AI For Students Studying

AI For Students Studying — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

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  PhotoLine

  PhotoLine is a general purpose bitmap and vector graphics editor developed and published by Computerinsel GmbH for Windows, macOS, and Linux/Wine. It was originally created in 1995 by Gerhard Huber and Martin Huber. The program combines bitmap and vector graphics editing in one seamless working application unlike most graphics software which tend to focus on either bitmap or vector editing and output. PhotoLine is considered as a market competitor to Adobe Photoshop. == Features == PhotoLine edits and composes multi-layer raster and vector images with deep support for masking and alpha compositing and with full color management. Editing and color management in PhotoLine is mostly non-destructive. Image data in layers is preserved without loss of information regardless of the document's image mode or layer transformation. color depth, image resolution, color model, and ICC profile are preserved for each individual layer or group of layers. Layers can be cloned and reused anywhere in the layer stack, including repurposed as layer masks. Layer blending and compositing in PhotoLine supports common blend modes, and features a layer blend range of -200 to +200 percent. It is also possible to control which channels are blended for each layer, adjustment layer, and layer mask or group of layers. Filters, adjustment layers, and brushes have access to Lab and HIS color modes (HIS is a variant of HSL), separately of the color model of the underlying image layer. In Addition to raster and vector editing, PhotoLine can be used for small desktop publishing projects. Multi-page documents with page spreads and text flow between text frames and pages are supported. Character and paragraph styles can be defined. Spot colors, bleed settings, a baseline grid, a table of contents generator, and PDF/X support help with these projects. PhotoLine is however much more limited when compared to dedicated publishing software such as Adobe InDesign or QuarkXPress. PhotoLine incorporates the Open-source software library LibRaw to read raw images from digital cameras for import. Developing these files is non-destructive with a choice of embedding the RAW image data either in the PhotoLine document or link to the external RAW image file. PhotoLine can open raw files as linear unmodified and non color managed source images. Photoshop PSD files can be imported and exported. Core functionality of PhotoLine can be extended through standard Photoshop filter plugins, the G'MIC digital image processing framework, and PSP tubes. External programs can be linked for a seamless round-trip workflow and files can be sent directly for processing in third-party design applications. Custom functionality is further supported through scripting and macro recording. == Early history == Developed by two brothers, Gerhard Huber and Martin Huber, PhotoLine was first released in January 1996 on the Atari ST line of personal computers from Atari Corporation. Previously, Gerhard and Martin had worked on making graphics cards for Atari computers and writing drivers for image scanners. Atari's market share was declining, and the brothers considered developing a video game to expand the business. This led them to search for image editing software that would run on Atari computers and fit their game project. Only an image editor called tms Cranach came close to what Gerhard and Martin had in mind. tms Cranach was a Raster graphics editor running on Atari's MegaST/STe, TT030, and Falcon030 systems. However, Cranach turned out to be expensive software and complicated to use. The brothers contacted tms (Cranach's developers) and this resulted in an offer from tms to purchase Cranach and its source code, as tms intended to exit the Atari software market. After the purchase of Cranach and its source code Gerhard and Martin initially continued to sell Cranach, but sales were low. In 1995 the two decided to start developing a new graphics editor called "PhotoLine". PhotoLine was developed from scratch and written in C++. It nevertheless contained a lot of know-how from Cranach (which was written in C). PhotoLine first release was launched one year later in 1996. With the growing popularity of Microsoft Windows, the release of Windows 95, and the limiting graphics hardware on the Atari platforms, the developers switched development platforms and continued development of PhotoLine for Windows only. The first Windows version (PhotoLine 2.2) was released in the middle of 1997. Shortly after, the Atari version was discontinued and saw its final release as PhotoLine 2.30. The Huber brothers released this final Atari version into the public domain in 2012. The first Classic Mac OS version of PhotoLine 6 appeared in 1999 after many ex-Atari users who had switched to Mac OS pressured the PhotoLine developers to release an Apple port. == Linux Support == PhotoLine runs natively under Windows and MacOS. While a native Linux version of PhotoLine is not available, running PhotoLine under Wine is actively supported and maintained by the developers. Running PhotoLine under Linux/Wine PhotoLine enables the user to allow Little CMS to fully support color management under Linux instead of the native OS CMS. == File format == Native PhotoLine files have the extension .PLD, which is an abbreviation of "PhotoLine Document". It can contain embedded JPEG, PNG, or camera raw images. It contains a preview image in JPEG or PNG format, which is used by the operating system or third-party applications to display a thumbnail of its contents. Thumbnails are natively supported on MacOS X. During installation on Windows the user is presented with an option to install a PLD thumbnail preview driver which enables thumbnails of PLD content in Windows Explorer. Alternatively, the FastPictureViewer Standalone Codec Pack provides the ability to display PLD thumbnails in Windows Explorer. == Version History == PhotoLine was first developed for the Atari ST computer. Version 2 was the first version for Windows, and since version 6 PhotoLine is also available for MacOS.

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  Is an AI Voice Assistant Worth It in 2026?

  Trying to pick the best AI voice assistant? An AI voice assistant is software that uses machine learning to help you get more done — it scales effortlessly from a single task to thousands. The best picks balance beginner-friendly simplicity with the depth power users need, and they ship updates often. Whether you are a beginner or a pro, the right AI voice assistant slots into your workflow and pays for itself fast. Read on for hands-on impressions, pricing tiers, and the standout features that matter.

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  Lori Levin

  Lorraine Susan (Lori) Levin is an American computer scientist and computational linguist specializing in natural language processing, particularly involving syntax, morphosyntax, and languages with small corpora. She is a research professor in the Language Technologies Institute of the Carnegie Mellon University School of Computer Science, and one of the founders of the North American Computational Linguistics Open Competition. == Education and career == Levin has a 1979 bachelor's degree in linguistics (summa cum laude) from the University of Pennsylvania, and a 1986 Ph.D. in linguistics from the Massachusetts Institute of Technology. Her dissertation, Operations on Lexical Forms: Unaccusative Rules in Germanic Languages, was jointly supervised by Joan Bresnan and Kenneth L. Hale. She worked as an assistant professor of linguistics at the University of Pittsburgh from 1983 until 1988, when she joined the Carnegie Mellon University Language Technologies Institute. == Recognition == Levin was named as a Fellow of the Association for Computational Linguistics in 2025, "for pioneering work on the use of phonetics, syntax, lexical semantics and dialogue modeling in machine translation and in the transfer of NLP technologies to low resource languages, as well as an enduring contribution to the North American Computational Linguistics Olympiad". Levin was awarded the Antonio Zampolli prize of the ELRA Language Resources Association at the LREC 2026 conference.

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  Xu Li (computer scientist)

  Xu Li is a Chinese computer scientist and co-founder and current CEO of SenseTime, an artificial intelligence (AI) company. Xu has led SenseTime since the company's incorporation and helped it independently develop its proprietary deep learning platform. == Education and research == Xu obtained both his bachelor's and master's degrees in computer science from Shanghai Jiao Tong University. He received his doctorate in computer science from the Chinese University of Hong Kong. Xu has published more than 50 papers at international conferences and in journals in the field of computer vision and won the Best Paper Award at the international conference on Non-Photorealistic Rendering and Animation (NPAR) 2012 and the Best Reviewer Award at the international conferences Asian Conference on Computer Vision ACCV 2012 and International Conference on Computer Vision (ICCV) 2015. He has three algorithms that have been included into the visual open-source platform OpenCV, and his "L0 Smoothing" algorithm garnered the most citations in research papers over a span of five years (2011–2015) within the ACM Transactions on Graphics (TOG), a scientific journal that Thomson Reuters InCites has placed first among software engineering journals. == Career == Previously, Xu worked at Lenovo Corporate Research & Development. He was also a visiting researcher at Motorola China R&D Institute, Omron Research Institute, and Microsoft Research. == Selected publications == Jimmy Ren, Xiaohao Chen, Jianbo Liu, Wenxiu Sun, Li Xu, Jiahao Pang, Qiong Yan, Yu-wing Tai, "Accurate Single Stage Detector Using Recurrent Rolling Convolution", (CVPR), 2017. Jimmy SJ. Ren, Yongtao Hu, Yu-Wing Tai, Chuan Wang, Li Xu, Wenxiu Sun, Qiong Yan, "Look, Listen and Learn – A Multimodal LSTM for Speaker Identification", The 30th AAAI Conference on Artificial Intelligence (AAAI), 2016 Jimmy SJ. Ren, Li Xu, Qiong Yan, Wenxiu Sun, "Shepard Convolutional Neural Networks" Advances in Neural Information Processing Systems (NIPS), 2015. Xiaoyong Shen, Chao Zhou, Li Xu, Jiaya Jia, "Mutual-Structure for Joint Filtering" International Conference on Computer Vision (ICCV), (oral presentation), 2015. Jianping Shi, Qiong Yan, Li Xu, Jiaya Jia, "Hierarchical Image Saliency Detection on Extended CSSD" IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2015. Jianping Shi, Xin Tao, Li Xu, Jiaya Jia, "Break Ames Room Illusion: Depth from General Single Images" ACM Transactions on Graphics (TOG), (Proc. ACM SIGGRAPH ASIA2015). Yongtao Hu, Jimmy SJ. Ren, Jingwen Dai, Chang Yuan, Li Xu, Wenping Wang, "Deep Multimodal Speaker Naming" ACM International Conference on Multimedia (MM), 2015. Li Xu, Jimmy SJ. Ren, Qiong Yan, Renjie Liao, Jiaya Jia "Deep Edge-Aware Filters" International Conference on Machine Learning (ICML), 2015. Jianping Shi, Li Xu, Jiaya Jia "Just Noticeable Defocus Blur Detection and Estimation" IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. Ziyang Ma, Renjie Liao, Xin Tao, Li Xu, Jiaya Jia, Enhua Wu "Handling Motion Blur in Multi-Frame Super-Resolution" IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. Xiaoyong Shen, Qiong Yan, Li Xu, Lizhuang Ma, Jiaya Jia"Multispectral Joint Image Restoration via Optimizing a Scale Map" IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2015. Jimmy SJ. Ren, Li Xu, "On Vectorization of Deep Convolutional Neural Networks for Vision Tasks" AAAI Conference on Artificial Intelligence (AAAI), 2015. == Awards and honors == Xu was ranked 7th in Fortune magazine's 2018 edition of its 40 Under 40. He was also named "China's Outstanding AI Industry Leader" by The Economic Observer, received the "Innovative Business Leader" Award under NetEase's "Future Technology Talent Awards", and was honored as Sina's "2017 Top Ten Economic Figures". In 2018, Xu was named EY's "Entrepreneur of the Year China" in the Technology category.

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  Content Security Policy

  Content Security Policy (CSP) is a computer security standard introduced to prevent cross-site scripting (XSS), clickjacking and other code injection attacks resulting from execution of malicious content in the trusted web page context. It is a Candidate Recommendation of the W3C working group on Web Application Security, widely supported by modern web browsers. CSP provides a standard method for website owners to declare approved origins of content that browsers should be allowed to load on that website—covered types are JavaScript, CSS, HTML frames, web workers, fonts, images, embeddable objects such as Java applets, ActiveX, audio and video files, and other HTML5 features. == Status == The standard, originally named Content Restrictions, was proposed by Robert Hansen in 2004, first implemented in Firefox 4 and quickly picked up by other browsers. Version 1 of the standard was published in 2012 as W3C candidate recommendation and quickly with further versions (Level 2) published in 2014. As of 2023, the draft of Level 3 is being developed with the new features being quickly adopted by the web browsers. The following header names are in use as part of experimental CSP implementations: Content-Security-Policy – standard header name proposed by the W3C document. Google Chrome supports this as of version 25. Firefox supports this as of version 23, released on 6 August 2013. WebKit supports this as of version 528 (nightly build). Chromium-based Microsoft Edge support is similar to Chrome's. X-WebKit-CSP – deprecated, experimental header introduced into Google Chrome, Safari and other WebKit-based web browsers in 2011. X-Content-Security-Policy – deprecated, experimental header introduced in Gecko 2 based browsers (Firefox 4 to Firefox 22, Thunderbird 3.3, SeaMonkey 2.1). A website can declare multiple CSP headers, also mixing enforcement and report-only ones. Each header will be processed separately by the browser. CSP can also be delivered within the HTML code using a meta tag, although in this case its effectiveness will be limited. Internet Explorer 10 and Internet Explorer 11 also support CSP, but only sandbox directive, using the experimental X-Content-Security-Policy header. A number of web application frameworks support CSP, for example AngularJS (natively) and Django (middleware). Instructions for Ruby on Rails have been posted by GitHub. Web framework support is however only required if the CSP contents somehow depend on the web application's state—such as usage of the nonce origin. Otherwise, the CSP is rather static and can be delivered from web application tiers above the application, for example on load balancer or web server. === Bypasses === In December 2015 and December 2016, a few methods of bypassing 'nonce' allowlisting origins were published. In January 2016, another method was published, which leverages server-wide CSP allowlisting to exploit old and vulnerable versions of JavaScript libraries hosted at the same server (frequent case with CDN servers). In May 2017 one more method was published to bypass CSP using web application frameworks code. == Mode of operation == If the Content-Security-Policy header is present in the server response, a compliant client enforces the declarative allowlist policy. One example goal of a policy is a stricter execution mode for JavaScript in order to prevent certain cross-site scripting attacks. In practice this means that a number of features are disabled by default: Inline JavaScript code