more than lush. No melody to be heard.” Another user commented, “This may be academically interesting, but the music still sounds fake enough to be unpleasant (i.e. there's no way I'd spend any time listening to this voluntarily).” Though this model is in the early stages, an important question that comes in mind is who will own the generated music. “When discussing this with my friends, an interesting question came up: Who owns the music this produces? Couldn't one generate music and upload that to Spotify and get paid based off the number of listens?.” another user added. To know more in detail, visit the OpenAI’s official website. Also, check out an experimental concert by MuseNet that was live-streamed on Twitch. OpenAI researchers have developed Sparse Transformers, a neural network which can predict what comes next in a sequence OpenAI Five bots destroyed human Dota 2 players this weekend OpenAI Five beats pro Dota 2 players; wins 2-1 against the gamers

Yesterday, Facebook in its first quarter financial reports revealed that it has to pay a sum of  $5 billion, a fine levied by the US Federal Trade Commission (FTC). This penalty is “in connection with the inquiry of the FTC into our platform and user data practices”, the company said. The company, in their report, mentioned that the expenses result in a 51% year-over-year decline in net income, to just $2.4bn. If they minus this one-time expense, Facebook’s earnings per share would have beaten analyst expectations, and its operating margin (22%) would have been 20 points higher. Facebook said, “We estimate that the range of loss in this matter is $3.0bn to $5.0bn. The matter remains unresolved, and there can be no assurance as to the timing or the terms of any final outcome.” In the wake of the Cambridge Analytica scandal, the FTC had commenced their investigation into Facebook’s privacy practices last year in March. This investigation was focussed whether the data practices that allowed Cambridge Analytica to obtain Facebook user data violated the company’s 2011 agreement with the FTC. “Facebook and the FTC have reportedly been negotiating over the settlement, which will dwarf the prior largest penalty for a privacy lapse, a $22.5m fine against Google in 2012”, The Guardian reports. Read Also: European Union fined Google 1.49 billion euros for antitrust violations in online advertising “Levying a sizable fine on Facebook would go against the reputation of the United States of not restraining the power of big tech companies”, The New York Times reports. Justin Brookman, a former official for the regulator who is currently a director of privacy at Consumers Union, nonprofit consumer advocacy group, said, “The F.T.C. is really limited in what they can actually do in enforcing a consent decree, but in the case of Facebook, they had public pressure on their side.” Christopher Wylie, a Research director at H&M and the Cambridge Analytica Whistleblower, voiced against Facebook by tweeting, “Facebook, you banned me for whistleblowing. You threatened @carolecadwalla and the Guardian. You tried to cover up your incompetent conduct. You thought you could simply ignore the law. But you can’t. Your house of cards will topple.” https://twitter.com/chrisinsilico/status/1121150233541525505 Senator Richard Blumenthal, Democrat of Connecticut, mentioned in a tweet, “Facebook must be held accountable — not just by fines — but also far-reaching reforms in management, privacy practices, and culture.” Debra Aho Williamson, an e-marketer analyst, warned that the expectation of an FTC fine may portend future trouble. “This is a significant development, and any settlement with the FTC may impact the ways advertisers can use the platform in the future,” she said. Jessica Liu, a marketing analyst for Forrester said that Facebook has to show signs that it’s improving on user data practices and content management. “Its track record has been atrocious. No more platitudes. What action is Facebook Inc actually taking?” “For Facebook, a $5 billion fine would amount to a fraction of its $56 billion in annual revenue. Any resolution would also alleviate some of the regulatory pressure that has been intensifying against the company over the past two and a half years”, the New York Times reports. To know more about this news in detail visit Facebook’s official press release. Facebook hires a new general counsel and a new VP of global communications even as it continues with no Chief Security Officer Facebook shareholders back a proposal to oust Mark Zuckerberg as the board’s chairperson “Is it actually possible to have a free and fair election ever again?,” Pulitzer finalist, Carole Cadwalladr on Facebook’s role in Brexit

Twitter, yesterday launched a dedicated reporting feature to allow users to more easily report manipulative elections-related content. This content includes but is not limited to: Misleading information about how to vote or register to vote (for example, that you can vote by Tweet, text message, email, or phone call); Misleading information about requirements for voting, including identification requirements; and Misleading statements or information about the official announced date or time of an election. On encountering a misleading tweet, users can select report tweet from the drop-down menu and mark it as “it’s misleading about voting”. They can also select the option that best tells how the tweet is misleading about voting. Last year, Twitter shared an update on their work on maintaining conversational health and protecting the integrity of the mid-term US elections. This work ranged from updating their rules, detecting and removing several fake accounts, and introducing new features like electoral labels for election candidates. Twitter says that the new reporting feature will be used to tackle deliberate attempts to mislead about voting, starting with India’s #LokSabhaElections2019. This strengthened approach will be fully operational in India beginning today and in the EU from April 29. However, Twitter is a bit late to join the party considering India is already in Phase 3 of its election process with election results to be announced on 23rd May. https://twitter.com/KoshyG/status/1121026950733025281 It is also surprising as to why Twitter has only chosen India and the EU for it’s reporting feature. General elections will be held in Guatemala on June 16, 2019, to elect the President and Congress. The 2019 Australian federal election will be held on Saturday 18 May 2019 to elect members of the 46th Parliament of Australia. https://twitter.com/moimoi_arr/status/1121248501134962688 https://twitter.com/madcatjo2point0/status/1121000788954796032 On asking a Twitter spokesperson, whether it'll be available in the US, Twitter told CNET: "We're exploring this for critical elections outside the United States, and we'll provide an update on 2020 if and when we have one." Dorsey meets Trump privately to discuss how to make public conversation “healthier and more civil” on Twitter. Jack Dorsey engages in yet another tone deaf “public conversation” to better Twitter Highlights from Jack Dorsey’s live interview by Kara Swisher on Twitter: on lack of diversity, tech responsibility, physical safety and more.

Just two days ago the research team at OpenAI developed Sparse Transformer, a deep neural network that sets new records at predicting what comes next in a sequence, be it text, images, or sound. This transformer uses an algorithmic improvement of the attention mechanism for extracting patterns from sequences that are 30 times longer. This Transformer incorporates an O(N \sqrt{N}) reformulation of the O(N^2) Transformer self-attention mechanism with several other improvements on rich data types. Initially, the models used on these data were designed for one domain. Also, it was difficult to scale to sequences more than a few thousand elements long. The new Sparse Transformer can model sequences with tens of thousands of elements with hundreds of layers for achieving state-of-the-art performance across multiple domains. With this technique, the researchers aim to build AI systems that possess a greater ability to understand the world. The team also introduced several other changes to the Transformer which includes a restructured residual block and weight initialization for improving the training of very deep networks.The team also introduced a set of sparse attention kernels that efficiently compute subsets of the attention matrix. The team further experimented on recomputation of attention weights during the backward pass to reduce memory usage. Initial Experimentation with Deep Attention In Transformers, ‘attention’ is defined as a process where every output element is connected to every input element, and the weightings between them are dynamically calculated based upon the circumstances. Transformers are more flexible than models with fixed connectivity patterns. These Transformers can consume large amounts of memory while being applied to data types with many elements, like images or raw audio. One way of reducing this memory consumption is by recomputing the attention matrix from checkpoints during backpropagation which is a well-established technique in deep learning for reducing memory usage. However, the major issue with recomputing the attention matrix was that it was reducing memory usage at the cost of more computation and also, it couldn’t deal with large inputs. To overcome this, the OpenAI researchers introduced Sparse Attention. Using Sparse Attention patterns for large inputs For very large inputs, computing a single attention matrix can become impractical. The OpenAI researchers instead opted for sparse attention patterns, where each of the output position computes weightings from a subset of input positions. In the entire process, the researchers first visualized the learned attention patterns for deep Transformers on images and then found out that many showed interpretable and structured sparsity patterns. The team also realized that the input portions are focused on small subsets and they show a high degree of regularity. The researchers also implemented a two-dimensional factorization of the attention matrix, where the network can attend to all positions through two steps of sparse attention. They implemented it to preserve the ability of their network to learn new patterns. The first version is strided attention which is roughly equivalent to each position attending to its row and its column and is a bit similar to the attention pattern. The second version is fixed attention which attends to a fixed column and the elements after the latest column element. According to the researchers, it is a useful pattern and can be used when the data doesn’t fit into a two-dimensional structure. Testing Sparse Transformers on density modeling tasks The researchers test their architecture on density modeling tasks including natural images, text, and raw audio using CIFAR-10, Enwik8, and Imagenet 64 datasets respectively.. The team trained strided Sparse Transformers on CIFAR-10 images represented as sequences of 3072 bytes. They also trained models on the EnWik8 dataset for representing the first 108 bytes of Wikipedia containing variability in the periodic structure. They further trained on the version of downsampled ImageNet 64. The researchers found out that sparse attention achieved lower loss than full attention and it is also faster. Future scope and limitations According to the researchers, the sparse attention patterns are only preliminary steps in the direction of efficient modeling of long sequences. The researchers think that exploring different patterns and combinations of sparsity is useful and learning sparse patterns is a promising avenue of research for the next generation of neural network architectures. According to them, the autoregressive sequence generation still seems impractical for very high-resolution images or video. The optimized attention operations may prove to be useful for modeling high dimensional data, like multi-scale approaches. This is just an overview of the Sparse Transformer architecture. For more detailed information, we recommend you to read the research paper. OpenAI Five bots destroyed human Dota 2 players this weekend OpenAI Five beats pro Dota 2 players; wins 2-1 against the gamers OpenAI introduces Neural MMO, a multiagent game environment for reinforcement learning agents

Boeing Co. recently signed a $43 million contract from the US Navy to develop a fleet of massive drone submarines called Orca Extra Large Unmanned Undersea Vehicles (XLUUVs). Boeing and the US Navy haven’t disclosed any details of the size of the submarines. However, the design of these unmanned submarines would be based on their previously developed underwater drone prototype Echo Voyager unmanned sub. Major work will be carried out in Boeing’s Huntington Beach facility, and the drones are expected to be completed by 2022. The Echo Voyager is a 51-foot-long drone submarine that can achieve a range of roughly 6,500 nautical miles and is built to incorporate a modular payload section, which will allow it to take on a variety of different missions. According to Boeing, it can ‘perform at sea for months at a time,’ and does not require launch or recovery by a support vehicle and runs on a hybrid system that combines battery and marine diesel. Source: Boeing Bryan Clark, a senior fellow at the Center for Strategic and Budgetary Assessments think tank in Washington, D.C, said, “What it shows is that the Navy is willing to start putting some real money behind the acquisition of unmanned undersea vehicles. This is the first time the Navy has put significant money down on UUV (unmanned underwater vehicles) that have a military, war-fighting capability." Margaret E. Kosal, associate professor in the Sam Nunn School of International Affairs at the Georgia Institute of Technology said, “Analysts say undersea drones could be used for missions once conducted by crewed submarines, while the lack of a crew gives the drones an advantage in conducting "persistent surveillance for activities that might take place in an area where there is concern about underwater mines.” Clark also added that developing undersea drones comes with added technical challenges which are not experienced by aerial counterparts. Rosa Zheng, a professor in the department of electrical and computer engineering at Lehigh University explains that water is a much thicker medium. This actually makes real-time communication more difficult than sending transmissions through air. Scott Savitz, a senior engineer at the Rand Corp. think tank, said that “unlike an aerial drone, which can access satellite communications to gain its bearings and show what it sees in real time to a human operator thousands of miles away, an underwater drone loses access to the electromagnetic spectrum once it is below the waterline.” It was just last month that Boeing’s safety analysis procedure was questioned as authorities around the world — including the U.S., Europe, China, and Indonesia — grounded Boeing 737 Max planes being subject to two fatal crashes in less than six months involving the same plane model. And Boeing taking up this project, people are skeptical of what the consequences would be. https://twitter.com/jvaughn575/status/1120514009915064322 To know more about this announcement in detail, head over to U.S Naval Institute’s official blogpost. “Deep learning is not an optimum solution for every problem faced”: An interview with Valentino Zocca 4 common challenges in Web Scraping and how to handle them Microsoft workers protest the lethal use of Hololens2 in the $480m deal with US military

It was black day yesterday for the AI community as it lost one of the most celebrated AI pioneers and visionary, Nils John Nilsson. Nilsson passed away at the age of 86 and he was the first Kumagai Professor of Engineering (Emeritus) in the Computer Science department at Stanford University. He is known for inventing A* algorithm for path finding and also for leading the Shakey project at SRI which was one of the first mobile robots with visual projection and trajectory planning. https://twitter.com/RealAAAI/status/1120704966757216256 Professor Nilsson has published five textbooks on artificial intelligence, namely, Problem-Solving Methods in Artificial Intelligence (1971), Principles of Artificial Intelligence (1980), Artificial Intelligence: A New Synthesis (1998), The Quest for Artificial Intelligence: A History of Ideas and Achievements (2010), and Understanding Beliefs (2014). https://twitter.com/astrorobotic/status/1120717546506919936 https://twitter.com/rodneyabrooks/status/1120801543635132417 He has also served on the editorial boards of the journal Artificial Intelligence and of the Journal of Artificial Intelligence Research. His contributions to the field of planning, search, knowledge representation, and robotics have been respected worldwide. Nilsson was the Chairman of the Computer Science department at Stanford, where he taught artificial intelligence and machine learning. He served the Stanford Artificial Intelligence Center for twenty-three years. He also carried out his research on how robots react to the dynamic world, plan actions based on it, and learn from experience. He has worked on statistical and neural-network approaches to pattern recognition at Stanford’s Artificial Intelligence Center. Additionally, he has contributed towards the STRIPS automatic planning system. In one of the books, The Quest for Artificial Intelligence: A History of Ideas and Achievements, Professor Nilsson wrote, “Clues about what might be needed to make machines intelligent are scattered abundantly throughout philosophy, logic, biology, psychology, statistics, and engineering. With gradually increasing intensity, people set about to exploit clues from these areas in their separate quests to automate some aspects of intelligence.” He also defined Artificial Intelligence in the same book, “Artificial intelligence (AI) may lack an agreed-upon definition… For me, artificial intelligence is that activity devoted to making machines intelligent, and intelligence is that quality that enables an entity to function appropriately and with foresight in its environment.” Computer Science professor, Andrew Ng expressed his condolences and said that he lost a friend. He appreciated his efforts on A* algorithm and believes that a lot of researchers rely on this wonderful invention. https://twitter.com/AndrewYNg/status/1120551175403786241 https://twitter.com/danieljdick/status/1120826488599670789 Researchers, engineers, and AI enthusiast are mourning and expressing their condolences throughout on internet. Professor Nilsson’s contribution to the field of AI will be remembered always. https://twitter.com/dandre/status/1120568645518860288 https://twitter.com/haymhirsh/status/1120650482018594821 https://twitter.com/Sadeghi_Afshin/status/1120756172557029377 To know more about this news, check out Stanford’s page. OpenAI Five bots destroyed human Dota 2 players this weekend AI Now Institute publishes a report on the diversity crisis in AI and offers 12 solutions to fix it IBM halt sales of Watson AI tool for drug discovery amid tepid growth: STAT report  

Facebook has been facing a lot of scrutiny from different governments all around the world over how it manages customer’s data on its social media platform. It was also under the spotlight for enabling the spreading of misinformation across its network and faces increased pressure to stop the same. Facebook has a series of data breaches and scandals in its recent history. Starting from the Cambridge Analytica data scandal, the massive 50M Facebook accounts that were compromised, to the recent data breach where it “unintentionally uploaded” 1.5 million email contacts without consent. To mitigate the fallout of its unending scandals, Facebook has announced two new hirings within its team, yesterday. Jennifer Newstead, currently a legal adviser to the U.S. State Department, will soon be joining as the general counsel of the company and will oversee Facebook’s global legal functions. John Pinette will be joining as the vice president of global communications. Pinette is currently the vice president of marketing and communications at Vulcan, the private company created by Microsoft co-founder Paul Allen. Newstead will be replacing Colin Stretch, who announced in July 2018 about his plans to retire from Facebook. However, he will continue at Facebook through the summer to help with the transition, the company mentions in their press release. Stretch had also appeared before Congress in October 2017, to speak on Russian interference in the presidential election. On the other hand, Pinette will be replacing Caryn Marooney, who announced her plans to leave, in February this year. Mentioning Newstead, Sheryl Sandberg, Facebook’s Chief Operating Officer, said, “Jennifer is a seasoned leader whose global perspective and experience will help us fulfill our mission. We are also truly grateful to Colin for his dedicated leadership and wise counsel over the past nine years. He has played a crucial role in some of our most important projects and has created a strong foundation for Jennifer to build upon.” Newstead’s assistance in drafting the Patriot Act in the wake of the Sept. 11 attacks has been noteworthy. According to The Verge, “ As The Hill points out, a 2002 Justice Department press release describes her (Newstead) as “helping craft” the legislation. Bush administration lawyer John Yoo described her as the “day-to-day manager of the Patriot Act in Congress” in his 2006 book.” “I’m excited to be joining Facebook at an important time and working with such a fantastic team,” Newstead said. “Facebook’s products play an important role in societies around the world. I am looking forward to working with the team and outside experts and regulators on a range of legal issues as we seek to uphold our responsibilities and shared values. Pinette, on the other hand, has led communications for Gates Ventures, the private office and innovation lab of Bill Gates for five years, served as head of Asia Pacific communications for Google, and also held various product and corporate communications leadership positions at Microsoft. He has also served as the first head of external communications for hedge fund Pershing Square Capital Management. “John’s deep understanding of the technology industry and his experience leading communications teams will be invaluable to helping us communicate the work we do at Facebook every day,” Sandberg said. “We are also thankful to Caryn for her exceptional contribution to Facebook over the past eight years. She has been an inspiring and thoughtful leader to our communications team and countless others at the company. Both she and Colin will be greatly missed.” Also, last year, after Alex Stamos, ex-Chief Security Officer at Facebook resigned from the company, Facebook stated that no one would replace Stamos. Facebook decided to not have a central point (CSO) but instead depend on the security teams, basically having no head leading the security team. This means Facebook does not even have a CSO in place. The public has found this move by Facebook appalling, adding more to its long list of poor decision making. A former FB employee told The Verge, “ The platform — with its tentacles in every last aspect of people's lives — is now receiving legal counsel by the woman who authored much of the Patriot Act”. Ryan Mac, a tech reporter, tweeted, “Will be interesting to see what the folks that FB hired away from privacy advocacy institutions like EFF and Access Now will do when they have to work with Newstead.” A US Tech reporter, Laurence Dodds, tweeted about John Pinette, “On his LinkedIn page, Pinette says that he was the director of communications for Microsoft between 1996 and 2007. That means that he was in the hot seat for Microsoft's big antitrust battle – a years-long political and legal confrontation very similar to the one FB is now facing.” To know more about this announcement in detail, visit Facebook’s official press release. “Is it actually possible to have a free and fair election ever again?,” Pulitzer finalist, Carole Cadwalladr on Facebook’s role in Brexit Facebook shareholders back a proposal to oust Mark Zuckerberg as the board’s chairperson Will Facebook enforce it’s updated “remove, reduce, and inform” policy to curb fake news and manage problematic content?

The EU parliament voted last week to develop what is being described as the largest biometric database on earth. Once created, the database will connect the systems used by various border control, migration and law enforcement agencies into a truly gigantic searchable database for both EU and Non EU citizens. The new database will be called the Common Identity Repository (CIR) and will unify records of over 350 million people. What’s the purpose of the Common Identity Repository? The CIR will streamline a number of operations, bringing together information that is highly distributed - and even siloed - into one place. It will mean that officials will only need to search a single database rather than multiple ones. But accessibility is only one element - it also brings together layers of biometric information such as fingerprints, faces and personal data, like passport numbers. According to Politico Europe, the new system “will grant officials access to a person’s verified identity with a single fingerprint scan.” The multifaceted nature of the system can be explained by the way it was approved by the European Parliament. It went through on two separate votes: one for merging systems used for things related to visas and borders were approved 511 to 123 (with nine abstentions), and the other for streamlining systems users for law enforcement, judicial, migration, and asylum matters was approved 510 to 130 (also with nine abstentions). On this EU officials stated last week that, "The systems covered by the new rules would include the Schengen Information System, Eurodac, the Visa Information System (VIS) and three new systems: the European Criminal Records System for Third Country Nationals (ECRIS-TCN), the Entry/Exit System (EES) and the European Travel Information and Authorisation System (ETIAS)" Criticism of the Common Identity Repository The plan has come in for serious criticism from those who argue that there are serious privacy rights at stake. The civil liberties advocacy group Statewatch had asserted last year that it would lead to the “creation of a Big Brother centralised EU state database and have called CIR as the point of no return.” The European Parliament says “the system will make EU information systems used in security, border and migration management interoperable enabling data exchange between the systems.” It is also argued by the critics that once up and running, CIR will be one of the biggest people-tracking databases in the world, right behind the systems used by the Chinese government and India's Aadhar system. https://twitter.com/fs0c131y/status/1120374735693598720 Microsoft and Cisco propose ideas for a Biometric privacy law after the state of Illinois passed one Biometric Information Privacy Act: It is now illegal for Amazon, Facebook or Apple to collect your biometric data without consent in Illinois SafeMessage: An AI-based biometric authentication solution for messaging platforms

Last week, the Austrian government released plans to eliminate internet anonymity. Austrian users will now have to provide operators with their true identities or they might be fined in millions. This means that users from Austria can’t comment or post anonymously now. The law will get in force from 2020. Users will now have to provide their first name, last name and address to platform operators, as per the government's new draft law on Diligence and Responsibility on the Web. The operators will have to supply that information to government agencies or, in some cases, to private people in cases of insult or defamation for investigation purpose. Media Minister Gernot Blümel, of the center-right Austrian People's Party (ÖVP), said at a press conference, "The legal requirements that are valid in the analog world must also be valid in the digital world. That is why there is now an abundance of resolutions to make the correction." He further added, “The so-called digital anonymity ban is an additional step in that direction.” This law is applicable to platforms that either have more than 100,000 registered users; or who earn more than 500,000 euros in annual revenues; or the ones that receive government press subsidies of more than 50,000 euros. Per the draft law, the platforms would also have a responsibility to determine if the ID information provided by users is accurate. The process of how these platforms choose to do so is up to them. Though the draft law does mention the use of dual-factor authentication by way of the user's mobile number. All the SIM cards in Austria need to be registered with a photo ID by the beginning of the next year. Even the web platforms who would be responsible for making information about the platform are required to appoint a liaison in Austria. If the regulation is not followed, then the person will be fined up to 100,000 euros. The fines could even reach as high as 500,000 euros to a million euros depending upon the severity of the violation. The Austrian Communications Authority also known as KommAustria is responsible for enforcement of the law. This law exempts e-commerce platforms as they are the platforms that earn no revenues from their content or from advertising. Privacy and law experts condemn Austria’s new law Most IT and privacy experts are against Austria’s internet anonymity law. Markus Dörfler, an IT lawyer says, "In the real world, I don't demand to see an ID as a precautionary measure.” He believes this step is towards the establishment of censorship and the law could limit the freedom of expression. He also thinks that this law would work against the European Convention on Human Rights (ECHR), according to which any limitations on the freedom of expression can only be made if they are "necessary in a democratic society." According to him, it is unlikely that most of the foreign social media platforms will appoint a liaison in Austria and if the law will be applied to them. He further adds, "No Chinese network is going to start checking the identities of its users in order to comply with the law.” Dörfler is also unclear about whether the law is in parallel with the 2016 ruling by the European Court of Justice on data retention because as per the ruling, "general and indiscriminate retention of data is not allowed.” It also invades the right to privacy and the protection of personal data. Nikolaus Forgó, tech law expert also adds his views saying, "This path won't even come close to achieving the goal of internet discipline." He further adds that the law will lead to high costs such as paying the liaison which would damage Austria's "already weak" digital infrastructure. Also, it would be difficult to protect such a large amount of data which will give rise to data protection concerns. The platform operators will get this huge amount of data in their hands which could be risky. According to tech law expert, Lukas Feiler from the law firm Baker McKenzie, the draft law is a violation of the EU’s e-commerce directive. Feiler said, "The e-commerce directive protects the freedom to provide services for online platforms.” According to Mario Lindner, a diversity spokesman for the center-left Social Democratic Party of Austria (SPÖ), “the draft law overshoots its target.” Linder further added, “What the government has presented is not a solution to the challenges that are facing us in the digital space." To know more about this news, check out the post by Standard. IBM sued by former employees on violating age discrimination laws in workplace Are the lawmakers and media being really critical towards Facebook? Microsoft says tech companies are “not comfortable” storing their data in Australia thanks to the new anti-encryption law

In this era where technologies are advancing and innovation is booming, issues like racism, ageism sexism, patriarchy and misogyny still prevail. Tech industries have also been in light because of these reasons. In 2014, Microsoft CEO, Satya Nadella’s comments on women made news as he suggested that women shouldn’t be asking for a raise. In 2016 Microsoft came up with an AI chatbot called Tay, that got racist by learning from the negative conversations on Twitter. And recently one of the female employees at Microsoft complained about sexual harassment. They shared their frustrations about discrimination and sexual harassment, which was ranging from sexist comments during work trips to being told to sit on a coworker’s lap in front of a human resources leader. She mentioned that an employee from a partner company threatened to kill her if she did not perform implied sexual acts during a work trip.  “I raised immediate attention to HR and management.” She further added, “My male manager told me that ‘it sounded like he was just flirting’ and I should ‘get over it’. HR basically said that since there was no evidence, and this man worked for a partner company and not Microsoft, there was nothing they could do.” It’s disheartening how giant tech companies like Microsoft have a lot of things going on inside and women employees suffer due to baseless responses from the management. According to Microsoft's recent diversity report, 87% of Microsoft employees are white or Asian and more than 73% are men. Employees are questioning the company over its diversity and employee policies. They have now started discussing on Yammer, Microsoft’s internal message board. A female engineer asked, "Does Microsoft have any plans to end the current policy that financially incentivizes discriminatory hiring practices?" In the same post she added, "To be clear, I am referring to the fact that senior leadership is awarded more money if they discriminate against Asians and white men." Similar posts on Yammer related to discriminatory hiring which read, “Women are less suited for engineering roles” received more than 800 comments where few agreed to the statement and few criticized it. A female program Manager commented on the post, “I have an ever-increasing file of white male Microsoft employees who have faced outright and overt discrimination because they had the misfortune of being born both white and male. This is unacceptable.” According to Quartz, a member of Microsoft’s employee investigations team replied to a post related to discrimination, “The company does not tolerate discrimination of any kind.” Employees are not satisfied and they feel that there have been no steps taken so far in this regard. In a statement to Quartz, an employee said, “HR, Satya, all the leadership are sending out emails that they want to have an inclusive culture, but they’re not willing to take any action other than talk about it. They allow people to post these damaging, stereotypical things about women and minorities, and they do nothing about it.” With all sorts of discrimination and harassment at the workplace, it is high time that tech industries introduce major policy changes to encourage a fair, open and comfortable environment for the employees especially women. And for this few have already taken a stand against such issues and are coming together for a transition. https://twitter.com/aprilwensel/status/1119372644418068480 To know more about this news, check out the post by Quartz. Microsoft Bling introduces Fire: a Finite state machine and regular expression manipulation library Microsoft reveals certain Outlook.com user accounts were hacked for months Microsoft makes the first preview builds of Chromium-based Edge available for testing

Facebook is constantly making news around the spread of misinformation and data privacy concerns and has been in the bad books of the lawmakers and privacy experts. Recently, Facebook decided to partner with Daily Caller, American news and opinion website that has promoted misinformation and is known for its pro-Trump content. Facebook and Daily Caller are planning to work together on Facebook’s fact-checking program project. This week, Facebook even announced that it added CheckYourFact.com, a fact-checking news site, which is a part of the Daily Caller. The company faced backlash from the journalist community because of this initiative. Facebook lost one of its major US partners, Snopes the news website for working on the fact-checking program. Facebook even opened up about exposing millions of user passwords in a plain text, last month. And according to a recent report, the count of user passwords exposed is much higher than what was declared last month. In addition to this just on Wednesday, Facebook broke the news that it may have “unintentionally uploaded” the email contacts of 1.5 million new users on its site since May 2016, without their consent. After a series of scandals by the company, Mark Zuckerberg, CEO at Facebook, is now in a major fix as the Federal Regulators are discussing the history of Facebook scandals. And yesterday Washington Post reported that Federal Regulators are into a discussion regarding how to hold Zuckerberg personally accountable for the company's history of mismanaging users' private data. It’s been over a year since FTC (Federal Trade Commission) is in a discussion with Facebook over its data-handling practices. Roger McNamee, an early investor in the company and one of Zuckerberg's foremost critics, said, “The days of pretending this is an innocent platform are over, and citing Mark in a large scale enforcement action would drive that home in spades.” This initiative by FTC looks like a warning bell for other tech giants who are into misusing user information as the agency might hold individuals over their misdeed at their respective organizations. Justin Brookman, a former policy director for technology research at the Federal Trade Commission, said, “While the FTC can name individual company leaders if they directed, controlled and knew about any wrongdoing, they typically only use that authority in fraud-like cases, so far as I can tell." This isn’t the first time Federal Regulators are planning on an action against the company. Earlier this year, advocacy groups such as Open Market Institute, Color of Change, and the Electronic Privacy Information Center among others, wrote to the Federal Trade Commission, requesting the government to intervene into how Facebook operates. FTC even planned to impose a fine of over $22.5 billion on Facebook for privacy violations. But it seems this time it’s not going to be easy for Mark Zuckerberg as this time, FTC officers are interested to directly aim at Zuckerberg by putting him personally under the order and subjecting him to federal oversight. Facebook confessed another data breach; says it “unintentionally uploaded” 1.5 million email contacts without consent FTC officials plan to impose a fine of over $22.5 billion on Facebook for privacy violations, Washington Post reports Facebook shareholders back a proposal to oust Mark Zuckerberg as the board’s chairperson  

STAT reported yesterday that IBM is halting the sales of their “Watson for Drug Discovery” machine learning/AI tool, according to sources within the company. According to STAT report, IBM is giving up its efforts to develop and flog its Drug Discovery technology due to “sluggish sales,”. But no one seems to have told IBM’s website programming team, because the pages of the product information are still up on the IBM website. They’re worth taking a look as to how the product has been over-promised by IBM. Apparently, IBM Watson Health uses AI software to help companies reveal the connection and relationship among genes, drugs, diseases, and other entities by analyzing multiple sets of life sciences knowledge. But according to the IEEE Spectrum report, IBM’s entire foray into health care has been marked by the familiar combination of overpromising and under-delivery. However, the service isn’t completely shutting down. IBM spokesperson Ed Barbini told to The Register: “We are not discontinuing our Watson for Drug Discovery offering, and we remain committed to its continued success for our clients currently using the technology. We are focusing our resources within Watson Health to double down on the adjacent field of clinical development where we see an even greater market need for our data and AI capabilities.” In other words, it appears the product won’t be sold to any new customers, however, organizations that want to continue using the system will still be supported. “The offering is staying on the market, and we'll work with clients who want to team with IBM in this area. But our future efforts will be more focused on clinical trials – it's a much bigger market and better use of our technology and tools.”, according to IBM The Drug Discovery service is made up of lots of different products or "modules," such as a search engine that allows chemists to crawl scientific abstracts to find information on a specific gene or chemical compound. There’s also a knowledge network that describes relationships between drugs and diseases. IBM’s Health division has been crumbling for a while. IBM Watson Health’s Oncology AI software dished out incorrect and unsafe recommendations during beta testing. And to add to their worry, in October last year Deborah DiSanzo, IBM’s head of Watson Health, stepped down from her position too. IBM CEO, Ginni Rometty, on bringing HR evolution with AI and its predictive attrition AI IBM announces the launch of Blockchain World Wire, a global blockchain network for cross-border payments Diversity in Faces: IBM Research’s new dataset to help build facial recognition systems that are fair

Nicholas Bergson-Shilcock, the co-founder of Recurse Center, announced yesterday, that the company has nearly achieved its 2012 goal of making RC 50% women. Recurse Center is a self-directed, community-driven educational retreat for programmers in New York City. After seven years, 48% of new hires at RC this year are women, trans, or non-binary. “We believe nearly every aspect of RC gets better when RC becomes more diverse...my cofounders and I have experienced RC across 60 batches: some with significant gender, racial, age, and other forms of diversity, and others with very little diversity. We believe firmly that the former are a better experience for everyone”, states Shilcock. RC mainly focused on three things as a part of its strategy to achieve its goal. These three things include: getting a strong and diverse pool of applicants, minimizing bias and evaluating everyone on the same admissions criteria, and building an environment where different people can easily thrive. As a part of RC’s strategy: It first focussed on getting as strong and diverse a range of applicants as possible. To achieve this, RC funded women and people from other traditionally underrepresented groups for the program. For instance, RC  partnered with Etsy in April 2012 to fund living expense grants for women who can’t afford to attend RC. RC further expanded its grants program in 2014 to include Black, Latina/o, Native American, and Pacific Islander people. By 2015, RC began funding grants itself and has managed to disburse over $1.5 million in grants so far. Apart from that, RC also offered merit-based fellowships of up to $10,000   to women, trans, and non-binary people that work on open source projects, research, and art. RC launched Joy of Computing last year which is a site that features technical work by members of the RC community. Secondly, RC focused on minimizing bias and evaluate everyone on the same admissions criteria. To achieve this, RC uses pseudonyms and hides the demographic information. For instance, RC updated its admissions review software in 2014 to replace people’s names with pseudonyms ( “Keyboarding Animal” or “Temperature Jeans” instead of “José Smith” or “Kimberly Lin”). Shilcock recommends that companies should document and clearly explain their admission criteria and process. Firms should also be very specific about what precisely comes under their criteria. RC also recommends training its interviewers and recording the interviews for quality control and training. Additionally, RC offers ongoing support and has a process in place for giving interviewers feedback Lastly, RC focused on building and nurturing an environment where different kind of people can thrive. To foster a healthy work environment, RC has explicit social rules in place that contribute towards making RC a friendly, and productive place to program and grow. RC also has a code of conduct in place which is a system for reporting violations and a response protocol. Moreover, it also focuses on welcoming people and making them a part of its community. RC is further working towards itself as a firm more accessible to the programming community. For instance, apart from attending RC for six or 12-week batches, people can now also attend for a week-long program and become alumni and lifelong member of the community. RC has also modified and updated some of its policies to make RC more family-friendly. There is now a lactation and wellness room at RC, which will allow parents to bring their children along with them. Shilcock states that earlier in 2012, only 5% of the Recursers were women, trans, or non-binary, but that figure has changed to 34% now. Also, of the nearly 150 people who have already joined RC’s batch for this year, 48% identify as women, trans, or non-binary. However, Shilcock states that although the numbers are quite promising, they can fluctuate. “We know it will take continuous investment and work to have any chance of consistently achieving a gender-balanced environment at RC”, writes Shilcock. For more information, check out the official Recurse Center announcement. Women win all open board director seats in Open Source Initiative 2019 board elections Google’s pay equity analysis finds men, not women, are underpaid; critics call out design flaws in the analysis Apollo 11 source code: A small step for a woman, and a huge leap for software engineering