A digital media service (DMS) is an online service provider that sells access to digital library of content such as films, software, games, images, literature, etc. While no transfer of property is made, a nearly perfect duplicate of the data (song movie, etc.) is made on a customer's computer. Content is either primarily hosted on a dedicated server, which is owned by the service provider, or it is hosted primarily on the hard drives of its customers using a P2P protocol with, perhaps, a dedicated server to supplement. == History == One example of the older business model is the iTunes Store, which still markets and prices data as individual retail products. There are no examples of the latter business model in operation yet, but one is currently in development by Global Gaming Factory X and expected to begin operation some time after they acquire The Pirate Bay domain on August 27, 2009. A key difference between the two models is that the model which relies on its customer base for offering their bandwidth for other customers to access customer hosted data can operate at significantly lower costs than a company that seeks to limit data access to a per-download fee in order to supplement the cost of using its own hosting and bandwidth. The P2P model holds the potential for companies to offer unlimited access to the largest data library in the history of the internet to its customers for a reasonably low membership rate that is relevant to the cost of operation. While the market is virtually untouched, the P2P supplemented model will need entrepreneurs who are able to overcome a series of challenges in order to compete with the older business model as well as that which is offered for free (and often against the wishes of copyright holders) by hundreds of P2P communities on the internet. These challenges include, but are not limited to: Offering better data quality, speed, convenience and ease of use, protocol, sense of security, indexing and search organization, site up time, data library size, customer support, advertising, artist/copyright holder incentives and compensation, incentives and compensation for customers hosting data and providing bandwidth, guaranteed seeding (available access to indexed data at all times), than competitors.
Limnu
Limnu was an online whiteboarding app founded in 2015 by David DeBry and David Hart. It allowed users to draw on virtual whiteboards and invite others by e-mail or by sharing a link. Invitees see any changes to the board in real time and, if allowed by the owner of the board, can also draw on the board. The service was accessible through a web application in desktop and mobile web browsers, as well as through an iOS application. It was headquartered in San Mateo, California. == History == In 2018, ZipSocket, a maker of online meeting software acquired Limnu. == Staff Directory == Andrew Kunz - CEO & Founder of ZipSocket Jenny Rice - Product Manager Max Requenes - Software Engineer Henry Maguire - Machine Learning Engineer
India AI Impact Summit 2026
The India AI Impact Summit 2026 (also abbreviated as the AI Impact Summit) was an international summit on artificial intelligence held at Bharat Mandapam, New Delhi, India, from 16 to 21 February 2026. It is the fourth in a series of global AI summits following the Bletchley Park AI Safety Summit in 2023, the AI Seoul Summit in 2024, and the AI Action Summit in Paris in 2025. Organised under the IndiaAI Mission by the Ministry of Electronics and Information Technology, it is the first summit in the series to be hosted by a Global South nation. This series of AI summits will continue with the AI Summit in Geneva to be hosted by Switzerland in 2027. The summit was inaugurated by Prime Minister Narendra Modi on 19 February 2026. The opening ceremony was also addressed by French President Emmanuel Macron and United Nations Secretary-General António Guterres. The summit was attended by over 20 heads of state and a delegation of global technology leaders including Sundar Pichai (Google), Sam Altman (OpenAI), and Demis Hassabis (DeepMind). The event faced criticism for organisational issues, misrepresentation of non-Indian products as Indian, and a perceived focus on trade fair activities over substantive governance. == Background == The AI Impact Summit was an international summit on artificial intelligence (AI) held in New Delhi from 16 to 20 February 2026. It followed the AI Action Summit in Paris in February 2025, the AI Seoul Summit in 2024 and the Bletchley Park AI Safety Summit in 2023. According to Crowell & Moring, the changing summit titles seemed to reflect a broader shift in focus away from AI safety and governance toward practical impact, implementation, and measurable outcomes. Ahead of the summit, an international panel of experts published the second International AI Safety Report. The summit was structured around three foundational pillars, termed "Sutras": People, Planet, and Progress. Seven thematic working groups were established to deliver outcomes across these pillars, covering AI for economic growth and social good; democratising AI resources; inclusion for social empowerment; safe and trusted AI; human capital; science; and resilience, innovation, and efficiency. == Programme == The summit ran over five days, later extended to six following overwhelming public response. Originally scheduled to conclude on 20 February, the event was extended to 21 February with expanded evening hours for the exhibition. === India AI Impact Expo === The India AI Impact Expo, inaugurated by Prime Minister Modi on 16 February, featured over 300 exhibitors from 30 countries across more than 10 thematic pavilions. Pavilions were organised across thematic zones aligned with the summit's three pillars, showcasing AI applications in healthcare, agriculture, education, and sustainable industry. === Leaders' Plenary and CEO Roundtable === The Leaders' Plenary on 19 February brought together heads of state, ministers, and representatives from multilateral institutions to outline national and global priorities on AI governance, infrastructure, and international cooperation. A CEO Roundtable, held the same evening, convened senior executives from global technology and industry firms with government leaders to discuss investment, research collaboration, and deployment of AI systems. === Research Symposium === A Research Symposium on AI and its Impact was held on 18 February, with the IIIT Hyderabad as knowledge partner. Discussions covered sovereign AI infrastructure, global adoption challenges, research breakthroughs, and policy priorities. == Participants == The summit drew delegations from over 100 countries, including more than 20 heads of state and 60 ministers. Notable attendees from the technology industry included Sundar Pichai (Google), Sam Altman (OpenAI), Dario Amodei (Anthropic), Demis Hassabis (Google DeepMind), and Mukesh Ambani (Reliance Industries). Representatives from multilateral institutions included Sangbu Kim of the World Bank. == Announcements and outcomes == === Indian AI models === Several Indian AI models and products were unveiled during the summit. Sarvam AI, an Indian AI laboratory, launched a new generation of large language models, including 30-billion and 105-billion parameter models using a mixture of experts architecture, as well as text-to-speech, speech-to-text, and vision models. Sarvam also introduced the Kaze smartglasses, described as the company's first hardware product, which Prime Minister Modi tested at the expo. The government-backed BharatGen Param2 model, a 17-billion parameter model supporting 22 Indian languages with multimodal capabilities, was also launched at the summit. === Infrastructure commitments === Union Minister Ashwini Vaishnaw outlined India's "whole-of-nation" AI strategy, describing plans to build a "frugal, sovereign and scalable" AI ecosystem. The government announced plans to add more than 20,000 GPUs to India's existing base of 38,000 under the IndiaAI Compute Portal. Microsoft announced at the summit that it was on track to invest US$50 billion by the end of the decade to bring AI to lower-income countries. Goa reaffirmed its commitment to artificial intelligence at the India AI Impact Summit 2026. === Guinness World Record === During the summit, India set a Guinness World Record for the most pledges received for an AI responsibility campaign in 24 hours, with 250,946 valid pledges collected between 16 and 17 February 2026. The campaign, conducted in partnership with Intel India as part of the IndiaAI Mission, exceeded its initial target of 5,000 pledges. == Controversies and criticisms == === Galgotias University incident === On 18 February, Galgotias University faced widespread criticism after a representative presented a robot dog at the university's exhibition pavilion as an indigenous development. Social media users identified the robot as the Unitree Go2, a commercially available product manufactured by Chinese company Unitree Robotics. IT Secretary S. Krishnan stated that the government did not want exhibitors to showcase items that were not their own, and the university was directed to vacate its stall. Galgotias University issued an apology, stating that the representative had been "ill-informed" and was not authorised to speak to the press. The incident drew political reactions, with the Indian National Congress using it to criticise the government. The controversy was amplified after Union IT Minister Ashwini Vaishnaw had earlier shared a video clip of the robot on social media, which was subsequently deleted. === Organisational issues === On day 1 of the Summit, Dhananjay Yadav, a Bengaluru-based entrepreneur had alleged that his product was stolen in the Summit. He called it as a pain for the people in an X post. He further wrote, "Think about this: We paid for flights, accommodation, logistics and even the booth. Only to see our wearables disappear inside a high-security zone". Later, the stolen devices were recovered by The Delhi Police. Bloomberg reported that delegates were left stranded without food or water during a security lockdown ahead of the Prime Minister's visit on 19 February. The summit venue was closed to the public on 19 February for the Prime Minister's visit, leading to criticism from attendees who had registered for that day. === Protests by the Indian Youth Congress (IYC) === On 20 February, some members of the Indian Youth Congress (IYC) carried out protests inside the venue with slogans such as "PM is compromised" and the criticism of the recent trade deal between India and the US. 4 of these members were sent to police custody by the court on 22 February. While Bharatiya Janta Party condemned these protests, with its spokesperson Shehzad Poonawalla saying, "From being anti-BJP, you have gone to being anti-national? If you have a problem with the BJP, then protest at the BJP office, Jantar Mantar, or outside the PM's office. But the people of the country and their alliance partners condemn them for their attempt to defame India in front of the entire world at the AI Summit." Congress leader Harish Rawat defended the protests, saying "it's also a fact that AI might become a tool in the hands of a few individuals… It's the opposition's job to warn against that… It's not the first time such international events have been opposed. I know how the BJP protested during the Commonwealth Games… To say that such opposition has happened for the first time is not correct. The BJP has been doing this while in the opposition." These protestors were granted bail by the Delhi high court on 2 March. == Reception and analysis == Bloomberg News reported that Prime Minister Modi used the summit to assert India's global AI ambitions following a challenging year in foreign policy. TechPolicy.Press published several critical analyses of the summit. One article argued that the summit's structure granted "multinational corporations parity with sovereign governments
2025 Bilderberg Conference
The 2025 Bilderberg Conference was held between June 12–June 15, 2025 at the Grand Hôtel in Stockholm, Sweden. The 2025 meeting was the 71st edition of the event. A Bilderberg Group press release listed 121 participants from 23 countries. Established in 1954 by Prince Bernhard of the Netherlands, Bilderberg conferences (or meetings) are an annual private gathering of the European and North American political and business elite. Events are attended by between 120 and 150 people each year invited by the Bilderberg Group's steering committee; including prominent politicians, CEOs, national security experts, academics and journalists. Bilderberg conferences operate under the Chatham House Rule, meaning that participants are sworn to secrecy and cannot disclose the identity or affiliation of any particular speaker. As a result, media are not invited and delegates rarely speak about what was discussed. Permits for two public demonstrations against the meeting were requested, one of which, a march from the Norrmalm Square to the Grand Hôtel, was planned for June 14. == Agenda == The key topics for discussion were announced on the Bilderberg website shortly before the meeting. These topics included: == Participants == A list of 121 participants was published on the Bilderberg website. This list may not be complete, as a source connected to the Bilderberg group told The Daily Telegraph in 2013 that some attendees do not have their names publicized. Prime Minister of Sweden Ulf Kristersson attended the meeting despite his name not appearing on the published participant list.
Riffusion
Riffusion is a neural network, designed by Seth Forsgren and Hayk Martiros, that generates music using images of sound rather than audio. The resulting music has been described as "de otro mundo" (otherworldly), although unlikely to replace man-made music. The model was made available on December 15, 2022, with the code also freely available on GitHub. The first version of Riffusion was created as a fine-tuning of Stable Diffusion, an existing open-source model for generating images from text prompts, on spectrograms, resulting in a model which used text prompts to generate image files which could then be put through an inverse Fourier transform and converted into audio files. While these files were only several seconds long, the model could also use latent space between outputs to interpolate different files together (using the img2img capabilities of SD). It was one of many models derived from Stable Diffusion. In December 2022, Mubert similarly used Stable Diffusion to turn descriptive text into music loops. In January 2023, Google published a paper on their own text-to-music generator called MusicLM. Forsgren and Martiros formed a startup, also called Riffusion, and raised $4 million in venture capital funding in October 2023.
Logogen model
The logogen model of 1969 is a model of speech recognition that uses units called "logogens" to explain how humans comprehend spoken or written words. Logogens are a vast number of specialized recognition units, each able to recognize one specific word. This model provides for the effects of context on word recognition. == Overview == The word logogen can be traced back to the Greek-language word logos, which means "word", and genus, which means "birth". British scientist John Morton's logogen model was designed to explain word recognition using a new type of unit known as a logogen. A critical element of this theory is the involvement of lexicons, or specialized aspects of memory that include semantic and phonemic information about each item that is contained in memory. A given lexicon consists of many smaller, abstract items known as logogens. Logogens contain a variety of properties about given word such as their appearance, sound, and meaning. Logogens do not store words within themselves, but rather they store information that is specifically necessary for retrieval of whatever word is being searched for. A given logogen will become activated by psychological stimuli or contextual information (words) that is consistent with the properties of that specific logogen and when the logogen's activation level rises to or above its threshold level, the pronunciation of the given word is sent to the output system. Certain stimuli can affect the activation levels of more than one word at a time, usually involving words that are similar to one another. When this occurs, whichever of the words' activation levels reaches the threshold level, it is that word that is then sent to the output system with the subject remaining unaware of any partially excited logogens. This assumption was made by Marslen-Wilson and Welch (1978), who added to the model some assumptions of their own in order to account for their experimental results. They also assumed that the analysis of phonetic input can only become available to other parts of the system by process of how the input affects the logogen system. Finally, Marslen-Wilson and Welch assume that the first syllable of a given word will increase the activation level of a given logogen more than those of the latter syllables, which supported the data found at the time. == Analysis == The logogen model can be used to help linguists explain particular occurrences in the human language. The most-helpful application of the model is to show how one accesses words and their meanings in the lexicon. The word-frequency effect is best explained by the logogen model in that words (or logogens) that have a higher frequency (or are more common) have a lower threshold. This means that they require less perceptual power in the brain to be recognized and decoded from the lexicon and are recognized faster than those words that are less common. Also, with high-frequency words, the recovery from lowering the item's threshold is less fulfilled compared to low-frequency words so less sensory information is needed for that particular item's recognition. There are ways to lower thresholds, such as repetition and semantic priming. Also, each time a word is encountered through these methods, the threshold for that word is temporarily lowered partially because of its recovering ability. This model also conveys that specific concrete words are recalled better because they use images and logogens, whereas abstract words are not as easily recalled well because they only use logogens, hence showing the difference in thresholds between these two types of words. At the time of its conception, Morton's logogen model was one of the most influential models in springing up other parallel word access models and served as the essential basis for these subsequent models. Morton's model also strongly influenced other contemporary theories on lexical access. However, despite the advantages that the logogen theory presents, it also displays some negative facets. First and foremost, the logogen model does not explain all occurrences in language, such as the introduction of new words or non-words into a person's lexicon. Also, because of the distinctive model application, it may vary in its effectiveness in different languages. == Criticisms == While this model does a reasonable job of understanding the underlying semantics of many aspects in psycholinguistics, there are some flaws that have been pointed out in the logogen model. It has been argued that the prior stimulus patterns that have been seen in the logogen theory are not centrally localized in the logogen itself but are actually distributed throughout the different pathways over which the stimulus is being processed. What this directs at is that the notion and proliferation of logogens was due to modality. In essence, the logogen is unnecessary in the idea of attaining the title of being a recognition unit because of the variety of pathways that it is open to, not just logogens. Another criticism has been that this model essentially ignores larger and more critical structures in language and phonetics such as the different syntactic rules or grammatical construction that innately exists in language. Since this model overtly limits itself to the scope of lexical access then this model is seen as biased and misunderstood. To many psychologists, the logogen model does not meet the functional or representational adequacy that a theory should include to sufficiently comprehend language. Also, another criticism is that the logogen theory was supposed to predict that stimulus degradation should affect priming and word frequency in humans. However, many psychologists have conducted studies and researched the model to show that only priming and not word frequency is interacted with stimulus degradation. Priming is supposed to deteriorate a stimulus because it postulates that the semantic characteristics of previously known words are fed back into the detector of a person which in turn raises the threshold of related items. In word frequency, stimulus degradation is supposed to occur because it postulates that familiar words have lower thresholds than their low-frequency counterparts. However, in studies, priming is the only structure that does show observable and notable stimulus decadence. Even though the logogen theory has many unfilled holes, Morton was a revolutionary of his field whose speculation and research has opened up a remarkable era of psycholinguistics. == Other models to consider == cohort model – This model was proposed by Marslen-Wilson and was designed specifically to account for auditory word recognition. It works by breaking the word down and states that when a word is heard all words that begin with the first sound of the target word are activated. This set of words is considered the cohort. Once the first cohort has been activated, the other information, or sounds in the word narrow down the choices. The person recognizes the word when you are left with a single choice; this is considered the "recognition point". checking model – This model was developed by Norris in 1986. In this particular model, he took the approach that any word that partially matches the input is analyzed and checked to see if it fits with the context of the situation. interactive-activation model – This model is considered a connectionist model. Proposed by McClelland and Rumelhart in the 1981 to 1982 period, it is based around nodes, which are visual features, and positions of letters within a given word. They also act as word detectors which have inhibitory and excitatory connections between them. This model starts with first letter and suggests that all the words with that first letter are activated at first and then going through the word one can determine what the word is they are looking at. The main principle is that mental phenomena can be described by interconnected networks of simple units. verification model – The model was developed by Curtis Becker in 1970. The main idea is that a small number of candidates that are activated in parallel are subject to a serial-verification process. This model starts the word-recognition process with a basic representation of the stimulus. Then, sensory trace, consisting of line features is used to activate word detectors. When an acceptable number of detectors are activated these are used to generate a search set. These items are drawn from the lexicon on the basis of similarity to the sensory trace, which help with the identity of the stimulus. Then, in a serial process the candidates are compared to the representation of the sensory-trace input. == Related concepts == word frequency – This is the belief that the speed and accuracy with which a word is recognized is related to how frequently the word occurs in our language. Each logogen has a threshold (for identification) and words with higher frequencies have lower thresholds. Words with higher freq
The Sword in the Stoned
"The Sword in the Stoned" is the fifth episode of the second season of the American fantasy comedy television series Ted. Written by Julius Sharpe, and directed by Seth MacFarlane, it premiered on the American streaming service Peacock, along with the rest of season two, on March 5, 2026. The series acts as a precursor to the Ted film franchise, showcasing the childhood lives of the protagonists. The series, set in 1994, focuses on John Bennett (Max Burkholder), the series' primary protagonist, an awkward high-school aged boy; along with Ted (MacFarlane), the series' titular anthropomorphic teddy bear. The two live with John's family, Susan (Alanna Ubach), his mild mannered mother, and Matty (Scott Grimes), his conservative father. Also residing with the family is Blaire (Giorgia Whigham), his radically liberal cousin whom often clashes with Matty. In the episode, Ted and John join the school play so they can have more extracurricular activities for their college applications, but the latter grows a connection with the school's popular teenager, Erin (Francesca Xuereb). Concurrently, Susan and Matty get a job at Dunkin' Donuts to help with their financial troubles, and Matty is given an opportunity to tell off Bill Clinton. Burkholder wore prop armor during the episode's play scenes. Bill Clinton’s appearance in the episode was portrayed by MacFarlane. After conventional makeup and visual techniques failed to convincingly resemble Clinton, the production used artificial intelligence to digitally replace MacFarlane's face with Clinton's likeness. Upon release, the episode received generally positive reviews from critics, though the use of AI in the Clinton scene was polarizing among audiences and reviewers. == Plot == John tells Ted that he is the last single guy left at their school, to which Ted points out the popular, single cheerleader, Erin, but John dismisses this. At home, Blaire tells John that he needs extracurricular activities to get into college, while Susan and Matty discuss their financial troubles, especially regarding John's college tuition. Looking over their options, they decide to audition for a school production of the play Camelot. Matty takes a job at Dunkin' Donuts, despite being told that nobody will give him a tip, and having to wear an incorrect name tag. Waiting for their auditions, John and Ted watch several poor auditions for the play before seeing Erin's, who delivers a flawless performance; John and Ted do less serious auditions, getting cast as knights, while Erin gets the role of Guinevere. Matty complains about his low salary, and Susan decides to get a job at Dunkin' Donuts beside him to help earn more income. Erin clashes with Lancelot's actor while rehearsing, and John compliments her performance, which she ignores, but, seeing Ted and John give good performances in a repetition exercise, she becomes interested in him, particularly since he treats her better than her stage-partner. Matty and Susan watch an employee training video, explaining how they should treat customers politely, not affecting Matty's nihilistic attitude. The manager announces that Bill Clinton is visiting their Dunkin' Donuts for publicity, and Matty sees this as a chance to tell Bill off. John and Erin practice lines, as she reveals the show is being taped so it can be sent to Emerson College in hopes of her getting in; Erin asks John to go out with her after the show. At dinner, Matty enthusiastically reveals what he plans to tell Bill, as John becomes stressed about the play when Susan tells there will be a large audience. Bill comes to the Dunkin' Donuts, and, seeing Matty is nervously insulting him, stages a private meeting with him, where Bill yells at Matty, calling him a loser before posing for a picture with Matty and subsequently throwing the cold coffee onto him. To ease the pressure, Ted and John take edibles from Blaire, but learn at the show that they contained mushrooms, causing them to stress further. On stage, Ted and John yell nervously that they're on drugs as the latter urinates in his costume, causing Erin to angrily storm off. == Production == "The Sword in the Stoned" was directed by series creator and lead Seth MacFarlane, and written by Julius Sharpe in his third and final writing credit for the series. When Ted and John are doing repetition exercises, they tackle each other to the ground, which required a stuntman named Ashton to play the role of Ted, according to Max Burkholder, who portrays John. Burkholder also recalled that, when Ted was choking John in the scene, he kept making a noise during the choking, which made Bill, the cameraman, laugh, despite being a "stone face" that never laughs, noting that seeing him be amused by the noise he was making assured Burkholder that what he was doing was "hilarious". Burkholder found the filming of the play scenes "weird", as he was put in fake armor with a hose inside his suit—which was filled with water mixed with yellow food coloring—that was made to create the urine stream that comes out of John's armor in the episode; he also noted that it took around 45 minutes to put on and take off the armor. He revealed that he himself had to urinate during the filming, as doing a scene about a character having to do so "really [broke] my brain", with the fact that it took 45 minutes to get the suit off adding to the frustration. Jennifer Ashley Connell, who worked for wardrobe, had to repeatedly go to Burkholder quickly between takes to dry off his pants with two hair dryers to make it look like the fake urine hadn't already streamed down his pants, so they could get as many shots of it as possible. Francesca Xuereb guest stars in the episode as Erin, the cheerleader who stars in the play. Incumbent president Bill Clinton was portrayed by MacFarlane, with artificial intelligence (AI) being used to digitally make MacFarlane's face look like Clinton's during post-production. Before settling on AI, the crew tried to use traditional computer-generated imagery and prosthetics, which made him look "terrifying", resulting in them deciding that AI would give them a more accurate look. One of the original technologies considered was one where, after scanning MacFarlane, a mesh of his head was created, and they had to use computer graphics to replace MacFarlane's face with Clinton's. An issue was faced, however, when they found the archival footage used as reference from the Clinton Library—an official Presidential Library containing information related to Clinton—to be extremely low-quality, making it hard to properly emulate his face, since only still images were of acceptable quality, and there weren't references of his moving face to work off of. A forensic artist was hired to help with this, and they created a 3D model of Clinton's head in ZBrush, based off of his presidential portrait. The model head worked for still frames, but movement was still difficult to do realistically, due to it being made for a "single-point perspective", which made details like the cheekbones or other minor issues more noticeable when using it for the scene. Since this did not work, AI was ultimately chosen through the studio Deep Voodoo, which used large language models to teach the tool how to correctly replicate Clinton's appearance. Defending the episode's use of AI, MacFarlane noted that the crew did not want people to focus on the tool being used, trying to utilize it in a way that wouldn't distract from the humor and narrative. Like the rest of the series, the episode was shot using ViewScreen; MacFarlane was able to act live with the cast as Ted due to ViewScreen, a technology that allows the production crew to visualize what Ted will look like in each scene in real time. == Release and reception == "The Sword in the Stoned" was first released on March 5, 2026, on the American streaming service Peacock, along with the rest of the second season. Nate Richards of Collider highlighted the Dunkin' Donuts subplot as an example of Scott Grimes delivering a "lot of laughs" through his performance as Matty. Dustin Rowles of Pajiba called "The Sword in the Stoned" one of the season's many episodes he'd recommend, particularly for the scenes of Ted and John being high on mushrooms during the play. Oppositely, Nick Valdez of ComicBook.com ranked the episode as the worst of the second season, criticizing it for not having a "huge impact" on the Bennett family dynamic like other episodes of the season do, and Susan and Matty's side story as the main reason he felt it was "[kept] from being great". Valdez noted the episode for likely being an advertisement for Dunkin' Donuts, calling the plot's ending scene involving Clinton the reason "it just all sticks out like a sore thumb". === Response to AI usage === The episode's use of AI for MacFarlane's portrayal of Clinton proved controversial, mainly on social media, where audiences asserted that the crew should have gotten an actor that resembl