Looking for the best AI paraphrasing tool? An AI paraphrasing tool is software that uses machine learning to help you get more done — it can save you hours every week by automating repetitive work. Most options offer a generous free tier, with paid plans unlocking higher limits, faster processing, and team features. Whether you are a beginner or a pro, the right AI paraphrasing tool slots into your workflow and pays for itself fast. This guide breaks down the top picks, their pros and cons, and who each one is best for.
Jais (language model)
Jais is an open-source large language model launched in August 2023. Developed as a collaboration between Emirati AI company G42, the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), and US-based Cerebras Systems, Jais was designed to produce high-quality Arabic text and was also trained on English data. The model's creation was motivated by the underrepresentation of the Arabic language in the field of generative artificial intelligence. It aims to provide a more culturally and linguistically accurate model for the world's 400 million Arabic speakers. Its name is a reference to Jebel Jais, the highest mountain in the UAE. == Background and development == Jais was developed in response to the limited availability of advanced generative artificial intelligence models for the Arabic language, despite it being spoken by over 400 million people. Existing models were often trained on limited or low-quality Arabic web content, resulting in poor performance. The project represents a significant investment by the United Arab Emirates in the field of AI as part of its national strategy. The model was created through a partnership between Inception (now Core42), a subsidiary of the Abu Dhabi-based AI company G42; the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI); and Cerebras Systems, a US company specializing in AI hardware. The model is named after Jebel Jais, the highest peak in the UAE. == Training == The initial version of Jais released in August 2023 had 13 billion parameters. In November 2023, Core42 released Jais 30B, an improved version with 30 billion parameters. Both models were trained on a subset of the Cerebras Condor Galaxy 1 supercomputer. The training dataset consisted of a mix of Arabic, English, and computer code. According to Timothy Baldwin, a professor of natural language processing at MBZUAI, training the model on a diverse Arabic dataset allows it to switch between dialects. == Features == Jais is designed to generate text in both English and Arabic. The project has also released instruction-tuned "Chat" variants for both the 13B and 30B models, which are specifically optimized for conversational applications. Additional functionality for working with images, graphs, and tabular data is planned for future releases.
Visual networking
Visual networking refers to an emerging class of user applications that combine digital video and social networking capabilities. It is based upon the premise that visual literacy, "the ability to interpret, negotiate and make meaning from information presented in the form of a moving image", is a powerful force in how humans communicate, entertain and learn. The duality of visual networking—subsuming entertainment and communications, professional and personal content, video and other digital media, data networks and social networks to create immersive experiences, when, where and how the user wants it. These applications have changed video content from long-form movies and broadcast television programming to a database of segments or "clips", and social network annotations. And the generation and distribution of content takes on a new dimension with Web 2.0 applications—participatory social-networks or communities that facilitate interactive creativity, collaboration and sharing between users. == History == The rise of visual networking is relatively recent phenomenon driven by the emergence of social networking capabilities and the ability to deliver interactive video over a broadband network. It is a natural evolution of the current social networking phenomena whereby social networking annotations are layered over broadband video to create highly interactive and immersive experiences between individuals and their content. Until early 2005 this was not considered viable due to the lack of web and broadband infrastructure designed to support the transmission of web video and the still nascent stage of social networks like MySpace and Facebook. The introduction of YouTube in February 2005 marked the first significant combination of broadband video and social network systems designed to allow users to share, rate and tag user generated and premium content. From 2006 to 2008 this trend continued to gain steam as individuals and businesses pursued new combinations of video and social networking across a wide range of entertainment, communication and learning applications. == Broadband video takes off == Video has largely been defined by its use as an entertainment medium. Since the commercial availability of the television in the late '30s video has become the dominant entertainment medium far eclipsing audio and text based entertainment both in terms of time and dollars spent. Within the past decade, video use has rapidly evolved across a broader range of devices, multiple locations and user applications. The popularization of the long-tail and user-generated video has further challenged people's ideas of what's possible with video. A key advantage of video relative to other media is its superior ability to communicate ideas and emotions economically. If a picture is worth a thousand words, then a video may be worth a thousand pictures. Video by its very nature is highly experiential, making communications more compelling, informative and memorable. == Social networking meets video == At the core of visual networking is the concept that people can participate in communities of content and communities of interest. A community of interest is defined as a community of people who share a common interest or passion. These people exchange ideas and thoughts about the given passion, but may know (or care) little about each other outside of this area. Participation in a community of interest can be compelling, entertaining and create a ‘sticky’ community where people return frequently and remain for extended periods. The unparalleled potential of the Internet to promote such connections is only now being fully recognized and exploited, through Web-based groups established for that purpose. Based on the six degrees of separation concept (the idea that any two people on the planet could make contact through a chain of no more than five intermediaries), social networking establishes interconnected Internet communities (sometimes known as personal networks) that help people make contacts that would be good for them to know, but that they would be unlikely to have met otherwise. == Transition from search to discovery == The phrase The Long Tail was, according to Chris Anderson, first coined by himself in October 2004. Anderson argued that products that are in low demand or have low sales volume can collectively make up a market share that rivals or exceeds the relatively few current bestsellers and blockbusters, if the store or distribution channel is large enough. The Long Tail also has implications for the producers of content; especially those whose products could not—for economic reasons—find a place in pre-Internet information distribution channels controlled by book publishers, record companies, movie studios, and television networks. Looked at from the producers' side, the Long Tail has made possible a flowering of creativity across all fields of human endeavor. One example of this is YouTube, where thousands of diverse videos—whose content, production value or lack of popularity make them inappropriate for traditional television—are easily accessible to a wide range of viewers. The benefit to the consumer is that they know have an almost infinite choice of content to select from able to create their own specific channels based upon their unique needs. A potential negative side effect of the long tail is the rapidly growing inventory of text, audio and video content. The storage and distribution systems of the past restricted the number of songs, video, and books making it easier to search for what was relevant to the individual. As the long-tail has grown, more and more relevant and irrelevant content passes an individual by without their knowledge. This is especially true for video because unlike text-based files which can searched and indexed for easy finding, video typically has only its title as a clue to what's in it. This lack of comprehensive meta-data has limited the applicability of traditional search models. Augmenting traditional search has been the emergence of content based discovery tools that make people aware of relevant content based upon their participation in communities of interest and/or communities of content. The idea is that users may or may not start out searching for something, but they soon begin reacting to things they find, exploring links on pages they stumble upon and taking cues from fellow surfers about where to go. Instead of the old, passive, lean-back style of watching video, viewers are actively seeking content through discovery. People interact with each other, posting comments on what they just saw. Many sites now allow people to vote on videos, ranking and rating them. Ranking is the result of one of a number of algorithms that measure how many people have watched something or how many sites link to it. == Early examples == YouTube is the best early example of a visual networking experience. YouTube is a video sharing website where users can upload, view and share video clips. Unregistered users can watch most videos on the site, while registered users are permitted to upload an unlimited number of videos. Few statistics are publicly available regarding the number of videos on YouTube. However, in July 2006, the company revealed that more than 100 million videos were being watched every day, and 2.5 billion videos were watched in June 2006. 50,000 videos were being added per day in May 2006, and this increased to 65,000 by July. In January 2008 alone, nearly 79 million users watched over 3 billion videos on YouTube. Telepresence refers to a set of technologies which allow a person to feel as if they were present, to give the appearance that they were present, or to have an effect, at a location other than their true location. Telepresence requires that the senses of the user, or users, are provided with such stimuli as to give the feeling of being in that other location. Additionally, the user(s) may be given the ability to affect the remote location. In this case, the user's position, movements, actions, voice, etc. may be sensed, transmitted and duplicated in the remote location to bring about this effect. Therefore, information may be traveling in both directions between the user and the remote location. Critical the creating an in-person experience is the presence of high-definition video perfectly synchronized with stereophonic sound. A minimum system usually includes visual feedback. Ideally, the entire field of view of the user is filled with a view of the remote location, and the viewpoint corresponds to the movement and orientation of the user's head. In this way, it differs from television or cinema, where the viewpoint is out of the control of the viewer. == Other applications == While still in its infancy, visual networking applications are beginning to emerge that span both consumer and business markets. === Mobile video === Proliferation of multi-function mobile devices, particularl
Chaffing and winnowing
Chaffing and winnowing is a cryptographic technique to achieve confidentiality without using encryption when sending data over an insecure channel. The name is derived from agriculture: after grain has been harvested and threshed, it remains mixed together with inedible fibrous chaff. The chaff and grain are then separated by winnowing, and the chaff is discarded. The cryptographic technique was conceived by Ron Rivest and published in an on-line article on 18 March 1998. Although it bears similarities to both traditional encryption and steganography, it cannot be classified under either category. This technique allows the sender to deny responsibility for encrypting their message. When using chaffing and winnowing, the sender transmits the message unencrypted, in clear text. Although the sender and the receiver share a secret key, they use it only for authentication. However, a third party can make their communication confidential by simultaneously sending specially crafted messages through the same channel. == How it works == The sender (Alice) wants to send a message to the receiver (Bob). In the simplest setup, Alice enumerates the symbols in her message and sends out each in a separate packet. If the symbols are complex enough, such as natural-language text, an attacker may be able to distinguish the real symbols from poorly faked chaff symbols, posing a similar problem as steganography in needing to generate highly realistic fakes; to avoid this, the symbols can be reduced to just single 0/1 bits, and realistic fakes can then be simply randomly generated 50:50 and are indistinguishable from real symbols. In general, the method requires each symbol to arrive in-order and to be authenticated by the receiver. When implemented over networks that may change the order of packets, the sender places the symbol's serial number in the packet, the symbol itself (both unencrypted), and a message authentication code (MAC). Many MACs use a secret key Alice shares with Bob, but it is sufficient that the receiver has a method to authenticate the packets. Rivest notes an interesting property of chaffing-and-winnowing is that third parties (such as an ISP) can opportunistically add it to communications without needing permission or coordination with the sender/recipient. A third-party (Charles) who transmits Alice's packets to Bob, interleaves the packets with corresponding bogus packets (called "chaff") with corresponding serial numbers, arbitrary symbols, and a random number in place of the MAC. Charles does not need to know the key to do that (real MACs are large enough that it is extremely unlikely to generate a valid one by chance, unlike in the example). Bob uses the MAC to find the authentic messages and drops the "chaff" messages. This process is called "winnowing". An eavesdropper located between Alice and Charles can easily read Alice's message. But an eavesdropper between Charles and Bob would have to tell which packets are bogus and which are real (i.e. to winnow, or "separate the wheat from the chaff"). That is infeasible if the MAC used is secure and Charles does not leak any information on packet authenticity (e.g. via timing). If a fourth party joins the example (named Darth) who wants to send counterfeit messages to impersonate Alice, it would require Alice to disclose her secret key. If Darth cannot force Alice to disclose an authentication key (the knowledge of which would enable him to forge messages from Alice), then her messages will remain confidential. Charles, on the other hand, is no target of Darth's at all, since Charles does not even possess any secret keys that could be disclosed. == Variations == The simple variant of the chaffing and winnowing technique described above adds many bits of overhead per bit of original message. To make the transmission more efficient, Alice can process her message with an all-or-nothing transform and then send it out in much larger chunks. The chaff packets will have to be modified accordingly. Because the original message can be reconstructed only by knowing all of its chunks, Charles needs to send only enough chaff packets to make finding the correct combination of packets computationally infeasible. Chaffing and winnowing lends itself especially well to use in packet-switched network environments such as the Internet, where each message (whose payload is typically small) is sent in a separate network packet. In another variant of the technique, Charles carefully interleaves packets coming from multiple senders. That eliminates the need for Charles to generate and inject bogus packets in the communication. However, the text of Alice's message cannot be well protected from other parties who are communicating via Charles at the same time. This variant also helps protect against information leakage and traffic analysis. == Implications for law enforcement == Ron Rivest suggests that laws related to cryptography, including export controls, would not apply to chaffing and winnowing because it does not employ any encryption at all. The power to authenticate is in many cases the power to control, and handing all authentication power to the government is beyond all reason The author of the paper proposes that the security implications of handing everyone's authentication keys to the government for law-enforcement purposes would be far too risky, since possession of the key would enable someone to masquerade and communicate as another entity, such as an airline controller. Furthermore, Ron Rivest contemplates the possibility of rogue law enforcement officials framing up innocent parties by introducing the chaff into their communications, concluding that drafting a law restricting chaffing and winnowing would be far too difficult. == Trivia == The term winnowing was suggested by Ronald Rivest's father. Before the publication of Rivest's paper in 1998 other people brought to his attention a 1965 novel, Rex Stout's The Doorbell Rang, which describes the same concept and was thus included in the paper's references.
Social Media Working Group Act of 2014
The Social Media Working Group Act of 2014 (H.R. 4263) is a bill that would direct the United States Secretary of Homeland Security to establish within the United States Department of Homeland Security (DHS) a social media working group (the Group) to provide guidance and best practices to the emergency preparedness and response community on the use of social media technologies before, during, and after a terrorist attack. The bill was introduced into the United States House of Representatives during the 113th United States Congress. == Background == === Social media === Social media is the social interaction among people in which they create, share or exchange information and ideas in virtual communities and networks. Andreas Kaplan and Michael Haenlein define social media as "a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of user-generated content." Furthermore, social media depend on mobile and web-based technologies to create highly interactive platforms through which individuals and communities share, co-create, discuss, and modify user-generated content. They introduce substantial and pervasive changes to communication between organizations, communities, and individuals. Social media differ from traditional or industrial media in many ways, including quality, reach, frequency, usability, immediacy, and permanence. === Virtual Social Media Working Group === First responders have increasingly used social media in emergency response and recovery operations. Social media tools are used to connect with citizens after a disaster and share information. The Virtual Social Media Working group (VSMWG) is an online platform that gives advice to first responders on how to safely and effectively use social media in emergency response operations. The working group is made up of subject matter experts from across the U.S. It was created by DHS in December 2010 and gives first responders guidance and best practices regarding the use of social media during emergencies. The DHS S&T and the VSMWG work with local and state governments, academics and nonprofits. Meetings of the VSMWG are chaired by the Under Secretary of Homeland Security for Science and Technology. == Provisions of the bill == This summary is based largely on the summary provided by the Congressional Research Service, a public domain source. The Social Media Working Group Act of 2014 would amend the Homeland Security Act of 2002 to direct the United States Secretary of Homeland Security to establish within the United States Department of Homeland Security (DHS) a social media working group (the Group) to provide guidance and best practices to the emergency preparedness and response community on the use of social media technologies before, during, and after a terrorist attack. The bill would require the Group to submit an annual report that includes: (1) a review of current and emerging social media technologies being used to support preparedness and response activities related to terrorist attacks, of best practices and lessons learned on the use of social media during the response to terrorist attacks that occurred during the period covered by the report, and of available training for government officials on the use of social media in response to a terrorist attack; (2) recommendations to improve DHS's use of social media and to improve information sharing among DHS and its components and among state and local governments; and (3) a summary of coordination efforts with the private sector to discuss and resolve legal, operational, technical, privacy, and security concerns. == Congressional Budget Office report == This summary is based largely on the summary provided by the Congressional Budget Office, as ordered reported by the House Committee on Homeland Security on June 11, 2014. This is a public domain source. H.R. 4263 would direct the Department of Homeland Security (DHS) to establish a working group to provide guidance and best practices on the use of social media technologies, specifically during a terrorist attack or other emergency. The group would prepare guidance for the emergency preparedness and response community. The bill would define the membership of the working group, which would include more than 20 experts from federal, state, local, and tribal governments along with nongovernmental organizations. The working group would be exempt from the Federal Advisory Committee Act and would be authorized to hold virtual meetings to fulfill the requirement to meet twice a year. The working group would be required to submit an annual report on emerging trends and best practices for emergency response through social media. Based on the cost of similar activities carried out under the DHS Acquisition and Accountability Efficiency Act and the Critical Infrastructure Research and Development Advancement Act of 2013, the Congressional Budget Office (CBO) estimates that the new DHS responsibilities and the annual report required by H.R. 4263 would cost a total of less than $500,000 annually, assuming the availability of appropriated funds. Enacting the legislation would not affect direct spending or revenues; therefore, pay-as-you-go procedures do not apply. H.R. 4263 contains no intergovernmental or private-sector mandates as defined in the Unfunded Mandates Reform Act and would impose no costs on state, local, or tribal governments. == Procedural history == The Social Media Working Group Act of 2014 was introduced into the United States House of Representatives on March 14, 2014, by Rep. Susan W. Brooks (R, IN-5). It was referred to the United States House Committee on Homeland Security and the United States House Homeland Security Subcommittee on Emergency Preparedness, Response, and Communications. On June 19, 2014, it was reported (amended) alongside House Report 113-480. On July 8, 2014, the House voted in Roll Call Vote 369 to pass the bill 375–19. == Debate and discussion == Nate Elliott, a social media expert at Forrester Research, explains that "the hope is when government or another authority tweets something, people will share it for them," but that this often doesn't happen. This problem, that "messages wash away very quickly," is the reason that the federal government is trying to formulate a better social media strategy. Rep. Steven Palazzo (R-MS), who co-sponsored the bill, stated that "social media has played a crucial role in emergency preparedness and response in Mississippi, including during disasters like Hurricane Isaac and the tornadoes that hit the Hattiesburg area a little over a year ago." He said that their goal with the bill was to "build upon existing public-private partnerships and use social media in a more strategic way in order to help save lives and property."
Conduit (company)
Conduit Ltd. is an international software company. From its founding in 2005 to 2013, its most well-known product was the Conduit toolbar, which was widely-described as malware. In 2013, it spun off its toolbar business; today, its main product is a mobile development platform that allows users to create native and web mobile applications for smartphones. == Products == From 2005 to 2013, the company's most well-known product was the Conduit toolbar, which is flagged by most antivirus software as potentially unwanted and adware. Conduit's toolbar software is often downloaded by malware packages from other publishers. The company spun off the toolbar division that manages the Conduit toolbar in 2013. Today, the company's main product is a mobile development platform that allows users to create native and web mobile applications for smartphones. App creation for its App Gallery is free, but it charges a monthly subscription fee to place apps on the App Store or Google Play. == History == Conduit was founded in 2005 by Shilo, Dror Erez, and Gaby Bilcyzk. Between years 2005 and 2013, it ran a successful but controversial toolbar platform business. Conduit was part of the so-called Download Valley companies monetizing free software and downloads by bundling adware. The toolbars were criticized by some as being very difficult to uninstall. The toolbar software was referred to as a "potentially unwanted program" by some in the computer industry because it could be used to change browser settings. The company had more than 400 employees in 2013. In September same year, Conduit spun off its entire website toolbar business division, which combined with Perion Network. After the deal, Conduit shareholders owned 81% of Perion's existing shares and both Perion and Conduit remained independent companies. The substantial size of the Conduit user base allowed Perion to immediately surpass AOL in U.S. searches. In 2015, Conduit announced it would purchase Keeprz, a mobile customer loyalty platform, for $45 million.
Information leakage
Information leakage happens whenever a system that is designed to be closed to an eavesdropper reveals some information to unauthorized parties nonetheless. In other words: Information leakage occurs when secret information correlates with, or can be correlated with, observable information. For example, when designing an encrypted instant messaging network, a network engineer without the capacity to crack encryption codes could see when messages are transmitted, even if he could not read them. == Risk vectors == A modern example of information leakage is the leakage of secret information via data compression, by using variations in data compression ratio to reveal correlations between known (or deliberately injected) plaintext and secret data combined in a single compressed stream. Another example is the key leakage that can occur when using some public-key systems when cryptographic nonce values used in signing operations are insufficiently random. Bad randomness cannot protect proper functioning of a cryptographic system, even in a benign circumstance, it can easily produce crackable keys that cause key leakage. Information leakage can sometimes be deliberate: for example, an algorithmic converter may be shipped that intentionally leaks small amounts of information, in order to provide its creator with the ability to intercept the users' messages, while still allowing the user to maintain an illusion that the system is secure. This sort of deliberate leakage is sometimes known as a subliminal channel. Generally, only very advanced systems employ defenses against information leakage. Following are the commonly implemented countermeasures : Use steganography to hide the fact that a message is transmitted at all. Use chaffing to make it unclear to whom messages are transmitted (but this does not hide from others the fact that messages are transmitted). For busy re-transmitting proxies, such as a Mixmaster node: randomly delay and shuffle the order of outbound packets - this will assist in disguising a given message's path, especially if there are multiple, popular forwarding nodes, such as are employed with Mixmaster mail forwarding. When a data value is no longer going to be used, erase it from the memory.