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  Cost-sensitive machine learning

  Cost-sensitive machine learning is an approach within machine learning that considers varying costs associated with different types of errors. This method diverges from traditional approaches by introducing a cost matrix, explicitly specifying the penalties or benefits for each type of prediction error. The inherent difficulty which cost-sensitive machine learning tackles is that minimizing different kinds of classification errors is a multi-objective optimization problem. == Overview == Cost-sensitive machine learning optimizes models based on the specific consequences of misclassifications, making it a valuable tool in various applications. It is especially useful in problems with a high imbalance in class distribution and a high imbalance in associated costs Cost-sensitive machine learning introduces a scalar cost function in order to find one (of multiple) Pareto optimal points in this multi-objective optimization problem (similar to the Weighted sum model) == Cost Matrix == The cost matrix is a crucial element within cost-sensitive modeling, explicitly defining the costs or benefits associated with different prediction errors in classification tasks. Represented as a table, the matrix aligns true and predicted classes, assigning a cost value to each combination. For instance, in binary classification, it may distinguish costs for false positives and false negatives. The utility of the cost matrix lies in its application to calculate the expected cost or loss. The formula, expressed as a double summation, utilizes joint probabilities: Expected Loss = ∑ i ∑ j P ( Actual i , Predicted j ) ⋅ Cost Actual i , Predicted j {\displaystyle {\text{Expected Loss}}=\sum _{i}\sum _{j}P({\text{Actual}}_{i},{\text{Predicted}}_{j})\cdot {\text{Cost}}_{{\text{Actual}}_{i},{\text{Predicted}}_{j}}} Here, P ( Actual i , Predicted j ) {\displaystyle P({\text{Actual}}_{i},{\text{Predicted}}_{j})} denotes the joint probability of actual class i {\displaystyle i} and predicted class j {\displaystyle j} , providing a nuanced measure that considers both the probabilities and associated costs. This approach allows practitioners to fine-tune models based on the specific consequences of misclassifications, adapting to scenarios where the impact of prediction errors varies across classes. == Applications == === Fraud Detection === In the realm of data science, particularly in finance, cost-sensitive machine learning is applied to fraud detection. By assigning different costs to false positives and false negatives, models can be fine-tuned to minimize the overall financial impact of misclassifications. === Medical Diagnostics === In healthcare, cost-sensitive machine learning plays a role in medical diagnostics. The approach allows for customization of models based on the potential harm associated with misdiagnoses, ensuring a more patient-centric application of machine learning algorithms. == Challenges == A typical challenge in cost-sensitive machine learning is the reliable determination of the cost matrix which may evolve over time. == Literature == Cost-Sensitive Machine Learning. USA, CRC Press, 2011. ISBN 9781439839287 Abhishek, K., Abdelaziz, D. M. (2023). Machine Learning for Imbalanced Data: Tackle Imbalanced Datasets Using Machine Learning and Deep Learning Techniques. (n.p.): Packt Publishing. ISBN 9781801070881

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  Sanchar Saathi

  Sanchar Saathi (lit. 'Communication Partner' or 'Communication Companion') is an Indian state-owned app and web portal, operated by the Department of Telecommunications, designed to assist Indian mobile users in tracking and blocking stolen or lost mobile devices. In late 2025, a government order requiring Sanchar Saathi to be pre-installed on all mobile devices sold nationwide, with explicit provisions on preventing users from deleting the app or disabling any of its broad functionalities, triggered widespread backlash. The order was subsequently withdrawn. == Background == The Telecommunications Act 2023 introduced an exceptionally broad definition of the term "telecommunications" and conferred wide-ranging powers on the government. Although the Department of Telecommunications (DoT) assured reporters that this definition would not be used to justify government overreach, a November 2024 amendment to the Telecom Cyber Security Rules expanded it further and introduced the concept of the Telecommunication Identifier User Entity (TIEU), enabling users to be personally identified through their phone numbers. Sanchar Saathi was launched amid a widespread rise in cybercrime and hacking, as part of the Indian government's effort to prevent stolen phones from being used for fraud and to promote a state-backed application. In an official statement, the DoT said, "India has big second-hand mobile device market. Cases have also been observed where stolen or blacklisted devices are being re-sold. It makes the purchaser abettor in crime and causes financial loss to them." == Launch == Sanchar Saathi was originally launched as a web portal in May 2023. It was later launched as a mobile app in January 2025. Describing itself as a "citizen-centric" safety tool, Sanchar Saathi allows users to check a device's IMEI, report and block lost or stolen phones, and flag suspected fraud communications. Under Sanchar Saathi's privacy policy, it can make and manage phone calls, view and send messages, read call logs, access photos and files, access the location and camera of the device in which the app is used, as well as read and write into the device's storage. According to official government data, by December 2025, the Sanchar Saathi app had helped recover more than 700,000 lost and stolen mobile devices across India. Users report around 2,000 fraud incidents through the app each day. == Pre-installation controversy == On 28 November 2025, the Bharatiya Janata Party government, led by prime minister Narendra Modi, privately ordered phone manufacturers, including Apple, Samsung, Xiaomi, Vivo, Oppo, among others, to pre-install the Sanchar Saathi app on new devices sold in the country, alongside mandating that old devices get issued a software update for the installation of the app. The order had a 90-day deadline and further included explicit provisions to ensure that the app is to be "readily visible and accessible to the end users at the time of first use or device setup" and that users should neither be able to delete the app nor disable or restrict any of its broad functionalities. The order caused widespread political backlash. K. C. Venugopal, a general secretary of the main opposition party, the Indian National Congress (or simply the Congress), called the order "beyond unconstitutional" and said, "A pre-loaded government app that cannot be uninstalled is a dystopian tool to monitor every Indian. It is a means to watch over every movement, interaction and decision of each citizen", adding, "Big Brother cannot watch us." Another Congress general secretary, Priyanka Gandhi, termed Sanchar Saathi a "snooping app", and attacked the government for "turning this country into a dictatorship". Uddhav Thackeray, former chief minister of Maharashtra, compared Sanchar Saathi to the Pegasus spyware. Sanjay Hegde, a senior advocate at the Supreme Court of India, said "Here in the garb of security, the intrusion is vast, unfettered, unguided and is totally disproportionate. The app ought to be struck down on that account". The Internet Freedom Foundation (IFF), an Indian digital rights advocacy organisation, said, "Forcing every smartphone to carry a permanent government app for a simple verification task is excessive and violates the Puttaswamy proportionality standard", referring to Puttaswamy v. Union of India, a 2017 landmark decision of the Supreme Court, which asserted that the right to privacy should be protected as a fundamental right. The IFF further said, "For this to work in practice, the app will almost certainly need system level or root level access, similar to carrier or OEM system apps, so that it cannot be disabled. That design choice erodes the protections that normally prevent one app from peering into the data of others, and turns Sanchar Saathi into a permanent, non-consensual point of access sitting inside the operating system of every Indian smartphone user." Moreover, the organisation said that while the app was being "framed as a benign IMEI checker", a server-side update could allow the app to engage in "client side scanning for 'banned' applications, flag VPN usage, correlate SIM activity, or trawl SMS logs in the name of fraud detection. Nothing in the order constrains these possibilities." In reaction to the controversy, Jyotiraditya Scindia, the union minister of communications, said, "There is no snooping or call monitoring", adding, "Obviously you can delete it. There is no problem. This is a matter of customer protection. It is not mandatory. If you don't want to register, and don't want to use the app, don't use it; don't register, and it will lay dormant." Scindia compared the app to other pre-installed mobile apps such as Google Maps, which he said could be deleted if users wished so. However, contrary to Scindia's statement, on many phone brands, such pre-installed apps cannot be deleted, although users can disable them. Furthermore, upon enquiry, Scindia did not clarify whether his remarks applied to the app after the order took effect, making no comment on the provision in the order that would prevent users from deleting the app. When Congress member Renuka Chowdhury submitted an adjournment motion notice in the Rajya Sabha seeking the suspension of all other matters to discuss the Sanchar Saathi issue, Kiren Rijiju, the union minister of parliamentary affairs, accused the opposition of "manufacturing issues" to stall session proceedings. By 2 December, it had been reported that Apple did not plan to comply with the order, citing privacy and security concerns for the iOS ecosystem and the fact that the order would violate its internal policy against the pre-installation of third-party software in iPhones. Although it was clarified that Apple did not intend to take the matter to court or publicly oppose the government, it was said that Apple "can't do this. Period." The order would have also required Google to create a custom version of Android solely for India which would include the Sanchar Saathi app, a requirement described to "not be acceptable to the company". Following the backlash, the order was revoked on 3 December 2025. In a press release, the government said, "Given Sanchar Saathi's increasing acceptance, Government has decided not to make the pre-installation mandatory for mobile manufacturers".

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  Non-photorealistic rendering

  Non-photorealistic rendering (NPR) is an area of computer graphics that focuses on enabling a wide variety of expressive styles for digital art, in contrast to traditional computer graphics, which focuses on photorealism. NPR is inspired by other artistic modes such as painting, drawing, technical illustration, and animated cartoons. NPR has appeared in movies and video games in the form of cel-shaded animation (also known as "toon" shading) as well as in scientific visualization, architectural illustration and experimental animation. == History and criticism of the term == The term non-photorealistic rendering is believed to have been coined by the SIGGRAPH 1990 papers committee, who held a session entitled "Non Photo Realistic Rendering". The term has received some criticism: The term "photorealism" has different meanings for graphics researchers (see "photorealistic rendering") and artists. For artists—who are the target consumers of NPR techniques—it refers to a school of painting that focuses on reproducing the effect of a camera lens, with all the distortion and hyper-reflections that it creates. For graphics researchers, however, it refers to an image that is visually indistinguishable from reality. In fact, graphics researchers lump the kinds of visual distortions that are used by photorealist painters into "non-photorealism". Describing something by what it is not is problematic. Equivalent (made-up) comparisons might be "non-elephant biology" or "non-geometric mathematics". NPR researchers have stated that they expect the term will disappear eventually and be replaced by the now more general term "computer graphics", with "photorealistic graphics" being the term used to describe "traditional" computer graphics. Many techniques that are used to create 'non-photorealistic' images are not rendering techniques. They are modelling techniques, or post-processing techniques. While the latter are coming to be known as 'image-based rendering', sketch-based modelling techniques, cannot technically be included under this heading, which is very inconvenient for conference organisers. The first conference on non-photorealistic animation and rendering included a discussion of possible alternative names. Among those suggested were "expressive graphics", "artistic rendering", "non-realistic graphics", "art-based rendering", and "psychographics". All of these terms have been used in various research papers on the topic, but the "non-photorealistic" term seems to have nonetheless taken hold. The first technical meeting dedicated to NPR was the ACM-sponsored Symposium on Non-Photorealistic Rendering and Animation(NPAR) in 2000. NPAR is traditionally co-located with the Annecy Animated Film Festival, running on even numbered years. From 2007 onward, NPAR began to also run on odd-numbered years, co-located with ACM SIGGRAPH. == 3D == Three-dimensional NPR is the style that is most commonly seen in video games and movies. The output from this technique is almost always a 3D model that has been modified from the original input model to portray a new artistic style. In many cases, the geometry of the model is identical to the original geometry, and only the material applied to the surface is modified. With increased availability of programmable GPU's, shaders have allowed NPR effects to be applied to the rasterised image that is to be displayed to the screen. The majority of NPR techniques applied to 3D geometry are intended to make the scene appear two-dimensional. NPR techniques for 3D images include cel shading and Gooch shading. Many methods can be used to draw stylized outlines and strokes from 3D models, including occluding contours and Suggestive contours. For enhanced legibility, the most useful technical illustrations for technical communication are not necessarily photorealistic. Non-photorealistic renderings, such as exploded view diagrams, greatly assist in showing placement of parts in a complex system. Cartoon rendering, also called cel shading or toon shading, is a non-photorealistic rendering technique used to give 3D computer graphics a flat, cartoon-like appearance. Its defining feature is the use of distinct shading colors rather than smooth gradients, producing a look reminiscent of comic books or animated films. This technique is often used to blend 3D objects and environments with 2D hand-animated elements while maintaining a consistent look. Treasure Planet movie by Disney is an example of blending these techniques. == 2D == The input to a two dimensional NPR system is typically an image or video. The output is a typically an artistic rendering of that input imagery (for example in a watercolor, painterly or sketched style) although some 2D NPR serves non-artistic purposes e.g. data visualization. The artistic rendering of images and video (often referred to as image stylization) traditionally focused upon heuristic algorithms that seek to simulate the placement of brush strokes on a digital canvas. Arguably, the earliest example of 2D NPR is Paul Haeberli's 'Paint by Numbers' at SIGGRAPH 1990. This (and similar interactive techniques) provide the user with a canvas that they can "paint" on using the cursor — as the user paints, a stylized version of the image is revealed on the canvas. This is especially useful for people who want to simulate different sizes of brush strokes according to different areas of the image. Subsequently, basic image processing operations using gradient operators or statistical moments were used to automate this process and minimize user interaction in the late nineties (although artistic control remains with the user via setting parameters of the algorithms). This automation enabled practical application of 2D NPR to video, for the first time in the living paintings of the movie What Dreams May Come (1998). More sophisticated image abstractions techniques were developed in the early 2000s harnessing computer vision operators e.g. image salience, or segmentation operators to drive stroke placement. Around this time, machine learning began to influence image stylization algorithms notably image analogy that could learn to mimic the style of an existing artwork. The advent of deep learning has re-kindled activity in image stylization, notably with neural style transfer (NST) algorithms that can mimic a wide gamut of artistic styles from single visual examples. These algorithms underpin mobile apps capable of the same e.g. Prisma In addition to the above stylization methods, a related class of techniques in 2D NPR address the simulation of artistic media. These methods include simulating the diffusion of ink through different kinds of paper, and also of pigments through water for simulation of watercolor. == Artistic rendering == Artistic rendering is the application of visual art styles to rendering. For photorealistic rendering styles, the emphasis is on accurate reproduction of light-and-shadow and the surface properties of the depicted objects, composition, or other more generic qualities. When the emphasis is on unique interpretive rendering styles, visual information is interpreted by the artist and displayed accordingly using the chosen art medium and level of abstraction in abstract art. In computer graphics, interpretive rendering styles are known as non-photorealistic rendering styles, but may be used to simplify technical illustrations. Rendering styles that combine photorealism with non-photorealism are known as hyperrealistic rendering styles. == Notable films and games == This section lists some seminal uses of NPR techniques in films, games and software. See cel-shaded animation for a list of uses of toon-shading in games and movies.

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  Jeremy Renner Official

  Jeremy Renner Official (or Jeremy Renner on the Google Play Store) was a mobile app created by American actor Jeremy Renner. He created the app in March 2017 to hear the input and comments of his fans. The app was shut down in September 2019 in part due to the frequent bullying and trolling that the platform had experienced. The app featured optional microtransactions, with some ranging up to roughly US$400 despite the app itself being free. Upon shutting down the app, Renner issued a mass-refund for the collectible "stars" in the app for purchases made within the last ninety days, from the day the announcement was posted. He then posted an apology to the app itself, and the app was deleted from both the Google Play Store and the App Store shortly after. == Usage == Upon downloading the app, the user was faced with a video of Renner speaking about his fans and superfans, regular giveaways, and real-life updates. While the app was active, Renner posted regular questions and comments for fans. Renner occasionally livestreamed about his work and day-to-day life. The community developed to include memes, selfies, and a "Happy Rennsday" event on Wednesdays. == History == === 2017–2019 === The app launched in March 2017 with a promotional contest. Renner's fans were encouraged to download the app and create comments about being Renner's biggest fan; Renner would then choose a winner and transport the winner and a guest to have lunch with him at the Calgary Expo. In the first few months Renner teased behind-the-scenes of projects he was working on, which he now sporadically does on Instagram. The app was similarly designed to Instagram as well, with a near identically styled layout. Around midway through 2019, a hoax account of Renner was made to mock the celebrity, joking about masturbating to porn and defending another hoax account of Casey Anthony. FastCompany wrote extensively about Renner's app in April 2019, calling it "a surprising new kind of social media". The Ringer stated "Jeremy Renner's Jeremy Renner app is the Jeremy Renner of apps." === After deletion (2019–2020) === After the shutdown of the app, a comedy-based pseudo-app with modular endings was released, called "The Jeremy Renner App Experience", in which the player plays as Jeremy Renner on the day of the Jeremy Renner Official app's shutdown. The app details several different choices on how Renner handles the situation. A six-part podcast was also created to mock the app's deletion, called The Renner Files, featuring Carolyn Goldfarb and Sarah Ramos. == Controversies == === Marketing === One of the main controversies of Renner's app was its marketing. The app's developers, Escapex, specialized in and grew famous for making similar monetized apps for celebrities. The marketing campaign was based on direct contact with Renner, whose chances were increased with regular payments for "stars", although very few encounters seemed to happen with Renner himself. The multiple problems with the app led the CEO of Escapex, Sephi Shapira, to call the app a "freak situation", and added "Am I concerned about this? Not more than I'm concerned about 50 other things I'm dealing with as a startup company." Along with the marketing failures, the app was seen as misrepresenting itself as seemingly erotic with some advertisements featuring Renner suggestively staring at the camera, despite the actual app being initially considered safe for children. === Harassment === After its release in 2017, the app was met with waves of harassment and bullying by many users on the app, most frequently by using impersonation — referenced in Renner's apology/deletion notice. Some death threats were made across the app by fraud accounts pretending to be several controversial celebrities, including O. J. Simpson and Casey Anthony. As early as October 2017, there were claims of censorship, bullying, and "contest-rigging". In September 2019, comedian Stefan Heck publicized his discovery of the fact that replies through the app appeared as if they were sent by Renner himself in push notifications. After several users abused this feature, Renner asked Escapex to shut down the app.

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  ROCm

  ROCm is an Advanced Micro Devices (AMD) software stack for graphics processing unit (GPU) programming. ROCm spans several domains, including general-purpose computing on graphics processing units (GPGPU), high performance computing (HPC), and heterogeneous computing. It offers several programming models: HIP (GPU-kernel-based programming), OpenMP (directive-based programming), and OpenCL. ROCm is free, libre and open-source software (except the GPU firmware blobs), and it is distributed under various licenses. The name initially stood for Radeon Open Compute platform; however, due to Open Compute being a registered trademark, the name no longer functions as an acronym. == Background == The first GPGPU software stack from ATI/AMD was Close to Metal, which became Stream. ROCm was launched around 2016 with the Boltzmann Initiative. ROCm stack builds upon previous AMD GPU stacks; some tools trace back to GPUOpen and others to the Heterogeneous System Architecture (HSA). === Heterogeneous System Architecture Intermediate Language === HSAIL was aimed at producing a middle-level, hardware-agnostic intermediate representation that could be JIT-compiled to the eventual hardware (GPU, FPGA...) using the appropriate finalizer. This approach was dropped for ROCm: now it builds only GPU code, using LLVM, and its AMDGPU backend that was upstreamed, although there is still research on such enhanced modularity with LLVM MLIR. == Programming abilities == ROCm as a stack ranges from the kernel driver to the end-user applications. AMD has introductory videos about AMD GCN hardware, and ROCm programming via its learning portal. One of the best technical introductions about the stack and ROCm/HIP programming, remains, to date, to be found on Reddit. == Hardware support == ROCm is primarily targeted at discrete professional GPUs, but consumer GPUs and APUs of the same architecture as a supported professional GPU are known to work with ROCm. For example, all professional GPUs of the RDNA 2 architecture are officially supported by ROCm 5.x; users report that Consumer RDNA2 units such as the Radeon 6800M APU and the Radeon 6700XT GPU also work. === Professional-grade GPUs === === Consumer-grade GPUs === == Software ecosystem == === Machine learning === Various deep learning frameworks have a ROCm backend: PyTorch TensorFlow ONNX MXNet CuPy MIOpen Caffe Iree (which uses LLVM Multi-Level Intermediate Representation (MLIR)) llama.cpp === Supercomputing === ROCm is gaining significant traction in the top 500. ROCm is used with the Exascale supercomputers El Capitan and Frontier. Some related software is to be found at AMD Infinity hub. === Other acceleration & graphics interoperation === As of version 3.0, Blender can now use HIP compute kernels for its renderer cycles. === Other languages === ==== Julia ==== Julia has the AMDGPU.jl package, which integrates with LLVM and selects components of the ROCm stack. Instead of compiling code through HIP, AMDGPU.jl uses Julia's compiler to generate LLVM IR directly, which is later consumed by LLVM to generate native device code. AMDGPU.jl uses ROCr's HSA implementation to upload native code onto the device and execute it, similar to how HIP loads its own generated device code. AMDGPU.jl also supports integration with ROCm's rocBLAS (for BLAS), rocRAND (for random number generation), and rocFFT (for FFTs). Future integration with rocALUTION, rocSOLVER, MIOpen, and certain other ROCm libraries is planned. === Software distribution === ==== Official ==== Installation instructions are provided for Linux and Windows in the official AMD ROCm documentation. ROCm software is currently spread across several public GitHub repositories. Within the main public meta-repository, there is an XML manifest for each official release: using git-repo, a version control tool built on top of Git, is the recommended way to synchronize with the stack locally. AMD starts distributing containerized applications for ROCm, notably scientific research applications gathered under AMD Infinity Hub. AMD distributes itself packages tailored to various Linux distributions. ==== Third-party ==== There is a growing third-party ecosystem packaging ROCm. Linux distributions are officially packaging (natively) ROCm, with various degrees of advancement: Arch Linux, Gentoo, Debian, Fedora , GNU Guix, and NixOS. There are Spack packages. == Components == There is one kernel-space component, ROCk, and the rest - there is roughly a hundred components in the stack - is made of user-space modules. The unofficial typographic policy is to use: uppercase ROC lowercase following for low-level libraries, i.e. ROCt, and the contrary for user-facing libraries, i.e. rocBLAS. AMD is active developing with the LLVM community, but upstreaming is not instantaneous, and as of January 2022, is still lagging. AMD still officially packages various LLVM forks for parts that are not yet upstreamed – compiler optimizations destined to remain proprietary, debug support, OpenMP offloading, etc. === Low-level === ==== ROCk – Kernel driver ==== ==== ROCm – Device libraries ==== Support libraries implemented as LLVM bitcode. These provide various utilities and functions for math operations, atomics, queries for launch parameters, on-device kernel launch, etc. ==== ROCt – Thunk ==== The thunk is responsible for all the thinking and queuing that goes into the stack. ==== ROCr – Runtime ==== The ROC runtime is a set of APIs/libraries that allows the launch of compute kernels by host applications. It is AMD's implementation of the HSA runtime API. It is different from the ROC Common Language Runtime. ==== ROCm – CompilerSupport ==== ROCm code object manager is in charge of interacting with LLVM intermediate representation. === Mid-level === ==== ROCclr Common Language Runtime ==== The common language runtime is an indirection layer adapting calls to ROCr on Linux and PAL on windows. It used to be able to route between different compilers, like the HSAIL-compiler. It is now being absorbed by the upper indirection layers (HIP and OpenCL). ==== OpenCL ==== ROCm ships its installable client driver (ICD) loader and an OpenCL implementation bundled together. As of January 2022, ROCm 4.5.2 ships OpenCL 2.2, and is lagging behind competition. ==== HIP – Heterogeneous Interface for Portability ==== The AMD implementation for its GPUs is called HIPAMD. There is also a CPU implementation mostly for demonstration purposes. ==== HIPCC ==== HIP builds a `HIPCC` compiler that either wraps Clang and compiles with LLVM open AMDGPU backend, or redirects to the NVIDIA compiler. ==== HIPIFY ==== HIPIFY is a source-to-source compiling tool. It translates CUDA to HIP and reverse, either using a Clang-based tool, or a sed-like Perl script. ==== GPUFORT ==== Like HIPIFY, GPUFORT is a tool compiling source code into other third-generation-language sources, allowing users to migrate from CUDA Fortran to HIP Fortran. It is also in the repertoire of research projects, even more so. === High-level === ROCm high-level libraries are usually consumed directly by application software, such as machine learning frameworks. Most of the following libraries are in the General Matrix Multiply (GEMM) category, which GPU architecture excels at. The majority of these user-facing libraries comes in dual-form: hip for the indirection layer that can route to Nvidia hardware, and roc for the AMD implementation. ==== rocBLAS / hipBLAS ==== rocBLAS and hipBLAS are central in high-level libraries, it is the AMD implementation for Basic Linear Algebra Subprograms. It uses the library Tensile privately. ==== rocSOLVER / hipSOLVER ==== This pair of libraries constitutes the LAPACK implementation for ROCm and is strongly coupled to rocBLAS. === Utilities === ROCm developer tools: Debug, tracer, profiler, System Management Interface, Validation suite, Cluster management. GPUOpen tools: GPU analyzer, memory visualizer... External tools: radeontop (TUI overview) == Comparison with competitors == ROCm competes with other GPU computing stacks: Nvidia CUDA and Intel OneAPI. === Nvidia CUDA === Nvidia's CUDA is closed-source, whereas AMD ROCm is open source. There is open-source software built on top of the closed-source CUDA, for instance RAPIDS. CUDA is able to run on consumer GPUs, whereas ROCm support is mostly offered for professional hardware such as AMD Instinct and AMD Radeon Pro. Nvidia provides a C/C++-centered frontend and its Parallel Thread Execution (PTX) LLVM GPU backend as the Nvidia CUDA Compiler (NVCC). === Intel OneAPI === All the oneAPI corresponding libraries are published on its GitHub Page. ==== Unified Acceleration Foundation (UXL) ==== Unified Acceleration Foundation (UXL) is a new technology consortium that are working on the continuation of the OneAPI initiative, with the goal to create a new open standard accelerator software ecosystem, related open standards and specification projects through Working Groups and Specia

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  Triller (app)

  Triller is an American video-sharing social networking service that was first released for iOS and Android in 2015. The service allowed users to create and share short-form videos, including videos set to, or automatically synchronized to, music using artificial intelligence technology. It initially operated as a video editing app before adding social networking features. Triller gained prominence in 2020 as a competitor to the similar Chinese-owned app TikTok, mainly in the United States and India (after the service was banned in the latter country). The app's success would allow its parent company to expand into sports broadcasting and promotion; including the distribution of pay-per-view boxing events under the Triller Fight Club banner (such as Mike Tyson vs. Roy Jones Jr. and Jake Paul vs. Ben Askren) that incorporated live music performances and appearances by various celebrities and entertainment personalities. == History == === Launch and early years === Triller was launched in 2015 by co-founders David Leiberman and Sammy Rubin. The app was originally positioned as a video editor, using artificial intelligence to automatically edit distinct clips into music videos. They later launched Triller Famous, a page within the app that featured curated selections of user videos. In 2016, the app was purchased by Carnegie Technologies and converted into a social networking service by allowing users to follow each other and share their videos publicly. In 2019, Ryan Kavanaugh's Proxima Media made a majority investment. It is headquartered in Los Angeles, California, and is currently led by CEO Mahi de Silva. === Media exposure and controversies === On June 29, 2020, Government of India banned TikTok, among other apps stating that they were "prejudicial to [the] sovereignty and integrity" of India. Triller, which had planned to enter into the Indian market by the end of 2020, saw a spike from less than 1 million users to over 30 million users in the country overnight. In July 2020, Triller sued ByteDance, the Chinese parent company of TikTok, for infringing patents relating to video editing. In response, TikTok and ByteDance filed a lawsuit against Triller, alleging the litigation initiated by Triller has "cast a cloud" over TikTok's reputation and business dealings. That Summer, U.S. president Donald Trump signed an executive order which threatened to ban TikTok from operating within the United States, citing threats to national security, unless it was sold by ByteDance. The Trump administration stated that TikTok had until November 12, 2020, to assure the administration that the app did not pose any national security threats to the U.S. Following this order and news of possible purchases of TikTok's American operations by companies such as Oracle, Triller jumped from number 198 to number one in the App Store in the U.S., while TikTok dropped down to number three. The discussions surrounding TikTok's potential ban in the United States caused popular TikTok stars, including Charli D’Amelio and her family, to join Triller. Trump joined Triller himself and posted his first video on August 15, 2020. The video received over a million views within hours. On August 12, 2020, Triller partnered with B2B music company 7digital, which will provide Triller with access to its catalogue of 80 million tracks and automatically report usage data to Sony Music, Warner Music Group, Universal Music Group and Merlin Network. The number of Triller's app installations came under scrutiny when third-party analytics firm Apptopia estimated only 52 million lifetime installations of the app by August 2020, while Triller claimed 250 million. Triller threatened to sue Apptopia for publishing the report. By October 2020, Triller claimed to serve 100 million active monthly users, but this number was quickly disputed by six former employees interviewed by Business Insider. Within a few weeks of Triller's claim, employees shared screenshots of the company's internal analytics that showed less than 2.5 million active monthly users. On October 2, 2020, Triller signed licensing deals with the rights societies PRS for Music, GEMA, STIM and IMRO, and the publishers Concord, Downtown and Peermusic. On February 5, 2021, Universal Music Group (UMG) pulled its library from Triller, citing unpaid music royalties. They alleged that Triller "shamefully withheld payments owed to our artists" and refused to negotiate future music licensing. Triller responded with the assertion that "relevant artists" were already partnered with Triller, so a deal with UMG was unnecessary. The two companies reached an expanded licensing agreement in May 2021. On March 24, 2021, Triller signed a licensing agreement with the National Music Publishers' Association. == Features == The Triller app allows users to create music videos, skits, and lip-sync videos containing background music. The app's spotlight feature is its special auto-editing tool, which uses artificial intelligence to automatically stitch separate video clips together without the user having to do it themselves. The separate video clips are created to the same background music, but users are able to shoot multiple takes with different filters or edits each time. Once the auto-editing tool stitches the individual clips together, users can rearrange and replace clips as desired. Users can also customize videos by applying filters and text. When creating a video, users can choose to make a "music video" or a "social video". A "music video" allows users to add music and trim the audio to personal preference. Unlike the music video option, a "social video" does not require the user to add music in the background. The app's auto-editing tool is only used when making music videos, as it uses the background track to help arrange and synchronize the clips. Users can also link their accounts with Apple Music or Spotify to integrate their playlists. Incomplete videos that are yet to be shared appear in a user's "Projects" folder. Once finalized, a video can be shared with other users of the app or through social media platforms such as Facebook, Instagram, Twitter (X), WhatsApp, and YouTube. Any video on Triller can also be downloaded or shared through links, text messages, or direct messaging to other users within the app. The app is divided into three video feeds, consisting of videos from creators that the user follows, the "Social" feed (which showcases trending videos and those by verified users), and the "Music" feed (which exclusively features music videos). Triller accounts can be made either public or private. When the account is public, any user can view the videos on that account. When the account is private, only approved users can view the videos on that account. Users with private accounts can change the privacy settings of individual videos on their accounts from private to public, making the selected videos viewable to anyone on the app. In accordance with online child privacy laws in the United States, children under the age of 13 must receive parental consent in order to create an account on Triller. == User characteristics and behavior == In August 2020, Triller reported that it had been downloaded over 250 million times worldwide with average rating of 4.00. Mobile analytics firm Apptopia disputed the numbers and claimed they were inflated, suggesting that the app had only been downloaded 52 million times since it first launched in 2015. Apptopia pulled the report after Triller threatened to sue the company. The app has been downloaded 23.8 million times in the U.S., with users spending an average of more than 20 minutes per day. A large number of downloads come from India, where TikTok has been banned, as well as from various European and African countries. In October 2020, Triller CEO Mike Lu stated that the app has 100 million monthly active users (MAU). In February 2021, Billboard reported that Triller had "reported higher numbers of monthly active users to the public than it reports to [music] rights holders." CEO Lu argued that "there is no legal definition" of monthly and daily active users, and that "if someone is trying to compare TikTok's MAU/DAU to ours—which means they are saying we have the same definition of MAU/DAU—there is an inherent misunderstanding about Triller's business and business model. It’s like trying to compare a fish and a bicycle." In a public statement, Lu denied that the company had inflated its user metrics. Triller has attracted celebrity users like Chance the Rapper, King Von, LIl Tecca, Lil Mosey, Justin Bieber, Marshmello, The Weeknd, Alicia Keys, Cardi B, Eminem, Post Malone and Kevin Hart. The app is also used by TikTok stars such as Charli D’Amelio, Josh Richards, Noah Beck, Griffin Johnson, and Dixie D’Amelio. Triller has offered large sums of money, company equity, and advisory roles to encourage prominent TikTok users to move to Triller, such as The Sway Boys. Sway House member J

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  Function representation

  Function Representation (FRep or F-Rep) is used in solid modeling, volume modeling and computer graphics. FRep was introduced in "Function representation in geometric modeling: concepts, implementation and applications" as a uniform representation of multidimensional geometric objects (shapes). An object as a point set in multidimensional space is defined by a single continuous real-valued function f ( X ) {\displaystyle f(X)} of point coordinates X [ x 1 , x 2 , . . . , x n ] {\displaystyle X[x_{1},x_{2},...,x_{n}]} which is evaluated at the given point by a procedure traversing a tree structure with primitives in the leaves and operations in the nodes of the tree. The points with f ( x 1 , x 2 , . . . , x n ) ≥ 0 {\displaystyle f(x_{1},x_{2},...,x_{n})\geq 0} belong to the object, and the points with f ( x 1 , x 2 , . . . , x n ) < 0 {\displaystyle f(x_{1},x_{2},...,x_{n})<0} are outside of the object. The point set with f ( x 1 , x 2 , . . . , x n ) = 0 {\displaystyle f(x_{1},x_{2},...,x_{n})=0} is called an isosurface. == Geometric domain == The geometric domain of FRep in 3D space includes solids with non-manifold models and lower-dimensional entities (surfaces, curves, points) defined by zero value of the function. A primitive can be defined by an equation or by a "black box" procedure converting point coordinates into the function value. Solids bounded by algebraic surfaces, skeleton-based implicit surfaces, and convolution surfaces, as well as procedural objects (such as solid noise), and voxel objects can be used as primitives (leaves of the construction tree). In the case of a voxel object (discrete field), it should be converted to a continuous real function, for example, by applying the trilinear or higher-order interpolation. Many operations such as set-theoretic, blending, offsetting, projection, non-linear deformations, metamorphosis, sweeping, hypertexturing, and others, have been formulated for this representation in such a manner that they yield continuous real-valued functions as output, thus guaranteeing the closure property of the representation. R-functions originally introduced in V.L. Rvachev's "On the analytical description of some geometric objects", provide C k {\displaystyle C^{k}} continuity for the functions exactly defining the set-theoretic operations (min/max functions are a particular case). Because of this property, the result of any supported operation can be treated as the input for a subsequent operation; thus very complex models can be created in this way from a single functional expression. FRep modeling is supported by the special-purpose language HyperFun. == Shape Models == FRep combines and generalizes different shape models like algebraic surfaces skeleton based "implicit" surfaces set-theoretic solids or CSG (Constructive Solid Geometry) sweeps volumetric objects parametric models procedural models A more general "constructive hypervolume" allows for modeling multidimensional point sets with attributes (volume models in 3D case). Point set geometry and attributes have independent representations but are treated uniformly. A point set in a geometric space of an arbitrary dimension is an FRep based geometric model of a real object. An attribute that is also represented by a real-valued function (not necessarily continuous) is a mathematical model of an object property of an arbitrary nature (material, photometric, physical, medicine, etc.). The concept of "implicit complex" proposed in "Cellular-functional modeling of heterogeneous objects" provides a framework for including geometric elements of different dimensionality by combining polygonal, parametric, and FRep components into a single cellular-functional model of a heterogeneous object.

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  PenTile matrix family

  PenTile matrix is a family of patented subpixel matrix schemes used in electronic device displays. PenTile is a trademark of Samsung. PenTile matrices are used in AMOLED and LCD displays. These subpixel layouts are specifically designed to operate with proprietary algorithms for subpixel rendering embedded in the display driver, allowing plug and play compatibility with conventional RGB (Red-Green-Blue) stripe panels. == Overview == "PenTile Matrix" (a neologism from penta-, meaning "five" in Greek and tile) describes the geometric layout of the prototypical subpixel arrangement developed in the early 1990s. The layout consists of a quincunx comprising two red subpixels, two green subpixels, and one central blue subpixel in each unit cell. It was inspired by biomimicry of the human retina, which has nearly equal numbers of L and M type cone cells, but significantly fewer S cones. As the S cones are primarily responsible for perceiving blue colors, which do not appreciably affect the perception of luminance, reducing the number of blue subpixels with respect to the red and green subpixels in a display does not reduce the image quality. However, the layout may cause color leakage image distortion, which can be reduced by filters. In some cases the layout causes reduced moiré and blockiness compared to conventional RGB layouts. The PenTile layout is specifically designed to work with and be dependent upon subpixel rendering that uses only one and a quarter subpixel per pixel, on average, to render an image. That is, that any given input pixel is mapped to either a red-centered logical pixel, or a green-centered logical pixel. === History === PenTile was invented by Candice H. Brown Elliott, for which she was awarded the Society for Information Display's Otto Schade Prize in 2014. The technology was licensed by the company Clairvoyante from 2000 until 2008, during which time several prototype PenTile displays were developed by a number of Asian liquid crystal display (LCD) manufacturers. In March 2008, Samsung Electronics acquired Clairvoyante's PenTile IP assets. Samsung then funded a new company, Nouvoyance, Inc. to continue development of the PenTile technology. == PenTile RGBG == PenTile RGBG layout used in AMOLED and plasma displays uses green pixels interleaved with alternating red and blue pixels. The human eye is most sensitive to green, especially for high resolution luminance information. The green subpixels are mapped to input pixels on a one-to-one basis. The red and blue subpixels are subsampled, reconstructing the chroma signal at a lower resolution. The luminance signal is processed using adaptive subpixel rendering filters to optimize reconstruction of high spatial frequencies from the input image, wherein the green subpixels provide the majority of the reconstruction. The red and blue subpixels are capable of reconstructing the horizontal and vertical spatial frequencies, but not the highest of the diagonal. Diagonal high spatial frequency information in the red and blue channels of the input image are transferred to the green subpixels for image reconstruction. Thus the RG-BG scheme creates a color display with one third fewer subpixels than a traditional RGB-RGB scheme but with the same measured luminance display resolution. This is similar to the Bayer filter commonly used in digital cameras. === Devices === As of 2021, "almost all" OLED screens in portable consumer devices use some form of Pentile subpixel layout. == PenTile RGBW == PenTile RGBW technology, used in LCD, adds an extra subpixel to the traditional red, green and blue subpixels that is a clear area without color filtering material and with the only purpose of letting backlight come through, hence W for white. This makes it possible to produce a brighter image compared to an RGB-matrix while using the same amount of power, or produce an equally bright image while using less power. The PenTile RGBW layout uses each red, green, blue and white subpixel to present high-resolution luminance information to the human eyes' red-sensing and green-sensing cone cells, while using the combined effect of all the color subpixels to present lower-resolution chroma (color) information to all three cone cell types. Combined, this optimizes the match of display technology to the biological mechanisms of human vision. The layout uses one third fewer subpixels for the same resolution as the RGB stripe (RGB-RGB) layout, in spite of having four color primaries instead of the conventional three, using subpixel rendering combined with metamer rendering. Metamer rendering optimizes the energy distribution between the white subpixel and the combined red, green, and blue subpixels: W <> RGB, to improve image sharpness. The display driver chip has an RGB to RGBW color vector space converter and gamut mapping algorithm, followed by metamer and subpixel rendering algorithms. In order to maintain saturated color quality, to avoid simultaneous contrast error between saturated colors and peak white brightness, while simultaneously reducing backlight power requirements, the display backlight brightness is under control of the PenTile driver engine. When the image is mostly desaturated colors, those near white or grey, the backlight brightness is significantly reduced, often to less than 50% peak, while the LCD levels are increased to compensate. When the image has very bright saturated colors, the backlight brightness is maintained at higher levels. The PenTile RGBW also has an optional high-brightness mode that doubles the brightness of the desaturated color image areas, such as black-and-white text, for improved outdoor viewability. === Devices === Motorola MC65 Motorola ES55 Motorola ES400 Motorola Atrix 4G Samsung Galaxy Note 10.1 2014 version Lenovo Yoga 2 Pro Lenovo Yoga 3 Pro HP ENVY TouchSmart 14-k022tx Sleekbook MSI GS60 Ghost Pro 4K Lenovo IdeaPad Y50 4K Asus ZenBook UX303LN 4K Asus ZenBook Pro UX501JW LG UH7500/6500/6100 LG ThinQ G7/G7+ Oculus Quest 1 == Controversy == An ongoing controversy regarding the definition or measurement of resolution of color subpixelated flat panel displays led many people to question the resolution claims of PenTile display products. Journalists have noted that in "just about every flat-panel TV in existence, each pixel is composed of one red, one green, and one blue subpixel (RGB), all of uniform size". In traditional flat-panel screens, the resolution is defined by the number of red, green, and blue subpixels, in groups of three, in an array in each axis. As a result, each pixel or group of subpixels can render any colour on the screen, regardless of neighbouring pixels. This is not the case with PenTile screens. The Video Electronics Standards Association (VESA) method of measuring and defining resolution in color displays is to measure the contrast of line pairs, requiring a minimum of 50% Michelson contrast for displays intended for rendering text. The developers of PenTile displays use this VESA criterion for contrast of line pairs to calculate the resolutions specified. In the RGBG layout the alternate red and blue subpixels are 'shared' or sub-sampled with neighboring pixels. Due to the one third lower subpixel density on PenTile displays the pixel structure may be more visible when compared to RGB stripe displays with the same pixel density. The loss of subpixels for a given resolution specification has led some journalists to describe the use of PenTile as "shady practice" and "sort of cheating". For a given size and resolution specification, the PenTile screen can appear grainy, pixelated, speckled, with blurred text on some saturated colors and backgrounds when compared to RGB stripe color. This effect is understood to be caused by the restriction of the number of subpixels that may participate in the image reconstruction when colors are highly saturated to primaries. In the RGBW case, this is caused as the W subpixel will not be available in order to maintain the saturated color. In the RGBG case, this effect will occur when the color boundary is primarily red or blue, as the fully populated (one green per pixel) sub-pixel cannot contribute. For all other cases, text and especially full color images are effectively reconstructed. == Advantages and disadvantages == The PenTile layout reduces the number of subpixels needed to create a specified resolution. Consequently it is possible to achieve an HD resolution on a PenTile AMOLED screen at lower cost than other technologies, and most reviewers note that "300 ppi" (as per VESA - not full pixels) resolution displays (such as Samsung Galaxy S III) make the PenTile effect less obvious than lower resolution PenTile displays (Droid Razr). The second advantage is lower power consumption: the HTC One S's use of a PenTile display makes it more energy efficient and thinner than equivalent LCD screens, giving it better battery life than the HTC One X's IPS LCD. A PenTile AMOLED screen is also

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  DataViva

  DataViva is an information visualization engine created by the Strategic Priorities Office of the government of Minas Gerais. DataViva makes official data about exports, industries, locations and occupations available for the entirety of Brazil through eight apps and more than 100 million possible visualizations. The first set of datum – also available at ALICEWEB – is provided by MDIC (Ministry of Development, Industry and Foreign Trade) / SECEX (Secretariat of Foreign Trade), an official institution of the Government of Brazil and shows foreign trade statistics for all exporting municipalities in the country. The other database, provided by Ministério do Trabalho e Emprego (MTE – Ministry of Labor and Employment), shows information about all the industries and occupations in Brazil (RAIS – Annual Social Information Report). The platform consists of eight core applications, each of which allows different ways of visualizing the data available. Some applications are descriptive, that is, showing data aggregated at various levels in a simple and comparative way, such as Treemapping. Others are prescriptive, using calculations that allow an analytic visualization of the data, based on theories such as the Product Space. All the applications are generated using D3plus, an open source JavaScript library built on top of D3.js by Alexander Simoes and Dave Landry. Inspired by The Observatory of Economic Complexity, DataViva is an open data, open-source, and free to use tool. It was developed in a partnership with Datawheel, co-founded by MIT Media Lab Professor César Hidalgo, and is maintained by the Government of Minas Gerais.

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  Resilience week

  Resilience week is an annual symposium established to enable cross-disciplinary and role based discussions to advance strategies and research that engenders resilience in critical infrastructure systems and communities. Damaging storms, cyber attack and the interconnection of critical infrastructure systems can lead to cascading events that not only affect local but also across regions. However, many of these interdependencies are not easily recognized and obscure and complicate the mitigation of risk. The purpose of the symposia series is hence to facilitate best practice in managing critical infrastructure risks, by bringing together businesses, government and researchers. == Background == Originally organized in 2008 as a focus on the new research area of resilient control systems, including the disciplinary areas of control system, cyber-security, cognitive psychology and any number of critical infrastructure domains. Resilience has long been recognized as an area that requires not only the contributions of multiple disciplines or multidisciplinary participation, but interdisciplinary interaction where there is a common language and familiarity of the contributors to what other disciplines (and roles) contribute. The resulting interactions developed by Resilience Week and associated activities are intended to culture this sharing environment as a safe zone for inclusion; more importantly, an environment that lends to developing the new science and practice. As the attributes of resilience are complex, the contributions and topics for the event have included both the disciplinary and the project considerations, in keynotes, panels and research presentations. Keynotes have included senior leadership in the Department of Energy, Department of Defense, Department of Homeland Security, the National Science Foundation, and other agencies in addition to National Academy and professional organization fellows and senior industry leaders. Project panels and research presentations include emergent topics in resilience to climate change, cyber attack, damaging storms and the energy assurance. Topics Areas of focus have included: Control Systems Cyber Systems Cognitive Systems Communications Systems Communities and Infrastructure Project Focus Areas have included: Dependencies and Interdependencies Cyber Resilience for Operating Technology Commercializing Research and Development Building Critical Infrastructure Resilience through Distributed Energy Resources Energy Equity and Community Resilience Proceedings are developed for each year of the event, documenting the diversity of the research and engagements within these topical areas. == Impacts for the future == Since its inception, the Resilience Week community has evolved from one that primarily included only university researchers to one that includes many government laboratories, universities and private industries in the US and internationally. This type of collaboration forms a feedback loop that informs the research with the current needs and hones best practices. The future of the event is to further advance discussions that advance investment, recognize priorities and expedite technologies and tools to proactively address our energy future, in light of the natural and manmade challenges, and rationalizing the complex relationships that exist in critical infrastructure.

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  Kdb+

  kdb+ is a column-based relational time series database (TSDB) with in-memory (IMDB) abilities, developed and marketed by KX Systems. The database is commonly used in high-frequency trading (HFT) to store, analyze, process, and retrieve large data sets at high speed. kdb+ has the ability to handle billions of records and analyzes data within a database. The database is available in 32-bit and 64-bit versions for several operating systems. Financial institutions use kdb+ to analyze time series data such as stock or commodity exchange data. The database has also been used for other time-sensitive data applications including commodity markets such as energy trading, telecommunications, sensor data, log data, machine and computer network usage monitoring along with real time analytics in Formula One racing. == Overview == kdb+ is a high-performance column-store database that was designed to process and store large amounts of data. Commonly accessed data is pushed into random-access memory (RAM), which is faster to access than data in disk storage. Created with financial institutions in mind, the database was developed as a central repository to store time series data that supports real-time analysis of billions of records. kdb+ has the ability to analyze data over time and responds to queries similar to Structured Query Language (SQL). Columnar databases return answers to some queries in a more efficient way than row-based database management systems. kdb+ dictionaries, tables and nanosecond time stamps are native data types and are used to store time series data. At the core of kdb+ is the built-in programming language, q, a concise, expressive query array language, and dialect of the language APL. Q can manipulate streaming, real-time, and historical data. kdb+ uses q to aggregate and analyze data, perform statistical functions, and join data sets and supports SQL queries The vector language q was built for speed and expressiveness and eliminates most need for looping structures. kdb+ includes interfaces in C, C++, Java, C#, and Python. == History == In 1998, KX released kdb, a database built on the language K written by Arthur Whitney. In 2003, kdb+ was released as a 64-bit version of kdb. In 2004, the kdb+ tick market database framework was released along with kdb+ taq, a loader for the New York Stock Exchange (NYSE) taq data. kdb+ was created by Arthur Whitney, building on his prior work with array languages. In April 2007, KX announced that it was releasing a version of kdb+ for Mac OS X. Then, kdb+ was also available on the operating systems Linux, Windows, and Solaris. In September 2012, version 3.0 was released. It was optimized for Intel's upgraded processors with support for WebSockets, and universally unique identifiers (UUIDs, termed globally unique identifiers (GUID)s in Microsoft software). Intel's Advanced Vector Extensions (AVX) and Streaming SIMD Extensions 4 (SSE4) 4.2 on the Sandy Bridge processors of the time allowed for enhanced support of the kdb+ system. In June 2013, version 3.1 was released, with benchmarks up to 8 times faster than older versions. In March 2020, version 4.0 was released. New features included Multithreaded primitives, Intel Optane DC persistent memory support and Data at Rest Encryption.

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  Sanctuary (app)

  Sanctuary is a mobile app focusing on astrology and mystical services. Users enter their birthday, time of birth, and place of birth information into the app and receive a birth chart as well as daily horoscope readings. Users can also sign up for a monthly membership and receive on-demand astrological readings via a text message format. The service has been described as being “Talkspace for astrology" and "Uber for astrological readings". The mobile app uses an A.I.-driven interface. On May 14, 2019, Apple featured Sanctuary as the App of the Day. == History == Sanctuary initially began as project within the incubator of Lorne Michaels’ Broadway Video Ventures. The app officially launched on March 21, 2019. Its backers include Broadway Video Ventures, Greycroft Partners, and Shari Redstone.

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  Tribute (website)

  Tribute is an American video-sharing website headquartered in Brooklyn. Created in 2014 by Andrew Horn and Rory Petty, the platform lets customers create video montages (called "tributes") for occasions including weddings, birthdays, anniversaries, get well soon, and memorials. Tribute.co allows users to record video messages, request submissions from friends and family, insert photos, add music, and send the resulting video tribute montage to a recipient. == Overview == Tribute's collaborative technology starts with inviting people to contribute via email, SMS or social media. Participants receive a prompt to record a short video via their phone, computer or tablet. The site's video editing software allows users to drag and drop the clips in their desired order without prior video editing experience. == History == When Andrew Horn turned twenty-seven, his girlfriend, Miki Agrawal surprised him with a video montage containing clips of his family and closest friends explaining why they loved him. This resulted in Andrew's idea to create Tribute–a "living eulogy" video-compilation service that he co-founded with software engineer Rory Petty. Founded in 2014, Tribute's activity accelerated in 2020 due to the COVID-19 pandemic, and it had sent over 5 million videos as of December 2021. While social distance restrictions were in effect, the site provided a way for people to connect while in-person celebrations were put on hold. For each video sold, Tribute makes one available to hospitals for free and has partnered with Cleveland Clinic Cancer Center in Ohio, Lurie Children's Hospital in Illinois and CarePoint Health in New Jersey.

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  WhatsApp

  WhatsApp Messenger, commonly known simply as WhatsApp, is an American social media, instant messaging (IM), and Voice over IP (VoIP) service accessible via desktop and mobile app. Owned by Meta Platforms, the service allows users to send text messages, voice messages, and video messages, make voice and video calls, and share images, documents, user locations, and other content. The service requires a cellular mobile telephone number to register. WhatsApp was launched in May 2009. In January 2018, WhatsApp released a standalone business app called WhatsApp Business which can communicate with the standard WhatsApp client. As of May 2025, the service had 3 billion monthly active users, making it the most used messenger app. The name of the app is meant to sound like "what's up". The service was created by WhatsApp Inc. of Mountain View, California, which was acquired by Facebook in February 2014 for approximately US$19.3 billion. It became the world's most popular messaging application in 2015, with 900 million users, and had more than 2 billion active users worldwide in February 2020. WhatsApp Business had approximately 200 million monthly users in 2023. By 2016, it had become the primary means of Internet communication in regions including the Americas, the Indian subcontinent, and large parts of Europe and Africa. == History == === 2009–2014 === WhatsApp was founded by Brian Acton and Jan Koum, former employees of Yahoo. Koum incorporated WhatsApp Inc. in California on February 24, 2009. A month earlier, Koum had purchased an iPhone, and he and Acton decided to create an app for the App Store. The idea started off as an app that would display statuses in a phone's Contacts menu, showing if a person was at work or on a call. Their discussions often took place at the home of Koum's Russian friend Alex Fishman in West San Jose. They realized that to take the idea further, they would need an iPhone developer. Fishman visited RentACoder.com, found Russian developer Igor Solomennikov, and introduced him to Koum. Koum named the app WhatsApp to sound like "what's up" and it was published on the Apple App Store and BlackBerry App World in May and June 2009 respectively. However, when early versions of WhatsApp kept crashing, Koum considered giving up and looking for a new job. Acton encouraged him to wait for a "few more months". In June 2009, when the app had been downloaded by only a handful of Fishman's Russian-speaking friends, Apple launched push technology, allowing users to be pinged even when not using the app. Koum updated WhatsApp so that everyone in the user's network would be notified when a user's status changed. This new facility, to Koum's surprise, was used by users to ping "each other with jokey custom statuses like, 'I woke up late' or 'I'm on my way.'" Fishman said, "At some point it sort of became instant messaging". WhatsApp 2.0, released for iPhone in August 2009, featured a purpose-designed messaging component; the number of active users suddenly increased to 250,000. Although Acton was working on another startup idea, he decided to join the company. In October 2009, Acton persuaded five former friends at Yahoo! to invest $250,000 in seed funding, and Acton became a co-founder and was given a stake. He officially joined WhatsApp on November 1. Koum then hired a friend in Los Angeles, Chris Peiffer, to develop a BlackBerry version, which arrived two months later. Subsequently, WhatsApp for Symbian OS was added in May 2010, and for Android OS in August 2010. In 2010 Google made multiple acquisition offers for WhatsApp, which were all declined. To cover the cost of sending verification texts to users, WhatsApp was changed from a free service to a paid one. In December 2009, the ability to send photos was added to the iOS version. By early 2011, WhatsApp was one of the top 20 apps in the U.S. Apple App Store. In April 2011, Sequoia Capital invested about $8 million for more than 15% of the company, after months of negotiation by Sequoia partner Jim Goetz. By February 2013, WhatsApp had about 200 million active users and 50 staff members. Sequoia invested another $50 million at a $1.5 billion valuation. Some time in 2013 WhatsApp acquired Santa Clara–based startup SkyMobius, the developers of Vtok, a video and voice calling app. As of December 2013, the service had 400 million monthly active users. That year, the company had $148 million in expenses and a net loss of $138 million. === 2014–2015 === On February 19, 2014, one year after the venture capital financing round at a $1.5 billion valuation, Facebook, Inc. (now Meta Platforms) agreed to acquire the company for US$19 billion, its largest acquisition to date. At the time, it was the largest acquisition of a venture-capital-backed company in history. Sequoia Capital received an approximate 5,000% return on its initial investment. Facebook paid $4 billion in cash, $12 billion in Facebook shares, and an additional $3 billion in restricted stock units granted to WhatsApp's founders Koum and Acton. Employee stock was scheduled to vest over four years subsequent to closing. Days after the announcement, WhatsApp users experienced a loss of service, leading to anger across social media. The acquisition was influenced by the data provided by Onavo, Facebook's research app for monitoring competitors and trending usage of social activities on mobile phones, as well as startups that were performing "unusually well". The acquisition caused many users to try, or move to, other message services. Telegram claimed that it acquired 8 million new users, and Line, 2 million. At a keynote presentation at the Mobile World Congress in Barcelona in February 2014, Facebook CEO Mark Zuckerberg said that Facebook's acquisition of WhatsApp was closely related to the Internet.org vision. A TechCrunch article said about Zuckerberg's vision:The idea, he said, is to develop a group of basic internet services that would be free of charge to use – "a 911 for the internet". These could be a social networking service like Facebook, a messaging service, maybe search and other things like weather. Providing a bundle of these free of charge to users will work like a gateway drug of sorts – users who may be able to afford data services and phones these days just don't see the point of why they would pay for those data services. This would give them some context for why they are important, and that will lead them to pay for more services like this – or so the hope goes. Three days after announcing the Facebook purchase, Koum said they were working to introduce voice calls. He also said that new mobile phones would be sold in Germany with the WhatsApp brand, and that their ultimate goal was to be on all smartphones. In August 2014, WhatsApp was the most popular messaging app in the world, with more than 600 million users. By early January 2015, WhatsApp had 700 million monthly users and over 30 billion messages every day. In April 2015, Forbes predicted that between 2012 and 2018, the telecommunications industry would lose $386 billion because of "over-the-top" services like WhatsApp and Skype. That month, WhatsApp had over 800 million users. By September 2015, it had grown to 900 million; and by February 2016, one billion. On November 30, 2015, the Android WhatsApp client made links to Telegram unclickable and not copyable. Multiple sources confirmed that it was intentional, not a bug, and that it had been implemented when the Android source code that recognized Telegram URLs had been identified. (The word "telegram" appeared in WhatsApp's code.) Some considered it an anti-competitive measure; WhatsApp offered no explanation. === 2016–2019 === On January 18, 2016, WhatsApp's co-founder Jan Koum announced that it would no longer charge users a $1 annual subscription fee, in an effort to remove a barrier faced by users without payment cards. He also said that the app would not display any third-party ads, and that it would have new features such as the ability to communicate with businesses. On May 18, 2017, the European Commission announced that it was fining Facebook €110 million for "providing misleading information about WhatsApp takeover" in 2014. The Commission said that in 2014 when Facebook acquired the messaging app, it "falsely claimed it was technically impossible to automatically combine user information from Facebook and WhatsApp." However, in the summer of 2016, WhatsApp had begun sharing user information with its parent company, allowing information such as phone numbers to be used for targeted Facebook advertisements. Facebook acknowledged the breach, but said the errors in their 2014 filings were "not intentional". In September 2017, WhatsApp's co-founder Brian Acton left the company to start a nonprofit group, later revealed as the Signal Foundation, which developed the WhatsApp competitor Signal. He explained his reasons for leaving in an interview with Forbes a year later. WhatsApp also

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  Groover

  Groover is an online platform, record label and distributor, connecting artists and musicians with music professionals and media outlets. The service was founded in 2018 in France and operates from offices in Paris and New York. The platform has over 3,000 active contacts, including SPIN Magazine and Sofar Sounds. Groover uses a micro-payment model. Among the platform's over 500,000 regular users are record labels such as Ninja Tune, Ba Da Bing Records, Dance To The Radio, Roche Musique, Wagram Music, Secret City Records, and artists including Bonobo, Michael Bolton, Aloe Blacc, Haddaway, Passenger, La Femme and Chinese Man. == History == Groover was launched at the MaMA Music Convention in October 2018. It was co-founded by Dorian Perron, Romain Palmieri, and Rafaël Cohen while they were students at UC Berkeley. Initially growing in France, the company has expanded to the United States, Canada, the United Kingdom, Brazil, Italy, and elsewhere in Europe. In March 2019, Groover was part of the Business France delegation at the South by Southwest (SXSW) festival. In June 2019, Groover raised €1.3 million from various angel investors. In April 2021, Groover acquired the platform Soonvibes, which had 70,000 users at the time, in order to strengthen its community in the electronic music space. In November 2021, Groover announced a €6 million funding round from Bpifrance Creative Industries and Partech. Between 2023 and 2025, Groover entered strategic partnerships with major artist service providers, including CD Baby, TuneCore, SoundCloud, UnitedMasters, Symphonic Distribution, Audiomack and SACEM. In February 2024, Groover announced a Series A funding round of $8 million from OneRagTime, Trind, Techmind, and Mozza Angels. == Function == Using a micro-payment system, professionals listen to tracks and provide written feedback. These professionals retain full editorial independence and are under no obligation to share the track or contact the artist. == Awards == 2nd Prize for Music Innovation 2023 from the Centre national de la musique (France) "Future Creator" Award at the Petit Poucet Competition 2019 Jury's Special Mention at the MaMA Invent 2019 competition 1st Prize for Digital Initiative in Culture, Communication & Media 2019 awarded by Audiens "Start-up of the Year" at the Social Music Awards 2020 French American Entrepreneurship Award 2022 at the French Consulate in New York

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