Curious about the best AI paragraph rewriter? An AI paragraph rewriter is software that uses machine learning to help you get more done — it combines speed, accuracy, and an interface that just works. Hands-on testing shows real-world results vary, so a short free trial is the smartest way to decide. Whether you are a beginner or a pro, the right AI paragraph rewriter slots into your workflow and pays for itself fast. Read on for hands-on impressions, pricing tiers, and the standout features that matter.
AdBlock
AdBlock is an ad-blocking browser extension for Google Chrome, Apple Safari (desktop and mobile), Firefox, Samsung Internet, Microsoft Edge and Opera. AdBlock allows users to prevent page elements, such as advertisements, from being displayed. It is free to download and use, and it includes optional donations to the developers. The AdBlock extension was created on December 8, 2009, which is the day that supports for extensions was added to Google Chrome. It was one of the first Google Chrome extensions that was made. Since 2016, AdBlock has been based on the Adblock Plus source code. In July 2018, AdBlock acquired uBlock, a commercial ad-blocker owned by uBlock LLC and based on uBlock Origin. In April 2021, eyeo GmbH (developer of Adblock Plus) announced its purchase of AdBlock, Inc (formerly BetaFish, Inc). == Crowdfunding == Gundlach launched a crowdfunding campaign on Crowdtilt in August 2013 in order to fund an ad campaign to raise awareness of ad-blocking and to rent a billboard at Times Square. After the one-month campaign, it raised $55,000. == Sales and acceptable ads == AdBlock was sold to an anonymous buyer in 2015 and on October 15, 2015, Gundlach's name was taken down from the site. In the terms of the deal, the original developer Michael Gundlach left operations to Adblock's continuing director, Gabriel Cubbage, and as of October 2, 2015, AdBlock began participating in the Acceptable Ads program. Acceptable Ads identifies "non-annoying" ads, which AdBlock shows by default. The intent is to allow non-invasive advertising, to either maintain support for websites that rely on advertising as a main source of revenue or for websites that have an agreement with the program. == Filters == AdBlock uses EasyList, the same filter syntax as Adblock Plus for Firefox, and natively supports the use of a number of filter lists. == Partnership with Amnesty International == On March 12, 2016, in support of World Day Against Cyber Censorship, and in partnership with Amnesty International, instead of blocking ads, AdBlock replaced ads with banners linked to articles on Amnesty's website, written by prominent free speech advocates such as Edward Snowden, to raise awareness of government-imposed online censorship and digital privacy issues around the world. The campaign was met with both praise and criticism, with AdBlock's CEO, Gabriel Cubbage, defending the decision in an essay on AdBlock's website, saying "We’re showing you Amnesty banners, just for today, because we believe users should be part of the conversation about online privacy. Tomorrow, those spaces will be vacant again. But take a moment to consider that in an increasingly information-driven world, when your right to digital privacy is threatened, so is your right to free expression." Meanwhile, Simon Sharwood of The Register characterized Cubbage's position as "'You should control your computer except when we feel political', says AdBlock CEO". == AdBlock for Firefox == On September 13, 2014, the AdBlock team released a version for Firefox users, ported from the code for Google Chrome, released under the same free software license as the original Adblock. The extension was removed on April 2, 2015, by an administrator on Mozilla Add-ons. On December 7, 2015, the official AdBlock site's knowledge base article stated that with version 44 or higher of Firefox desktop and Firefox Mobile, AdBlock will not be supported. The last version of Adblock for those platforms will work on older versions of Firefox. AdBlock was released again on Mozilla Add-ons on November 17, 2016. On April 1, 2012, Adblock developer Michael Gundlach tweaked the code to display LOLcats instead of simply blocking ads. Initially developed as a short-lived April Fools joke, the response was so positive that CatBlock was continued to be offered as an optional add-on supported by a monthly subscription. On October 23, 2014, the developer decided to end official support for CatBlock, and made it open-source, under GPLv3 licensing, as the original extension.
The Best Free AI Marketing Tool for Beginners
Looking for the best AI marketing tool? An AI marketing tool is software that uses machine learning to help you get more done — it can save you hours every week by automating repetitive work. Most options offer a generous free tier, with paid plans unlocking higher limits, faster processing, and team features. Whether you are a beginner or a pro, the right AI marketing tool slots into your workflow and pays for itself fast. Read on for hands-on impressions, pricing tiers, and the standout features that matter.
Yun Sing Koh
Yun Sing Koh (born 1978) is a New Zealand computer science academic, and is a full professor at the University of Auckland, specialising in machine learning and artificial intelligence. She is a co-director of the Centre of Machine Learning for Social Good, and the Advanced Machine Learning and Data Analytics Research (MARS) Lab at Auckland. == Academic career == Koh earned a Bachelor of Science with Honours and a Master of Software Engineering at the University of Malaya. She then completed a PhD titled Generating sporadic association rules at the University of Otago in 2007. Koh joined the faculty of the University of Auckland in 2010, rising to full professor. As of 2024, she is director of the Centre of Machine Learning for Social Good at Auckland, alongside Gillian Dobbie and Daniel Wilson, and is director of the Master of AI course at the university. Koh also co-directs the Advanced Machine Learning and Data Analytics Research (MARS) Lab. Koh's research covers machine learning and artificial intelligence. She is especially interested in designing machine learning algorithms for data streams, and has led research using AI systems to identify individual stoats for pest population research. In 2018 she was awarded a Marsden grant for a research project "An Adaptive Predictive System for Life-long Learning on Data Streams", and has been part of three MBIE projects. In 2025 the stoat identification project Koh co-leads with Daniel Wilson was awarded $1 million per annum by the MBIE Smart Ideas fund. Koh was a finalist in the AI in Climate section of the Women in AI Australia and New Zealand Awards in 2022. She was a 2023 Fellow at the United States National Science Foundation-funded Convergence Research (CORE) Institute. Koh has chaired a number of sessions at international conferences on data mining. In March 2026 it was announced that Koh would be a member of the New Zealand Human Rights Commission's Expert Advisory Group on Artificial Intelligence, Emerging Digital Technologies and Human Rights. == Selected works == Philippe Fournier-Viger; Jerry Chun-Wei Lin; Rage Uday Kiran; Yun Sing Koh; Rincy Thomas (2017). "A Survey of Sequential Pattern Mining". Data Science and Pattern Recognition. 1 (1): 54–77. Wikidata Q138719481. Yun Sing Koh; Nathan Rountree; Richard O’Keefe (1 April 2006). "Finding Non-Coincidental Sporadic Rules Using Apriori-Inverse". International Journal of Data Warehousing and Mining (in Ndonga). 2 (2): 38–54. doi:10.4018/JDWM.2006040102. ISSN 1548-3924. Wikidata Q125185222. Russel Pears; Sripirakas Sakthithasan; Yun Sing Koh (11 January 2014). "Detecting concept change in dynamic data streams". Machine Learning. 97 (3): 259–293. doi:10.1007/S10994-013-5433-9. ISSN 1573-0565. Zbl 1319.68186. Wikidata Q125185156. David Tse Jung Huang; Yun Sing Koh; Gillian Dobbie; Russel Pears (December 2014), Detecting Volatility Shift in Data Streams, Institute of Electrical and Electronics Engineers, doi:10.1109/ICDM.2014.50, Wikidata Q125185151 Sidney Tsang; Yun Sing Koh; Gillian Dobbie (2011). "RP-Tree: Rare Pattern Tree Mining". Lecture Notes in Computer Science: 277–288. doi:10.1007/978-3-642-23544-3_21. ISSN 0302-9743. Wikidata Q125185206. Yun Sing Koh; Sri Devi Ravana (24 May 2016). "Unsupervised Rare Pattern Mining". ACM Transactions on Knowledge Discovery from Data. 10 (4): 1–29. doi:10.1145/2898359. ISSN 1556-4681. Wikidata Q125185136. Jack Julian; Yun Sing Koh; Albert Bifet (1 October 2025), Building adaptive knowledge bases for evolving continual learning models (PDF), vol. 1, doi:10.1038/S44387-025-00028-4, Wikidata Q138719496
Is an AI Clip Maker Worth It in 2026?
Trying to pick the best AI clip maker? An AI clip maker 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 clip maker slots into your workflow and pays for itself fast. This guide breaks down the top picks, their pros and cons, and who each one is best for.
List of artificial intelligence journals
This is a list of notable peer-reviewed academic journals that publish research in the field of artificial intelligence (AI), including areas such as machine learning, computer vision, natural language processing, robotics, and intelligent systems. == General artificial intelligence == Artificial Intelligence (journal) – Elsevier Journal of Artificial Intelligence Research (JAIR) – AI Access Foundation Knowledge-Based Systems – Elsevier == Machine learning == Data Mining and Knowledge Discovery – Springer Machine Learning (journal) – Springer Journal of Machine Learning Research – Microtome Pattern Recognition (journal) – Elsevier Neural Networks (journal) – Elsevier Neural Computation (journal) – MIT Press Neurocomputing (journal) - Elsevier == Deep learning and neural computation == IEEE Transactions on Evolutionary Computation – IEEE IEEE Transactions on Neural Networks and Learning Systems – IEEE Nature Machine Intelligence – Springer Nature == Computer vision == International Journal of Computer Vision – Springer IEEE Transactions on Pattern Analysis and Machine Intelligence – IEEE Machine Vision and Applications – Springer == Natural language processing == Computational Linguistics (journal) – MIT Press Natural Language Processing Transactions of the Association for Computational Linguistics – ACL == Robotics and intelligent systems == IEEE Transactions on Robotics – IEEE Autonomous Robots – Springer Journal of Intelligent & Robotic Systems – Springer == Interdisciplinary and ethics in AI == AI & Society – Springer Artificial Life – MIT Press Philosophy & Technology – Springer Minds and Machines – Springer
Neuroph
Neuroph is an object-oriented artificial neural network framework written in Java. It can be used to create and train neural networks in Java programs. Neuroph provides Java class library as well as GUI tool easyNeurons for creating and training neural networks. It is an open-source project hosted at SourceForge under the Apache License. Versions before 2.4 were licensed under LGPL 3, from this version the license is Apache 2.0 License. == Features == Neuroph's core classes correspond to basic neural network concepts like artificial neuron, neuron layer, neuron connections, weight, transfer function, input function, learning rule etc. Neuroph supports common neural network architectures such as Multilayer perceptron with Backpropagation, Kohonen and Hopfield networks. All these classes can be extended and customized to create custom neural networks and learning rules. Neuroph has built-in support for image recognition.