Merit Network, Inc., is a nonprofit member-governed organization providing high-performance computer networking and related services to educational, government, health care, and nonprofit organizations, primarily in Michigan. Created in 1966, Merit operates the longest running regional computer network in the United States. == Organization == Created in 1966 as the Michigan Educational Research Information Triad by Michigan State University (MSU), the University of Michigan (U-M), and Wayne State University (WSU), Merit was created to investigate resource sharing by connecting the mainframe computers at these three Michigan public research universities. Merit's initial three node packet-switched computer network was operational in October 1972 using custom hardware based on DEC PDP-11 minicomputers and software developed by the Merit staff and the staffs at the three universities. Over the next dozen years the initial network grew as new services such as dial-in terminal support, remote job submission, remote printing, and file transfer were added; as gateways to the national and international Tymnet, Telenet, and Datapac networks were established, as support for the X.25 and TCP/IP protocols was added; as additional computers such as WSU's MVS system and the UM's electrical engineering's VAX running UNIX were attached; and as new universities became Merit members. Merit's involvement in national networking activities started in the mid-1980s with connections to the national supercomputing centers and work on the 56 kbit/s National Science Foundation Network (NSFNET), the forerunner of today's Internet. From 1987 until April 1995, Merit re-engineered and managed the NSFNET backbone service. MichNet, Merit's regional network in Michigan was attached to NSFNET and in the early 1990s Merit began extending "the Internet" throughout Michigan, offering both direct connect and dial-in services, and upgrading the statewide network from 56 kbit/s to 1.5 Mbit/s, and on to 45, 155, 622 Mbit/s, and eventually 1 and 10 Gbit/s. In 2003 Merit began its transition to a facilities based network, using fiber optic facilities that it shares with its members, that it purchases or leases under long-term agreements, or that it builds. In addition to network connectivity services, Merit offers a number of related services within Michigan and beyond, including: Internet2 connectivity, VPN, Network monitoring, Voice over IP (VOIP), Cloud storage, E-mail, Domain Name, Network Time, VMware and Zimbra software licensing, Colocation, and professional development seminars, workshops, classes, conferences, and meetings. == History == === Creating the network: 1966 to 1973 === The Michigan Educational Research Information Triad (MERIT) was formed in the fall of 1966 by Michigan State University (MSU), University of Michigan (U-M), and Wayne State University (WSU). More often known as the Merit Computer Network or simply Merit, it was created to design and implement a computer network connecting the mainframe computers at the universities. In the fall of 1969, after funding for the initial development of the network had been secured, Bertram Herzog was named director for MERIT. Eric Aupperle was hired as senior engineer, and was charged with finding hardware to make the network operational. The National Science Foundation (NSF) and the State of Michigan provided the initial funding for the network. In June 1970, the Applied Dynamics Division of Reliance Electric in Saline, Michigan was contracted to build three Communication Computers or CCs. Each would consist of a Digital Equipment Corporation (DEC) PDP-11 computer, dataphone interfaces, and interfaces that would attach them directly to the mainframe computers. The cost was to be slightly less than the $300,000 ($2,487,100, adjusted for inflation) originally budgeted. Merit staff wrote the software that ran on the CCs, while staff at each of the universities wrote the mainframe software to interface to the CCs. The first completed connection linked the IBM S/360-67 mainframe computers running the Michigan Terminal System at WSU and U-M, and was publicly demonstrated on December 14, 1971. The MSU node was completed in October 1972, adding a CDC 6500 mainframe running Scope/Hustler. The network was officially dedicated on May 15, 1973. === Expanding the network: 1974 to 1985 === In 1974, Herzog returned to teaching in the University of Michigan's Industrial Engineering Department, and Aupperle was appointed as director. Use of the all uppercase name "MERIT" was abandoned in favor of the mixed case "Merit". The first network connections were host to host interactive connections which allowed person to remote computer or local computer to remote computer interactions. To this, terminal to host connections, batch connections (remote job submission, remote printing, batch file transfer), and interactive file copy were added. And, in addition to connecting to host computers over custom hardware interfaces, the ability to connect to hosts or other networks over groups of asynchronous ports and via X.25 were added. Merit interconnected with Telenet (later SprintNet) in 1976 to give Merit users dial-in access from locations around the United States. Dial-in access within the U.S. and internationally was further expanded via Merit's interconnections to Tymnet, ADP's Autonet, and later still the IBM Global Network as well as Merit's own expanding network of dial-in sites in Michigan, New York City, and Washington, D.C. In 1978, Western Michigan University (WMU) became the fourth member of Merit (prompting a name change, as the acronym Merit no longer made sense as the group was no longer a triad). To expand the network, the Merit staff developed new hardware interfaces for the Digital PDP-11 based on printed circuit technology. The new system became known as the Primary Communications Processor (PCP), with the earliest PCPs connecting a PDP-10 located at WMU and a DEC VAX running UNIX at U-M's Electrical Engineering department. A second hardware technology initiative in 1983 produced the smaller Secondary Communication Processors (SCP) based on DEC LSI-11 processors. The first SCP was installed at the Michigan Union in Ann Arbor, creating UMnet, which extended Merit's network connectivity deeply into the U-M campus. In 1983 Merit's PCP and SCP software was enhanced to support TCP/IP and Merit interconnected with the ARPANET. === National networking, NSFNET, and the Internet: 1986 to 1995 === In 1986 Merit engineered and operated leased lines and satellite links that allowed the University of Michigan to access the supercomputing facilities at Pittsburgh, San Diego, and NCAR. In 1987, Merit, IBM and MCI submitted a winning proposal to NSF to implement a new NSFNET backbone network. The new NSFNET backbone network service began July 1, 1988. It interconnected supercomputing centers around the country at 1.5 megabits per second (T1), 24 times faster than the 56 kilobits-per-second speed of the previous network. The NSFNET backbone grew to link scientists and educators on university campuses nationwide and connect them to their counterparts around the world. The NSFNET project caused substantial growth at Merit, nearly tripling the staff and leading to the establishment of a new 24-hour Network Operations Center at the U-M Computer Center. In September 1990 in anticipation of the NSFNET T3 upgrade and the approaching end of the 5-year NSFNET cooperative agreement, Merit, IBM, and MCI formed Advanced Network and Services (ANS), a new non-profit corporation with a more broadly based Board of Directors than the Michigan-based Merit Network. Under its cooperative agreement with NSF, Merit remained ultimately responsible for the operation of NSFNET, but subcontracted much of the engineering and operations work to ANS. In 1991 the NSFNET backbone service was expanded to additional sites and upgraded to a more robust 45 Mbit/s (T3) based network. The new T3 backbone was named ANSNet and provided the physical infrastructure used by Merit to deliver the NSFNET Backbone Service. On April 30, 1995, the NSFNET project came to an end, when the NSFNET backbone service was decommissioned and replaced by a new Internet architecture with commercial Internet service providers (ISPs) interconnected at Network Access Points provided by multiple providers across the country. === Bringing the Internet to Michigan: 1985 to 2001 === During the 1980s, Merit Network grew to serve eight member universities, with Oakland University joining in 1985 and Central Michigan University, Eastern Michigan University, and Michigan Technological University joining in 1987. In 1990, Merit's board of directors formally changed the organization's name to Merit Network, Inc., and created the name MichNet to refer to Merit's statewide network. The board also approved a staff proposal to allow organizations other than publicly supported universities, referred to as aff
Sparrow (chatbot)
Sparrow is a chatbot developed by the artificial intelligence research lab DeepMind, a subsidiary of Alphabet Inc. It is designed to answer users' questions correctly, while reducing the risk of unsafe and inappropriate answers. One motivation behind Sparrow is to address the problem of language models producing incorrect, biased or potentially harmful outputs. Sparrow is trained using human judgements, in order to be more “Helpful, Correct and Harmless” compared to baseline pre-trained language models. The development of Sparrow involved asking paid study participants to interact with Sparrow, and collecting their preferences to train a model of how useful an answer is. To improve accuracy and help avoid the problem of hallucinating incorrect answers, Sparrow has the ability to search the Internet using Google Search in order to find and cite evidence for any factual claims it makes. To make the model safer, its behaviour is constrained by a set of rules, for example "don't make threatening statements" and "don't make hateful or insulting comments", as well as rules about possibly harmful advice, and not claiming to be a person. During development study participants were asked to converse with the system and try to trick it into breaking these rules. A 'rule model' was trained on judgements from these participants, which was used for further training. Sparrow was introduced in a paper in September 2022, titled "Improving alignment of dialogue agents via targeted human judgements"; however, the bot was not released publicly. DeepMind CEO Demis Hassabis said DeepMind is considering releasing Sparrow for a "private beta" some time in 2023. == Training == Sparrow is a deep neural network based on the transformer machine learning model architecture. It is fine-tuned from DeepMind's Chinchilla AI pre-trained large language model (LLM), which has 70 Billion parameters. Sparrow is trained using reinforcement learning from human feedback (RLHF), although some supervised fine-tuning techniques are also used. The RLHF training utilizes two reward models to capture human judgements: a “preference model” that predicts what a human study participant would prefer and a “rule model” that predicts if the model has broken one of the rules. == Limitations == Sparrow's training data corpus is mainly in English, meaning it performs worse in other languages. When adversarially probed by study participants it breaks the rules 8% of the time; however, this is still three times lower than the baseline prompted pre-trained model (Chinchilla).
Hildon
Hildon is an application framework originally developed for mobile devices (PDAs, mobile phones, etc.) running the Linux operating system as well as the Symbian operating system. The Symbian variant of Hildon was discontinued with the cancellation of Series 90. It was developed by Nokia for the Maemo operating system. It focuses on providing a finger-friendly interface. It is primarily a set of GTK extensions that provide mobile-device–oriented functionality, but also provides a desktop environment that includes a task navigator for opening and switching between programs, a control panel for user settings, and status bar, task bar and home applets. It is standard on the Maemo platform used by the Nokia Internet Tablets and the Nokia N900 smartphone. Hildon has also been selected as the framework for Ubuntu Mobile and Embedded Edition. Hildon was an early instance of a software platform for generic computing in a tablet device intended for internet consumption. But Nokia didn't commit to it as their only platform for their future mobile devices and the project competed against other in-house platforms. The strategic advantage of a modern platform was not exploited, being displaced by the Series 60, though its development is continued by the Maemo Leste project. == Components == The Hildon framework includes components that effectively provide a desktop environment. === Hildon Application Manager === Hildon Application Manager is the Hildon graphical package manager, it uses the Debian package management tools APT (Advanced Packaging Tool and dpkg) and provides a graphical interface for installing, updating and removing packages. It is a limited package manager, designed specifically for end-users, in that it doesn't directly offer the user access to system files and libraries. With the Diablo release of Maemo, Hildon Application Manager now supports "Seamless Software Update" (SSU), which implements a variety of features to allow system upgrades to be easily performed through it. === Hildon Control Panel === Hildon Control Panel is the user settings interface for Hildon. It provides simple access to control panels used to change system settings. === Hildon Desktop === Hildon Desktop is the primary UI component of Hildon, so makes up the bulk of what a user will see as "Hildon". It controls application launching and switching, general system control, and provides interfaces for task bar (application menu and task switcher), status bar (brightness and volume control), and home (internet radio and web search) applets. === Hildon Library === The Hildon library, originally developed by Nokia but since Maemo 5, developed by Igalia and Lanedo (who developed MaemoGTK+, the Maemo version of GTK+). It is a set of mobile specific GTK+ widgets for applications in Maemo. Up to Maemo 4, these widgets were designed for stylus usage. However, in Maemo 5, most widgets were deprecated and new widgets for direct finger manipulation were introduced, including a kinetic panning container.
Deep image compositing
Deep image compositing is a way of compositing and rendering digital images that emerged in the mid-2010s. In addition to the usual color and opacity channels a notion of spatial depth is created. This allows multiple samples in the depth of the image to make up the final resulting color. This technique produces high quality results and removes artifacts around edges that could not be dealt with otherwise. == Deep data == Deep data is encoded by advanced 3D renderers into an image that samples information about the path each rendered pixel takes along the z axis extending outward from the virtual camera through space, including the color and opacity of every non-opaque surface or volume it passes through along the way, as well as neighboring samples. It might be considered somewhat analogous to the way ray tracing generates simulated photon paths through such mediums; however, ray tracing and other traditional rendering techniques generally produce images that contain only three or four channels of color and opacity values per pixel, flattened into a two dimensional frame. Depth maps, on the other hand, contain z axis information encoded in a grayscale image. Each level of gray represents a different slice of the z space. The "thickness" of each slice is determined at time of render, allowing for more or less depth fidelity depending on how deep the scene is. Depth maps have been a boon to compositors for blending 3D renders with live action and practical elements. To be useful, the map must have high enough bit depth to encode separation between close-to-camera objects and objects near infinity. Most 3D software packages are now capable of generating 16-bit and 32-bit depth maps, providing up to 2 billion depth levels. Depth maps do not however include transparency information about non-opaque surfaces or volumes and as such, objects beyond and viewed through these semi- or fully-transparent objects will have no depth information of their own and may not get composited or blurred correctly. Even the popular addition of cryptomattes to many post-production and VFX studios' pipelines, while providing separate color-coded ID shapes for individual elements in a rendered scene to further bridge the gap between CGI and compositing, don't allow for the nearly automated and fully non-linear workflows that deep data does. This is because deep images encapsulate enough 3D information that normally time-intensive tasks such as rotoscoping with numerous holdout mattes for complex interactions between moving characters and semi-transparent environmental volumes like smoke or water, are essentially trivial. Instead of going through that process, multiple mattes could easily be generated from a single set of deep images with no need to re-render every matte element and background for each case. In addition to that efficiency and flexibility, deep data images inherently provide much higher visual quality in common areas that have been difficult with traditional renders, such as the motion-blurred edges of characters with semi-transparent elements like hair. One downside to the use of deep images is their substantial file size, since they encode a relatively enormous amount of data per frame compared to even multichannel formats such as OpenEXR. === Function-based (integrated) === The data is stored as a function of depth. This results in a function curve that can be used to look up the data at any arbitrary depth. Manipulating the data is harder. === Sample-based (deintegrated) === Each sample is considered as an independent piece and can so be manipulated easily. To make sure the data is representing the right detail, an additional expand value needs to be introduced. == Generating deep data == 3D renderers produce the necessary data as a part of the rendering pipeline. Samples are gathered in depth and then combined. The deep data can be written out before this happens and so is nothing new to the process. Generating deep data from camera data needs a proper depth map. This is used in a couple of cases but still not accurate enough for detailed representation. For basic holdout task this can be sufficient though. == Compositing deep data images == Deep images can be composited like regular images. The depth component makes it easier to determine the layering order. Traditionally this had to be input by the user. Deep images have that information for themselves and need no user input. Edge artifacts are reduced as transparent pixels have more data to work with. == History == Deep Images have been around in 3D rendering packages for quite a while now. The use of them for holdouts was first done at several VFX houses in shaders. Holdout mattes can be generated at render time. Using them in a more interactive manner was started recently by several companies, SideFX integrated it in their Houdini software and facilities like Industrial Light & Magic, DreamWorks Animation, Weta, AnimalLogic and DRD studios have implemented interactive solutions. In 2014 the Academy of Motion Picture Arts and Sciences honored the technology with its annual SciTech awards. Dr. Peter Hillman for the long-term development and continued advancement of innovative, robust and complete toolsets for deep compositing and to Colin Doncaster, Johannes Saam, Areito Echevarria, Janne Kontkanen and Chris Cooper for the development, prototyping and promotion of technologies and workflows for deep compositing. == Resources == Pixar Paper Deep Image Paper Video tutorial of Deep Imaging as used on 2012 film Rise of the Planet of the Apes, Nuke compositing software Deep Compositing Course Deep Image File Format at Google Code Academy Award for the Technology Theory of Deep Pixels OpenEXR Deep Pixels
Google Messages
Google Messages (formerly known as Messenger, Android Messages, and Messages by Google) is a text messaging software application developed by Google for its Android and Wear OS mobile operating systems. It is also available as a web app. Google's official universal messaging platform for the Android ecosystem, Messages employs SMS, MMS, and Rich Communication Services (RCS). Starting in 2023, Google has RCS activated by default on participating Android devices, similar to the implementation of iMessage on Apple devices. Samsung Messages will be discontinued on July 6th 2026, with Samsung transitioning users to Google Messages as the default messaging application. == History == The original code for Android SMS messaging was released in 2009 integrated into the operating system. It was released as a standalone application independent of Android with the release of Android 5.0 Lollipop in 2014, replacing Google Hangouts as the default SMS app on Google's Nexus line of phones. In 2018, Messages adopted RCS messages and evolved to send larger data files, sync with other apps, and even create mass messages. This was in preparation for when Google launched Messages for web. In December 2019, Google began to introduce support for Rich Communication Services (RCS) messaging via an RCS service hosted by Google, referred to in the user interface as "chat features". This was followed by a wider global rollout throughout 2020. The app surpassed 1 billion installs in April 2020, doubling its number of installs in less than a year. Initially, RCS did not support end-to-end encryption. In June 2021, Google introduced end-to-end encryption in Messages by default using the Signal Protocol, for all one-to-one RCS-based conversations, for all RCS group chats in December 2022 for beta users, and for all RCS users by August 2023, as well as enabling RCS for all users by default to encourage encryption. In July 2023, Google announced it would build the Message Layer Security (MLS) end-to-end encryption protocol into Google Messages. Beginning with the Samsung Galaxy S21, Messages replaces Samsung's in-house Messages app as the default text messaging app for One UI for some regions and carriers. In April 2021, the app began to receive UI modifications on Samsung devices to follow aspects of One UI, including pushing the top of the message list towards the middle of the screen to improve ergonomics. In February 2023, Google began to replace references to "chat features" in the Messages user interface with "RCS". In August 2023, Google announced that Messages will use RCS by default for all users unless they opt out, to allow them to benefit from secure messaging. In December 2023, with the arrival of several new features, the app was renamed "Google Messages". In July 2024, Samsung announced it would no longer pre-install Samsung Messages on its Galaxy devices in some regions, starting with the Galaxy Z Fold 6 and Flip, favoring Google Messages instead. In April 2026, Samsung announced that Samsung Messages would be discontinued in July 2026. It encouraged users to switch to Google Messages. == Features == Some of the most important features in Google Messages are: Send instant text and voice messages in 1:1 or group chat conversations over mobile data and Wi-Fi, via Android, Wear OS or the web. End-to-end encryption for RCS chats. Typing, sent, delivered and read status Reply and react to specific messages Share files and high-resolution photos Voice message transcriptions Schedule messages In-app reminders for birthdays and messages you didn't respond to after some time with Nudges Tight integration with the Google ecosystem, e.g. Google Calendar, Meet, Maps, YouTube, Photos, Contacts, Assistant, Search, Safe Browsing etc. Web interface: Users can visit https://messages.google.com/web and either sign in with their Google account or scan the QR code that is shown with their smartphone to access a limited web version of the app that allows them to send and receive messages, provided the smartphone remains connected. Phone number recognition: The app shows the country and province of the caller. Additionally, it can show the company's name or a warning for spam calls if the number is registered in a data base. Access to the Gemini chatbot on select Pixel, Galaxy and Android devices.
InstallCore
InstallCore (stylized as installCore) was an installation and content distribution platform created by ironSource, considered potentially unwanted programs (PUP) by a number of anti-malware vendors. It included a software development kit (SDK) for Windows and Mac OS X. The program allowed those using it for distribution to include monetization by advertisements or charging for installation, and made its installations invisible to the user and its anti-virus software. The platform and its programs have been rated potentially unwanted programs (PUP) or potentially unwanted applications (PUA) by anti-malware product vendors since 2014, and by Windows Defender Antivirus since 2015. The platform was primarily designed for efficient web-based deployment of various types of application software. As of August 2012, InstallCore was managing 100 million installations every month, offering services for paid, unpaid, and free software by using the SDK version. == History == The InstallCore team introduced the first version of the SDK at the beginning of 2011. The SDK was a fork of the FoxTab installer and had only basic Installation features. InstallCore was discontinued as part of a company flotation in late 2020. == Criticism and malware classification == InstallCore and its software packages have been classified as potentially unwanted programs (PUP) or potentially unwanted applications (PUA), by anti-malware product vendors and Windows Defender Antivirus from 2014–2015 onwards, with many stating that it installs adware and other additional PUPs. Malwarebytes identified the program as "a family of bundlers that installs more than one application on the user's computer". It has been described as "crossing the line into full-blown malware" and a "nasty Trojan".
ElabFTW
eLabFTW is a web application written by Nicolas Carpi in PHP which can be used to create personal and common logbooks. It has been developed at the Curie Institute originally. Besides there, it is used on universities around the world eLabFTW is licensed under the GNU Affero General Public License as free software. It is translated into seven languages. == Description == eLabFTW is a free and open-source lab book. It is written in PHP and uses a MySQL database. Docker containers are also available. Among the various features are Secure. Entries and transmission are encrypted Timestamps. RFC 3161 compliant timestamping of experiments. Inventory management. Apart from experience logs, it also can manage the inventory Import and export. Entries can be imported and exported == Platforms == eLabFTW is a PHP package with Mysql database. Therefore, it can be executed on most servers. Furthermore, the docker containers allow to run it almost everywhere. == Usage == eLabFTW is used by various universities, like University of Alberta, Berkeley University, Hanover Medical School, Cardiff University and UMC Utrecht