Explore Then Commit (ETC) is an algorithm for the multi-armed bandit problem foc,used on finding the best trade-off between exploration and exploitation. == Multi-armed bandit problem == The multi-armed bandit problem is a sequential game where one player has to choose at each turn between K {\displaystyle K} actions (arms). Behind every arm a {\displaystyle a} is an unknown distribution ν a {\displaystyle \nu _{a}} that lies in a set D {\displaystyle {\mathcal {D}}} known by the player (for example, D {\displaystyle {\mathcal {D}}} can be the set of Gaussian distributions or Bernoulli distributions). At each turn t {\displaystyle t} the player chooses (pulls) an arm a t {\displaystyle a_{t}} , they then get an observation X t {\displaystyle X_{t}} of the distribution ν a t {\displaystyle \nu _{a_{t}}} . === Regret minimization === The goal is to minimize the regret at time T {\displaystyle T} that is defined as R T := ∑ a = 1 K Δ a E [ N a ( T ) ] {\displaystyle R_{T}:=\sum _{a=1}^{K}\Delta _{a}\mathbb {E} [N_{a}(T)]} where μ a := E [ ν a ] {\displaystyle \mu _{a}:=\mathbb {E} [\nu _{a}]} is the mean of arm a {\displaystyle a} μ ∗ := max a μ a {\displaystyle \mu ^{}:=\max _{a}\mu _{a}} is the highest mean Δ a := μ ∗ − μ a {\displaystyle \Delta _{a}:=\mu ^{}-\mu _{a}} N a ( t ) {\displaystyle N_{a}(t)} is the number of pulls of arm a {\displaystyle a} up to turn t {\displaystyle t} The player has to find an algorithm that chooses at each turn t {\displaystyle t} which arm to pull based on the previous actions and observations ( a s , X s ) s < t {\displaystyle (a_{s},X_{s})_{s Productivity software (also called personal productivity software or office productivity software) is application software used for producing information (such as documents, presentations, worksheets, databases, charts, graphs, digital paintings, electronic music and digital video). Its names arose from it increasing productivity, especially of individual office workers, from typists to knowledge workers, although its scope is now wider than that. Office suites, which brought word processing, spreadsheet, and relational database programs to the desktop in the 1980s, are the core example of productivity software. They revolutionized the office with the magnitude of the productivity increase they brought as compared with the pre-1980s office environments of typewriters, paper filing, and handwritten lists and ledgers. In the United States, as of 2015, some 78% of "middle-skill" occupations (those that call for more than a high school diploma but less than a bachelor's degree) required the use of productivity software. == Details == Productivity software traditionally runs directly on a computer. For example, Plus/4 model of computer contains in ROM for applications of productivity software. Productivity software is one of the reasons people use personal computers. == Office suite == An office suite is a bundle of productivity software (a software suite) intended to be used by office workers. The components are generally distributed together, have a consistent user interface and usually can interact with each other, sometimes in ways that the operating system would not normally allow. The earliest office suite for personal computers was MicroPro International's StarBurst in the early 1980s, comprising the WordStar word processor, the CalcStar spreadsheet and the DataStar database software. Other suites arose in the 1980s, and Microsoft Office came to dominate the market in the 1990s, a position it retains as of 2024. During the 1990s, office suite products gained popularity by offering bundles of applications that, when bought as part of a suite, effectively discounted the individual applications, with four or five applications being bundled for the price of two applications bought separately. When faced with such potential savings, customers could be "tempted by the suite, rather than the value of a particular product", and by 1994 more than 60 percent of the sales of Microsoft Word and around 70 percent of the sales of Microsoft Excel were as part of sales of Microsoft Office. Such considerations had an impact on vendors of individual applications, often smaller companies, raising concerns that office suites were "stifling innovation", and even established vendors such as Borland and WordPerfect were having to adapt to the suite phenomenon, Borland ultimately deciding to sell its Quattro Pro spreadsheet to WordPerfect as the latter sought to assemble its own suite product. The dominant suite vendors, Microsoft and Lotus, downplayed competition and innovation concerns, claiming that users were still able to exercise choice and that "user-driven development" was guiding the evolution of office suites. Another view was that component-based software would eventually emerge, focusing development on more specialised components used by productivity software, empowering "a plethora of third-party developers", and that a "mix and match" approach of such components would adapt to the user's way of working. === Office suite components === The base components of office suites are: Word processor Spreadsheet Presentation program Other components include: Database software Graphics suite (raster graphics editor, vector graphics editor, image viewer) Desktop publishing software Formula editor Diagramming software Email client Communication software Personal information manager Notetaking Groupware Project management software Table (information) Web log analysis software Shopping for the best AI pair programmer? An AI pair programmer is software that uses machine learning to help you get more done — it keeps getting smarter as the underlying models improve. Pricing, accuracy, and the size of the model behind the tool are the three factors that most affect daily usefulness. Whether you are a beginner or a pro, the right AI pair programmer slots into your workflow and pays for itself fast. We tested the leading options and ranked them by quality, value, and ease of use. Looking for the best AI copywriting tool? An AI copywriting 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 copywriting tool 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. James Frederick Allen (born 1950) is an American computational linguist recognized for his contributions to temporal logic, in particular Allen's interval algebra. He is interested in knowledge representation, commonsense reasoning, and natural language understanding, believing that "deep language understanding can only currently be achieved by significant hand-engineering of semantically-rich formalisms coupled with statistical preferences". He is the John H. Dessaurer Professor of Computer Science at the University of Rochester. == Biography == Allen received his Ph.D. from the University of Toronto in 1979, under the supervision of C. Raymond Perrault, after which he joined the faculty at Rochester. At Rochester, he was department chair from 1987 to 1990, directed the Cognitive Science Program from 1992 to 1996, and co-directed the Center for the Sciences of Language from 1996 to 1998. He served as the Editor-in-Chief of Computational Linguistics from 1983–1993. Since 2006 he has also been associate director of the Florida Institute for Human and Machine Cognition. == Academic life == === TRIPS project === The TRIPS project is a long-term research to build generic technology for dialogue (both spoken and 'chat') systems, which includes natural language processing, collaborative problem solving, and dynamic context-sensitive language modeling. This is contrast with the data driven approaches by machine learning, which requires to collect and annotate corpora, i.e. training data, firstly. === PLOW agent === PLOW agent is a system that learns executable task models from a single collaborative learning session, which integrates wide AI technologies including deep natural language understanding, knowledge representation and reasoning, dialogue systems, planning/agent-based systems, and machine learning. This paper won the outstanding paper award at AAAI in 2007. == Selected works == === Books === Allen is the author of the textbook Natural Language Understanding (Benjamin-Cummings, 1987; 2nd ed., 1995). He is also the co-author with Henry Kautz, Richard Pelavin, and Josh Tenenberg of Reasoning About Plans (Morgan Kaufmann, 1991). === Articles === 2007. PLOW: A Collaborative Task Learning Agent. (with Nathanael Chambers et al) AAAI'07 won the outstanding paper award at AAAI in 2007. 2006. Chester: Towards a Personal Medication Advisor. (with N. Blaylock, et al) Biomedical informatics 39(5) 1998. TRIPS: An Integrated Intelligent Problem-Solving Assistant. (with George Ferguson) AAAI'98 1983. Maintaining Knowledge about Temporal Intervals. CACM 26, 11, 832-843 == Awards and honors == In 1991 he was elected as a fellow of the Association for the Advancement of Artificial Intelligence (1990, founding fellow). In 1992 he became the Dessaurer Professor at Rochester. Adobe ImageReady was a bitmap graphics editor that was shipped with Adobe Photoshop for six years. It was available for Windows, Classic Mac OS and Mac OS X from 1998 to 2007. ImageReady was designed for web development and closely interacted with Photoshop. == Function == ImageReady was designed for web development rather than effects-intensive photo manipulation. To that end, ImageReady has specialized features such as animated GIF creation, image compression optimization, image slicing, adding rollover effects, and HTML generation. Photoshop versions with which ImageReady was released have an "Edit in ImageReady" button that enables editing of image directly in ImageReady. ImageReady, in turn, has an "Edit in Photoshop" button. ImageReady has strong resemblances to Photoshop; it can even use the same set of Photoshop filters. One set of tools that does not resemble the Photoshop tools, however, is the Image Map set of tools, indicated by a shape or arrow with a hand that varied depending upon the version. This toolbox has several features not found in Photoshop, including: Toggle Image Map Visibility and Toggle Slice Visibility tools: toggle between showing and hiding image maps and slices, respectively Export Animation Frames as Files option: saves all or specified frames for an alternate use, e.g., to e-mail slides for review Preview Document tool: provides a preview of rollover effects in ImageReady rather than previewing them in a browser Preview in Default Browser tool: previews the image in a browser, including any rollover or animation effects Edit in Photoshop button: opens the current image in Photoshop == History == Adobe ImageReady 1.0 was released in July 1998 as a standalone application. Version 2.0 was packaged with Photoshop 5.5, and the program was included with Photoshop through version 9.0 (CS2). Starting with Photoshop 7.0, Adobe changed the version numbers of ImageReady to match. With the release of the Creative Suite 3, ImageReady was discontinued. According to Adobe, ImageReady's most popular features were merged into Photoshop. (Even before discontinuation, some of ImageReady's web optimization functionality could be found in Photoshop's Save For Web & Devices tool.) Around the same time, Adobe purchased rival software developer Macromedia, whose application Fireworks had been a competitor to ImageReady. Klaus-Robert Müller (born 1964 in Karlsruhe, West Germany) is a German computer scientist and physicist, most noted for his work in machine learning and brain–computer interfaces. == Career == Klaus-Robert Müller received his Diplom in mathematical physics and PhD in theoretical computer science from the University of Karlsruhe. Following his Ph.D. he went to Berlin as a postdoctoral fellow at GMD (German National Research Center for Computer Science) Berlin (now part of Fraunhofer Institute for Open Communication Systems), where he started building up the Intelligent Data Analysis (IDA) group. From 1994 to 1995 he was a research fellow at Shun'ichi Amari's lab at the University of Tokyo. 1999 Müller became an associate professor for neuroinformatics at the University of Potsdam, transitioning to the full professorship for Neural Networks and Time Series Analysis in 2003. Since 2006 he holds the chair for Machine Learning at Technische Universität Berlin. Since 2012 he holds a distinguished professorship at Korea University in Seoul. He co-founded and is co-director of the Berlin Big Data Center (BBDC) of TU Berlin. As of 2017, 29 former doctoral or postdoctoral researchers of Klaus-Robert Müller have become full professors themselves. Bernhard Schölkopf and Alexander J. Smola were supervised by him as members of his research group. Since 2020 he is director of the Berlin Institute for the Foundations of Learning and Data (BIFOLD), a German National AI Competence Center, and director of the European Laboratory for Learning and Intelligent Systems (ELLIS) unit Berlin. In 2020/2021 he spent his sabbatical at Google Brain as a principal scientist. == Research == Müller has contributed extensively to several major interests of machine learning, including support vector machines (SVMs) and kernel methods, and artificial neural networks. He pioneered applying new methods of pattern recognition in domains like brain–computer interfaces, using them for patients with Locked-in syndrome. He is one of the leading computer scientists affiliated with Germany. His current research interests include: Statistical learning theory (Support Vector Machines, Deep Neural Networks, Boosting) Learning of non-stationarity data Fusion of structured heterogeneous multi-modal data, co-adaptation Applications: MEG, EEG, NIRS, ECoG, EMG, Brain Computer Interfaces, computational neuroscience, computer vision, genomic data analysis, computational chemistry and atomistic simulations, digital pathology == Honours and awards == Klaus-Robert Müller was elected a fellow of the German National Academy of Sciences Leopoldina in 2012. In 2017 he was elected member of the Berlin-Brandenburg Academy of Sciences and Humanities and also external scientific member of the Max Planck Society. In 2021 he was elected member of the German Academy of Science and Engineering. His work was honoured with several awards, including: 2026 Gottfried Wilhelm Leibniz Prize 2025 IEEE Neural Network Pioneer Award 2024 Feynman Prize in Nanotechnology 2023 Hector Fellow 2025, 2024, 2023, 2022, 2021, 2020, and 2019 Clarivate Highly Cited Researcher 2017 Vodafone Innovations Award 2017 2014 Science Prize of Berlin 2014 by the Governing Mayor of Berlin 2014 European Research Council Panel Consolidator Grants 2009 Best Paper award by IEEE Engineering in Medicine and Biology Society EMBS 2006 SEL-ALCATEL Research Prize for Technical Communication 1999 Olympus Award for Pattern Recognition == Books == with Holzinger, Andreas; et al., eds. (2022). xxAI – Beyond Explainable Artificial Intelligence. Lecture Notes in Computer Science. Vol. 13200. Springer Cham. doi:10.1007/978-3-031-04083-2. ISBN 978-3-031-04082-5. with Schütt, Kristof T.; et al., eds. (2020). Machine Learning Meets Quantum Physics. Lecture Notes in Physics. Vol. 968. Springer Cham. doi:10.1007/978-3-030-40245-7. ISBN 978-3-030-40244-0. S2CID 242406994. with Samek, Wojciech; et al., eds. (2019). Explainable AI: Interpreting, Explaining and Visualizing Deep Learning. Lecture Notes in Computer Science. Vol. 11700. Springer Cham. doi:10.1007/978-3-030-28954-6. ISBN 978-3-030-28953-9. with Montavon, Grégoire; et al., eds. (2012). Neural Networks: Tricks of the Trade. Lecture Notes in Computer Science. Vol. 7700 (2nd ed.). Springer Berlin, Heidelberg. doi:10.1007/978-3-642-35289-8. ISBN 978-3-642-35288-1. S2CID 39578794.Productivity software
Is an AI Pair Programmer Worth It in 2026?
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James F. Allen (computer scientist)
Adobe ImageReady
Klaus-Robert Müller