AI Generator Letter

AI Generator Letter — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Chatbot

    Chatbot

    A chatbot (originally chatterbot) is a software application or web interface designed to converse through text or speech. Modern chatbots are typically online and use generative artificial intelligence systems that are capable of maintaining a conversation with a user in natural language and simulating the way a human would behave as a conversational partner. Such chatbots often use deep learning and natural language processing. Simpler chatbots have existed for decades. Chatbots have gained popularity during the AI boom of the 2020s, with the releases of generative AI chatbots such as ChatGPT, Gemini, Claude, and Grok. These chatbots typically use fine-tuned large language models to generate text. A major area where chatbots have long been used is customer service and support, with various sorts of virtual assistants. == History == === Turing test === In 1950, Alan Turing published an article entitled "Computing Machinery and Intelligence" in which he proposed what is now called the Turing test as a criterion of intelligence. This criterion depends on the ability of a computer program to impersonate a human in a real-time written conversation with a human judge, to the extent that the judge is incapable of reliably distinguishing, on the basis of the conversational content alone, between the program and a real human. === Early chatbots === Joseph Weizenbaum's program ELIZA was first published in 1966. Weizenbaum did not claim that ELIZA was genuinely intelligent, and the introduction to his paper presented it more as a debunking exercise:In artificial intelligence, machines are made to behave in wondrous ways, often sufficient to dazzle even the most experienced observer. But once a particular program is unmasked, once its inner workings are explained, its magic crumbles away; it stands revealed as a mere collection of procedures. The observer says to himself "I could have written that". With that thought, he moves the program in question from the shelf marked "intelligent", to that reserved for curios. The object of this paper is to cause just such a re-evaluation of the program about to be "explained". Few programs ever needed it more. ELIZA's key method of operation involves the recognition of clue words or phrases in the input, and the output of the corresponding pre-prepared or pre-programmed responses that can move the conversation forward in an apparently meaningful way (e.g. by responding to any input that contains the word 'MOTHER' with 'TELL ME MORE ABOUT YOUR FAMILY'). Thus an illusion of understanding is generated, even though the processing involved has been merely superficial. ELIZA showed that such an illusion is surprisingly easy to generate because human judges are ready to give the benefit of the doubt when conversational responses are capable of being interpreted as "intelligent". Following ELIZA, psychiatrist Kenneth Colby developed PARRY in 1972. From 1978 to some time after 1983, the CYRUS project led by Janet Kolodner constructed a chatbot simulating Cyrus Vance (57th United States Secretary of State). It used case-based reasoning, and updated its database daily by parsing wire news from United Press International. The program was unable to process the news items subsequent to the surprise resignation of Cyrus Vance in April 1980, and the team constructed another chatbot simulating his successor, Edmund Muskie. In 1984, an interactive version of the program Racter was released which acted as a chatbot. A.L.I.C.E. was released in 1995. This uses a markup language called AIML, which is specific to its function as a conversational agent, and has since been adopted by various other developers of, so-called, Alicebots. A.L.I.C.E. is a weak AI without any reasoning capabilities. It is based on a similar pattern matching technique as ELIZA in 1966. This is not strong AI, which would require sapience and logical reasoning abilities. Jabberwacky, released in 1997, learns new responses and context based on real-time user interactions, rather than being driven from a static database. Chatbot competitions focus on the Turing test or more specific goals. Two such annual contests are the Loebner Prize and The Chatterbox Challenge (the latter has been offline since 2015, however, materials can still be found from web archives). Pre-dating the current generation of large language models, Gavagai, a Swedish language technology startup, created a Twitter-based bot in 2015 and DBpedia created a chatbot during the 2017 Google Summer of Code that communicated through Facebook Messenger. === Modern chatbots based on large language models === Modern chatbots like ChatGPT are often based on foundational large language models called generative pre-trained transformers (GPT). They are based on a deep learning architecture called the transformer, which contains artificial neural networks. They generate text after being trained on a large text corpus, and have emergent abilities that they are not specifically trained for. Chatbots integrated into apps and websites can call image-generation models or search the web. Some platforms also enable users to interact with conversational interfaces directly through web-based chat environments, allowing real-time assistance, content generation, and task automation without requiring software installation. == Application == === Messaging apps === Many companies' chatbots run on messaging apps or simply via SMS. They are used for B2C customer service, sales and marketing. In 2016, Facebook Messenger allowed developers to place chatbots on their platform. There were 30,000 bots created for Messenger in the first six months, rising to 100,000 by September 2017. Since September 2017, this has also been as part of a pilot program on WhatsApp. Airlines KLM and Aeroméxico both announced their participation in the testing; both airlines had previously launched customer services on the Facebook Messenger platform. The bots usually appear as one of the user's contacts, but can sometimes act as participants in a group chat. Many banks, insurers, media companies, e-commerce companies, airlines, hotel chains, retailers, health care providers, government entities, and restaurant chains have used chatbots to answer simple questions, increase customer engagement, for promotion, and to offer additional ways to order from them. Chatbots are also used in market research to collect short survey responses. A 2017 study showed 4% of companies used chatbots. In a 2016 study, 80% of businesses said they intended to have one by 2020. ==== As part of company apps and websites ==== Previous generations of chatbots were present on company websites, e.g. Ask Jenn from Alaska Airlines which debuted in 2008 or Expedia's virtual customer service agent which launched in 2011. The newer generation of chatbots includes IBM Watson-powered "Rocky", introduced in February 2017 by the New York City-based e-commerce company Rare Carat to provide information to prospective diamond buyers. ==== Chatbot sequences ==== Used by marketers to script sequences of messages, very similar to an autoresponder sequence. Such sequences can be triggered by user opt-in or the use of keywords within user interactions. After a trigger occurs a sequence of messages is delivered until the next anticipated user response. Each user response is used in the decision tree to help the chatbot navigate the response sequences to deliver the correct response message. === Company internal platforms === Companies have used chatbots for customer support, human resources, or in Internet-of-Things (IoT) projects. Overstock.com, for one, has reportedly launched a chatbot named Mila to attempt to automate certain processes when customer service employees request sick leave. Other large companies such as Lloyds Banking Group, Royal Bank of Scotland, Renault and Citroën are now using chatbots instead of call centres with humans to provide a first point of contact. In large companies, like in hospitals and aviation organizations, chatbots are also used to share information within organizations, and to assist and replace service desks. === Customer service === Chatbots have been proposed as a replacement for customer service departments. In 2026, The Financial Times reported on agentic chatbots that could do shopping for customers once given instructions. In 2016, Russia-based Tochka Bank launched a chatbot on Facebook for a range of financial services, including a possibility of making payments. In July 2016, Barclays Africa also launched a Facebook chatbot. === Healthcare === Chatbots are also appearing in the healthcare industry. A study suggested that physicians in the United States believed that chatbots would be most beneficial for scheduling doctor appointments, locating health clinics, or providing medication information. A 2025 review found that participants often rated chatbot responses as more empathic than those from clinicians. In 2020, WhatsApp worked with th

    Read more →
  • Verge3D

    Verge3D

    Verge3D is a real-time renderer and a toolkit used for creating interactive 3D experiences running on websites. == Overview == Verge3D enables users to convert content from 3D modelling tools (Blender, 3ds Max, and Maya are currently supported) to view in a web browser. Verge3D was created by the same core group of software engineers that previously created the Blend4Web framework. == Features == Verge3D uses WebGL for rendering. It incorporates components of the Three.js library and exposes its API to application developers. Puzzles Application functionality can be added via JavaScript, either by writing code directly or by using Puzzles, Verge3D’s visual programming environment based on Google Blockly. Puzzles is aimed primarily at non-programmers allowing quick creation of interactive scenarios in a drag-and-drop fashion. App Manager and web publishing App Manager is a lightweight web-based tool for creating, managing and publishing Verge3D projects, running on top of the local development server. Verge3D Network service integrated in the App Manager allows for publishing Verge3D applications via Amazon S3 and EC2 cloud services. PBR For purposes of authoring materials, a glTF 2.0-compliant physically based rendering pipeline is offered alongside the standard shader-based approach. PBR textures can be authored using external texturing software such as Substance Painter for which Verge3D offers the corresponding export preset. Besides the glTF 2.0 model, Verge3D supports physical materials of 3ds Max and Maya (with Autodesk Arnold as reference), and Blender's real-time Eevee materials. glTF and DCC software integration Verge3D integrates directly with Blender, 3ds Max, and Maya, enabling users to create 3D geometry, materials, and animations inside the software, then export them in the JSON-based glTF format. The Sneak Peek feature allows for exporting and viewing scenes from the DCC tool environment. Facebook 3D posts For Facebook publishing, Verge3D offers a specific GLB export option. The exported GLB files are displayed and can be opened in the App Manager. Asset compression Exported files can optionally use LZMA compression, resulting in a reduction in file size of up to 6x. UI and website layouts Interface layouts, created using external WYSIWYG editors, can be linked with Puzzles to trigger changes to a 3D scene being rendered in the browser and vice versa. Animation Verge3D supports skeletal animation, including animation of bipeds and character rigs, and allows for animation of material parameters. Model parts can also be set up to be dragged by the user. Physics The physics module can be linked separately to enable collision detection, dynamically moving objects, support for characters and vehicles, springs, ropes and cloth simulation. As of version 2.11, simple physics simulations can be created and controlled without coding via Puzzles, the visual programming system used by Verge3D. AR/VR The 2.10 update added support for WebXR, an in-development open technology designed to enable virtual reality and augmented reality experiences to be displayed in web browsers. It works with both headsets with controllers, like the HTC Vive and Oculus Rift, and those without, like Google Cardboard. AR/VR experiences can enabled via Puzzles or JavaScript. == Workflow == Verge3D's workflow differs substantially from other mainstream WebGL frameworks. Development of a new Verge3D application is usually started from modeling, texturing and animating 3D objects. The models are assembled in the 3D authoring tool. The scene file is then used as a basis for a Verge3D project initialized from the App Manager. An interactive scenario is optionally added using the Puzzles editor. A Verge3D application can be previewed in the web browser at any development stage using the App Manager. The finished web application can be deployed on the Verge3D Network, on Facebook or on the user's website. == Notable uses == NASA's Jet Propulsion Laboratory used Verge3D to create an interactive 3D visualization of the Mars InSight lander. The web application allows for exploring and interacting with the real-time model of the spacecraft, with the possibility to move different parts and unfurl the solar panels. NASA's older interactive web application Experience Curiosity was ported to Verge3D from Blend4Web. The application makes it possible to operate the rover, control its cameras and the robotic arm and reproduces some of the prominent events of the Mars Science Laboratory mission. Route 66 Digital's Escape Room used Verge3D and Blender. This interactive short explores how users can navigate 3D spaces and interact with objects without the need for instruction.

    Read more →
  • Front-end web development

    Front-end web development

    Front-end web development is the development of the graphical user interface of a website through the use of HTML, CSS, and JavaScript so users can view and interact with that website. == Tools used for front-end development == There are several tools and platforms, such as WordPress, Joomla, and Drupal, available that can be used to develop the front end of a website. === HyperText Markup Language === HyperText Markup Language (HTML) is the modern standard for displaying and structuring web content across the internet. HTML defines what elements will be displayed on a website, and how they will be arranged. All major web browsers are designed to interpret HTML, and most modern websites serve HTML to the user. Hypertext is text displayed on a computer with references to other text, these references (or links,) are termed "hyperlinks." When an internet user interacts with a hyperlinked item, the website serves the user the linked data. This data can be another HTML web-page, JavaScript, or anything else. The latest major release of HTML is HTML5, originally published on October 28, 2014 as a W3C recommendation. A web page may be developed to include many markup tags. For each pair of markup tag normally starts with a Start tag and ends with a matching end tag. The text in between the Start tag and the End tag is called an HTML Element. [1] === Cascading Style Sheets === Cascading Style Sheets (CSS) control the presentation and style of a website. CSS uses a cascading system to resolve style conflicts by applying style rules based on specificity, inheritance, and importance. Media queries allow for adjustments to the site's layout and appearance depending on factors such as screen size and resolution. CSS can be applied in three ways: external stylesheets linked in an HTML file, internal