SmarterChild was a chatbot available on AOL Instant Messenger and Windows Live Messenger (previously MSN Messenger) networks. == History == SmarterChild was an apparently intelligent agent or "bot" developed by ActiveBuddy, Inc., with offices in New York and Sunnyvale. It was widely distributed across global instant messaging networks. SmarterChild became very popular, attracting over 30 million Instant Messenger "buddies" on AIM (AOL), MSN and Yahoo Messenger over the course of its lifetime. Founded in 2000, ActiveBuddy was the brainchild of Robert Hoffer and Timothy Kay, who later brought seasoned advertising executive Peter Levitan on board as CEO. The concept for conversational instant messaging bots came from the founder's vision to add natural language comprehension functionality to the increasingly popular AIM instant messaging application. The original implementation took shape as a demo that Kay programmed in Perl in his Los Altos garage to connect a single buddy name, "ActiveBuddy", to look up stock symbols, and later allow AIM users to play Colossal Cave Adventure, a word-based adventure game, and MIT's Boris Katz Start Question Answering System but quickly grew to include a wide range of database applications the company called 'knowledge domains' including instant access to news, weather, stock information, movie times, yellow pages listings, and detailed sports data, as well as a variety of tools (personal assistant, calculators, translator, etc.). None of the individual domains which the company had named “stocksBuddy”, “sportsBuddy”, etc. ever launched publicly. When Stephen Klein came on board as COO — and eventually CEO — he insisted that all of the disparate test “buddies” be launched together with the company’s highly-developed colloquial chat domain. He suggested using “SmarterChild”, a username coined by Tim Kay which Tim was using to test various things. The bundled domains were launched publicly as SmarterChild (on AIM initially) in June 2001. SmarterChild provided information wrapped in fun and quirky conversation. The company generated no revenue from SmarterChild, but used it as a demonstration of the power of what Klein called “conversational computing”. The company subsequently marketed Automated Service Agents—delivering immediate answers to customer service inquiries—-to large corporations, like Comcast, Cingular, TimeWarner Cable, etc. SmarterChild's popularity spawned targeted marketing-oriented bots for Radiohead, Austin Powers, Intel, Keebler, The Sporting News and others. ActiveBuddy co-founders, Kay and Hoffer, as co-inventors, were issued two controversial U.S. patents in 2002. ActiveBuddy changed its name to Colloquis (briefly Conversagent) and targeted development of consumer-facing enterprise customer service agents, which the company marketed as Automated Service Agents. Microsoft acquired Colloquis in October 2006 and proceeded to de-commission SmarterChild and kill off the Automated Service Agent business as well. Robert Hoffer, ActiveBuddy co-founder, licensed the technology from Microsoft after Microsoft abandoned the Colloquis technology.
Zero-shot learning
Zero-shot learning (ZSL) is a problem setup in deep learning where, at test time, a learner observes samples from classes which were not observed during training, and needs to predict the class that they belong to. The name is a play on words based on the earlier concept of one-shot learning, in which classification can be learned from only one, or a few, examples. Zero-shot methods generally work by associating observed and non-observed classes through some form of auxiliary information, which encodes observable distinguishing properties of objects. For example, given a set of images of animals to be classified, along with auxiliary textual descriptions of what animals look like, an artificial intelligence model which has been trained to recognize horses, but has never been given a zebra, can still recognize a zebra when it also knows that zebras look like striped horses. This problem is widely studied in computer vision, natural language processing, and machine perception. == Background and history == The first paper on zero-shot learning in natural language processing appeared in a 2008 paper by Chang, Ratinov, Roth, and Srikumar, at the AAAI'08, but the name given to the learning paradigm there was dataless classification. The first paper on zero-shot learning in computer vision appeared at the same conference, under the name zero-data learning. The term zero-shot learning itself first appeared in the literature in a 2009 paper from Palatucci, Hinton, Pomerleau, and Mitchell at NIPS'09. This terminology was repeated later in another computer vision paper and the term zero-shot learning caught on, as a take-off on one-shot learning that was introduced in computer vision years earlier. In computer vision, zero-shot learning models learned parameters for seen classes along with their class representations and rely on representational similarity among class labels so that, during inference, instances can be classified into new classes. In natural language processing, the key technical direction developed builds on the ability to "understand the labels"—represent the labels in the same semantic space as that of the documents to be classified. This supports the classification of a single example without observing any annotated data, the purest form of zero-shot classification. The original paper made use of the Explicit Semantic Analysis (ESA) representation but later papers made use of other representations, including dense representations. This approach was also extended to multilingual domains, fine entity typing and other problems. Moreover, beyond relying solely on representations, the computational approach has been extended to depend on transfer from other tasks, such as textual entailment and question answering. The original paper also points out that, beyond the ability to classify a single example, when a collection of examples is given, with the assumption that they come from the same distribution, it is possible to bootstrap the performance in a semi-supervised like manner (or transductive learning). Unlike standard generalization in machine learning, where classifiers are expected to correctly classify new samples to classes they have already observed during training, in ZSL, no samples from the classes have been given during training the classifier. It can therefore be viewed as an extreme case of domain adaptation. == Prerequisite information for zero-shot classes == Naturally, some form of auxiliary information has to be given about these zero-shot classes, and this type of information can be of several types. Learning with attributes: classes are accompanied by pre-defined structured description. For example, for bird descriptions, this could include "red head", "long beak". These attributes are often organized in a structured compositional way, and taking that structure into account improves learning. While this approach was used mostly in computer vision, there are some examples for it also in natural language processing. Learning from textual description. As pointed out above, this has been the key direction pursued in natural language processing. Here class labels are taken to have a meaning and are often augmented with definitions or free-text natural-language description. This could include for example a wikipedia description of the class. Class-class similarity. Here, classes are embedded in a continuous space. A zero-shot classifier can predict that a sample corresponds to some position in that space, and the nearest embedded class is used as a predicted class, even if no such samples were observed during training. == Generalized zero-shot learning == The above ZSL setup assumes that at test time, only zero-shot samples are given, namely, samples from new unseen classes. In generalized zero-shot learning, samples from both new and known classes, may appear at test time. This poses new challenges for classifiers at test time, because it is very challenging to estimate if a given sample is new or known. Some approaches to handle this include: a gating module, which is first trained to decide if a given sample comes from a new class or from an old one, and then, at inference time, outputs either a hard decision, or a soft probabilistic decision a generative module, which is trained to generate feature representation of the unseen classes—a standard classifier can then be trained on samples from all classes, seen and unseen. == Domains of application == Zero shot learning has been applied to the following fields: image classification semantic segmentation image generation object detection natural language processing computational biology abstract reasoning
Acousto-electronics
Acousto-electronics (also spelled 'Acoustoelectronics') is a branch of physics, acoustics and electronics that studies interactions of ultrasonic and hypersonic waves in solids with electrons and with electro-magnetic fields. Typical phenomena studied in acousto-electronics are acousto-electric effect and also amplification of acoustic waves by flows of electrons in piezoelectric semiconductors, when the drift velocity of the electrons exceeds the velocity of sound. The term 'acousto-electronics' is often understood in a wider sense to include numerous practical applications of the interactions of electro-magnetic fields with acoustic waves in solids. In particular, these are signal processing devices using surface acoustic waves (SAW), different sensors of temperature, pressure, humidity, acceleration, etc.
Hardware security
Hardware security is a discipline originated from the cryptographic engineering and involves hardware design, access control, secure multi-party computation, secure key storage, ensuring code authenticity, measures to ensure that the supply chain that built the product is secure among other things. A hardware security module (HSM) is a physical computing device that safeguards and manages digital keys for strong authentication and provides cryptoprocessing. These modules traditionally come in the form of a plug-in card or an external device that attaches directly to a computer or network server. Some providers in this discipline consider that the key difference between hardware security and software security is that hardware security is implemented using "non-Turing-machine" logic (raw combinatorial logic or simple state machines). One approach, referred to as "hardsec", uses FPGAs to implement non-Turing-machine security controls as a way of combining the security of hardware with the flexibility of software. Hardware backdoors are backdoors in hardware. Conceptionally related, a hardware Trojan (HT) is a malicious modification of electronic system, particularly in the context of integrated circuit. A physical unclonable function (PUF) is a physical entity that is embodied in a physical structure and is easy to evaluate but hard to predict. Further, an individual PUF device must be easy to make but practically impossible to duplicate, even given the exact manufacturing process that produced it. In this respect it is the hardware analog of a one-way function. The name "physical unclonable function" might be a little misleading as some PUFs are clonable, and most PUFs are noisy and therefore do not achieve the requirements for a function. Today, PUFs are usually implemented in integrated circuits and are typically used in applications with high security requirements. Many attacks on sensitive data and resources reported by organizations occur from within the organization itself.
DVD
DVD (digital video disc or digital versatile disc) is a digital optical disc data storage format. It was invented and developed in 1995 and first released on November 1, 1996, in Japan. The medium can store any kind of digital data and has been widely used to store video programs (watched using DVD players), software and other computer files. DVDs offer significantly higher storage capacity than compact discs (CD) while having the same dimensions. A standard single-layer DVD can store up to 4.7 GB of data, a dual-layer DVD up to 8.5 GB. Dual-layer, double-sided DVDs can store up to a maximum of 17.08 GB. Prerecorded DVDs are mass-produced using molding machines that physically stamp data onto the DVD. Such discs are a form of DVD-ROM because data can only be read and not written or erased. Blank recordable DVD discs (DVD-R and DVD+R) can be recorded once using a DVD recorder and then function as a DVD-ROM. Rewritable DVDs (DVD-RW, DVD+RW, and DVD-RAM) can be recorded and erased many times. DVDs are used in DVD-Video consumer digital video format and less commonly in DVD-Audio consumer digital audio format, as well as for authoring DVD discs written in a special AVCHD format to hold high definition material (often in conjunction with AVCHD format camcorders). DVDs containing other types of information may be referred to as DVD data discs. == Etymology == The Oxford English Dictionary comments that, "In 1995, rival manufacturers of the product initially named digital video disc agreed that, in order to emphasize the flexibility of the format for multimedia applications, the preferred abbreviation DVD would be understood to denote digital versatile disc." The OED also states that in 1995, "The companies said the official name of the format will simply be DVD. Toshiba had been using the name 'digital video disc', but that was switched to 'digital versatile disc' after computer companies complained that it left out their applications." "Digital versatile disc" is the explanation provided in a DVD Forum Primer from 2000 and in the DVD Forum's mission statement, which the purpose is to promote broad acceptance of DVD products on technology, across entertainment, and other industries. Because DVDs became highly popular for the distribution of movies in the 2000s, the term DVD became popularly used in English as a noun to describe specifically a full-length movie released on the format; for example the phrase "to watch a DVD" describes watching a movie on DVD. == History == === Development and launch === Released in 1987, CD Video used analog video encoding on optical discs matching the established standard 120 mm (4.7 in) size of audio CDs. Video CD (VCD) became one of the first formats for distributing digitally encoded films in this format, in 1993. In the same year, two new optical disc storage formats were being developed. One was the Multimedia Compact Disc (MMCD), backed by Philips and Sony (developers of the CD and CD-i), and the other was the Super Density (SD) disc, supported by Toshiba, Time Warner, Matsushita Electric, Hitachi, Mitsubishi Electric, Pioneer, Thomson, and JVC. By the time of the press launches for both formats in January 1995, the MMCD nomenclature had been dropped, and Philips and Sony were referring to their format as Digital Video Disc (DVD). On May 3, 1995, an ad hoc industry technical group formed from five computer companies (IBM, Apple, Compaq, Hewlett-Packard, and Microsoft) issued a press release stating that they would only accept a single format. The group voted to boycott both formats unless the two camps agreed on a single, converged standard. They recruited Lou Gerstner, president of IBM, to pressure the executives of the warring factions. In one significant compromise, the MMCD and SD groups agreed to adopt proposal SD 9, which specified that both layers of the dual-layered disc be read from the same side—instead of proposal SD 10, which would have created a two-sided disc that users would have to turn over. Philips/Sony strongly insisted on the source code, EFMPlus, that Kees Schouhamer Immink had designed for the MMCD, because it makes it possible to apply the existing CD servo technology. Its drawback was a loss from 5 to 4.7 Gigabytes of capacity. As a result, the DVD specification provided a storage capacity of 4.7 GB (4.38 GiB) for a single-layered, single-sided disc and 8.5 GB (7.92 GiB) for a dual-layered, single-sided disc. The DVD specification ended up similar to Toshiba and Matsushita's Super Density Disc, except for the dual-layer option. MMCD was single-sided and optionally dual-layer, whereas SD was two half-thickness, single-layer discs which were pressed separately and then glued together to form a double-sided disc. Philips and Sony decided that it was in their best interests to end the format war, and on September 15, 1995 agreed to unify with companies backing the Super Density Disc to release a single format, with technologies from both. After other compromises between MMCD and SD, the group of computer companies won the day, and a single format was agreed upon. The computer companies also collaborated with the Optical Storage Technology Association (OSTA) on the use of their implementation of the ISO-13346 file system (known as Universal Disk Format) for use on the new DVDs. The format's details were finalized on December 8, 1995. In November 1995, Samsung announced it would start mass-producing DVDs by September 1996. The format launched on November 1, 1996, in Japan, mostly with music video releases. The first major releases from Warner Home Video arrived on December 20, 1996, with four titles being available. The format's release in the U.S. was delayed multiple times, from August 1996, to October 1996, November 1996, before finally settling on early 1997. Players began to be produced domestically that winter, with March 24, 1997, as the U.S. launch date of the format proper in seven test markets. Approximately 32 titles were available on launch day, mainly from the Warner Bros., MGM, and New Line libraries, with the notable inclusion of the 1996 film Twister. However, the launch was planned for the following day (March 25), leading to a distribution change with retailers and studios to prevent similar violations of breaking the street date. The nationwide rollout for the format happened on August 22, 1997. DTS announced in late 1997 that they would be coming onto the format. The sound system company revealed details in a November 1997 online interview, and clarified it would release discs in early 1998. However, this date would be pushed back several times before finally releasing their first titles at the 1999 Consumer Electronics Show. In 2001, blank DVD recordable discs cost the equivalent of $27.34 US dollars in 2022. === Adoption === Movie and home entertainment distributors adopted the DVD format to replace the ubiquitous VHS tape as the primary consumer video distribution format. Immediately following the formal adoption of a unified standard for DVD, two of the four leading video game console companies (Sega and The 3DO Company) said they already had plans to design a gaming console with DVDs as the source medium. Sony stated at the time that they had no plans to use DVD in their gaming systems, despite being one of the developers of the DVD format and eventually the first company to actually release a DVD-based console. Game consoles such as the PlayStation 2, Xbox, and Xbox 360 use DVDs as their source medium for games and other software. Contemporary games for Windows were also distributed on DVD. Early DVDs were mastered using DLT tape, but using DVD-R DL or +R DL eventually became common. TV DVD combos, combining a standard definition CRT TV or an HD flat panel TV with a DVD mechanism under the CRT or on the back of the flat panel, and VCR/DVD combos were also available for purchase. For consumers, DVD soon overtook VHS as the favored choice for home movie releases. In 2001, DVD players outsold VCRs for the first time in the United States. At that time, one in four American households owned a DVD player. By 2007, about 80% of Americans owned a DVD player, a figure that had surpassed VCRs; it was also higher than personal computers or cable television. == Specifications == The DVD specifications created and updated by the DVD Forum are published as so-called DVD Books (e.g. DVD-ROM Book, DVD-Audio Book, DVD-Video Book, DVD-R Book, DVD-RW Book, DVD-RAM Book, DVD-AR (Audio Recording) Book, DVD-VR (Video Recording) Book, etc.). DVD discs are made up of two discs; normally one is blank, and the other contains data. Each disc is 0.6 mm thick, and they are glued together to form a DVD disc. The gluing process must be done carefully to make the disc as flat as possible to avoid both birefringence and "disc tilt", which is when the disc is not perfectly flat, preventing it from being read. Some specifications for mechanical, physical and optical characteristics of DV
17LIVE
17LIVE is an international entertainment platform. As of 2024, 17LIVE is the #3 live broadcasting platform globally, formed by its flagship live stream app 17LIVE (LIVIT in English markets), MEME Live and live stream e-commerce platforms HandsUP and OrderPally. == History == 17LIVE was first founded in Taiwan in 2015 by Jeffery Huang. The company has maintained its leading position since its entry into the Japan market in 2017, becoming the biggest platform for live entertainment in Japan, Taiwan, Hong Kong, and other countries. In 2017, 17 closed out US$33M in series B round to merge with dating software Paktor, with Joseph Phua (Co-founder of Paktor) taking over the leadership of 17LIVE as CEO and Co-founder, as well as to enter the Japan and Hong Kong market. Within one year, 17 Media became the #1 market leader in Japan. In 2018, the company raised $25M in series C round as it got ready for US IPO, which failed to materialize. 17LIVE had an unsuccessful US IPO attempt in 2018. Since then, the company reformed and transformed the business. Some key initiatives include the hiring of current CEO Hirofumi Ono, spin-off of Paktor (dating software business unit), full buy-out of founder Jeffery Huang, acquisition of MEME and HandsUp, and more. Despite the failed IPO attempt, the company continued to push for international expansion, including creating ‘LIVIT’ for the English-speaking markets to enter US, India, and North Africa. In 2019, 17's flagship live streaming app reached 10M downloads in Japan, and the business continues to push for both organic and inorganic expansion. Some key M&A highlights in the year include the acquisition of MEME Live in Southeast Asia, as well as HandsUp, a live e-commerce platform. In 2020, M17 closed out $26.5M in Series D round to continue organic growth in Japan, US and Middle East. In the same year, the company also sold its dating app business, Parktor, to rationalise M17 into a live-stream pure play business, followed by the appointment of its current Chairman, Joseph Phua, and previous Global CEO, Hirofumi Ono. With the buy-out and departure of founder Jeff Huang, the parent holding company M17 Entertainment Limited was officially renamed as 17 LIVE Group. An estimated 60 million users registered in 154 countries and territories in April 2022. In 2022, September, 17LIVE announced Group CEO Hirofumi Ono steps down. Alex Lien takes over the leadership as new Group COO; Jing Shen Ng appointed Group CTO. In 2023, March, 17LIVE announced Alex Lien promoted to Global CEO. Kenta Masuda appointed as Global CFO. === Collaboration with Ayumi Hamasaki === To celebrate its 4th anniversary, 17LIVE collaborated with Japanese singer-songwriter Ayumi Hamasaki, who led the 17LIVE 4th Anniversary meets Ayumi Hamasaki series starting October 18, 2021. Along with composer and arranger Yuta Nakano, Hamasaki judged auditioning artists competing for the chance to work with her and her production team for a debut single. The series was streamed live on the 17LIVE website, the final airing on November 11. The eventual winner was named as Yoshitaka_song. When asked why she collaborated with 17LIVE as a producer, Hamasaki commented: "Although the world has become like this (during COVID-19), I believe that the art of entertainment can give people dreams, hope, courage, and strength. I hope that kind of light will continue to shine through the entertainment industry." == Features == On 17LIVE, artists (LIVERs) are able to broadcast live, and post photos and videos from their album. The app has been designed for LIVERs to simply open the App, and start sharing contents without the need to edit or professionally curate their videos. The platform cultivates LIVERs, supports them with a local content management team, and provides artists with various functions, such as real time chatting, gifting, fan clubs, interactive competition and events. Today, 17LIVE has 46 thousands contracted artists and more than 2.3 million MAU, who spend 44 minutes on the platform every day. 17LIVE continues to advocate content-driven philosophy and delivers diverse topics, from politics and music to entertainment, to broaden its audience groups. 17LIVE also hosts offline flash events and concerts to attract new users and support LIVERs better connect with their fans. == Operation == 17LIVE has over 700 employees globally. The app provides few monetization models for LIVERs on the platform, including: Gifting: user / fans buy virtual gifts on the app to send to their favored LIVERs. Subscription: monthly subscription fan club service for access to exclusive content Pay-per-view: ticket service for online streaming concerts E-commerce: live e-commerce platform In the past, 17LIVE has encountered some regulatory headwinds with reported incidents of inappropriate livestream content on the platform. The incidents were direct results of the lack of oversight and supervision capability in place in the business at the time. Over the years, 17LIVE claims to have put in tremendous manpower and effort into improving, monitoring and maintaining control over both the live stream content and the KYC procedures and systems.
Active networking
Active networking is a communication pattern that allows packets flowing through a telecommunications network to dynamically modify the operation of the network. Active network architecture is composed of execution environments (similar to a unix shell that can execute active packets), a node operating system capable of supporting one or more execution environments. It also consists of active hardware, capable of routing or switching as well as executing code within active packets. This differs from the traditional network architecture which seeks robustness and stability by attempting to remove complexity and the ability to change its fundamental operation from underlying network components. Network processors are one means of implementing active networking concepts. Active networks have also been implemented as overlay networks. == What does it offer? == Active networking allows the possibility of highly tailored and rapid "real-time" changes to the underlying network operation. This enables such ideas as sending code along with packets of information allowing the data to change its form (code) to match the channel characteristics. The smallest program that can generate a sequence of data can be found in the definition of Kolmogorov complexity. The use of real-time genetic algorithms within the network to compose network services is also enabled by active networking. == How it relates to other networking paradigms == Active networking relates to other networking paradigms primarily based upon how computing and communication are partitioned in the architecture. === Active networking and software-defined networking === Active networking is an approach to network architecture with in-network programmability. The name derives from a comparison with network approaches advocating minimization of in-network processing, based on design advice such as the "end-to-end argument". Two major approaches were conceived: programmable network elements ("switches") and capsules, a programmability approach that places computation within packets traveling through the network. Treating packets as programs later became known as "active packets". Software-defined networking decouples the system that makes decisions about where traffic is sent (the control plane) from the underlying systems that forward traffic to the selected destination (the data plane). The concept of a programmable control plane originated at the University of Cambridge in the Systems Research Group, where (using virtual circuit identifiers available in Asynchronous Transfer Mode switches) multiple virtual control planes were made available on a single physical switch. Control Plane Technologies (CPT) was founded to commercialize this concept. == Fundamental challenges == Active network research addresses the nature of how best to incorporate extremely dynamic capability within networks. In order to do this, active network research must address the problem of optimally allocating computation versus communication within communication networks. A similar problem related to the compression of code as a measure of complexity is addressed via algorithmic information theory. One of the challenges of active networking has been the inability of information theory to mathematically model the active network paradigm and enable active network engineering. This is due to the active nature of the network in which communication packets contain code that dynamically change the operation of the network. Fundamental advances in information theory are required in order to understand such networks. == Nanoscale active networks == As the limit in reduction of transistor size is reached with current technology, active networking concepts are being explored as a more efficient means accomplishing computation and communication. More on this can be found in nanoscale networking.