Cloud-based quantum computing refers to the remote access of quantum computing resources—such as quantum emulators, simulators, or processors—via the internet. Cloud access enables users to develop, test, and execute quantum algorithms without the need for direct interaction with specialized hardware, facilitating broader participation in quantum software development and experimentation. In 2016, IBM launched the IBM Quantum Experience, one of the first publicly accessible quantum processors connected to the cloud. In early 2017, researchers at Rigetti Computing demonstrated programmable quantum cloud access through their software platform Forest, which included the pyQuil Python library. Since the early-2020s, cloud-based quantum computing has grown significantly, with multiple providers offering access to a variety of quantum hardware modalities, including superconducting qubits, trapped ions, neutral atoms, and photonic systems. Major platforms such as Amazon Braket, Azure Quantum, and qBraid aggregate quantum devices from hardware developers like IonQ, Rigetti Computing, QuEra, Pasqal, Oxford Quantum Circuits, and IBM Quantum. These platforms provide unified interfaces for users to write and execute quantum algorithms across diverse backends, often supporting open-source SDKs such as Qiskit, Cirq, and PennyLane. The proliferation of cloud-based access has played a key role in accelerating quantum education, algorithm research, and early-stage application development by lowering the barrier to experimentation with real quantum hardware. Cloud-based quantum computing has expanded access to quantum hardware and tools beyond traditional research laboratories. These platforms support educational initiatives, algorithm development, and early-stage commercial applications. == Applications == Cloud-based quantum computing is used across education, research, and software development, offering remote access to quantum systems without the need for on-site infrastructure. === Education === Quantum cloud platforms have become valuable tools in education, allowing students and instructors to engage with real quantum processors through user-friendly interfaces. Educators use these platforms to teach foundational concepts in quantum mechanics and quantum computing, as well as to demonstrate and implement quantum algorithms in a classroom or laboratory setting. === Scientific Research === Cloud-based access to quantum hardware has enabled researchers to conduct experiments in quantum information, test quantum algorithms, and compare quantum hardware platforms. Experiments such as testing Bell's theorem or evaluating quantum teleportation protocols have been performed on publicly available quantum processors. === Software Development and Prototyping === Developers use cloud-based platforms to prototype quantum software applications across fields such as optimization, machine learning, and chemistry. These platforms offer SDKs and APIs that integrate classical and quantum workflows, enabling experimentation with quantum algorithms in real-world or simulated environments. === Public Engagement and Games === Quantum cloud tools have also been used to create educational games and interactive applications aimed at increasing public understanding of quantum concepts. These efforts help bridge the gap between theoretical content and intuitive learning. == Existing platforms == qBraid Lab by qBraid is a cloud-based platform for quantum computing. It provides software tools for researchers and developers in quantum, as well as access to quantum hardware. qBraid provides cloud based access to Microsoft Azure Quantum and Amazon Braket devices including IQM, QuEra, Pasqal, Rigetti, IonQ, QIR simulators, Amazon Braket simulators, and the NEC Vector Annealer, as of August 2025. qBraid's base version is free, where unlimited hardware and simulator access is available with the purchase of credits. Quandela Cloud by Quandela is the platform to access first cloud-accessible European photonic quantum computer. The computer is interfaced using the Perceval scripting language, with tutorials and documentation available online for free. Xanadu Quantum Cloud by Xanadu is a platform with cloud-based access to three fully programmable photonic quantum computers. Forest by Rigetti Computing is a tool suite for cloud-based quantum computing. It includes a programming language, development tools and example algorithms. LIQUi> by Microsoft is a software architecture and tool suite for quantum computing. It includes a programming language, example optimization and scheduling algorithms, and quantum simulators. Q#, a quantum programming language by Microsoft on the .NET Framework seen as a successor to LIQUi|>. IBM Quantum Platform by IBM, providing access to quantum hardware as well as HPC simulators. These can be accessed programmatically using the Python-based Qiskit framework, or via graphical interface with the IBM Q Experience GUI. Both are based on the OpenQASM standard for representing quantum operations. There is also a tutorial and online community. Quantum in the Cloud by The University of Bristol, which consists of a quantum simulator and a four qubit optical quantum system. Quantum Playground by Google is an educational resource which features a simulator with a simple interface, and a scripting language and 3D quantum state visualization. Quantum in the Cloud is an experimental quantum cloud platform for access to a four-qubit nuclear magnetic resonance-NMRCloudQ computer, managed by Tsinghua University. Quantum Inspire by Qutech is the first platform in Europe providing cloud-based quantum computing to two hardware chips. Next to a 5-qubit transmon processor, Quantum Inspire is the first platform in the world to provide online access to a fully programmable 2-qubit electron spin quantum processor. Amazon Braket is a cloud-based quantum computing platform hosted by AWS which, as of June 2025, provides access to quantum computers built by IonQ, Rigetti, IQM, and QuEra. Braket also provides a quantum algorithm development environment and simulator. Forge by QC Ware is a cloud-based quantum computing platform that provides access to D-Wave hardware, as well as Google and IBM simulators. The platform offers a 30-day free trial, including one minute of quantum computing time. Quantum-as-a-Service by Scaleway is a cloud-based platform created in 2022 to access to real quantum hardware from IQM Quantum Computers, Alpine Quantum Technologies, Quandela and Pasqal. It also include access to GPU-powered emulators such as Aer, Qsim and Quandela proprietary emulation.
Real-time computer graphics
Real-time computer graphics or real-time rendering is the sub-field of computer graphics focused on producing and analyzing images in real time. The term can refer to anything from rendering an application's graphical user interface (GUI) to real-time image analysis, but is most often used in reference to interactive 3D computer graphics, typically using a graphics processing unit (GPU). One example of this concept is a video game that rapidly renders changing 3D environments to produce an illusion of motion. Computers have been capable of generating 2D images such as simple lines, images and polygons in real time since their invention. However, quickly rendering detailed 3D objects is a daunting task for traditional Von Neumann architecture-based systems. An early workaround to this problem was the use of sprites, 2D images that could imitate 3D graphics. Different techniques for rendering now exist, such as ray-tracing and rasterization. Using these techniques and advanced hardware, computers can now render images quickly enough to create the illusion of motion while simultaneously accepting user input. This means that the user can respond to rendered images in real time, producing an interactive experience. == Principles of real-time 3D computer graphics == The goal of computer graphics is to generate computer-generated images, or frames, using certain desired metrics. One such metric is the number of frames generated in a given second. Real-time computer graphics systems differ from traditional (i.e., non-real-time) rendering systems in that non-real-time graphics typically rely on ray tracing. In this process, millions or billions of rays are traced from the camera to the world for detailed rendering—this expensive operation can take hours or days to render a single frame. Real-time graphics systems must render each image in less than 1/30th of a second. Ray tracing is far too slow for these systems; instead, they employ the technique of z-buffer triangle rasterization. In this technique, every object is decomposed into individual primitives, usually triangles. Each triangle gets positioned, rotated and scaled on the screen, and rasterizer hardware (or a software emulator) generates pixels inside each triangle. These triangles are then decomposed into atomic units called fragments that are suitable for displaying on a display screen. The fragments are drawn on the screen using a color that is computed in several steps. For example, a texture can be used to "paint" a triangle based on a stored image, and then shadow mapping can alter that triangle's colors based on line-of-sight to light sources. === Video game graphics === Real-time graphics optimizes image quality subject to time and hardware constraints. GPUs and other advances increased the image quality that real-time graphics can produce. GPUs are capable of handling millions of triangles per frame, and modern DirectX/OpenGL class hardware is capable of generating complex effects, such as shadow volumes, motion blurring, and triangle generation, in real-time. The advancement of real-time graphics is evidenced in the progressive improvements between actual gameplay graphics and the pre-rendered cutscenes traditionally found in video games. Cutscenes are typically rendered in real-time—and may be interactive. Although the gap in quality between real-time graphics and traditional off-line graphics is narrowing, offline rendering remains much more accurate. === Advantages === Real-time graphics are typically employed when interactivity (e.g., player feedback) is crucial. When real-time graphics are used in films, the director has complete control of what has to be drawn on each frame, which can sometimes involve lengthy decision-making. Teams of people are typically involved in the making of these decisions. In real-time computer graphics, the user typically operates an input device to influence what is about to be drawn on the display. For example, when the user wants to move a character on the screen, the system updates the character's position before drawing the next frame. Usually, the display's response-time is far slower than the input device—this is justified by the immense difference between the (fast) response time of a human being's motion and the (slow) perspective speed of the human visual system. This difference has other effects too: because input devices must be very fast to keep up with human motion response, advancements in input devices (e.g., the current Wii remote) typically take much longer to achieve than comparable advancements in display devices. Another important factor controlling real-time computer graphics is the combination of physics and animation. These techniques largely dictate what is to be drawn on the screen—especially where to draw objects in the scene. These techniques help realistically imitate real world behavior (the temporal dimension, not the spatial dimensions), adding to the computer graphics' degree of realism. Real-time previewing with graphics software, especially when adjusting lighting effects, can increase work speed. Some parameter adjustments in fractal generating software may be made while viewing changes to the image in real time. == Rendering pipeline == The graphics rendering pipeline ("rendering pipeline" or simply "pipeline") is the foundation of real-time graphics. Its main function is to render a two-dimensional image in relation to a virtual camera, three-dimensional objects (an object that has width, length, and depth), light sources, lighting models, textures and more. === Architecture === The architecture of the real-time rendering pipeline can be divided into conceptual stages: application, geometry and rasterization. === Application stage === The application stage is responsible for generating "scenes", or 3D settings that are drawn to a 2D display. This stage is implemented in software that developers optimize for performance. This stage may perform processing such as collision detection, speed-up techniques, animation and force feedback, in addition to handling user input. Collision detection is an example of an operation that would be performed in the application stage. Collision detection uses algorithms to detect and respond to collisions between (virtual) objects. For example, the application may calculate new positions for the colliding objects and provide feedback via a force feedback device such as a vibrating game controller. The application stage also prepares graphics data for the next stage. This includes texture animation, animation of 3D models, animation via transforms, and geometry morphing. Finally, it produces primitives (points, lines, and triangles) based on scene information and feeds those primitives into the geometry stage of the pipeline. === Geometry stage === The geometry stage manipulates polygons and vertices to compute what to draw, how to draw it and where to draw it. Usually, these operations are performed by specialized hardware or GPUs. Variations across graphics hardware mean that the "geometry stage" may actually be implemented as several consecutive stages. ==== Model and view transformation ==== Before the final model is shown on the output device, the model is transformed onto multiple spaces or coordinate systems. Transformations move and manipulate objects by altering their vertices. Transformation is the general term for the four specific ways that manipulate the shape or position of a point, line or shape. ==== Lighting ==== In order to give the model a more realistic appearance, one or more light sources are usually established during transformation. However, this stage cannot be reached without first transforming the 3D scene into view space. In view space, the observer (camera) is typically placed at the origin. If using a right-handed coordinate system (which is considered standard), the observer looks in the direction of the negative z-axis with the y-axis pointing upwards and the x-axis pointing to the right. ==== Projection ==== Projection is a transformation used to represent a 3D model in a 2D space. The two main types of projection are orthographic projection (also called parallel) and perspective projection. The main characteristic of an orthographic projection is that parallel lines remain parallel after the transformation. Perspective projection utilizes the concept that if the distance between the observer and model increases, the model appears smaller than before. Essentially, perspective projection mimics human sight. ==== Clipping ==== Clipping is the process of removing primitives that are outside of the view box in order to facilitate the rasterizer stage. Once those primitives are removed, the primitives that remain will be drawn into new triangles that reach the next stage. ==== Screen mapping ==== The purpose of screen mapping is to find out the coordinates of the primitives during the clipping stage. ==== Rasterizer stage ==== The rasterizer
Data communication
Data communication is the transfer of data over a point-to-point or point-to-multipoint communication channel. Data communication comprises data transmission and data reception and can be classified as analog transmission and digital communications. Analog data communication conveys voice, data, image, signal or video information using a continuous signal, which varies in amplitude, phase, or some other property. In baseband analog transmission, messages are represented by a sequence of pulses by means of a line code; in passband analog transmission, they are communicated by a limited set of continuously varying waveforms, using a digital modulation method. Passband modulation and demodulation are carried out by modem equipment. Digital transmission and digital reception are the transfer of either a digitized analog signal or a born-digital bitstream. Baseband digital transmission is regarded as comprising part of a digital signal, whereas passband transmission of digital data may also or alternatively be considered a form of digital-to-analog conversion. Data communication channels include copper wires, optical fibers, wireless communication using radio spectrum, storage media and computer buses. The data are represented as an electromagnetic signal, such as an electrical voltage, radiowave, microwave, or infrared signal. == Distinction between related subjects == Digital transmission or data transmission traditionally belongs to telecommunications and electrical engineering. Basic principles of data transmission may also be covered within the computer science or computer engineering topic of data communications, which also includes computer networking applications and communication protocols, for example, routing, switching and inter-process communication. Although the Transmission Control Protocol (TCP) involves transmission, TCP and other transport layer protocols are covered in computer networking but not discussed in a textbook or course about data transmission. In most textbooks, the term analog transmission only refers to the transmission of an analog message signal (without digitization) by means of an analog signal, either as a non-modulated baseband signal or as a passband signal using an analog modulation method such as AM or FM. It may also include analog-over-analog pulse modulated baseband signals such as pulse-width modulation. In a few books within the computer networking tradition, analog transmission also refers to passband transmission of bit-streams using digital modulation methods such as FSK, PSK and ASK. The theoretical aspects of data transmission are covered by information theory and coding theory. == Protocol layers and sub-topics == Courses and textbooks in the field of data transmission typically deal with the following OSI model protocol layers and topics: Layer 1, the physical layer: Channel coding including Digital modulation schemes Line coding schemes Forward error correction (FEC) codes Bit synchronization Multiplexing Equalization Channel models Layer 2, the data link layer: Channel access schemes, media access control (MAC) Packet mode communication and Frame synchronization Error detection and automatic repeat request (ARQ) Flow control Layer 6, the presentation layer: Source coding (digitization and data compression), and information theory. Cryptography (may occur at any layer) It is also common to deal with the cross-layer design of those three layers. == Applications and history == Data (mainly but not exclusively informational) has been sent via non-electronic (e.g. optical, acoustic, mechanical) means since the advent of communication. Analog signal data has been sent electronically since the advent of the telephone. However, the first data electromagnetic transmission applications in modern time were electrical telegraphy (1809) and teletypewriters (1906), which are both digital signals. The fundamental theoretical work in data transmission and information theory by Harry Nyquist, Ralph Hartley, Claude Shannon and others during the early 20th century, was done with these applications in mind. In the early 1960s, Paul Baran invented distributed adaptive message block switching for digital communication of voice messages using switches that were low-cost electronics. Donald Davies invented and implemented modern data communication during 1965–7, including packet switching, high-speed routers, communication protocols, hierarchical computer networks and the essence of the end-to-end principle. Baran's work did not include routers with software switches and communication protocols, nor the idea that users, rather than the network itself, would provide the reliability. Both were seminal contributions that influenced the development of computer networks. Data transmission is utilized in computers in computer buses and for communication with peripheral equipment via parallel ports and serial ports such as RS-232 (1969), FireWire (1995) and USB (1996). The principles of data transmission are also utilized in storage media for error detection and correction since 1951. The first practical method to overcome the problem of receiving data accurately by the receiver using digital code was the Barker code invented by Ronald Hugh Barker in 1952 and published in 1953. Data transmission is utilized in computer networking equipment such as modems (1940), local area network (LAN) adapters (1964), repeaters, repeater hubs, microwave links, wireless network access points (1997), etc. In telephone networks, digital communication is utilized for transferring many phone calls over the same copper cable or fiber cable by means of pulse-code modulation (PCM) in combination with time-division multiplexing (TDM) (1962). Telephone exchanges have become digital and software controlled, facilitating many value-added services. For example, the first AXE telephone exchange was presented in 1976. Digital communication to the end user using Integrated Services Digital Network (ISDN) services became available in the late 1980s. Since the end of the 1990s, broadband access techniques such as ADSL, Cable modems, fiber-to-the-building (FTTB) and fiber-to-the-home (FTTH) have become widespread to small offices and homes. The current tendency is to replace traditional telecommunication services with packet mode communication such as IP telephony and IPTV. Transmitting analog signals digitally allows for greater signal processing capability. The ability to process a communications signal means that errors caused by random processes can be detected and corrected. Digital signals can also be sampled instead of continuously monitored. The multiplexing of multiple digital signals is much simpler compared to the multiplexing of analog signals. Because of all these advantages, because of the vast demand to transmit computer data and the ability of digital communications to do so and because recent advances in wideband communication channels and solid-state electronics have allowed engineers to realize these advantages fully, digital communications have grown quickly. The digital revolution has also resulted in many digital telecommunication applications where the principles of data transmission are applied. Examples include second-generation (1991) and later cellular telephony, video conferencing, digital TV (1998), digital radio (1999), and telemetry. Data transmission, digital transmission or digital communications is the transfer of data over a point-to-point or point-to-multipoint communication channel. Examples of such channels include copper wires, optical fibers, wireless communication channels, storage media and computer buses. The data are represented as an electromagnetic signal, such as an electrical voltage, radio wave, microwave, or infrared light. While analog transmission is the transfer of a continuously varying analog signal over an analog channel, digital communication is the transfer of discrete messages over a digital or an analog channel. The messages are either represented by a sequence of pulses by means of a line code (baseband transmission) or by a limited set of continuously varying waveforms (passband transmission), using a digital modulation method. The passband modulation and corresponding demodulation (also known as detection) are carried out by modem equipment. According to the most common definition of a digital signal, both baseband and passband signals representing bit-streams are considered as digital transmission, while an alternative definition only considers the baseband signal as digital, and passband transmission of digital data as a form of digital-to-analog conversion. Data transmitted may be digital messages originating from a data source, for example, a computer or a keyboard. It may also be an analog signal, such as a phone call or a video signal, digitized into a bit-stream, for example,e using pulse-code modulation (PCM) or more advanced source coding (analog-to-digital conversion and
Web content development
Web content development is the process of researching, writing, gathering, organizing, and editing information for publication on websites. Website content may consist of prose, graphics, pictures, recordings, movies, or other digital assets that could be distributed by a hypertext transfer protocol server, and viewed by a web browser. == Web developers and content developers == When the World Wide Web began, web developers either developed online content themselves, or modified existing documents and coded them into hypertext markup language (HTML). In time, the field of website development came to encompass many technologies, so it became difficult for website developers to maintain so many different skills. Content developers are specialized website developers who have content generation skills such as graphic design, multimedia development, professional writing, and documentation. They can integrate content into new or existing websites without using information technology skills such as script language programming and database programming. Content developers or technical content developers can also be technical writers who produce technical documentation that helps people understand and use a product or service. This documentation includes online help, manuals, white papers, design specifications, developer guides, deployment guides, release notes, etc. == Search engine optimization == Content developers may also be search engine optimization specialists, or internet marketing professionals. High quality, unique content is what search engines are looking for. Content development specialists, therefore, have a very important role to play in the search engine optimization process. One issue currently plaguing the world of web content development is keyword-stuffed content which are prepared solely for the purpose of manipulating search engine rankings. The effect is that content is written to appeal to search engine (algorithms) rather than human readers. Search engine optimization specialists commonly submit content to article directories to build their website's authority on any given topic. Most article directories allow visitors to republish submitted content with the agreement that all links are maintained. This has become a method of search engine optimization for many websites today. If written according to SEO copywriting rules, the submitted content will bring benefits to the publisher (free SEO-friendly content for a webpage) as well as to the author (a hyperlink pointing to his/her website, placed on an SEO-friendly webpage). == New content types == Web content is no longer restricted to text. Search engines now index audio/visual media, including video, images, PDFs, and other elements of a web page. Website owners sometimes use content protection networks to scan for plagiarized content.
Microformat
Microformats (μF) are predefined HTML markup (like HTML classes) created to serve as descriptive and consistent metadata about elements, designating them as representing a certain type of data (such as contact information, geographic coordinates, events, products, recipes, etc.). They allow software to process the information reliably by having set classes refer to a specific type of data rather than being arbitrary. Microformats emerged around 2005 and were predominantly designed for use by search engines, web syndication and aggregators such as RSS. Google confirmed in 2020 that it still parses microformats for use in content indexing. Microformats are referenced in several W3C social web specifications, including IndieAuth and Webmention. Although the content of web pages has been capable of some "automated processing" since the inception of the web, such processing is difficult because the markup elements used to display information on the web do not describe what the information means. Microformats can bridge this gap by attaching semantics, and thereby obviating other, more complicated, methods of automated processing, such as natural language processing or screen scraping. The use, adoption and processing of microformats enables data items to be indexed, searched for, saved or cross-referenced, so that information can be reused or combined. As of 2013, microformats allow the encoding and extraction of event details, contact information, social relationships and similar information. Microformats2, abbreviated as mf2, is the updated version of microformats. Mf2 provides an easier way of interpreting HTML structured syntax and vocabularies than the earlier ways that made use of RDFa and microdata. == Background == Microformats emerged around 2005 as part of a grassroots movement to make recognizable data items (such as events, contact details or geographical locations) capable of automated processing by software, as well as directly readable by end-users. Link-based microformats emerged first. These include vote links that express opinions of the linked page, which search engines can tally into instant polls. CommerceNet, a nonprofit organization that promotes e-commerce on the Internet, has helped sponsor and promote the technology and support the microformats community in various ways. CommerceNet also helped co-found the Microformats.org community site. Neither CommerceNet nor Microformats.org operates as a standards body. The microformats community functions through an open wiki, a mailing list, and an Internet relay chat (IRC) channel. Most of the existing microformats originated at the Microformats.org wiki and the associated mailing list by a process of gathering examples of web-publishing behaviour, then codifying it. Some other microformats (such as rel=nofollow and unAPI) have been proposed, or developed, elsewhere. == Technical overview == XHTML and HTML standards allow for the embedding and encoding of semantics within the attributes of markup elements. Microformats take advantage of these standards by indicating the presence of metadata using the following attributes: class Classname rel relationship, description of the target address in an anchor-element (...) rev reverse relationship, description of the referenced document (in one case, otherwise deprecated in microformats) For example, in the text "The birds roosted at 52.48, -1.89" is a pair of numbers which may be understood, from their context, to be a set of geographic coordinates. With wrapping in spans (or other HTML elements) with specific class names (in this case geo, latitude and longitude, all part of the geo microformat specification): Software agents can recognize exactly what each value represents and can then perform a variety of tasks such as indexing, locating it on a map and exporting it to a GPS device. === Examples === In this example, the contact information is presented as follows: With hCard microformat markup, that becomes: Here, the formatted name (fn), organisation (org), telephone number (tel) and web address (url) have been identified using specific class names and the whole thing is wrapped in class="vcard", which indicates that the other classes form an hCard (short for "HTML vCard") and are not merely coincidentally named. Other, optional, hCard classes also exist. Software, such as browser plug-ins, can now extract the information, and transfer it to other applications, such as an address book. == Specific microformats == Several microformats have been developed to enable semantic markup of particular types of information. However, only hCard and hCalendar have been ratified, the others remaining as drafts: hAtom (superseded by h-entry and h-feed) – for marking up Atom feeds from within standard HTML hCalendar – for events hCard – for contact information; includes: adr – for postal addresses geo – for geographical coordinates (latitude, longitude) hMedia – for audio/video content hAudio – for audio content hNews – for news content hProduct – for products hRecipe – for recipes and foodstuffs. hReview – for reviews rel-directory – for distributed directory creation and inclusion rel-enclosure – for multimedia attachments to web pages rel-license – specification of copyright license rel-nofollow, an attempt to discourage third-party content spam (e.g. spam in blogs) rel-tag – for decentralized tagging (Folksonomy) XHTML Friends Network (XFN) – for social relationships XOXO – for lists and outlines == Uses == Using microformats within HTML code provides additional formatting and semantic data that applications can use. For example, applications such as web crawlers can collect data about online resources, or desktop applications such as e-mail clients or scheduling software can compile details. The use of microformats can also facilitate "mash ups" such as exporting all of the geographical locations on a web page into (for example) Google Maps to visualize them spatially. Several browser extensions, such as Operator for Firefox and Oomph for Internet Explorer, provide the ability to detect microformats within an HTML document. When hCard or hCalendar are involved, such browser extensions allow microformats to be exported into formats compatible with contact management and calendar utilities, such as Microsoft Outlook. When dealing with geographical coordinates, they allow the location to be sent to applications such as Google Maps. Yahoo! Query Language can be used to extract microformats from web pages. On 12 May 2009 Google announced that they would be parsing the hCard, hReview and hProduct microformats, and using them to populate search result pages. They subsequently extended this in 2010 to use hCalendar for events and hRecipe for cookery recipes. Similarly, microformats are also processed by Bing and Yahoo!. As of late 2010, these are the world's top three search engines. Microsoft said in 2006 that they needed to incorporate microformats into upcoming projects, as did other software companies. Alex Faaborg summarizes the arguments for putting the responsibility for microformat user interfaces in the web browser rather than making more complicated HTML: Only the web browser knows what applications are accessible to the user and what the user's preferences are It lowers the barrier to entry for web site developers if they only need to do the markup and not handle "appearance" or "action" issues Retains backwards compatibility with web browsers that do not support microformats The web browser presents a single point of entry from the web to the user's computer, which simplifies security issues == Evaluation == Various commentators have offered review and discussion on the design principles and practical aspects of microformats. Microformats have been compared to other approaches that seek to serve the same or similar purpose. As of 2007, there had been some criticism of one, or all, microformats. The spread and use of microformats was being advocated as of 2007. Opera Software CTO and CSS creator Håkon Wium Lie said in 2005 "We will also see a bunch of microformats being developed, and that’s how the semantic web will be built, I believe." However, in August 2008 Toby Inkster, author of the "Swignition" (formerly "Cognition") microformat parsing service, pointed out that no new microformat specifications had been published since 2005. === Design principles === Computer scientist and entrepreneur, Rohit Khare stated that reduce, reuse, and recycle is "shorthand for several design principles" that motivated the development and practices behind microformats. These aspects can be summarized as follows: Reduce: favor the simplest solutions and focus attention on specific problems; Reuse: work from experience and favor examples of current practice; Recycle: encourage modularity and the ability to embed, valid XHTML can be reused in blog posts, RSS feeds, and anywhere else you can access the web. === Accessibi
Rabbit r1
The Rabbit r1 is an artificial intelligence personal assistant device developed by the American technology startup Rabbit Inc and co-designed by Teenage Engineering. It was announced at the 2024 Consumer Electronics Show as a handheld device intended to perform digital tasks through voice commands, touch interaction, and web-based AI agents. The r1 was marketed around Rabbit's concept of a "large action model" (LAM), which the company described as software able to operate websites and services on behalf of users. The device runs rabbitOS, an operating system based on the Android Open Source Project. Its services have included AI search, image recognition, voice interaction, music playback, rideshare and food-ordering integrations, and later experimental web-agent features such as LAM Playground and teach mode. Initial reviews were largely negative, with reviewers criticizing the device's limited functionality, bugs, and unclear advantages over a smartphone. Critics also questioned Rabbit's claims after the r1 software was shown to run on an Android phone. Rabbit continued to issue software updates after launch, including rabbitOS 2 in September 2025, which introduced a redesigned card-based interface, gesture navigation, and a "creations" feature for generating small software tools and experiences on the device. Rabbit Inc was founded by Jesse Lyu Cheng. == Hardware == Display: A 2.88-inch touchscreen for interactive user input. Input: push-to-talk button to activate voice commands; scroll wheel; Gyroscope; Magnetometer; Accelerometer; GPS. Camera: 8 MP single camera, with a resolution of 3264x2448, allowing for the connected external AI to use computer vision. Audio: Equipped with a speaker and dual microphones for audio interaction. Connectivity: Supports Wi-Fi and cellular connections via a SIM card slot to access internet services. Processor: Runs on a 2.3GHz MediaTek Helio P35 processor. Memory: Contains 4GB of RAM for operational tasks. Storage: Offers 128GB of internal storage for data. Ports: Utilizes a USB-C port for charging and data connections. == Software == The Rabbit r1 runs rabbitOS, which is based on the Android Open Source Project (AOSP), specifically Android 13. Rabbit founder Jesse Lyu described rabbitOS as a "very bespoke AOSP" after reports that the r1's software could be run on a conventional Android phone. Rabbit described the r1 as using a large action model (LAM), a type of AI agent intended to perform tasks across software interfaces rather than only answer questions. At launch, the device supported a limited set of services, including AI search, vision features, music playback, and some third-party integrations. Perplexity.ai was one of the AI services used to answer user queries. In 2024, Rabbit released several software updates that added features and attempted to address early criticism of the device. In July 2024, the company launched "beta rabbit", an advanced search and conversation mode for more complex queries. In October 2024, it released LAM Playground, a web-based agent feature intended to let the r1 operate websites on behalf of users. Reviewers found the feature experimental; Android Authority reported that it could perform some navigation tasks but struggled with CAPTCHAs, loops, and unintended behavior. In November 2024, Rabbit introduced a beta "teach mode", which allowed users to demonstrate web-based tasks in the Rabbithole web portal and later ask the r1 to repeat them. The company described teach mode as experimental, and The Verge noted that Rabbit warned users that results could be unpredictable and that CAPTCHA-protected sites could cause problems. Rabbit released rabbitOS 2 in September 2025. The update redesigned the interface around a card-based layout, added additional touchscreen gestures, and introduced "creations", a feature that lets users generate simple software tools, games, and interfaces through natural-language prompts. Coverage of the update described it as a major software overhaul rather than new hardware. == Reception == === Funding === Rabbit raised $20 million in funding from Khosla Ventures, Synergis Capital and Kakao Investment in October 2023. The company announced an additional $10 million in funding in December 2023. === Sales === Following its announcement at the 2024 Consumer Electronics Show, 130,000 units were sold. On August 13, 2024, Rabbit announced that sales of r1 had expanded to the entire European Union (except Malta) and United Kingdom. On August 21, 2024, sales of r1 expanded to Singapore. === Reviews === The r1 was met with strong criticism immediately after Rabbit began shipping the device. Some reviews questioned what the device was able to do that a smartphone could not, while comparing it to the similar Humane Ai Pin. YouTuber Marques Brownlee called the device "barely reviewable". Android Authority's Mishaal Rahman managed to install Rabbit r1's software on a Pixel 6a smartphone, after a tipster shared an APK file. The Verge echoed the claims made by Rahman. In response, Lyu published statements confirming its use of Android, but denying that the r1 is an Android app. Mashable called its Vision features impressive, but said that "these praise-worthy features are overshadowed by buggy performance". Ars Technica wrote a blog post claiming "the company is blocking access from bootleg APKs". TechCrunch gave a slightly more positive review, calling the device a "fun peep at a possible future", but could not "advise anyone to buy one now." Shortly after the launch of r1, Rabbit began a weekly cadence of software updates to address much of the criticism from the early reviews, including "battery and GPS performance, time zone selection, and more". Digital Trends said the Magic Camera feature "takes the most mundane, ordinary, and badly composed photos and makes something fun and eye-catching from them." Mashable said the "beta rabbit" feature "makes Rabbit R1 more conversational and intelligent". Later coverage noted that Rabbit continued to update the r1 after its poorly received launch. The Verge reported in September 2024 that about 5,000 of roughly 100,000 purchasers were using the device at any given moment, citing Lyu, and described the product as having launched before it was ready. In 2025, coverage of rabbitOS 2 described the update as an attempt to reset the device's software experience after the criticism of its original release. == Controversies == === GAMA project === Rabbit Inc has garnered attention due to allegations surrounding its funding and the company's past projects. The company came under scrutiny when Stephen Findeisen, known as Coffeezilla on YouTube, published a video in May 2024, alleging that Rabbit Incorporation was "built on a scam". Rabbit Incorporation, initially named Cyber Manufacturing Co, rebranded just two months before launching the Rabbit R1. The company, under its former name, raised $6 million in November 2021 for a project called GAMA, described as a "Next Generation NFT Project." Jesse Lyu, the CEO of Rabbit Incorporation, referred to GAMA as a "fun little project." Coffeezilla, who investigates influencer scams, highlighted old Clubhouse recordings of Jesse Lyu discussing the GAMA project. In these recordings, Lyu emphasized the substantial funding behind GAMA and its potential to be a revolutionary, carbon-negative cryptocurrency. Coffeezilla questioned the whereabouts of the funds raised for GAMA, estimating that approximately $1 million in refunds to investors remained unresolved. He suggested that the rebranding to Rabbit Incorporation and the shift to developing the Rabbit R1 were attempts to divert from the GAMA project's issues. In response to Coffeezilla's inquiries, Rabbit Incorporation stated that the $6 million raised was used for the GAMA project. The company said that NFTs cannot be refunded unless the owner agrees to "burn" them on the blockchain. Rabbit Incorporation also said that the GAMA project was open-sourced and returned to the community, aligning with community feedback. They also mentioned that efforts to buy back NFTs were made to counteract malicious trading and maintain market stability. === Security === In June 2024, Engadget reported that the Rabbitude team, a community reverse engineering project, had gained access to the r1's codebase revealing that r1's software contained several hardcoded API keys in its code for ElevenLabs, Microsoft Azure, Yelp, and Google Maps, potentially allowing unauthorized access to r1 responses, including those containing the users' personal information. For a short time, Rabbit immediately began revoking and rotating those secrets and confirmed that the code was leaked by an employee who had "been terminated and remains under investigation". In July 2024, the company revealed that all user chats and device pairing data were logged on the r1 with no ability to delete them. This meant that lost or stolen devices could be used to extract user
Mike Little
Mike Little (born 12 May 1962) is an English web developer and writer. He is the co-founder of the free and open source web publishing software WordPress. == Biography == Mike Little was born in Manchester, England in 1962 to a Nigerian father, who was a mathematics lecturer and musician, and an English mother who worked as a primary school teacher. Little was placed into foster care when he was four months of age, and was later adopted by the same family. He grew up on a council estate in Brinnington, Stockport, and was educated at Stockport School. In 2003, Little and Matt Mullenweg started working on a project in which they built on b2/cafelog and later named it WordPress, releasing the first version on 27 May 2003. Little states that, despite not being invited to join his co-founder's for-profit business Automattic, he and Mullenweg remain on good terms. He clarified: "I don’t want it to sound like he cheated me out of something or ripped me off in some way. He didn’t." In June 2013, Little was awarded the SAScon's "Outstanding Contribution to Digital" award for his part in co-founding and developing WordPress. Little has been described as "modest" and living in "virtual anonymity". He has one daughter. He identifies as a follower of Stoicism and a humanist, and in 2021, he became a patron of charity Humanists UK.