"Darwin among the Machines" is a letter to the editor published in The Press newspaper on 13 June 1863 in Christchurch, New Zealand. The title, which was chosen by the author, references the work of Charles Darwin. Written by Samuel Butler but signed Cellarius, the letter raised the possibility that machines were a kind of "mechanical life" undergoing constant evolution, and that eventually machines might supplant humans as the dominant species. == Book of the Machines == Butler developed this and subsequent articles into The Book of the Machines, three chapters of Erewhon, published anonymously in 1872. The Erewhonian society Butler envisioned had long ago undergone a revolution that destroyed most mechanical inventions. The narrator of the story finds a book that details the reasons for this revolution, which he translates for the reader. Despite the initial popularity of Erewhon, Butler commented in the preface to the second edition that reviewers had "in some cases been inclined to treat the chapters on Machines as an attempt to reduce Mr. Darwin's theory to an absurdity." He protested that "few things would be more distasteful to me than any attempt to laugh at Mr. Darwin", but also added "I am surprised, however, that the book at which such an example of the specious misuse of analogy would seem most naturally levelled should have occurred to no reviewer; neither shall I mention the name of the book here, though I should fancy that the hint given will suffice", which may suggest that the chapter on Machines was in fact a satire intended to illustrate the "specious misuse of analogy", even if the target was not Darwin; Butler, fearing that he had offended Darwin, wrote him a letter explaining that the actual target was Joseph Butler's 1736 The Analogy of Religion, Natural and Revealed, to the Constitution and Course of Nature. The Victorian scholar Herbert Sussman has suggested that although Butler's exploration of machine evolution was intended to be whimsical, he may also have been genuinely interested in the notion that living organisms are a type of mechanism and was exploring this notion with his writings on machines, while the philosopher Louis Flaccus called it "a mixture of fun, satire, and thoughtful speculation." == Evolution of Global Intelligence == George Dyson applies Butler's original premise to the artificial life and intelligence of Alan Turing in Darwin Among the Machines: The Evolution of Global Intelligence (1998) ISBN 0-7382-0030-1, to suggest that the internet is a living, sentient being. Dyson's main claim is that the evolution of a conscious mind from today's technology is inevitable. It is not clear whether this will be a single mind or multiple minds, how smart that mind would be, and even if we will be able to communicate with it. He also clearly suggests that there are forms of intelligence on Earth that we are currently unable to understand. From the book: "What mind, if any, will become apprehensive of the great coiling of ideas now under way is not a meaningless question, but it is still too early in the game to expect an answer that is meaningful to us."
Gemini Enterprise Agent Platform
Gemini Enterprise Agent Platform (formerly known as Vertex AI) is a managed machine learning (ML) and artificial intelligence (AI) platform developed by Google Cloud. It provides a unified environment for building, training, deploying, and scaling ML models and generative AI applications. The platform integrates tools for the full ML lifecycle, including data preparation, model training, evaluation, deployment, and monitoring, under a single API and user interface. Vertex AI was announced at Google I/O and released as a generally available product on May 18, 2021. At launch, Google described Vertex AI as unifying its AutoML offerings with its prior Cloud AI Platform capabilities, and as adding operational features intended to help teams move models from experimentation into production use. On April 22, 2026, Google announced Gemini Enterprise Agent Platform as the replacement evolution of Vertex AI. == History == Google Cloud announced the general availability of Vertex AI on May 18, 2021, at the Google I/O developer conference. The platform was designed to consolidate Google Cloud's previously separate ML offerings, including AutoML and the legacy AI Platform, into a single system. At launch, Google claimed that Vertex AI required roughly 80% fewer lines of code to train a model compared to competing platforms. In June 2023, Google made generative AI support in Vertex AI generally available, giving developers access to foundation models including PaLM 2, Imagen, and Codey through the platform's Model Garden and the newly launched Generative AI Studio. At the time of this launch, Model Garden included over 60 models from Google and its partners. In August 2023, at the Google Cloud Next conference, Google announced further updates to Vertex AI, including the addition of third-party models such as Claude 2 from Anthropic and Llama 2 from Meta to the Model Garden, as well as new tools called Vertex AI Extensions for connecting models to APIs for real-time data retrieval. At the same event, Vertex AI Search and Conversation were made generally available, providing enterprise search and chatbot capabilities powered by foundation models. In April 2024, at Google Cloud Next, the company introduced Vertex AI Agent Builder, a no-code tool for creating AI-powered conversational agents built on top of Gemini large language models. This brought together the existing Vertex AI Search and Conversation products with new developer tools for building generative AI experiences. == Features == === Model training === Vertex AI supports both AutoML, which enables code-free model training on tabular, image, text, or video data, and custom training, which gives users full control over the ML framework, training code, and hyperparameter tuning. The platform provides serverless training as well as dedicated training clusters with GPU and TPU accelerators. Vertex AI Vizier handles automatic hyperparameter tuning, and Vertex AI Experiments allows comparison and tracking of training runs. === Model Garden === The Vertex AI Model Garden is a curated catalog of over 200 enterprise-ready models, including Google's own foundation models (such as Gemini, Imagen, and Veo), third-party models (such as Anthropic's Claude and Mistral AI models), and popular open-source models (such as Llama and Gemma). Models are accessible as fully managed model-as-a-service APIs. === Pipelines (workflow orchestration) === Vertex AI Pipelines provides managed orchestration of ML workflows and supports pipelines built with the Kubeflow Pipelines SDK, among other options described in Google Cloud documentation. === Vertex AI Studio === Vertex AI Studio provides tools for prompt design, testing, and model management, allowing developers to prototype and build generative AI applications using natural language, code, images, or video. === Agent Builder and Agent Engine === Vertex AI Agent Builder is a suite of products for building, deploying, and governing AI agents in production environments. It supports development with the open-source Agent Development Kit (ADK) and other frameworks. Vertex AI Agent Engine provides the underlying infrastructure for deploying and scaling agents, with support for enterprise security features including HIPAA compliance, customer-managed encryption keys (CMEK), and VPC Service Controls. === Generative AI tooling and model access === Google markets Vertex AI as providing access to Google foundation models (including the Gemini family) and developer tools such as Vertex AI Studio, along with a model catalog that includes Google and selected open source models (marketed as "Model Garden"). Google has also offered products within Vertex AI aimed at building generative search and conversational applications, including offerings named "Vertex AI Search" and "Vertex AI Conversation" as reported in 2023 coverage of platform updates. === MLOps tools === The platform includes a range of MLOps capabilities: Vertex AI Pipelines for orchestrating and automating ML workflows as reusable pipelines. Vertex AI Feature Store for serving, sharing, and reusing ML features across projects. Vertex AI Model Registry for storing, versioning, and managing trained models. Vertex AI Model Monitoring for detecting training-serving skew and inference drift in deployed models. Vertex Explainable AI for interpreting model predictions. Vertex AI Workbench for managed JupyterLab notebook environments integrated with Google Cloud Storage and BigQuery. == Industry recognition == Google was named a Leader for the fifth consecutive year in the 2024 Gartner Magic Quadrant for Cloud AI Developer Services, a recognition that encompasses Vertex AI and its related offerings. Google was also recognized as a Leader in the 2024 Gartner Magic Quadrant for Data Science and Machine Learning Platforms and was named a Leader in the Forrester Wave for AI/ML Platforms, Q3 2024. In October 2025, Google was also named a Leader in the 2025 IDC (International Data Corporation) MarketScape for Worldwide GenAI Life-Cycle Foundation Model Software. == Pricing == Vertex AI uses a pay-as-you-go pricing model, with costs determined by the specific services consumed, including model training, prediction serving, and data storage. For generative AI tasks, pricing is based on a per-token model, with rates varying depending on the specific model used and whether tokens are input or output. Google offers a free tier for new users, which includes limited custom training hours and online prediction usage, along with an introductory US$300 in Google Cloud credits valid for 90 days. == Adoption == In the year following its 2021 launch, Google reported that usage of Vertex AI and BigQuery had driven 2.5 times more machine learning predictions compared to the prior year, and that active customers of Vertex AI Workbench had grown 25-fold over a six-month period. Early enterprise adopters included Ford, Wayfair, and Seagate, among others. Wayfair reported that it was able to run large model training jobs 5 to 10 times faster using the platform.
Kimchi (software)
Kimchi is a web management tool to manage Kernel-based Virtual Machine (KVM) infrastructure. Developed with HTML5, Kimchi is developed to intuitively manage KVM guests, create storage pools, manage network interfaces (bridges, VLANs, NAT), and perform other related tasks. The name is an extended acronym for KVM infrastructure management. It is an Apache-licensed project hosted on GitHub, and incubated by oVirt.org.
Digital signage
Digital signage is a segment of electronic signage that uses digital display technologies to present multimedia content in both public and private environments. Content may include video, images, text, or interactive media and is typically displayed for purposes such as advertising, information dissemination, branding, or entertainment. Digital signage systems can be either networked or standalone. Networked systems are managed through centralized content management systems (CMS), often cloud-based, enabling remote updates, scheduling, real-time data integration, and dynamic content delivery. These systems may also incorporate audience analytics, IoT sensors, or AI-driven personalization. Standalone systems, by contrast, operate without a network connection. They rely on local media playback via USB drives, SD cards, or internal storage. These solutions are simpler and suitable for locations where connectivity is limited or content changes infrequently. == Applications of digital signage == Digital signage is widely used in transportation hubs, retail stores, restaurants, corporate buildings, hotels, educational institutions, healthcare facilities, and public spaces. One prominent application of digital signage is Digital Out-of-Home (DOOH) advertising, which leverages digital signage displays in public spaces to deliver targeted advertisements to people outside of their homes. DOOH has become a significant segment of digital signage, providing advertisers with a dynamic and contextually relevant way to engage with audiences. == Components == === Hardware components === Digital signage hardware includes the physical equipment used to show multimedia content in public and private spaces. ==== Display devices ==== Display devices are the most prominent components of a digital signage system, serving as the primary medium for presenting content. Display devices come in various technologies, such as LCD, LED, and OLED formats, each offering different advantages in terms of clarity, color reproduction, and energy efficiency. In addition to flat-panel displays, projectors are also commonly used in digital signage, particularly in large-scale settings. Projectors can cast large-format visuals onto walls, screens, or other surfaces, providing flexibility in display size and positioning. Screen sizes vary widely to suit different applications. Smaller panels are often used in kiosks and point-of-sale systems, while larger displays, such as video walls and projection surfaces, are deployed in venues like stadiums, auditoriums, and other public spaces. Many digital signage displays are also equipped with touchscreen capabilities, allowing for interactive applications. These interactive displays are commonly used in information kiosks, wayfinding systems, and self-service applications. ==== Playback devices ==== Playback devices are specialized hardware components that manage the storage, processing, and transmission of multimedia content to digital signage displays and projectors. They serve as the crucial link between the content management system (CMS) and the visual output, ensuring seamless playback of static images, video files, animated graphics, and real-time content, such as news feeds. Playback devices can be standalone units or integrated into display hardware using System-on-Chip (SoC) technology. The latter reduces hardware complexity and installation time, making the system more efficient. These devices support remote or local content updates, allowing digital signage operators to manage networks effectively. Content can be updated via cloud-based platforms for centralized control or through direct interfaces on-site, depending on the system's configuration and deployment requirements. ==== Mounting systems ==== Mounting systems provide structural support for digital signage displays, enabling deployment across diverse environments. Typical configurations include wall mounts, ceiling mounts, and floor stands each engineered to meet specific spatial and functional requirements. === Software components === Digital signage software is responsible for content creation, scheduling, and management. It enables users to manage and distribute content to one or more playback devices. ==== Software compatibility ==== Digital signage software supports various operating systems, including Android, Windows, Linux, iOS, tvOS, webOS, Tizen, ChromeOS, macOS, and others. This allows customers to choose the hardware and software solution that best suits their digital signage needs. == Interactivity == Interactivity in digital signage allows users to interact directly with displays using input methods like touch, gestures, voice, or proximity sensors. This feature enables real-time responses and personalized content, improving the user experience. Interactive digital signage is commonly used in places like retail, transportation, education, and public spaces to create engaging and informative interactions. Additionally, self-service kiosks are often integrated into interactive signage solutions, allowing users to perform tasks such as ordering products, checking in for flights, accessing information, or making payments. These kiosks empower users to complete transactions or obtain services independently, improving efficiency and convenience in high-traffic locations. == Audience measurement and context-aware content adaptation == === Audience measurement === Cameras can be integrated into digital signage systems to enable audience measurement. They are used to detect and count viewers, estimate demographics such as age and gender, measure dwell time and attention, and sometimes analyze emotional reactions using computer vision techniques. This process is valuable for understanding audience behavior and refining business strategies. Privacy concerns are addressed by anonymizing collected data and avoiding the storage of personally identifiable information. === Context-aware digital signage === Context-aware digital signage refers to systems that adjust content based on environmental or audience data. The infrastructure supporting context awareness, including sensors and analytics systems, also facilitates the collection of audience insights. While these insights may be primarily used for reporting, optimization, or planning future campaigns rather than immediate content adjustments, they play a crucial role in the overall context-aware ecosystem. ==== Contextual information ==== Contextual information in the realm of context-aware digital signage refers to data about the environment, audience, and other factors that influence how digital signage content is displayed. This information helps the system to deliver more relevant, timely, and personalized content to its audience. Contextual information can include, but is not limited to: Audience demographics — this can involve detecting the age, gender, or even emotional state of viewers through cameras or sensors. It helps tailor content to specific audience segments, improving engagement. Time and weather — the system may adjust content based on the time of day or current weather conditions. For example, weather-appropriate content (like a raincoat ad on a rainy day) or time-specific content (like dinner menu promotions in the evening) can be shown. Emergency information — in situations of emergency, systems can prioritize displaying urgent notifications such as fire alerts, disaster warnings, or evacuation instructions. This can be crucial for public safety in crowded environments or densely populated areas. The system may adapt content in real-time to inform and guide individuals to safety, offering location-specific instructions or emergency service contacts. == Challenges == === Display blindness === Digital signage in public spaces has been found to lose visibility, significantly diminishing its ability to capture attention. This issue, known as "Display Blindness", was identified by Müller et al. and refers to the phenomenon where digital advertisements are largely overlooked by passersby. Observations indicate that many of these advertisements fail to resonate with their audience, often being irrelevant or unengaging, which leads to passive reception and reduced interaction. == Comparison with print signage == Digital signage and traditional print signage serve similar purposes by delivering visual information to a target audience, but they differ significantly in terms of flexibility, cost, maintenance, and environmental impact. Digital signage is advantageous in low-light or nighttime environments, where its internal illumination ensures visibility without the need for external lighting, unlike printed signs, which may require additional fixtures to be seen after dark. === Content and flexibility === Digital signage allows for dynamic and real-time content updates, often controlled remotely through content management systems. This makes it well-suited for environments where information chan
The Holocaust and social media
The representation of the Holocaust on social media has been a subject of scholarly inquiry and media attention. == Selfies at Holocaust memorial sites == Some visitors take selfies at Holocaust memorials, which has been the subject of controversy. In 2018, Rhian Sugden, a British model, received criticism after posting a selfie at the Memorial to the Murdered Jews of Europe in Berlin with the caption "ET phone home". She later removed the caption, but defended taking the photograph. Other celebrities have also been criticised for photographs at the Berlin memorial, including Indian actress Priyanka Chopra and US politician Pete Buttigieg, whose husband posted a photograph of him at the memorial on a personal social media account. The Israeli artist and satirist Shahak Shapira set up the website yolocaust.de in 2017 to expose people who take inappropriate selfies at the Holocaust memorial in Berlin. Shapira went through thousands of selfies posted to social media sites such as Facebook, Instagram, Tinder, and Grindr, choosing the twelve that he found most offensive. When the images were moused over, the website replaces the memorial backdrop with black and white images of Nazi victims. "Yolocaust" is a portmanteau of "Holocaust" and YOLO, an acronym for "you only live once". The website went viral, receiving 1.2 million views in the first 24 hours after its launch. Shapira honored requests to take down all of the photographs, which he had used without permission, and the website remains with only a textual documentation of the project. In an analysis of comments by Internet users on the project, Christoph Bareither estimated that 75% were positive. However, the memorial's architect, Peter Eisenman, criticized the website. In his 2018 book Postcards from Auschwitz, Grinnell professor Daniel P. Reynolds defends the practice of selfie-taking at Holocaust sites. In 2019, the Auschwitz-Birkenau State Museum requested that visitors not take inappropriate selfies, although the museum's staff acknowledged that other visitors take selfies in a thoughtful and respectful manner, which they did not criticize. In an academic paper, Gemma Commane and Rebekah Potton analyze the use of Instagram to share tourist photographs at Holocaust sites and conclude that "Instagram encourages conversation and empathy, keeping the Holocaust visible in youth discourses". According to their analysis, most images are tagged with respectful hashtags such as #tragic, #remembrance, and #sadness. The Auschwitz museum has an official Instagram account, auschwitzmemorial, which it uses to share selected appropriate Instagram posts. However, the image feed for the hashtag "Auschwitz" includes potentially offensive images such as an image of "Nazi Vs. Jews #beerpong". This image, according to the authors, expresses "mockery and contempt" for Holocaust victims. They also document offensive memes using images of Holocaust atrocities and shared on Instagram. Some social media users post in order to criticize what they see as inappropriate behavior at Holocaust sites, with one commenting, "Taking photos posing next to razor wire, selfies with victim's hair in the background, and even group shots in front of the crematoria had to be seen to be believed." == Assessment of tourism == Social media posts have been used by researchers to analyze the phenomenon of Holocaust-related tourism. == Social media groups == People have created groups on Facebook to discuss issues related to the Holocaust. One paper analyses two such groups, "The Holocaust and My Family" and "The Descendants of the Victims and Survivors of the Holocaust" in which people engage in collective trauma processing. == Eva.stories == In 2019, Israeli high-tech entrepreneur Mati Kochavi created a fictitious Instagram account for Eva Heyman, a Hungarian-Jewish girl who was murdered in Auschwitz concentration camp. The project met with mixed reception. Israeli prime minister Benjamin Netanyahu praised the project, saying that it "exposes the immense tragedy of our people through the story of one girl". == Holocaust denial == The issue of Holocaust denial on social media has also attracted attention. In October 2020, Facebook reversed its policy and banned Holocaust denial from the platform. Founder Mark Zuckerberg had previously argued that such content should not be banned on freedom of speech grounds.
Sketchpad
Sketchpad (a.k.a. Robot Draftsman) is a computer program written by Ivan Sutherland in 1963 in the course of his PhD thesis, for which he received the Turing Award in 1988, and the Kyoto Prize in 2012. It pioneered human–computer interaction (HCI), and is considered the ancestor of modern computer-aided design (CAD) programs and as a major breakthrough in the development of computer graphics in general. For example, Sketchpad inspired the graphical user interface (GUI) and object-oriented programming. Using the program, Sutherland showed that computer graphics could be used for both artistic and technical purposes and for demonstrating a novel method of human–computer interaction. == History == See History of the graphical user interface for a more detailed discussion of GUI development. == Software == Sketchpad was the earliest program ever to use a complete graphical user interface. The clever way the program organizes its geometric data pioneered the use of master (objects) and occurrences (instances) in computing and pointed forward to object-oriented programming. The main idea was to have master drawings which can be instantiated into many duplicates. When a master drawing is changed, then all instances change also. This was the first known form of an entity component system: for example instead of encapsulating points inside of a line object, the points are stored in a ring buffer as described in pages 48 to 52 of the paper, and the line only points to them. This allowed moving one point to alter all the shapes that use it in a single operation. The structures in Sketchpad were also able to store pointers to functions, to achieve a different behavior depending on the kind of object. In figure 3.8 of the paper, the "instances generic block" stores several "subroutine entries" which are pointers to functions: "display", "howbig" etc. This was an early form of virtual functions. Geometric constraints was another major invention in Sketchpad, letting a user easily constrain geometric properties in the drawing: for instance, the length of a line or the angle between two lines could be fixed. As a trade magazine said, clearly Sutherland "broke new ground in 3D computer modeling and visual simulation, the basis for computer graphics and CAD/CAM". Very few programs can be called precedents for his achievements. Patrick J. Hanratty is sometimes called the "father of CAD/CAM" and wrote PRONTO, a numerical control language at General Electric in 1957, and wrote CAD software while working for General Motors beginning in 1961. Sutherland wrote in his thesis that Bolt, Beranek and Newman had a "similar program" and T-Square was developed by Peter Samson and one or more fellow MIT students in 1962, both for the PDP-1. The Computer History Museum holds program listings for Sketchpad. == Hardware == Sketchpad ran on the MIT Lincoln Laboratory TX-2 (1958) computer at the Massachusetts Institute of Technology (MIT), which had 64k of 36-bit words. The user drew on the computer monitor screen with the recently invented light pen, which relayed information on its position by computing at what time the light from the scanning cathode-ray tube screen is detected. To configure the initial position of the light pen, the word INK was displayed on the screen, which, upon tapping, initialised the program with a white cross to continue keeping track of the pen's movement relative to its prior position. Of the 36 bits available to store each display spot in the display file, 20 gave the coordinates of that spot for the display system and the remaining 16 gave the address of the n-component element responsible for adding that spot to display. The TX-2 was an experimental machine and the hardware changed often (on Wednesdays, according to Sutherland). By 1975, the light pen and the cathode-ray tube with which it had been used had been removed. == Publications == The Sketchpad program was part and parcel of Sutherland's Ph.D. thesis at MIT and peripherally related to the Computer-Aided Design project at that time. Sketchpad: A Man-Machine Graphical Communication System.
Digital goods
Digital goods or e-goods are intangible goods that exist in digital form. Examples are Wikipedia articles; digital media, such as e-books, downloadable music, internet radio, internet television and streaming media; fonts, logos, photos and graphics; digital subscriptions; online ads (as purchased by the advertiser); internet coupons; electronic tickets; electronically treated documentation in many different fields; downloadable software (Digital Distribution) and mobile apps; cloud-based applications and online games; virtual goods used within the virtual economies of online games and communities; community access; workbooks; worksheets; planners; e-learning (online courses); webinars, video tutorials, blog posts; cards; patterns; website themes and templates. == Legal concerns about digital goods == Special legal concerns regarding digital goods include copyright infringement and taxation. Also the question of the ownership (versus licensed use or service only) of purely digital goods is not finally resolved. For instance, the software installers of the digital software distributor gog.com are technically independent to the account but are still subject to the EULA, where a "licensed, not sold" formulation is used. Therefore, it is not clear if the software can be legally used after a hypothetical loss of the account; a question which was also raised before in practice for the similar service Steam. In July 2012, the European Court of Justice ruled in the case UsedSoft GMbH v. Oracle International Corp. that the sale of a software product, either through a physical support or download, constituted a transfer of ownership in EU law, thus the first sale doctrine applies; the ruling thereby breaks the "licensed, not sold" legal theory, but leaves open numerous questions. Therefore, it is also permissible to resell software licenses even if the digital good has been downloaded directly from the Internet, as the first-sale doctrine applied whenever software was originally sold to a customer for an unlimited amount of time, thus prohibiting any software maker from preventing the resale of their software by any of their legitimate owners. The court requires that the previous owner must no longer be able to use the licensed software after the resale, but finds that the practical difficulties in enforcing this clause should not be an obstacle to authorizing resale, as they are also present for software which can be installed from physical supports, where the first-sale doctrine is in force. In several cases, content providers have faced criticism for revoking access to digital goods due to expired licenses or the discontinuation of a product, such as ebooks (which resulted in a lawsuit against Amazon.com, Inc.), digital video (with Sony Interactive Entertainment revoking access to purchased StudioCanal content from its now-defunct PlayStation video store; a similar move involving Warner Bros. Discovery content was averted by an updated license agreement), and video games (such as Ubisoft discontinuing and revoking access to its game The Crew without providing refunds or the ability to redownload the game) In September 2024, the U.S. state of California implemented a consumer protection law that prohibits the use of terms such as "buy" or "purchase" during transactions involving digital goods if there is no way to obtain the purchases in a manner that cannot be revoked by the seller (such as allowing it to be downloaded for permanent, offline access), and requires a disclaimer to be displayed to the customer at the time of purchase.