Comparing the best AI clip maker? An AI clip maker is software that uses machine learning to help you get more done — it lowers the barrier so anyone can produce professional output. Privacy matters too: check whether your data trains the model and whether a no-log or enterprise tier is available. Whether you are a beginner or a pro, the right AI clip maker slots into your workflow and pays for itself fast. We tested the leading options and ranked them by quality, value, and ease of use.
AVS Video Editor
AVS Video Editor is a video editing software published by Online Media Technologies Ltd. It is a part of AVS4YOU software suite which includes video, audio, image editing and conversion, disc editing and burning, document conversion and registry cleaner programs. It offers the opportunity to create and edit videos with a vast variety of video and audio effects, text and transitions; capture video from screen, web or DV cameras and VHS tape; record voice; create menus for discs, as well as to save them to plenty of video file formats, burn to discs or publish on Facebook, YouTube, Flickr, etc. == Description == === Interface === The layout consists of the timeline or storyboard view, preview pane and media library (transitions, video effects, text or disc menus) collections. The storyboard view shows the sequence of video clips with the transitions between them and used to change the order of clips or add transitions. Timeline view consists of main video, audio, effects, video overlay and text lines for editing. Once on the timeline video can be duplicated, split, muted, frozen, cropped, stabilized, its speed can be slowed down or increased, audio and color corrected. === Importing footage === Video, audio and image files necessary for video project can be imported into the program from computer hard disk drive. User can also capture video from computer screen, web or mini DV camera, as well as from VHS tape, record voice. === Output (web, device, disc, format) === AVS Video Editor gives the opportunity to save video to a computer hard drive to one of the video formats: AVI, DVD, Blu-ray, MOV, MP4, M4V, MPEG, WMV, MKV, WebM, M2TS, TS, FLV, SWF, RM, 3GP, GIF, DPG, AMV, MTV; burn to DVD or Blu-ray disc with menus; create a video for mobile players, mobile phones or gaming consoles and upload it right to the device. The most popular devices such as Apple iPod, Apple iPhone, Apple iPad, Sony PSP, Samsung Galaxy, Android and BlackBerry smartphones and tablets are supported. There is also an option to create a video that can be streamed via web and save it into Flash or WebM format or for the popular web services: YouTube, Facebook, Telly (Twitvid), Dailymotion, Flickr and Dropbox. === Features === Single and multithread modes: if a computer supports multi-threading, video creation process is performed faster in multithread mode, especially on a multi-core system. Customization of the output file settings, such as bitrate, frame rate, frame size, video and audio codecs, etc. Transitions - help video clips smoothly go into one another, dissolve or overlap two video or image files. Fade in and fade out video and audio files - dissolve a video to and from a blank image, reduce the audio volume at the end of the video and increase at the beginning. Slideshow creation - create a presentation of a series of still images. Voice recording Projects - once a project is created and saved, the next time saving video to some other format will be fast, projects are also used if a user do not have a possibility to create, edit and save video all at once. Video overlay option - superpose video image over the video clip that is being edited. Disk menu and chapters creation - an option for DVD and Blu-ray video. Freeze frame - make a still shot from a video clip. Stabilization feature - reduce jittering or blurring caused by shaky motions of a camera. Enhanced deinterlacing method - increase video quality for interlaced input file - spots and blurred areas are compensated. Scene detection - search and separate one scene of the video from the other. Loop DVD and SWF - output SWF and DVD video are played back continuously. Caching for processing high definition files - create a duplicate video file smaller in size to use it on the preview window and accelerate processing of HD files. Chroma key option - add video overlay half transparent so that only part of it is visible and all the rest disappears to reveal the video underneath. Capture video material from DV tapes, VHS tapes, web cameras, etc. Movie closing credits - add information on movie editing, e.g. crew, cast, data, etc. Creeping line, subtitles, text - add different captions (static and animated), shapes and images to video. Speech balloons and other graphic objects - geometrical shapes to highlight an object in the video. Zoom effect - magnify or reduce the view of the image. Rotate effect - rotate video image at different degrees, e.g. 90, 180, etc. Grayscale and old movie effects - create a black and white video image. Old movie adds also scratches, noise, shake and dust to video, as if it's being played on an old projector. Blur and sharpen effects - visually smooth and soften an image, or make video image better focused. Snow and particles effects - adds snow or various objects (bubbles, flowers, leaves, butterflies etc.) that are moving, flying or falling on the video. Pan and zoom Timer, countdown effects - add a timepiece that measures or counts down a time interval to the video being edited. Snapshots - capture a particular moment of a video clip. Sound track replacement - mute audio track from video and add another one. Audio amplify, noise removal, equalizer, etc. - make video sound louder, attenuate the noise, change frequency pattern of the audio, make some other audio adjustments. Trim and multi-trim options - change video clip duration cutting out unnecessary parts or detect scenes and cut out parts in any place of the video clip. Color correction (brightness, temperature, contrast, saturation, gamma, etc.) effects - allow adjustment of tonal range, color, and sharpness of video files. Crop scale effect - get rid of mattes that appear after changing aspect ratio of a video file. Adjusting the Playback Speed Volume and balance - change sound volume in the output video. Change volume value proportion for main video and added soundtrack, completely mute main video audio and leave added soundtrack only, etc. === Utilities embedded into AVS Video Editor === AVS Mobile Uploader is used to transfer edited and converted media files to portable devices via Bluetooth, Infrared or USB connection. AVS Video Burner is used to burn converted video files to different disc types: CD, DVD, Blu-ray. AVS Video Recorder is used to capture video from analog video sources and supports different types of devices: capture card, web camera (webcam), DV camera, HDV camera. AVS Video Uploader is used to transfer video files to popular video-sharing websites, like Facebook, Dailymotion, YouTube, Photobucket, TwitVid, MySpace, Flickr. AVS Screen Capture is used to capture any actions on the desktop to make presentations or video tutorials more vivid and easily comprehensible. == Important upgrades == The initial release of AVS Video Editor was in 2003 when the program was offered inside AVS software bundles together with AVS Video Tools, AVS Audio Tools and DVD Copy software. In 2005 the program is offered as a part of multifunctional AVS4YOU software suite. AVS Video Editor is frequently updated. The main updates include adding several important features for video editing
Planner (programming language)
Planner (often seen in publications as "PLANNER" although it is not an acronym) is a programming language designed by Carl Hewitt at MIT, and first published in 1969. First, subsets such as Micro-Planner and Pico-Planner were implemented, and then essentially the whole language was implemented as Popler by Julian Davies at the University of Edinburgh in the POP-2 programming language. Derivations such as QA4, Conniver, QLISP and Ether (see scientific community metaphor) were important tools in artificial intelligence research in the 1970s, which influenced commercial developments such as Knowledge Engineering Environment (KEE) and Automated Reasoning Tool (ART). == Procedural approach versus logical approach == The two major paradigms for constructing semantic software systems were procedural and logical. The procedural paradigm was epitomized by Lisp which featured recursive procedures that operated on list structures. The logical paradigm was epitomized by uniform proof procedure resolution-based derivation (proof) finders. According to the logical paradigm it was “cheating” to incorporate procedural knowledge. == Procedural embedding of knowledge == Planner was invented for the purposes of the procedural embedding of knowledge and was a rejection of the resolution uniform proof procedure paradigm, which Converted everything to clausal form. Converting all information to clausal form is problematic because it hides the underlying structure of the information. Then used resolution to attempt to obtain a proof by contradiction by adding the clausal form of the negation of the theorem to be proved. Using only resolution as the rule of inference is problematical because it hides the underlying structure of proofs. Also, using proof by contradiction is problematical because the axiomatizations of all practical domains of knowledge are inconsistent in practice. Planner was a kind of hybrid between the procedural and logical paradigms because it combined programmability with logical reasoning. Planner featured a procedural interpretation of logical sentences where an implication of the form (P implies Q) can be procedurally interpreted in the following ways using pattern-directed invocation: Forward chaining (antecedently): If assert P, assert Q If assert not Q, assert not P Backward chaining (consequently) If goal Q, goal P If goal not P, goal not Q In this respect, the development of Planner was influenced by natural deductive logical systems (especially the one by Frederic Fitch [1952]). == Micro-planner implementation == A subset called Micro-Planner was implemented by Gerry Sussman, Eugene Charniak and Terry Winograd and was used in Winograd's natural-language understanding program SHRDLU, Eugene Charniak's story understanding work, Thorne McCarty's work on legal reasoning, and some other projects. This generated a great deal of excitement in the field of AI. It also generated controversy because it proposed an alternative to the logic approach that had been one of the mainstay paradigms for AI. At SRI International, Jeff Rulifson, Jan Derksen, and Richard Waldinger developed QA4 which built on the constructs in Planner and introduced a context mechanism to provide modularity for expressions in the database. Earl Sacerdoti and Rene Reboh developed QLISP, an extension of QA4 embedded in INTERLISP, providing Planner-like reasoning embedded in a procedural language and developed in its rich programming environment. QLISP was used by Richard Waldinger and Karl Levitt for program verification, by Earl Sacerdoti for planning and execution monitoring, by Jean-Claude Latombe for computer-aided design, by Nachum Dershowitz for program synthesis, by Richard Fikes for deductive retrieval, and by Steven Coles for an early expert system that guided use of an econometric model. Computers were expensive. They had only a single slow processor and their memories were very small by comparison with today. So Planner adopted some efficiency expedients including the following: Backtracking was adopted to economize on the use of time and storage by working on and storing only one possibility at a time in exploring alternatives. A unique name assumption was adopted to save space and time by assuming that different names referred to different objects. For example, names like Peking (previous PRC capital name) and Beijing (current PRC capital transliteration) were assumed to refer to different objects. A closed-world assumption could be implemented by conditionally testing whether an attempt to prove a goal exhaustively failed. Later this capability was given the misleading name "negation as failure" because for a goal G it was possible to say: "if attempting to achieve G exhaustively fails then assert (Not G)." == The genesis of Prolog == Gerry Sussman, Eugene Charniak, Seymour Papert and Terry Winograd visited the University of Edinburgh in 1971, spreading the news about Micro-Planner and SHRDLU and casting doubt on the resolution uniform proof procedure approach that had been the mainstay of the Edinburgh Logicists. At the University of Edinburgh, Bruce Anderson implemented a subset of Micro-Planner called PICO-PLANNER, and Julian Davies (1973) implemented essentially all of Planner. According to Donald MacKenzie, Pat Hayes recalled the impact of a visit from Papert to Edinburgh, which had become the "heart of artificial intelligence's Logicland," according to Papert's MIT colleague, Carl Hewitt. Papert eloquently voiced his critique of the resolution approach dominant at Edinburgh "…and at least one person upped sticks and left because of Papert." The above developments generated tension among the Logicists at Edinburgh. These tensions were exacerbated when the UK Science Research Council commissioned Sir James Lighthill to write a report on the AI research situation in the UK. The resulting report [Lighthill 1973; McCarthy 1973] was highly critical although SHRDLU was favorably mentioned. Pat Hayes visited Stanford where he learned about Planner. When he returned to Edinburgh, he tried to influence his friend Bob Kowalski to take Planner into account in their joint work on automated theorem proving. "Resolution theorem-proving was demoted from a hot topic to a relic of the misguided past. Bob Kowalski doggedly stuck to his faith in the potential of resolution theorem proving. He carefully studied Planner.”. Kowalski [1988] states "I can recall trying to convince Hewitt that Planner was similar to SL-resolution." But Planner was invented for the purposes of the procedural embedding of knowledge and was a rejection of the resolution uniform proof procedure paradigm. Colmerauer and Roussel recalled their reaction to learning about Planner in the following way: "While attending an IJCAI convention in September ‘71 with Jean Trudel, we met Robert Kowalski again and heard a lecture by Terry Winograd on natural language processing. The fact that he did not use a unified formalism left us puzzled. It was at this time that we learned of the existence of Carl Hewitt’s programming language, Planner. The lack of formalization of this language, our ignorance of Lisp and, above all, the fact that we were absolutely devoted to logic meant that this work had little influence on our later research." In the fall of 1972, Philippe Roussel implemented a language called Prolog (an abbreviation for PROgrammation en LOGique – French for "programming in logic"). Prolog programs are generically of the following form (which is a special case of the backward-chaining in Planner): When goal Q, goal P1 and ... and goal Pn Prolog duplicated the following aspects of Micro-Planner: Pattern directed invocation of procedures from goals (i.e. backward chaining) An indexed data base of pattern-directed procedures and ground sentences. Giving up on the completeness paradigm that had characterized previous work on theorem proving and replacing it with the programming language procedural embedding of knowledge paradigm. Prolog also duplicated the following capabilities of Micro-Planner which were pragmatically useful for the computers of the era because they saved space and time: Backtracking control structure Unique Name Assumption by which different names are assumed to refer to distinct entities, e.g., Peking and Beijing are assumed to be different. Reification of Failure. The way that Planner established that something was provable was to successfully attempt it as a goal and the way that it establish that something was unprovable was to attempt it as a goal and explicitly fail. Of course the other possibility is that the attempt to prove the goal runs forever and never returns any value. Planner also had a (not expression) construct which succeeded if expression failed, which gave rise to the “Negation as Failure” terminology in Planner. Use of the Unique Name Assumption and Negation as Failure became more questionable when attention turned to Open Systems. The following capabiliti
Ramification problem
In philosophy and artificial intelligence (especially, knowledge based systems), the ramification problem is concerned with the indirect consequences of an action. It might also be posed as how to represent what happens implicitly due to an action or how to control the secondary and tertiary effects of an action. It is strongly connected to, and is opposite the qualification side of, the frame problem. Limit theory helps in operational usage. For instance, in KBE derivation of a populated design (geometrical objects, etc., similar concerns apply in shape theory), equivalence assumptions allow convergence where potentially large, and perhaps even computationally indeterminate, solution sets are handled deftly. Yet, in a chain of computation, downstream events may very well find some types of results from earlier resolutions of ramification as problematic for their own algorithms.
John F. Sowa
John Florian Sowa (born 1940) is an American computer scientist, an expert in artificial intelligence and computer design, and the inventor of conceptual graphs. == Biography == Sowa received a BS in mathematics from Massachusetts Institute of Technology in 1962, an MA in applied mathematics from Harvard University in 1966, and a PhD in computer science from the Vrije Universiteit Brussel in 1999 with a dissertation titled "Knowledge Representation: Logical, Philosophical, and Computational Foundations". Sowa spent most of his professional career at IBM, starting in 1962 at IBM's applied mathematics group. Over the decades he has researched and developed emerging fields of computer science from compilers, programming languages, and system architecture to artificial intelligence and knowledge representation. In the 1990s Sowa was associated with the IBM Educational Center in New York. Over the years he taught courses at the IBM Systems Research Institute, Binghamton University, Stanford University, the Linguistic Society of America and the Université du Québec à Montréal. He is a fellow of the Association for the Advancement of Artificial Intelligence. After early retirement at IBM, Sowa in 2001 cofounded VivoMind Intelligence, Inc. with Arun K. Majumdar. With this company he was developing data-mining and database technology, more specifically high-level "ontologies" for artificial intelligence and automated natural language understanding. Currently Sowa is working with Kyndi Inc., also founded by Majumdar. John Sowa is married to the philologist Cora Angier Sowa, and they live in Croton-on-Hudson, New York. == Work == Sowa's research interests since the 1970s were in the field of artificial intelligence, expert systems and database query linked to natural languages. In his work he combines ideas from numerous disciplines and eras modern and ancient, for example, applying ideas from Aristotle, the medieval scholastics to Alfred North Whitehead and including database schema theory, and incorporating the model of analogy of Islamic scholar Ibn Taymiyyah in his works. === Conceptual graph === Sowa invented conceptual graphs, a graphic notation for logic and natural language, based on the structures in semantic networks and on the existential graphs of Charles S. Peirce. He introduced the concept in the 1976 article "Conceptual graphs for a data base interface" in the IBM Journal of Research and Development. He elaborated upon it in the 1983 book Conceptual structures: information processing in mind and machine. In the 1980s, this theory had "been adopted by a number of research and development groups throughout the world. International conferences on conceptual structures (ICCS) have been held since 1993, following a series of conceptual graph workshops that began in 1986. === Sowa's law of standards === In 1991, Sowa first stated his Law of Standards: "Whenever a major organization develops a new system as an official standard for X, the primary result is the widespread adoption of some simpler system as a de facto standard for X." Like Gall's law, The Law of Standards is essentially an argument in favour of underspecification. Examples include: The introduction of PL/I resulting in COBOL and FORTRAN becoming the de facto standards for business and scientific programming respectively The introduction of Algol-68 resulting in Pascal becoming the de facto standard for academic programming The introduction of the Ada language resulting in C becoming the de facto standard for US Department of Defense programming The introduction of OS/2 resulting in Windows becoming the de facto standard for desktop OS The introduction of X.400 resulting in SMTP becoming the de facto standard for electronic mail The introduction of X.500 resulting in LDAP becoming the de facto standard for directory services == Publications == 1984. Conceptual Structures - Information Processing in Mind and Machine. The Systems Programming Series, Addison-Wesley 1991. Principles of Semantic Networks. Morgan Kaufmann. Mineau, Guy W; Moulin, Bernard; Sowa, John F, eds. (1993). Conceptual Graphs for Knowledge Representation. LNCS. Vol. 699. doi:10.1007/3-540-56979-0. ISBN 978-3-540-56979-4. S2CID 32275791. 1994. International Conference on Conceptual Structures (2nd : 1994 : College Park, Md.) Conceptual structures, current practices : Second International Conference on Conceptual Structures, ICCS'94, College Park, Maryland, USA, August 16–20, 1994 : proceedings. William M. Tepfenhart, Judith P. Dick, John F. Sowa, eds. Ellis, Gerard; Levinson, Robert; Rich, William; Sowa, John F, eds. (1995). Conceptual Structures: Applications, Implementation and Theory. LNCS. Vol. 954. doi:10.1007/3-540-60161-9. ISBN 978-3-540-60161-6. S2CID 27300281. Lukose, Dickson; Delugach, Harry; Keeler, Mary; Searle, Leroy; Sowa, John, eds. (1997). Conceptual Structures: Fulfilling Peirce's Dream. LNCS. Vol. 1257. doi:10.1007/BFb0027865. ISBN 3-540-63308-1. S2CID 1934069. 2000. Knowledge representation : logical, philosophical, and computational foundations, Brooks Cole Publishing Co., Pacific Grove Articles, a selection Sowa, J. F. (July 1976). "Conceptual Graphs for a Data Base Interface". IBM Journal of Research and Development. 20 (4): 336–357. doi:10.1147/rd.204.0336. Sowa, J. F.; Zachman, J. A. (1992). "Extending and formalizing the framework for information systems architecture". IBM Systems Journal. 31 (3): 590–616. doi:10.1147/sj.313.0590. 1992. "Conceptual Graph Summary"; In: T.E. Nagle et al. (Eds.). Conceptual Structures: Current Research and Practice. Chichester: Ellis Horwood. 1995. "Top-level ontological categories." in: International journal of human-computer studies. Vol. 43, Iss. 5–6, Nov. 1995, pp. 669–685 2006. "Semantic Networks". In: Encyclopedia of Cognitive Science.. John Wiley & Sons.
Objective vision
Objective Vision (Object Oriented Visionary) is a project mainly aimed at real-time computer vision and simulation vision of living creatures. it has three sections containing an open-source library of programming functions for using inside the projects, Virtual laboratory for scholars to check the application of functions directly and by command-line code for external and instant access, and the research section consists of paperwork and libraries to expand the scientific prove of works. == Background == The process has been used in the OVC libraries is as same as what's happening when living see a picture, and it's designed to give the researchers to experience the brain's visual cortex most close simulation for picture perception. The OVC was designed to work as a simulated visual cortex that has a critical job in processing and classify the objects to make it easier to work with pictures and graphical perception and processing. The human brain is much more aware of how it solves complex problems such as playing chess or solving algebra equations, which is why computer programmers have had so much success building machines that emulate this type of activity. but when the whole process is still a riddle that how the entities visionary system works. The project was simulated the visionary system by how it starts to convert the signals to image(actually the edges and colors) and then recognizing the shapes to find a relation between brain's information and image. The Objective Visionary system actually is concentrating on the separable sections, this separation gives the application visionary system the excellence processing result, because with this method the system do not waste much time on processing non significant sections and signals. this operation in the Objective Vision project called objective processing and because the O.V. mission is focused on human visionary simulation, so the developer refers with Objective Vision. == History == Objective-Vision is a Human (Natural) Visionary simulation Project developed by Michael Bidollahkhany. Following an explosion of interest during the 21st century were characterized by the maturing of the field and the significant growth of active applications; simulation of visionary systems, visionary based autonomous vehicle guidance, medical imaging (2D and 3D) and automatic surveillance are the most rapidly developing areas. This progress can be seen in an increasing number of software and hardware products on the market, as well as in a number of digital image processing software and APIs and also machine vision courses offered at universities worldwide. Therefore, the OVC project has been released as a research software project in 2016. One of important parts of this project was O.V.C. (Objective Vision Class library), that was designed to able companies and scientists to use the brain's most likely functionalities as visionary libraries to simplify and accelerate the image processing algorithms developments. The project started under MIT copyright license, but since 2018 the project continued as classified based on sponsors opinion. == The Algorithm == As developers claimed the algorithm used in the class library and developer's kit of project has been developed based on natural visionary system, and the functionalities containing image processing, optimization and labeling etc. are mostly upgraded and near techniques. Suppose that we've a picture of a jungle, or somewhere else, with this library developer will be able to manipulate not only the pixel of images for data extraction, but automatically based on which algorithm is used and image quality, he can manipulate directly a list of objects, same pixels and every data project needs to have, said the developer in his lecture answering how the algorithm works. === Viewpoint === For long times digital image processing and storing, was actually by processing just pixels; this Project tries to present a new kind of image processing and even storing, "objective vision" or "object-oriented visionary" is called. This project officially launched in May 2016, with the aim of making more adaptation between Computer Vision (Include Visionary, Digital image processing, discernment and even Perception) and Human Visual System; about development of the project: "...so we decided to research on Human Vision System, besides we worked on Artificial Retinal image processing and new visionary optimization unit(Presented at Istanbul Technical University Conference(Turkey 2015-2016)) and grew our research to Visionary CORTEX of Brain", Michael Bidollahkhany said. == Applications == The OVC application areas include: 2D and 3D feature toolkits Egomotion estimation Human–computer interaction (HCI) Mobile robotics Motion understanding Object identification Segmentation and recognition Stereopsis stereo vision: depth perception from two cameras Structure from motion (SFM) Motion tracking == Programming language == In first initial release of Objective Visionary Project the algorithm has been written in C++ and C#, and the virtual laboratory has been developed in C# and Delphi. Based on developers last lecture since the second release the complete algorithm has been re-written in C# based on .Net Core 1.0 to make it easier to work on different operating systems.
Rohit Chadda
Rohit Chadda (born 26 August 1982) is an Indian investment banker and entrepreneur, who is the President & COO of Times Network. He leads the tech business portfolio and AI transformation of Times Group covering verticals like media tech, OTT, fintech, health tech, edu tech, ecommerce, gaming and sports. Previously, CEO of the digital business at Essel Group (Zee Entertainment, Zee Media and DNA), he was the co-founder of online food ordering platform Foodpanda. He is also the founder of omni-channel digital payments platform PayLo. He has been attributed for the turnaround of Zee Digital driving 4x growth in 2 years and bringing Zee's digital business to the second position on ComScore from ninth position making Zee the second largest digital media group in India. He has been featured among Top Tech CEOs of the decade (2010–2020) in India and was featured among Fortune 40 under 40 in 2015. == Education and early career == Chadda graduated from Delhi Technological University (formerly Delhi College of Engineering) with a degree in computer engineering and worked as a software engineer for Computer Sciences Corporation. In 2007 he joined Indian Institute of Management Calcutta to do his MBA after which he worked at Merrill Lynch as an investment banker in United Kingdom. He took an internal transfer to India in 2011. == Career == === Foodpanda === Chadda began his career in 2012 when he co-founded foodpanda. foodpanda expanded to around 40 countries before being bought by Delivery Hero. Before foodpanda got popular, he joked that he delivered pizza for a living. foodpanda had raised a total investment of over US$300 million till 2015. Chadda in the middle of 2015 stepped down from day-to-day responsibilities at Foodpanda to launch his digital payments startup. Foodpanda was acquired by its global competitor Delivery Hero in 2016. === Paylo === In 2015, he launched an omni-channel digital payments platform PayLo which acquired the in-restaurant payments app Ruplee in March 2016 for an undisclosed sum. PayLo was successful in the wake of demonetisation in India and expanded pan-India before being acquired by Immortal Technologies. Chadda believes that execution is more important than the idea to make a startup successful and the key challenge for experienced professionals to work in a startup environment is to unlearn what they have previously learned. PayLo acquired Ruplee before being itself acquired by Immortal Technologies. === Zee Group === Chadda took over as CEO of digital publishing of Zee Group in May 2019. Since 2017, he had led global product and strategy for Zee Group launching ZEE5, the flagship OTT of Zee Entertainment, across 170+ countries. Since June 2019, Zee Digital, the online arm of the Zee group, has registered the highest growth year-on-year among the top media publishers in India. Times Internet Limited, Network 18 Group, and India Today Group have grown by 45%, 21%, and 22% respectively from June 2020 over June 2019 while Zee Digital witnessed a growth of 123% over the same period. Zee Digital achieved its first milestone in September 2019 by crossing 100 million unique monthly visitors and was ranked 6th in the news and information category on ComScore India rankings at the time. Later in the month of March 2020 it crossed 150 million unique monthly visitors mark moving to 4th position. Further in May 2020 Zee Digital moved to 3rd position by crossing 185 million unique monthly visitors mark before finally ranking 2nd position in June 2020 in the ComScore rankings among all digital media groups in India. Chadda has led the transformation of the business of Zee Digital by scaling it to over 200 million users from 60 million users making it the second-largest digital media group in India. He attributes the growth from rank 9 to rank 2 in one year to the data and technology driven approach to content and the focus on vernacular languages. During his tenure, Zee Digital launched 8 new brand websites and 3 new languages to expand the product portfolio to 20 brands and 12 languages. During the US elections in November 2020, Zee Digital launched the English global news channel WION through a digital first approach across Asia Pacific, Middle East, UK and North America. Chadda launched Zee's UGC short video platform HiPi in the midst of the TikTok ban in India. Hipi was first launched within ZEE5 app ecosystem to capitalise on the reach of the OTT platform. After the success of the POC, he launched a standalone app for HiPi. HiPi is a short video platform that provides a complete video creation ecosystem along with news avenues of monetisation to content creators. He plans to use Zee's network reach of 600 million broadcast viewers and 300 million digital users to get creators on HiPi. HiPi launched India's first digital star hunt to allow users to audition for ZEE5 original shows through the short video platform. === Times Group === Chadda took over as President & COO of Times Network in September 2022. Leading the digital transformation of the group Chadda launched 11 new products in 18 months expanding the group's presence to various verticals in the tech business like fintech, health tech, edu tech, auto tech, OTT, ecommerce and gaming while extending the news vertical into business news, tech news and various vernacular languages. Within 4 months of his stint, in January 2023 he launched the digital platform for ET Now, targeting Gen Z, early jobbers and first time investors and laying the foundation for the fintech expansion for the brand. Since then, the product has expended to Hindi language targeting the larger Indian audience through the launch of ET Now Swadesh and further expanding to fintech business by launching ET Now Advisor, a distribution business focussing to upselling of cards, loans etc. to consumers by educating them and enabling them to make the right choices. ET Now reached 10 million users within the first 20 days of launch and became the No.1 business news channel on YouTube with 200 million views in April and May 2024. Expanding to health-tech, he launched AI powered daily health companion Health & Me in the presence of actor & fitness enthusiast Milind Soman. Chadda unveiled the auto-tech platform for Times Drive together with Union Minister of Road Transport and Highways, Nitin Gadkari showcasing the AI assisted platform that helps consumers make the right decisions when it comes to their automotive needs. In order to expand the group's presence into tech and gaming, Chadda acquired India's largest and most popular tech magazine Digit along with their digital platforms Digit.in and Skoar.gg in June 2024. Within a year, he was able to turnaround Digit's business with Digit.in becoming the No.1 Tech news platform in India in April 2025. Times Network launched college discovery platform unilist.in to enable students and parents search for the right course and institute for their higher education needs. With a focus on sports and gaming, Chadda launched India's first Inter-college esports championship under the brand of SKOAR College Gaming Championship. Times Network launched its OTT app Times Play under his leadership. The platform expanded its presence in the US through a partnership with Sling TV. He launched Pickleball Now which is the World's first TV channel focussed on the sport of Pickleball covering tournaments and leagues across the World. The channel has presence on TV and digital platforms and is being distributed to global markets through partnerships with BOTIM, Distro TV, Yupp TV and Rumble. In India, the channel is available on Jio TV, Jio TV+, Airtel Xtream Play, OTT Play, Dailyhunt. Times Group has launched India's Official Pickleball League affiliated with Indian Pickleball Association and Global Pickelball Federation which shall also be streamed live on Pickleball Now from 1st to 7th Dec 2025. === Investing and speaking === Chadda is a mentor at Esselerator, a Startup accelerator by Subhash Chandra Foundation. Esselerator is an initiative by Subhash Chandra, a billionaire Media baron, to promote and support tech entrepreneurs in domains like Media, Fintech and Education. Its powered by TiE Mumbai. Chadda is an angel investor in multiple technology startups like online school aggregator platform SchoolForSure.com. In 2019, he spoke at DPS to students on starting a business. At the time he remained CEO of Zee group's digital business division. == Philanthropy == Chadda organised a £1 mliion charity bike ride in aid of the British Asian Trust which saw participation by the Prince of Wales. Chadda presented the Prince of Wales with a cycling vest, which was said to be for his grandchildren. Chadda supports a non-profit organisation Mukkamaar founded by Bollywood actress Ishita Sharma that works towards fighting crime against women by teaching free self defence to young girls. He is helping the organisation launch their digital program through a WhatsApp-based chatbot. == A