Tabnine is a code completion tool which uses generative artificial intelligence to assist users by autocompleting code. It was created in 2018 by Jacob Jackson, a student at the University of Waterloo. It is now developed by Tabnine, a software company founded under the name Codota by Dror Weiss and Eran Yahav in Tel Aviv, Israel, in 2013, and renamed to Tabnine in 2021. Initially established under the name Codota, the company underwent a rebranding in May 2021 following the release of the company’s first large language model based AI coding assistant, adopting the name Tabnine. == History == Tabnine was established as Codota in 2013 by Dror Weiss and Eran Yahav in Tel Aviv, Israel. Tabnine, initially founded under the name Codota, was created to develop tools based on over a decade of academic research at the Technion. Codota, the predecessor of Tabnine, secured $2 million in seed investment in June 2017. Following this, in June 2018, the company introduced the first AI-based code completion for Java IDE. In 2019, Codota acquired a product called Tabnine, which used the newly available large-language model technology to provide generative AI for software code across a broader range of programming languages across five IDEs. Codota replaced its earlier approach to code generation with this new approach to generative AI. The company secured a Series A round of funding in April 2020, raising $12 million. On May 26, 2021, Codota changed its name to Tabnine and underwent a corresponding rebranding. By April 2022, Tabnine reached over one million users. In June of the same year, Tabnine launched models that could predict full lines and snippets of code. The same year it raised $15.5 mln in a funding round led co-led by Qualcomm Ventures. In June 2023, Tabnine introduced an AI-powered chat agent, enabling developers to use natural language to generate code, to explain code, to generate tests and documentation, and to propose fixes to code. In November 2023, Tabnine closed a Series B round of funding, raising $25 million to scale the company’s operations. == Operations == Tabnine's headquarters is located in Tel Aviv, Israel, with an additional corporate entity in the United States. As of November 2023, Tabnine generative AI for software development is used by a million developers. It has 10 million installations across VS Code and JetBrains. Since its founding, Dror Weiss has served as CEO, with Eran Yahav as CTO.
Spike-and-slab regression
Spike-and-slab regression is a type of Bayesian linear regression in which a particular hierarchical prior distribution for the regression coefficients is chosen such that only a subset of the possible regressors is retained. The technique is particularly useful when the number of possible predictors is larger than the number of observations. The idea of the spike-and-slab model was originally proposed by Mitchell & Beauchamp (1988). The approach was further significantly developed by Madigan & Raftery (1994) and George & McCulloch (1997). A recent and important contribution to this literature is Ishwaran & Rao (2005). == Model description == Suppose we have P possible predictors in some model. Vector γ has a length equal to P and consists of zeros and ones. This vector indicates whether a particular variable is included in the regression or not. If no specific prior information on initial inclusion probabilities of particular variables is available, a Bernoulli prior distribution is a common default choice. Conditional on a predictor being in the regression, we identify a prior distribution for the model coefficient, which corresponds to that variable (β). A common choice on that step is to use a normal prior with a mean equal to zero and a large variance calculated based on ( X T X ) − 1 {\displaystyle (X^{T}X)^{-1}} (where X {\displaystyle X} is a design matrix of explanatory variables of the model). A draw of γ from its prior distribution is a list of the variables included in the regression. Conditional on this set of selected variables, we take a draw from the prior distribution of the regression coefficients (if γi = 1 then βi ≠ 0 and if γi = 0 then βi = 0). βγ denotes the subset of β for which γi = 1. In the next step, we calculate a posterior probability for both inclusion and coefficients by applying a standard statistical procedure. All steps of the described algorithm are repeated thousands of times using the Markov chain Monte Carlo (MCMC) technique. As a result, we obtain a posterior distribution of γ (variable inclusion in the model), β (regression coefficient values) and the corresponding prediction of y. The model got its name (spike-and-slab) due to the shape of the two prior distributions. The "spike" is the probability of a particular coefficient in the model to be zero. The "slab" is the prior distribution for the regression coefficient values. An advantage of Bayesian variable selection techniques is that they are able to make use of prior knowledge about the model. In the absence of such knowledge, some reasonable default values can be used; to quote Scott and Varian (2013): "For the analyst who prefers simplicity at the cost of some reasonable assumptions, useful prior information can be reduced to an expected model size, an expected R2, and a sample size ν determining the weight given to the guess at R2." Some researchers suggest the following default values: R2 = 0.5, ν = 0.01, and π = 0.5 (parameter of a prior Bernoulli distribution).
International Webmasters Association
The International Webmasters Association (IWA) is a non-profit association for education and certification of web professionals founded in 1996. It provides a Certified Web Professional certification. One of its objectives is to build a World Wide Web that is a true global community. According to the IWA, as of 2025 it has more than 100 official chapters with over 300,000 individual members in 106 countries. In 2001, the IWA merged with the HTML Writers Guild (HWG) and joined the World Wide Web Consortium (W3C). IWA's accomplishments include the publishing of the industry's first guidelines for ethical and professional standards, web certification and education programs, specialized employment resources, and technical assistance to individuals and businesses. IWA members participate to the activities of W3C WCAG Working Group, ATAG Working Group, and the XHTML Working Group. They have also participated in other initiatives such as the Multimodal Interaction Working Group which developed EMMA, the Extensible MultiModal Annotation markup language.
Infone
Infone was a service launched by Metro One Telecommunications in 2003. The service was discontinued effective December 14, 2005. == How it worked == Infone included directory assistance and other services via a toll-free phone number. A user could call 888-411-1111 to request directory assistance, directions, traffic information, movie times, call completion, dinner reservation assistance and other services. Infone provided a number of innovative 411 'concierge'-like services, including movie listings from a live operator, and offered a feature where they could provide information from a linked Microsoft Outlook calendar when set up in advance. For a period of time they advertised heavily on U.S. television, featuring ads with then Governor of Minnesota Jesse Ventura, emphasizing their use of all U.S. based operators. The price offered was $0.89 per call up to 15 minutes (for use when the operator connects you to the requested number, as well as for additional information requests afterwards), with $0.05 for each additional minute, making Infone also a competitively priced long-distance service. New users received 5–10 free calls. Infone identified a registered user (along with billing information; the service was only payable by credit card) by caller ID (numbers were registered on signing up) and by an advanced voiceprint recognition system (VPRS) from SpeechWorks that identified the user when the user called from an unregistered telephone number (or no caller ID) through the use of a personal phrase spoken by the user (e.g., "Hello Infone!") after the welcome tone.
MADI
Multichannel Audio Digital Interface (MADI) standardized as AES10 by the Audio Engineering Society (AES) defines the data format and electrical characteristics of an interface that carries multiple channels of digital audio. The AES first documented the MADI standard in AES10-1991 and updated it in AES10-2003 and AES10-2008. The MADI standard includes a bit-level description and has features in common with the two-channel AES3 interface. MADI supports serial digital transmission over coaxial cable or fibre-optic lines of 28, 56, 32, or 64 channels; and sampling rates to 96 kHz and beyond with an audio bit depth of up to 24 bits per channel. Like AES3 and ADAT Lightpipe, it is a unidirectional interface from one sender to one receiver. == Development and applications == MADI was developed by AMS Neve, Solid State Logic, Sony and Mitsubishi and is widely used in the audio industry, especially in the professional audio sector. It provides advantages over other audio digital interface protocols and standards such as AES3, ADAT Lightpipe, TDIF (Tascam Digital Interface), and S/PDIF (Sony/Philips Digital Interface). These advantages include: Support for a greater number of channels per line Use of coaxial and optical fiber media that support transmission of audio signals over 100 meters, up to 3000 meters over multi-mode and 40,000 meters over single-mode optical fiber The original specification (AES10-1991) defined the MADI link as a 56-channel transport for linking large-format mixing consoles to digital multitrack recording devices. Large broadcast studios also adopted it for routing multi-channel audio throughout their facilities. The 2003 revision (AES10-2003) adds a 64-channel capability by removing varispeed operation and supports 96 kHz sampling frequency with reduced channel capacity. The latest AES10-2008 standard includes minor clarifications and updates to correspond to the current AES3 standard. Audio over Ethernet of various types is the primary alternative to MADI for transport of many channels of professional digital audio. == Transmission format == MADI links use a transmission format similar to Fiber Distributed Data Interface (FDDI) networking. Since MADI is most often transmitted on copper links via 75-ohm coaxial cables, it more closely compares to the FDDI specification for copper-based links, called CDDI. AES10-2003 recommends using BNC connectors with coaxial cables and SC connectors with optic fibers. MADI over fibre can support a range of up to 2 km. The basic data rate is 100 Mbit/s of data using 4B5B encoding to produce a 125 MHz physical baud rate. Unlike AES3, this clock is not synchronized to the audio sample rate, and the audio data payload is padded using JK sync symbols. Sync symbols may be inserted at any subframe boundary, and must occur at least once per frame. Though the standard disassociates the transmission clock from the audio sample rate, and thus requires a separate word clock connection to maintain synchronization, some vendors do give the option of locking to parts of the transmission timing information for purposes of deriving a word clock. The audio data is almost identical to the AES3 payload, though with more channels. Rather than letters, MADI assigns channel numbers from 0–63. Frame synchronization is provided by sync symbols outside the data itself, rather than an embedded preamble sequence, and the first four time slots of each sub-channel are encoded as normal data, used for sub-channel identification: Bit 0: Set to 1 to mark channel 0, the first channel in each frame Bit 1: Set to 1 to indicate that this channel is active (contains interesting data) Bit 2: notA/B channel marker, used to mark left (0) and right (1) channels. Generally, even channels are A and odd channels are B. Bit 3: Set to 1 to mark the beginning of a 192-sample data block == Sampling frequency == The original AES10-1991 specification allowed 56 channels at sample rates from 32 to 48 kHz with an additional vari-speed range of ± 12.5%. This leads to a total range of 28 to 54 kHz. At the highest frequency, this produces a total of 56 × 32 × 54 = 96768 kbit/s, leaving 3.232% of the channel for synchronization marks and transmit clock error. The 2003 revision specifies different relations between sampling frequency and number of channels. 32 kHz to 48 kHz ± 12.5%, 56 channels; 32 kHz to 48 kHz nominal, 64 channels; 64 kHz to 96 kHz ± 12.5%, 28 channels. With a 48 kHz sampling frequency, 64 channels take 64 × 32 × 48000 = 98.304 Mbit/s. Adding the minimum 8 × 58 kbit/s of framing produces 98688 bit/s, leaving 1.312% free for timing variation and other overhead. Both versions of the standard accommodate higher sampling frequencies (for example, 96 kHz or 192 kHz) by using two or more channels per audio sample on the link.
Gitter
Gitter is an open-source instant messaging and chat room system for developers and users of GitLab and GitHub repositories. Gitter is provided as software as a service, with a free option providing all basic features and the ability to create a single private chat room, and paid subscription options for individuals and organisations, which allows them to create arbitrary numbers of private chat rooms. Individual chat rooms can be created for individual Git repositories on GitHub. Chatroom privacy follows the privacy settings of the associated GitHub repository: thus, a chatroom for a private (i.e. members-only) GitHub repository is also private to those with access to the repository. A graphical badge linking to the chat room can then be placed in the git repository's README file, bringing it to the attention of all users and developers of the project. Users can chat in the chat rooms, or access private chat rooms for repositories they have access to, by logging into Gitter via GitHub. Gitter is similar to Slack. Like Slack, it automatically logs all messages in the cloud. In late 2020, New Vector Limited acquired Gitter from GitLab, and announced Gitter's features would eventually be moved to New Vector's flagship product, Element, thereby replacing Gitter entirely. On February 13, 2023, Gitter migrated their service to a custom-branded Matrix instance that uses Element for its web interface. == Features prior to Migration to Matrix == Gitter supports: Notifications, which are batched up on mobile devices to avoid annoyance Inline media files Viewing and subscribing to ("starring") multiple chat rooms in one web browser tab Linking to individual files in the linked git repository Linking to GitHub issues (by typing # and then the issue number) in the linked Git repository, with hovercards showing the details of the issue GitHub-flavored Markdown in chat messages Online status for users User hovercards, based on their GitHub profiles and statistics (number of GitHub followers, etc.) Browsable and searchable message archives, grouped by month Connection from IRC clients Gitter on iOS support authentication using GitHub or Twitter === Integrations with non-GitHub sites and applications === Gitter integrates with Trello, Jenkins, Travis CI, Drone (software), Heroku, and Bitbucket, among others. === Apps === Official Gitter apps for Windows, Mac, Linux, iOS and Android are available. === Account registration === Like other chat technologies, Gitter allows clients to instant message each other. It allows people to authenticate using a GitHub account and join a chatroom from a web browser, thus not requiring one to install any software, or create additional online accounts. == History == Gitter was created by some developers who were initially trying to create a generic web-based chat product, but then wrote extra code to hook their chat application up to GitHub to meet their own needs, and realised that they could turn the combined product into a viable specialist product in its own right. Gitter came out of beta in 2014. During the beta period, Gitter delivered 1.8 million chat messages. On March 15, 2017, GitLab announced the acquisition of Gitter. Included in the announcement was the stated intent that Gitter would continue as a standalone project. It was published as open source under an MIT License as of June 2017. On September 30, 2020, New Vector Limited acquired Gitter from GitLab, and announced upcoming support for the Matrix protocol in Gitter, which went live by the end of the year. Gitter's features would eventually be moved to New Vector's flagship product, Element, thereby replacing Gitter entirely. On February 13, 2023, Gitter migrated their service to a custom-branded Matrix instance that uses Element for its web interface. == Implementation prior to Migration to Matrix == The Gitter web application is implemented entirely in JavaScript, with the back end being implemented on Node.js. The source code to the web application was formerly proprietary (it was open-sourced in June 2017), although Gitter had made numerous auxiliary projects available as open-source software, such as an IRC bridge for IRC users who prefer using IRC client applications (and their extra features) to converse in the Gitter chat rooms.
Mixvoip
Mixvoip S.A. is a Luxembourg-based telecommunications service provider founded in 2008. The company offers IP telephony, high-speed Internet connectivity, and IT solutions to businesses and individuals. == Company history == In November 2017, Mixvoip expanded its operations to Belgium and Germany. At the beginning of 2019, the company acquired the telecommunications provider Voipgate. In December 2019, Mixvoip was named Telecom Company of the Year at the Luxembourg ICT Awards 2019 organized by Farvest and IT One. A 2024 article in Duke described the company's transition during the 2010s from traditional telephony services to cloud-based communication platforms. In the end of 2024, the ILR published the statistics about electronic communications in Luxembourg, including Mixvoip in the fix telephony section. In July 2025, Mixvoip acquired Crossing Telecom. In 2026, Mixvoip acquired Nomado's portfolio.