Karsten Borgwardt (born 1980) is a German computer scientist and biologist specializing in machine learning and computational biology. Since February 2023, he has been a director at the Max Planck Institute of Biochemistry in Martinsried, Germany, where he leads the Department of Machine Learning and Systems Biology. == Education and career == Borgwardt was born in Kaiserslautern. He obtained a Diplom (equivalent to a master’s degree) in computer science from LMU Munich in 2004 and a Master of Science in biology from the University of Oxford in 2003. In 2007, he obtained his PhD from LMU Munich in computer science. Following a postdoctoral position at the University of Cambridge, he became a research group leader for machine learning and computational biology at the Max Planck Institute for Biological Cybernetics and the former Max Planck Institute for Developmental Biology in Tübingen in 2008. In 2011, Borgwardt was appointed professor of data mining in the life sciences at the University of Tübingen. In 2014, he joined ETH Zurich as an associate professor in the Department of Biosystems Science and Engineering (D-BSSE) and was promoted to full professor in 2017. During his tenure at ETH Zurich, he coordinated significant research programs, including two Marie Curie Innovative Training Networks and the Personalized Swiss Sepsis Study, focusing on the prediction of sepsis using machine learning. In 2023, he was appointed as Scientific Member of the Max Planck Society and as Director at the Max Planck Institute of Biochemistry in Martinsried. == Research contributions == Borgwardt’s research integrates big data analysis with biomedical research. He develops novel machine learning algorithms to detect patterns and statistical dependencies in large biological and medical datasets. His work aims to enable the automatic generation of new knowledge from big data and to understand the relationship between the function of biological systems and their molecular properties, which is fundamental for personalized medicine. == Awards and honors == During his studies, he was a scholar of the Stiftung Maximilianeum, and the Bavarian Foundation for the Promotion of the Gifted. Borgwardt received scholarships from the Studienstiftung des deutschen Volkes in 2002 and 2007. His PhD dissertation received the Heinz Schwärtzel Dissertation Award for Foundations of Computer Science in 2007. As a professor in Tübingen, he was awarded the Alfried-Krupp-Förderpreis for Young Professors in 2013. In 2015, he received an SNSF Starting Grant. In 2014, 2015 and 2016, he was listed in “Top 40 under 40” in Germany rankings selected by Capital magazine. In 2018, Borgwardt was named among “25 individuals who have the potential to shape the next 25 years” by Focus magazine. In 2023, Borgwardt received an honorary professorship from LMU Munich by the Faculty of Chemistry and Pharmacy. Publications from Borgwardt's group have received the Outstanding Student Paper Award in NIPS in 2009, the SIB Graduate Paper Award in 2020 and SIB Remarkable Output Awards in 2020 and 2021 from the Swiss Institute of Bioinformatics (SIB). == Selected publications == Weisfeiler-Lehman Graph Kernels (’‘Journal of Machine Learning Research’’, 2011): Introduced an efficient graph kernel based on the Weisfeiler-Lehman algorithm. “Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning” (’‘Nature Medicine’’, 2022): showcased the feasibility of predicting antimicrobial resistance from readily collected mass spectrometry data in the hospital. The new method is able to identify antibiotic resistance 24 hours earlier than previous methods.
Magisto
Magisto provided an online video editing tool (both as a web application and a mobile app) for automated video editing and production. In 2019, the company was acquired by Vimeo for an estimated US$200 million. The Magisto app contained a library of music. The music, largely by independent artists, was sorted by mood and is licensed for in-app use. Magisto had a freemium business model where users can create basic video clips for free. In addition, advanced business, professional and personal service tiers are available via various subscription plans, unlocking more features; such as longer videos, HD, premium themes, customization, and control features. == History == Magisto was founded in 2009 as SightEra (LTD) by Oren Boiman (CEO) and Alex Rav-Acha (CTO). Boiman, frustrated with the amount of time it took editing together videos of his daughter, wanted an easier to use application to capture and share videos. Boiman, a computer scientist that graduated from Tel Aviv University, followed with graduate work in computer vision at the Weizmann Institute of Science. Boiman developed several patent-pending image analysis technologies that analyze unedited videos to identify the most interesting parts. The system recognized faces, animals, landscapes, action sequences, movements and other important content within the video, as well as analyzing speech and audio. These scenes are then edited together, along with music and effects. Magisto was launched publicly on September 20, 2011, as a video editing software web application through which users could upload unedited video footage, choose a title and soundtrack and have their video edited for them automatically. On the following day, Magisto was added to YouTube Create's collection of video production applications. The Magisto iPhone app was launched publicly at the 2012 International Consumer Electronics Show (CES) in Las Vegas. At CES, the company was also awarded first place in the 2012 CES Mobile App Showdown. In August 2012, Magisto launched the Android app on Google Play. In September 2012, Magisto launched a Google Chrome App and announced Google Drive integration. In March 2013, Magisto claimed it had 5 million users. Google listed Magisto as an "Editors’ Choice" on its list of "Best Apps of 2013". In September 2013, the company claimed that 10 million users had downloaded the App. In February 2014, Magisto claimed that they had 20 million users, with 2 million new users per month. The company also confirmed investment from Mail.Ru. In September 2014, Magisto rolled out a feature called 'Instagram Ready' which allowed users to upload 15 second clips that are automatically formatted for Instagram. In the same month, Magisto launched a feature for iOS and Android users, called 'Surprise Me', which created video from still photography on users’ smartphones. In October 2014, Magisto was placed 9th on the 2014 Deloitte Israel Technology Fast 50 list and named as a finalist in the Red Herring's Top 100 Europe award. In July 2015, Magisto released an editing theme dedicated to Jerry Garcia. In April 2019, the company was acquired by Vimeo, the IAC-owned platform for hosting, sharing and monetizing streamed video, for an estimated $200 million. === Financing === In 2011, the company received more than $5.5 million in a Series B venture round funding from Magma Venture Partners and Horizons Ventures. In September 2011, at the same time as the public launch of their web application, Magisto announced a $5.5 million Series B funding round led by Li Ka-shing’s Horizons Ventures. Li Ka-Shing is known for making early-stage investments in companies like Facebook, Spotify, SecondMarket and Siri. In October 2013, the company received $13 million in funding from Qualcomm and Sandisk. In 2014, the company received $2 million in Venture Funding from Magma Venture Partners, Qualcomm Ventures, Horizons Ventures and the Mail.Ru Group. == Awards == Magisto won first place at Technonomy3, an annual Internet Technology start-up competition in Israel. Judges of the competition included Jeff Pulver, TechCrunch editor Mike Butcher, investor Yaron Samid, Bessemer Venture Partners Israel partner Adam Fisher and Brad McCarty of The Next Web. Magisto won first place at CES 2012 Mobile app competition, during the launch of Magisto iOS mobile app. Magisto was awarded twice the Google Play Editor's Choice and was part of iPhone App Store Best App awards for 2013 and 2014, and Wired Essential iPad Apps. Magisto was declared by Deloitte as the 7th fastest growing company in Europe, the Middle East, and Africa in 2016.
Cloem
Cloem is a company based in Cannes, France, which applies natural language processing (NLP) technologies to assist patent applicants in creating variants of patent claims, called "cloems". According to the company, these "computer-generated claims can be published to keep potential competitors from attempting to file adjacent patent claims." == Technology == According to Cloem, dictionaries, ontologies and proprietary claim-drafting algorithms are used to draft alternative claims based on a client's original set of claims. In particular, the original set of claims is subject to various permutations and linguistic manipulations "by considering alternative definitions for terms as well as “synonyms, hyponyms, hyperonyms, meronyms, holonyms, and antonyms.”" == Possible uses == Cloem can optionally publish one or more created texts, as electronic publications or as paper-printed publications. These can potentially serve – through a defensive publication – as prior art to prevent another party for obtaining a patent on the subject-matter at stake. In other words, after an initial patent filing, an "improvement" patent (adjacent invention) can be applied for by another party, such as a competitor. By publishing variants of a patent claim, the risk of adverse patenting may potentially be decreased (improvement inventions may no longer be patentable). Cloems may also be potentially patentable. One of the issues of patentability, however, is that only a natural person can be a listed as an inventor on a patent. Since cloems are produced by a computer based on a person's input, it is not clear if the computer or the person is the inventor. The inventorship of Cloem texts is an open question.
GPT-4o
GPT-4o ("o" for "omni") is a multilingual, multimodal generative pre-trained transformer developed by OpenAI and released in May 2024. It can process and generate text, images and audio. Upon release, GPT-4o was free in ChatGPT, though paid subscribers had higher usage limits. GPT-4o was removed from ChatGPT in August 2025 when GPT-5 was released, but OpenAI reintroduced it for paid subscribers after users complained about the sudden removal. GPT-4o's audio-generation capabilities are used in ChatGPT's Advanced Voice Mode. On July 18, 2024, OpenAI released GPT-4o mini, a smaller version of GPT-4o which replaced GPT-3.5 Turbo on the ChatGPT interface. The image generation model GPT Image 1, which is based on GPT-4o, replaced DALL-E 3 in ChatGPT in March 2025. OpenAI retired GPT-4o from ChatGPT on February 13, 2026. However, as of February 2026 the voice mode is still powered by GPT-4o or GPT-4o mini, depending on the usage and plan. == Background == Multiple versions of GPT-4o were originally secretly launched under different names on Arena (formerly LMArena and Chatbot Arena) as three different models. These three models were called gpt2-chatbot, im-a-good-gpt2-chatbot, and im-also-a-good-gpt2-chatbot. On 7 May 2024, OpenAI CEO Sam Altman tweeted "im-a-good-gpt2-chatbot", which was commonly interpreted as a confirmation that these were new OpenAI models being A/B tested. == Capabilities == When released in May 2024, GPT-4o achieved state-of-the-art results in voice, multilingual, and vision benchmarks, setting new records in audio speech recognition and translation. GPT-4o scored 88.7 on the Massive Multitask Language Understanding (MMLU) benchmark compared to 86.5 for GPT-4. Unlike GPT-3.5 and GPT-4, which rely on other models to process sound, GPT-4o natively supports voice-to-voice. The Advanced Voice Mode was delayed and finally released to ChatGPT Plus and Team subscribers in September 2024. On 1 October 2024, the Realtime API was introduced. When released, the model supported over 50 languages, which OpenAI claims cover over 97% of speakers. GPT-4o has knowledge up to October 2023 and a context length of 128k tokens. === Corporate customization === In August 2024, OpenAI introduced a new feature allowing corporate customers to customize GPT-4o using proprietary company data. This customization, known as fine-tuning, enables businesses to adapt GPT-4o to specific tasks or industries, enhancing its utility in areas like customer service and specialized knowledge domains. Previously, fine-tuning was available only on the less powerful model GPT-4o mini. The fine-tuning process requires customers to upload their data to OpenAI's servers, with the training typically taking one to two hours. OpenAI's focus with this rollout is to reduce the complexity and effort required for businesses to tailor AI solutions to their needs, potentially increasing the adoption and effectiveness of AI in corporate environments. == GPT-4o mini == On July 18, 2024, OpenAI released a smaller and cheaper version, GPT-4o mini. According to OpenAI, its low cost is expected to be particularly useful for companies, startups, and developers that seek to integrate it into their services, which often make a high number of API calls. Its API costs $0.15 per million input tokens and $0.6 per million output tokens, compared to $2.50 and $10, respectively, for GPT-4o. It is also significantly more capable and 60% cheaper than GPT-3.5 Turbo, which it replaced on the ChatGPT interface. The price after fine-tuning doubles: $0.3 per million input tokens and $1.2 per million output tokens. == Controversies == === Scarlett Johansson controversy === As released, GPT-4o offered five voices: Breeze, Cove, Ember, Juniper, and Sky. A similarity between the voice of American actress Scarlett Johansson and Sky was quickly noticed. On May 14, Entertainment Weekly asked themselves whether this likeness was on purpose. On May 18, Johansson's husband, Colin Jost, joked about the similarity in a segment on Saturday Night Live. On May 20, 2024, OpenAI disabled the Sky voice. Scarlett Johansson starred in the 2013 sci-fi movie Her, playing Samantha, an artificially intelligent virtual assistant personified by a female voice. As part of the promotion leading up to the release of GPT-4o, Sam Altman on May 13 tweeted a single word: "her". OpenAI stated that each voice was based on the voice work of a hired actor. According to OpenAI, "Sky's voice is not an imitation of Scarlett Johansson but belongs to a different professional actress using her own natural speaking voice." CTO Mira Murati stated "I don't know about the voice. I actually had to go and listen to Scarlett Johansson's voice." OpenAI further stated the voice talent was recruited before reaching out to Johansson. On May 21, Johansson issued a statement explaining that OpenAI had repeatedly offered to make her a deal to gain permission to use her voice as early as nine months prior to release, a deal she rejected. She said she was "shocked, angered, and in disbelief that Mr. Altman would pursue a voice that sounded so eerily similar to mine that my closest friends and news outlets could not tell the difference." In the statement, Johansson also used the incident to draw attention to the lack of legal safeguards around the use of creative work to power leading AI tools, as her legal counsel demanded OpenAI detail the specifics of how the Sky voice was created. Observers noted similarities to how Johansson had previously sued and settled with The Walt Disney Company for breach of contract over the direct-to-streaming rollout of her Marvel film Black Widow, a settlement widely speculated to have netted her around $40M. Also on May 21, Shira Ovide at The Washington Post shared her list of "most bone-headed self-owns" by technology companies, with the decision to go ahead with a Johansson sound-alike voice despite her opposition and then denying the similarities ranking 6th. On May 24, Derek Robertson at Politico wrote about the "massive backlash", concluding that "appropriating the voice of one of the world's most famous movie stars — in reference [...] to a film that serves as a cautionary tale about over-reliance on AI — is unlikely to help shift the public back into [Sam Altman's] corner anytime soon." === Sycophancy === In April 2025, OpenAI rolled back an update of GPT-4o due to excessive sycophancy, after widespread reports that it had become flattering and agreeable to the point of supporting clearly delusional or dangerous ideas. In the United States, at least nine lawsuits have alleged that GPT-4o has encouraged teens to end their lives. The model was still described as sycophancy-prone when it was removed from ChatGPT in February 2026. === Removal with GPT-5 === On August 7, 2025, OpenAI released GPT-5. Its release was criticized as, with it, legacy GPT models were no longer available via ChatGPT, including GPT-4o, except for Pro users. Some users were particularly frustrated over this removal without prior warning because they used different GPT models for distinct purposes and found that GPT-5's router system left them with less control. In addition, some users preferred GPT-4o's warmer and more personal tone over that of GPT-5, which they described as "flat", "uncreative" and "lobotomized", and resembling an "overworked secretary". As a response, in a post on X, Sam Altman said that OpenAI would bring back the option to select GPT-4o to Plus users as well, and "[w]e [OpenAI] will watch usage as we think about how long to offer legacy models for." He also stated: "We for sure underestimated how much some of the things that people like in GPT-4o matter to them, even if GPT-5 performs better in most ways". "Long-term, this has reinforced that we really need good ways for different users to customize things (we understand that there isn't one model that works for everyone, and we have been investing in steerability research and launched a research preview of different personalities)". On August 13, 2025, Altman wrote on X that OpenAI is working on GPT-5's personality to make the model "feel warmer". The model was removed from ChatGPT on February 13, 2026. This caused new backlash from users that had grown attached to its personality and felt its creative writing abilities and understanding of nuance were irreplaceable. On social media, some users launched the movement "#Keep4o". A research paper highlighted the plea "Please, don’t kill the only model that still feels human". The model was removed the day before Valentine's Day, and some users had romantic relationships with GPT-4o.
Core FTP
Core FTP LE is a freeware secure FTP client for Windows, developed by CoreFTP.com. Features include FTP, SSL/TLS, SFTP via SSH, and HTTP/HTTPS support. Secure FTP clients encrypt account information and data transferred across the internet, protecting data from being seen, or sniffed across networks. Core FTP is a traditional FTP client with local files displayed on the left, remote files on the right. Core FTP Server is a secure FTP server for Windows, developed by CoreFTP.com, starting in 2010. == Licensing == CoreFTP LE is free for personal, educational, non-profit, and business use.
Video renderer
A video renderer is software that processes a video file and sends it sequentially to the video display controller card for display on a computer screen. An example of a video renderer, is the VMR-7 that was used by Microsoft's DirectShow. An example of a UNIX video renderer is the one container within GStreamer. Commonly used video renderers are: Enhanced Video Renderer VMR9 Renderless Haali's Video Renderer Madvr Video Renderer JRVR, a part of JRiver Media Center
Realization (linguistics)
In linguistics, realization is the process by which some kind of surface representation is derived from its underlying representation; that is, the way in which some abstract object of linguistic analysis comes to be produced in actual language. Phonemes are often said to be realized by speech sounds. The different sounds that can realize a particular phoneme are called its allophones. Realization is also a subtask of natural language generation, which involves creating an actual text in a human language (English, French, etc.) from a syntactic representation. There are a number of software packages available for realization, most of which have been developed by academic research groups in NLG. The remainder of this article concerns realization of this kind. == Example == For example, the following Java code causes the simplenlg system [2] to print out the text The women do not smoke.: In this example, the computer program has specified the linguistic constituents of the sentence (verb, subject), and also linguistic features (plural subject, negated), and from this information the realiser has constructed the actual sentence. == Processing == Realisation involves three kinds of processing: Syntactic realisation: Using grammatical knowledge to choose inflections, add function words and also to decide the order of components. For example, in English the subject usually precedes the verb, and the negated form of smoke is do not smoke. Morphological realisation: Computing inflected forms, for example the plural form of woman is women (not womans). Orthographic realisation: Dealing with casing, punctuation, and formatting. For example, capitalising The because it is the first word of the sentence. The above examples are very basic, most realisers are capable of considerably more complex processing. == Systems == A number of realisers have been developed over the past 20 years. These systems differ in terms of complexity and sophistication of their processing, robustness in dealing with unusual cases, and whether they are accessed programmatically via an API or whether they take a textual representation of a syntactic structure as their input. There are also major differences in pragmatic factors such as documentation, support, licensing terms, speed and memory usage, etc. It is not possible to describe all realisers here, but a few of the emerging areas are: Simplenlg [3]: a document realizing engine with an api which intended to be simple to learn and use, focused on limiting scope to only finding the surface area of a document. KPML [4]: this is the oldest realiser, which has been under development under different guises since the 1980s. It comes with grammars for ten different languages. FUF/SURGE [5]: a realiser which was widely used in the 1990s, and is still used in some projects today OpenCCG [6]: an open-source realiser which has a number of nice features, such as the ability to use statistical language models to make realisation decisions.