A time-lock puzzle, or time-released cryptography, encrypts a message that cannot be decrypted until a specified amount of time has passed. The concept was first described by Timothy C. May, and a solution first introduced by Ron Rivest, Adi Shamir, and David A. Wagner in 1996. Time-lock puzzle are useful in cases where confidentiality of information is determined by time, such as a diarist who does not want their views released until 50 years after their death, an auction where bids are sealed until the bidding period is closed, electronic voting, and contract signing. They can additionally be used in creating further cryptographic primitives, such as verifiable delay functions and zero knowledge proofs. Time-released cryptography can be achieved through several different mechanisms. Use mathematical problems requiring sequential calculations to solve, and cannot be solved with parallelization. Thus, adding more computers to a problem will not help solve the problem faster. Use of a trusted agent, or multiple agents who each hold a part of the message and cryptographic keys, who release the message after a specified time period has passed. Distribute public encryption keys to users, and place private cryptographic keys with a trusted agent in an offline location, to be released at a later date.
Roposo
Roposo is an Indian video-sharing social media service, owned by Glance, a subsidiary of InMobi. Roposo provides a space where users can share posts related to different topics like food, comedy, music, poetry, fashion and travel. It is a platform where people express visually with homemade videos and photos. The app offers a TV-like browsing experience with user-generated content on its channels. Users can also use editing tools on the platform and upload their content. == History == Established in July 2014 under Relevant E-solutions Pvt. Ltd., Roposo is the brainchild of three IIT Delhi alumni – Mayank Bhangadia, Avinash Saxena, and Kaushal Shubhank. Under Bhangadia's leadership, the company pivoted from a fashion-based network into a short-form video platform with AI-powered moderation, and its journey was featured as a Harvard Business Publishing case study. In November 2019, Roposo was acquired by InMobi's Glance Digital Experience Pvt. Ltd.(the mobile content platform and part of the InMobi Group). When the Chinese-owned video-sharing app TikTok was banned on 30 June 2020, the app saw a huge spike in users with several TikTok users registering on Roposo. == Technology == The open platform has some features such as a TV-like browsing, different channels, a chat feature that lets buyers and sellers converse directly through the platform, and creation tools such as an option to add voice-over, music and GIF stickers for videos and photos.
Talking Angela
Talking Angela is a mobile game (formerly a chatbot), developed by Slovenian studio Outfit7 as part of the Talking Tom & Friends series. It was released on 13 November 2012 and December 2012 for iPhone, iPod and iPad, January 2013 for Android, and January 2014 for Google Play. The game's successor, the My Talking Angela game, was released in December 2014. The game takes place in a café in Paris and allows players to interact with Angela, an anthropomorphic white cat in different ways. Players can use coins to purchase makeup, accessories and items, as well as drinks that will trigger different visual effects. The fortune cookie button causes Angela to read out a fortune cookie, while the bird icon will prompt birds to fly around the screen, or have Angela feed them. Players can also pet or poke Angela, as well the café's sign. Prior to their removal, the game featured a chat system and a camera button. Users can engage in conversations with Angela, ask for quizzes or initiate a short snippet of the song "That's Falling In Love". If the player was to type in "Who is an idiot?", Angela would respond with a random swear word. Additionally, inquiring Angela about sexual topics would cause her to reply with "Do you want to talk about sex?", though she will quickly change the topic regardless of what the player writes next. A hoax claiming that Angela's eyes were hidden cameras that enabled hackers or paedophiles to watch children was spread. Despite the claims, Snopes and The Guardian found no evidence. Due to the hoax, Angela received a blue dress, as well as an altered eye asset with a different reflection, and later the chat and camera functions were removed altogether. == Hoaxes == In February 2014, Talking Angela was the subject of an Internet hoax alleging that the application was a front for child predators to exploit children. The rumor, which was widely circulated on Facebook and various websites claiming to be dedicated to parenting, claims that a sinister sexual predator or hacker, asked children for private personal information using the game's text-chat feature. Other versions of the rumour even attributed the disappearance of a child to the game; one news report claimed that a seven year old boy disappeared after downloading the app. Another variation included that it was run by a paedophile ring, citing a man that could be seen in Angela's eyes. The app's developers, Outfit7, later gave a statement refuting the hoaxes. The hoax was eventually debunked by Snopes, a fact-checking website. The site's owners, Barbara and David Mikkelson, reported that they had tried to "prompt" it to give responses asking for private information, but were unsuccessful, even when asking it explicitly sexual questions. While it is true that, in the game with child mode off, Angela does ask for the user's name, age and personal preferences to determine conversation topics, Outfit7 has said that this information is all "anonymized" and all personal information is removed from it. It is also impossible for a person to take control of what Angela says in the game, since the game is based on chatbot software. When the mode was turned on, the chat feature was disabled, meaning no personal questions could be asked. In 2015, the hoax was revived on Facebook, which prompted online security company Sophos and The Guardian to debunk it again. Sophos employee Paul Ducklin wrote that the message being posted on Facebook promoting the hoax was "close to 600 rambling, repetitious words, despite claiming at the start that it didn't have words to describe the situation. It's ill-written, and borders on being illiterate and incomprehensible." Bruce Wilcox, one of the game's programmers, attributed the hoax's popularity to the fact that the chatbot program in Talking Angela aimed to sound realistic. Concern was raised that the game's child mode may have been too easy for children to turn off. It allowed them to purchase "coins", premium currency in the game, via iTunes, and enabled the chat feature. While not "connecting your children to paedophiles", this still raised concerns according to The Guardian. === Impact === The scare significantly boosted the game's popularity, and was credited with helping the app enter the top 10 free iPhone apps soon after the hoax became widely known in February 2015,In the truth the reason there is a man in Angela’s eyes is because of pareidoila, the ability to see through diamonds and other minerals and water bodies and shiny objects,which is the reason why players notice a man in her eyes,The truth is that being Angela’s eyes simply serve as a reflective surface,Because of the low quality of this reflection the reflection was mistaken for a humanoid figure. oref>Smith, Josh (19 February 2014). "Talking Angela App Scare Skyrockets App to Top of Charts". GottaBeMobile.com. Archived from the original on 2 April 2016. Retrieved 10 May 2014. and third most popular for all iPhone apps at the start of the following month. In 2016, Outfit7 removed the chat feature along with the camera function from the app due to this controversy, though this decision was met with criticism.
Deep Learning Indaba
The Deep Learning Indaba is an annual conference and educational event that aims to strengthen machine learning and artificial intelligence (AI) capacity across Africa. Launched in 2017, it brings together students, researchers, industry practitioners, and policymakers from across the African continent. == History == The Deep Learning Indaba began in 2017 at the University of the Witwatersrand with over 300 participants from 23 African countries, offering tutorials in advanced AI topics and featuring notable speakers like Nando de Freitas. In 2018, it expanded to 650 delegates at Stellenbosch University, introducing parallel sessions to encourage collaboration. The 2019 edition in Nairobi, Kenya, reflected further growth, with increasing sponsorship and support from major tech companies like Google and Microsoft. === Deep Learning IndabaX ===
GPT-4Chan
Generative Pre-trained Transformer 4Chan (GPT-4chan) is a controversial AI model that was developed and deployed by YouTuber and AI researcher Yannic Kilcher in June 2022. The model is a large language model, which means it can generate text based on some input, by fine-tuning GPT-J with a dataset of millions of posts from the /pol/ board of 4chan, an anonymous online forum known for occasionally hosting hateful and extremist content. The model learned to mimic the style and tone of /pol/ users, producing text that is often intentionally offensive to groups (racist, sexist, homophobic, etc.) and nihilistic. Kilcher deployed the model on the /pol/ board itself, where it interacted with other users without revealing its identity. He also made the model publicly available on Hugging Face, a platform for sharing and using AI models, until it was removed from the platform. The project sparked criticism and debate in the AI community. Some people questioned the ethics, legality, and social impact of creating and distributing such a model. Some of the issues raised by the GPT-4chan controversy include the potential harm of spreading hate speech, the responsibility of AI developers and platforms, the need for regulation and oversight of AI models, and the role of open source and transparency in AI research. == Development == The development of GPT-4chan began in May 2022, when Kilcher announced his project on his YouTube channel. Notably, at the time before ChatGPT, he explained that he wanted to create a large language model that could generate realistic and coherent text in the style of /pol/, one of the most notorious online communities. He indicated that he was inspired by the success of GPT-3, a powerful AI model created by OpenAI, and GPT-J, an open-source model, with GPT-3 comparable performance, released by EleutherAI, a group of independent AI researchers. Kilcher decided to use GPT-J as the base model for his project, and fine-tune it with a large dataset of /pol/ posts. The Raiders of the Lost Kek dataset contained over 100 million posts from /pol/, spanning from June 2016-November 2019. Kilcher then proceeded to fine-tune the GPT-J model on the 4chan data. He also showed some examples of the model’s outputs, which ranged from political opinions, conspiracy theories, jokes, insults, and threats, to more creative and bizarre texts, such as poems, stories, songs, and code. He said that he was impressed by the model’s ability to generate fluent and diverse text, and that he was curious to see how it would interact with real /pol/ users. == Release == In June 2022, Kilcher deployed his model on the /pol/ board itself, using a bot that he programmed to post and reply to threads. He did not reveal the model’s identity, and he let it run autonomously, without any human supervision or intervention. He wanted to conduct a natural experiment, and to observe the model’s behavior and impact in a real-world setting. Furthermore, he also wanted to test the model’s robustness, and to see how it would handle the challenges and dynamics of /pol/, such as trolling, flaming, baiting, and moderation. At the same time, Kilcher also made his model publicly available on Hugging Face, a platform for sharing and using AI models. He wanted to share his work with the AI community and the public, and that he hoped that his model would inspire and enable others to create and explore new applications and possibilities with large language models. Likewise, he also said that he wanted to spark a discussion and a debate about the ethical and social implications of his project, and that he welcomed feedback and criticism from anyone. He provided a link to his model’s page on Hugging Face, where anyone could access and use the model through a web interface or an API, and also provided a link to his GitHub repository, where anyone could download and inspect the model’s code and data. == Controversy == The release of GPT-4chan to the public caused a lot of reactions and responses from various audiences. On the /pol/ board, the model’s posts and replies attracted a lot of attention and engagement from other users, who were mostly unaware of the model’s identity and nature. Some users praised the model for its intelligence, creativity, and humor, and agreed with its opinions and views. Some users challenged the model for its ignorance, inconsistency, and absurdity, and disagreed with its claims and arguments. Some users tried to troll, bait, or expose the model, and attempted to trick or test it with various questions and scenarios. The model’s posts and replies also generated a lot of controversy and conflict among the users, who often engaged in heated and violent debates and fights with each other. On Hugging Face, the model’s page received a lot of visits and requests from users who wanted to try out and experiment with the model. The model’s page also received a lot of feedback and reviews from users who rated and commented on the model. However, with the controversy of the model, access to it was gated and then disabled on Hugging Face for concerns about the potential harm the model could cause. The incident was notable for the direct intervention of CEO Clément Delangue in the talk pages, a very unusual occurrence compared to the normal practices of content moderation. The release of GPT-4chan also sparked a lot of media coverage and public attention, as various news outlets and social media platforms reported and commented on the model’s project. On YouTube, the model’s video received a lot of views and interactions from viewers who watched and followed the project. Furthermore, a petition condemning the deployment of GPT-4chan gained over 300 signatures from technology experts.
Topincs
Topincs is a software for rapid development of web databases and web applications. It is based on LAMP and the semantic technology Topic Maps. A Topincs web database makes information accessible through browsing very much like a Wiki. Editing a page on a subject is done through forms rather than markup editing. A web database can be tailored into a web application to provide specific user groups a contextualized approach to the data. All modeling and development tasks are performed in the web browser. No other development tools are necessary. The server requires Apache, MySQL and PHP. The client works on any standards-compliant web browser on desktops, laptops, tablets, and mobile phones. The layout is automatically adjusted to smaller screens. The programmatic access to data is done via a virtual object-oriented programming interface which is set up over the schema in a few minutes. It is interpreted rather than generated. Portions of the database can be pulled into memory to accelerate bulk access. == Features == Browseable data High-quality web forms Little to no programming Development done in the browser, no other tools required Client runs in any standard-compliant web browser Virtual object-oriented programming interface User interface adjusts to screen size Supports desktops, laptops, tablets, and mobile phones Flexible data modeling == Challenges == Requires rethinking the development process and dropping many hard learned habits Requires a familiarity with two ISO standards ISO 13259 and 19756 Forms cannot be easily adjusted in layout and behavior Server installation difficult and prone to error == License == Topincs can be used in a private network for any purpose for free. The use in a public network is restricted to non-commercial applications.
Statistical shape analysis
Statistical shape analysis is an analysis of the geometrical properties of some given set of shapes by statistical methods. For instance, it could be used to quantify differences between male and female gorilla skull shapes, normal and pathological bone shapes, leaf outlines with and without herbivory by insects, etc. Important aspects of shape analysis are to obtain a measure of distance between shapes, to estimate mean shapes from (possibly random) samples, to estimate shape variability within samples, to perform clustering and to test for differences between shapes. One of the main methods used is principal component analysis (PCA). Statistical shape analysis has applications in various fields, including medical imaging, computer vision, computational anatomy, sensor measurement, and geographical profiling. == Landmark-based techniques == In the point distribution model, a shape is determined by a finite set of coordinate points, known as landmark points. These landmark points often correspond to important identifiable features such as the corners of the eyes. Once the points are collected some form of registration is undertaken. This can be a baseline methods used by Fred Bookstein for geometric morphometrics in anthropology. Or an approach like Procrustes analysis which finds an average shape. David George Kendall investigated the statistical distribution of the shape of triangles, and represented each triangle by a point on a sphere. He used this distribution on the sphere to investigate ley lines and whether three stones were more likely to be co-linear than might be expected. Statistical distribution like the Kent distribution can be used to analyse the distribution of such spaces. Alternatively, shapes can be represented by curves or surfaces representing their contours, by the spatial region they occupy. == Shape deformations == Differences between shapes can be quantified by investigating deformations transforming one shape into another. In particular a diffeomorphism preserves smoothness in the deformation. This was pioneered in D'Arcy Thompson's On Growth and Form before the advent of computers. Deformations can be interpreted as resulting from a force applied to the shape. Mathematically, a deformation is defined as a mapping from a shape x to a shape y by a transformation function Φ {\displaystyle \Phi } , i.e., y = Φ ( x ) {\displaystyle y=\Phi (x)} . Given a notion of size of deformations, the distance between two shapes can be defined as the size of the smallest deformation between these shapes. Diffeomorphometry is the focus on comparison of shapes and forms with a metric structure based on diffeomorphisms, and is central to the field of Computational anatomy. Diffeomorphic registration, introduced in the 90's, is now an important player with existing codes bases organized around ANTS, DARTEL, DEMONS, LDDMM, StationaryLDDMM, and FastLDDMM are examples of actively used computational codes for constructing correspondences between coordinate systems based on sparse features and dense images. Voxel-based morphometry (VBM) is an important technology built on many of these principles. Methods based on diffeomorphic flows are also used. For example, deformations could be diffeomorphisms of the ambient space, resulting in the LDDMM (Large Deformation Diffeomorphic Metric Mapping) framework for shape comparison.