AI For Business Ualbany

AI For Business Ualbany — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Argumentation framework

    Argumentation framework

    In artificial intelligence and related fields, an argumentation framework is a way to deal with contentious information and draw conclusions from it using formalized arguments. In an abstract argumentation framework, entry-level information is a set of abstract arguments that, for instance, represent data or a proposition. Conflicts between arguments are represented by a binary relation on the set of arguments. In concrete terms, an argumentation framework is represented with a directed graph such that the nodes are the arguments, and the arrows represent the attack relation. There exist some extensions of the Dung's framework, like the logic-based argumentation frameworks or the value-based argumentation frameworks. == Abstract argumentation frameworks == === Formal framework === Abstract argumentation frameworks, also called argumentation frameworks à la Dung, are defined formally as a pair: A set of abstract elements called arguments, denoted A {\displaystyle A} A binary relation on A {\displaystyle A} , called attack relation, denoted R {\displaystyle R} For instance, the argumentation system S = ⟨ A , R ⟩ {\displaystyle S=\langle A,R\rangle } with A = { a , b , c , d } {\displaystyle A=\{a,b,c,d\}} and R = { ( a , b ) , ( b , c ) , ( d , c ) } {\displaystyle R=\{(a,b),(b,c),(d,c)\}} contains four arguments ( a , b , c {\displaystyle a,b,c} and d {\displaystyle d} ) and three attacks ( a {\displaystyle a} attacks b {\displaystyle b} , b {\displaystyle b} attacks c {\displaystyle c} and d {\displaystyle d} attacks c {\displaystyle c} ). Dung defines some notions : an argument a ∈ A {\displaystyle a\in A} is acceptable with respect to E ⊆ A {\displaystyle E\subseteq A} if and only if E {\displaystyle E} defends a {\displaystyle a} , that is ∀ b ∈ A {\displaystyle \forall b\in A} such that ( b , a ) ∈ R , ∃ c ∈ E {\displaystyle (b,a)\in R,\exists c\in E} such that ( c , b ) ∈ R {\displaystyle (c,b)\in R} , a set of arguments E {\displaystyle E} is conflict-free if there is no attack between its arguments, formally : ∀ a , b ∈ E , ( a , b ) ∉ R {\displaystyle \forall a,b\in E,(a,b)\not \in R} , a set of arguments E {\displaystyle E} is admissible if and only if it is conflict-free and all its arguments are acceptable with respect to E {\displaystyle E} . === Different semantics of acceptance === ==== Extensions ==== To decide if an argument can be accepted or not, or if several arguments can be accepted together, Dung defines several semantics of acceptance that allows, given an argumentation system, sets of arguments (called extensions) to be computed. For instance, given S = ⟨ A , R ⟩ {\displaystyle S=\langle A,R\rangle } , E {\displaystyle E} is a complete extension of S {\displaystyle S} only if it is an admissible set and every acceptable argument with respect to E {\displaystyle E} belongs to E {\displaystyle E} , E {\displaystyle E} is a preferred extension of S {\displaystyle S} only if it is a maximal element (with respect to the set-theoretical inclusion) among the admissible sets with respect to S {\displaystyle S} , E {\displaystyle E} is a stable extension of S {\displaystyle S} only if it is a conflict-free set that attacks every argument that does not belong in E {\displaystyle E} (formally, ∀ a ∈ A ∖ E , ∃ b ∈ E {\displaystyle \forall a\in A\backslash E,\exists b\in E} such that ( b , a ) ∈ R {\displaystyle (b,a)\in R} , E {\displaystyle E} is the (unique) grounded extension of S {\displaystyle S} only if it is the smallest element (with respect to set inclusion) among the complete extensions of S {\displaystyle S} . There exists some inclusions between the sets of extensions built with these semantics : Every stable extension is preferred, Every preferred extension is complete, The grounded extension is complete, If the system is well-founded (there exists no infinite sequence a 0 , a 1 , … , a n , … {\displaystyle a_{0},a_{1},\dots ,a_{n},\dots } such that ∀ i > 0 , ( a i + 1 , a i ) ∈ R {\displaystyle \forall i>0,(a_{i+1},a_{i})\in R} ), all these semantics coincide—only one extension is grounded, stable, preferred, and complete. Some other semantics have been defined. One introduce the notation E x t σ ( S ) {\displaystyle Ext_{\sigma }(S)} to note the set of σ {\displaystyle \sigma } -extensions of the system S {\displaystyle S} . In the case of the system S {\displaystyle S} in the figure above, E x t σ ( S ) = { { a , d } } {\displaystyle Ext_{\sigma }(S)=\{\{a,d\}\}} for every Dung's semantic—the system is well-founded. That explains why the semantics coincide, and the accepted arguments are: a {\displaystyle a} and d {\displaystyle d} . ==== Labellings ==== Labellings are a more expressive way than extensions to express the acceptance of the arguments. Concretely, a labelling is a mapping that associates every argument with a label in (the argument is accepted), out (the argument is rejected), or undec (the argument is undefined—not accepted or refused). One can also note a labelling as a set of pairs ( a r g u m e n t , l a b e l ) {\displaystyle ({\mathit {argument}},{\mathit {label}})} . Such a mapping does not make sense without additional constraint. The notion of reinstatement labelling guarantees the sense of the mapping. L {\displaystyle L} is a reinstatement labelling on the system S = ⟨ A , R ⟩ {\displaystyle S=\langle A,R\rangle } if and only if : ∀ a ∈ A , L ( a ) = i n {\displaystyle \forall a\in A,L(a)={\mathit {in}}} if and only if ∀ b ∈ A {\displaystyle \forall b\in A} such that ( b , a ) ∈ R , L ( b ) = o u t {\displaystyle (b,a)\in R,L(b)={\mathit {out}}} ∀ a ∈ A , L ( a ) = o u t {\displaystyle \forall a\in A,L(a)={\mathit {out}}} if and only if ∃ b ∈ A {\displaystyle \exists b\in A} such that ( b , a ) ∈ R {\displaystyle (b,a)\in R} and L ( b ) = i n {\displaystyle L(b)={\mathit {in}}} ∀ a ∈ A , L ( a ) = u n d e c {\displaystyle \forall a\in A,L(a)={\mathit {undec}}} if and only if L ( a ) ≠ i n {\displaystyle L(a)\neq {\mathit {in}}} and L ( a ) ≠ o u t {\displaystyle L(a)\neq {\mathit {out}}} One can convert every extension into a reinstatement labelling: the arguments of the extension are in, those attacked by an argument of the extension are out, and the others are undec. Conversely, one can build an extension from a reinstatement labelling just by keeping the arguments in. Indeed, Caminada proved that the reinstatement labellings and the complete extensions can be mapped in a bijective way. Moreover, the other Datung's semantics can be associated to some particular sets of reinstatement labellings. Reinstatement labellings distinguish arguments not accepted because they are attacked by accepted arguments from undefined arguments—that is, those that are not defended cannot defend themselves. An argument is undec if it is attacked by at least another undec. If it is attacked only by arguments out, it must be in, and if it is attacked some argument in, then it is out. The unique reinstatement labelling that corresponds to the system S {\displaystyle S} above is L = { ( a , i n ) , ( b , o u t ) , ( c , o u t ) , ( d , i n ) } {\displaystyle L=\{(a,{\mathit {in}}),(b,{\mathit {out}}),(c,{\mathit {out}}),(d,{\mathit {in}})\}} . === Inference from an argumentation system === In the general case when several extensions are computed for a given semantic σ {\displaystyle \sigma } , the agent that reasons from the system can use several mechanisms to infer information: Credulous inference: the agent accepts an argument if it belongs to at least one of the σ {\displaystyle \sigma } -extensions—in which case, the agent risks accepting some arguments that are not acceptable together ( a {\displaystyle a} attacks b {\displaystyle b} , and a {\displaystyle a} and b {\displaystyle b} each belongs to an extension) Skeptical inference: the agent accepts an argument only if it belongs to every σ {\displaystyle \sigma } -extension. In this case, the agent risks deducing too little information (if the intersection of the extensions is empty or has a very small cardinal). For these two methods to infer information, one can identify the set of accepted arguments, respectively C r σ ( S ) {\displaystyle Cr_{\sigma }(S)} the set of the arguments credulously accepted under the semantic σ {\displaystyle \sigma } , and S c σ ( S ) {\displaystyle Sc_{\sigma }(S)} the set of arguments accepted skeptically under the semantic σ {\displaystyle \sigma } (the σ {\displaystyle \sigma } can be missed if there is no possible ambiguity about the semantic). Of course, when there is only one extension (for instance, when the system is well-founded), this problem is very simple: the agent accepts arguments of the unique extension and rejects others. The same reasoning can be done with labellings that correspond to the chosen semantic : an argument can be accepted if it is in for each labelling and refused if it is out for each labelling, the others being in an undecided state (the status of the arguments can remind the

    Read more →
  • Magnetoquasistatic field

    Magnetoquasistatic field

    A magnetoquasistatic field is a class of electromagnetic field in which a slowly oscillating magnetic field is dominant. A magnetoquasistatic field is typically generated by low-frequency induction from a magnetic dipole or a current loop. The magnetic near-field of such an emitter behaves differently from the more commonly used far-field electromagnetic radiation. At low frequencies the rate of change of the instantaneous field strength with each cycle is relatively slow, giving rise to the name "magneto-quasistatic". The near field or quasistatic region typically extends no more than a wavelength from the antenna, and within this region the electric and magnetic fields are approximately decoupled. Weakly conducting non-magnetic bodies, including the human body and many mineral rocks, are effectively transparent to magnetoquasistatic fields, allowing for the transmission and reception of signals through such obstacles. Also, long-wavelength (i.e. low-frequency) signals are better able to propagate round corners than shorter-wave signals. Communication therefore need not be line-of-sight. The communication range of such signals depends on both the wavelength and the electromagnetic properties of the intervening medium at the chosen frequency, and is typically limited to a few tens of meters. == Physical principles == The laws of primary interest are Ampère's circuital law (with the displacement current density neglected) and the magnetic flux continuity law. These laws have associated with them continuity conditions at interfaces. In the absence of magnetizable materials, these laws determine the magnetic field intensity H given its source, the current density J. H is not everywhere irrotational. However, it is solenoidal everywhere. == Equipment design == A typical antenna comprises a 50-turn coil around a polyoxymethylene tube with diameter 16.5 cm, driven by a class E oscillator circuit. Such a device is readily portable when powered by batteries. Similarly, a typical receiver consist of an active receiving loop with diameter of one meter, an ultra-low-noise amplifier, and a band-pass filter. In operation the oscillator drives current through the transmitting loop to create an oscillating magnetic field. This field induces a voltage in the receiving loop, which is then amplified. Because the quasistatic region is defined within one wavelength of the electromagnetic source, emitters are limited to a frequency range between about 1 kHz and 1 MHz. Reducing the oscillating frequency increases the wavelength and hence the range of the quasistatic region, but reduces the induced voltage in the receiving loops which worsens the signal-to-noise ratio. In experiments carried out by the Carnegie Institute of Technology, the maximum range reported by was 50 meters. == Applications == === Resonant inductive coupling === In resonant coupling, the source and receiver are tuned to resonate at the same frequency and are given similar impedances. This allows power as well as information to flow from the source to the receiver. Such coupling via the magnetoquasistatic field is called resonant inductive coupling and can be used for wireless energy transfer. Applications include induction cooking, induction charging of batteries and some kinds of RFID tag. === Communications === Conventional electromagnetic communication signals cannot pass through the ground. Most mineral rock is neither electrically conducting nor magnetic, allowing magnetic fields to penetrate. Magnetoquasistatic systems have been successfully used for underground wireless communication, both surface-to-underground and between underground parties. At extremely low frequencies, below about 1 kHz, the wavelength is long enough for long-distance communication, although at a slow data rate. Such systems have been installed in submarines, with the local antenna comprising a wire up to several kilometers in length and trailed behind the vessel when at or near the surface. === Position and orientation tracking === Wireless position tracking is being increasingly used in applications such as navigation, security, and asset tracking. Conventional position tracking devices use high frequencies or microwaves, including global positioning systems (GPS), ultra-wide band (UWB) systems, and radio frequency identification systems (RFID), but these systems can easily be blocked by obstacles in their path. Magnetoquasistatic positioning takes advantage of the fact that the fields are largely undisturbed when in the presence of human beings and physical structures, and can be used for both position and orientation tracking for ranges up to 50 meters. To accurately determine the orientation and position of a dipole/emitter, allowance must be made not only for the field pattern generated by the emitter, but also for the eddy-currents they induce in the earth, which create secondary fields detectable by the receivers. By using complex image theory to correct this field generation from earth, and by using frequencies on the order of a few hundred kilohertz to obtain the required signal-to-noise ratio (SNR), it is possible to analyze the position of the dipole through azimuthal orientation, θ {\displaystyle \theta } , and inclination orientation, ϕ {\displaystyle \phi } . A Disney research team has used this technology to effectively determine the position and orientation of an American football, something not traceable through conventional wave propagation techniques due to human body obstruction. They inserted an oscillator-driven coil, around the diameter of the center of the ball, to generate the magnetoquasistatic field. The signal was able to pass undisturbed through multiple players.

    Read more →
  • Hashtag

    Hashtag

    A hashtag is a metadata tag operator that is prefaced by the hash symbol, #. On social media, hashtags are used on microblogging and photo-sharing services–especially Twitter and Tumblr–as a form of user-generated tagging that enables cross-referencing of content by topic or theme. For example, a search within Instagram for the hashtag #flowers returns all posts that have been tagged with that term. After the initial hash symbol, a hashtag may include letters, numerals or other punctuation. The use of hashtags was first proposed by American blogger and product consultant Chris Messina in a 2007 tweet. Messina made no attempt to patent the use because he felt that "they were born of the internet, and owned by no one". Hashtags became entrenched in the culture of Twitter and soon emerged across Instagram, Facebook, and YouTube. In June 2014, hashtag was added to the Oxford English Dictionary as "a word or phrase with the symbol # in front of it, used on social media websites and apps so that you can search for all messages with the same subject". == Origin and acceptance == The number sign or hash symbol, #, has long been used in information technology to highlight specific pieces of text. In 1970, the number sign was used to denote immediate address mode in the assembly language of the PDP-11 when placed next to a symbol or a number, and around 1973, '#' was introduced in the C programming language to indicate special keywords that the C preprocessor had to process first. The pound sign was adopted for use within IRC (Internet Relay Chat) networks around 1988 to label groups and topics. Channels or topics that are available across an entire IRC network are prefixed with a hash symbol # (as opposed to those local to a server, which uses an ampersand '&'). The use of the pound sign in IRC inspired Chris Messina to propose a similar system on Twitter to tag topics of interest on the microblogging network. He proposed the usage of hashtags on Twitter: How do you feel about using # (pound) for groups. As in #barcamp [msg]? According to Messina, he suggested use of the hashtag to make it easy for lay users without specialized knowledge of search protocols to find specific relevant content. Therefore, the hashtag "was created organically by Twitter users as a way to categorize messages". The first published use of the term "hash tag" was in a blog post "Hash Tags = Twitter Groupings" by Stowe Boyd, on August 26, 2007, according to lexicographer Ben Zimmer, chair of the American Dialect Society's New Words Committee. Messina's suggestion to use the hashtag was not immediately adopted by Twitter, but the convention gained popular acceptance when hashtags were used in tweets relating to the 2007 San Diego forest fires in Southern California. The hashtag gained international acceptance during the 2009–2010 Iranian election protests; Twitter users used both English- and Persian-language hashtags in communications during the events. Hashtags have since played critical roles in recent social movements such as #jesuischarlie, #BLM, and #MeToo. Beginning July 2, 2009, Twitter began to hyperlink all hashtags in tweets to Twitter search results for the hashtagged word (and for the standard spelling of commonly misspelled words). In 2010, Twitter introduced "Trending Topics" on the Twitter front page, displaying hashtags that are rapidly becoming popular, and the significance of trending hashtags has become so great that the company makes significant efforts to foil attempts to spam the trending list. During the 2010 World Cup, Twitter explicitly encouraged the use of hashtags with the temporary deployment of "hashflags", which replaced hashtags of three-letter country codes with their respective national flags. Other platforms such as YouTube and Gawker Media followed in officially supporting hashtags, and real-time search aggregators such as Google Real-Time Search began supporting hashtags. == Format == A hashtag must begin with a hash (#) character followed by other characters, and is terminated by a space or the end of the line. Some platforms may require the # to be preceded with a space. Most or all platforms that support hashtags permit the inclusion of letters (without diacritics), numerals, and underscores. Other characters may be supported on a platform-by-platform basis. Some characters, such as "&", are generally not supported as they may already serve other search functions. Hashtags are not case sensitive (a search for "#hashtag" will match "#HashTag" as well), but the use of embedded capitals (i.e., CamelCase) increases legibility and improves accessibility. Languages that do not use word dividers handle hashtags differently. In China, microblogs Sina Weibo and Tencent Weibo use a double-hashtag-delimited #HashName# format, since the lack of spacing between Chinese characters necessitates a closing tag. Twitter uses a different syntax for Chinese characters and orthographies with similar spacing conventions: the hashtag contains unspaced characters, separated from preceding and following text by spaces (e.g., '我 #爱 你' instead of '我#爱你') or by zero-width non-joiner characters before and after the hashtagged element, to retain a linguistically natural appearance (displaying as unspaced '我‌#爱‌你', but with invisible non-joiners delimiting the hashtag). === Etiquette and regulation === Some communities may limit, officially or unofficially, the number of hashtags permitted on a single post. Misuse of hashtags can lead to account suspensions. Twitter warns that adding hashtags to unrelated tweets, or repeated use of the same hashtag without adding to a conversation can filter an account from search results, or suspend the account. Individual platforms may deactivate certain hashtags either for being too generic to be useful, such as #photography on Instagram, or due to their use to facilitate illegal activities. === Alternate formats === In 2009, StockTwits began using ticker symbols preceded by the dollar sign (e.g., $XRX). In July 2012, Twitter began supporting the tag convention and dubbed it the "cashtag". The convention has extended to national currencies, and Cash App has implemented the cashtag to mark usernames. == Function == Hashtags are particularly useful in unmoderated forums that lack a formal ontological organization. Hashtags help users find content similar interest. Hashtags are neither registered nor controlled by any one user or group of users. They do not contain any set definitions, meaning that a single hashtag can be used for any number of purposes, and that the accepted meaning of a hashtag can change with time. Hashtags intended for discussion of a particular event tend to use an obscure wording to avoid being caught up with generic conversations on similar subjects, such as a cake festival using #cakefestival rather than simply #cake. However, this can also make it difficult for topics to become "trending topics" because people often use different spelling or words to refer to the same topic. For topics to trend, there must be a consensus, whether silent or stated, that the hashtag refers to that specific topic. Hashtags may be used informally to express context around a given message, with no intent to categorize the message for later searching, sharing, or other reasons. Hashtags may thus serve as a reflexive meta-commentary. This can help express contextual cues or offer more depth to the information or message that appears with the hashtag. "My arms are getting darker by the minute. #toomuchfaketan". AnoHashtags can also be used to express personal feelings and emotions. ther function of the hashtag can be used to express personal feelings and emotions. For example, with "It's Monday!! #excited #sarcasm" in which the adjectives are directly indicating the emotions of the speaker. Verbal use of the word hashtag is sometimes used in informal conversations. Use may be humorous, such as "I'm hashtag confused!" By August 2012, use of a hand gesture, sometimes called the "finger hashtag", in which the index and middle finger both hands are extended and arranged perpendicularly to form the hash, was documented. === Co-optation by other industries === Companies, businesses, and advocacy organizations have taken advantage of hashtag-based discussions for promotion of their products, services or campaigns. In the early 2010s, some television broadcasters began to employ hashtags related to programs in digital on-screen graphics, to encourage viewers to participate in a backchannel of discussion via social media prior to, during, or after the program. Television commercials have sometimes contained hashtags for similar purposes. The increased usage of hashtags as brand promotion devices has been compared to the promotion of branded "keywords" by AOL in the late 1990s and early 2000s, as such keywords were also promoted at the end of television commercials and series episodes. Organized real-world events have used hashta

    Read more →
  • Media Block

    Media Block

    A Media Block or Integrated Media Block (IMB) is a component in a digital cinema projection system. Its purpose is to convert the Digital Cinema Package (DCP) content into data that ultimately produces picture and sound in a theater in compliance with DCI anti-piracy encryption requirements. == Terminology == DCI specification allows for two different security system architectures. In the first the Media Block is outside of the projector. This design is simply referred to as a "Media Block" and is typically a device attached directly to the motherboard of a Digital Cinema server. The media block is usually connected to the projector by dual-link SDI cables. Such media block is limited to processing 2K output, downscaling 4K DCPs if necessary. The second architecture describes an "Integrated Media Block". This refers to a device attached and integrated directly into the projector, which receives image data from the server, usually via a cat6 Ethernet connection. They can process 2K and 4K output. Some hardware implementations integrate the entire server on a single board and are able to work both as a MB as well as an IMB. == Security features == All security functions are contained within a Secure Processing Block (SPB), a tamper-proof physical device. Upon ingestion into a DCP server, Key Delivery Messages (KDM) are stored on flash memory in the media block or IMB. A KDM is written to enable the playback of a specific DCP during a specific time window and on a specific media block or IMB, identified by its serial number during the authoring process. Media blocks and IMBs also contain a secure clock that is set in the factory cannot be altered by the end user, which the DCP servers to which they are attached use to determine showtimes. The secure clock prevents theaters from showing encrypted movies outside the times authorized by the KDM (e.g. after it has expired) by simply changing the date and time in the server's BIOS. Media blocks and IMBs also typically include anti-tamper devices, designed to self-destruct the unit if unauthorized modification of its hardware, software or secure clock is attempted.

    Read more →
  • AI literacy

    AI literacy

    AI literacy or artificial intelligence literacy is "a set of competencies that enables individuals to critically evaluate AI technologies; communicate and collaborate effectively with AI; and use AI as a tool online, at home, and in the workplace." AI is employed in a variety of applications, including self-driving automobiles, virtual assistants and text generation by generative AI models. Users of these tools should be able to make informed decisions. AI literacy may have an impact on students' future employment prospects. With the rise of generative AI platforms, AI literacy has become a topic of conversation in the field of education. Some think AI literacy is essential for school and college students, while others restrict or prohibit the use of AI in assignments, viewing it as a form of academic dishonesty. However, many researchers and educational institutions promote a more nuanced approach, encouraging critical engagement with AI while developing policies that balance academic integrity with opportunities for learning. == Definitions == Other definitions of AI literacy include the ability to understand, use, monitor, and critically reflect on AI applications. That use of the term usually refers to teaching skills and knowledge to the general public, particularly those who are not adept in AI and the ability to understand, use, evaluate, and ethically navigate AI. As research into AI literacy is still emerging and focused on developing context-specific skills, there is not yet a single, broadly agreed-upon definition. AI literacy is linked to other forms of literacy. AI literacy requires digital literacy, whereas scientific and computational literacy may inform it. Data literacy also significantly overlaps with it. == Categories == AI literacy encompasses multiple categories, including a theoretical understanding of how artificial intelligence works, the usage of artificial intelligence technologies, and the critical appraisal of artificial intelligence, and its ethics. === Know and understand AI === Knowledge and understanding of AI refers to a basic understanding of what artificial intelligence is and how it works. This includes familiarity with machine learning algorithms and the limitations and biases present in AI systems. Users who know and understand AI should be familiar with various technologies that use artificial intelligence, including cognitive systems, robotics and machine learning. This includes recognizing that large language models (LLMs) are machine learning models trained on extensive datasets which generate new text rather than retrieving pre-written responses. === Use and apply AI === Using and applying AI refers to the ability to use AI tools to solve problems and perform tasks such as programming and analyzing big data. Some consider prompt engineering, the practice of designing effective prompts to guide generative AI platforms more effectively, as another competency within AI literacy. === Evaluate and create AI === Evaluation and creation refers to the ability to critically evaluate the quality and reliability of AI systems. It also refers to designing and building fair and ethical AI systems. To evaluate correctly, users should also learn in which areas AI is strong, and in which areas it is weak. === AI ethics === AI ethics refers to understanding the moral implications of AI, and the making informed decisions regarding the use of AI tools. This area includes considerations such as: Accountability: Hold AI actors accountable for the operation of AI systems and adherence to ethical ideals. Accuracy: Identify and report sources of error and uncertainty in algorithms and data. Auditability: Enable other parties to audit and assess algorithm behavior via transparent information sharing. Explainability: Make sure that algorithmic judgments and the underlying data can be presented in simple language. Fairness: Prevent biases and consider varied viewpoints. To do so, increase the diversity of researchers in the field. Human Centricity and Well-being: Prioritize human well-being in AI development and deployment. Human rights Alignment: Ensure that technology do not infringe internationally recognized human rights. Inclusivity: Make AI accessible to everyone. Progress: Choose high value initiatives. Responsibility, accountability, and transparency: Foster trust via responsibility, accountability, and fairness. Robustness and Security: Make AI systems safe, secure, and resistant to manipulation or data breach. Sustainability: Choose implementations that generate long-term, useful benefits. Environmental Implications: How this tool impacts the environment, any restrictions or laws, if this impact is worth the effects or not. === Enabling AI === Support AI by developing associated knowledge and skills such as programming and statistics. == Promoting AI literacy == Several governments have recognized the need to promote AI literacy, including among adults. Such programs have been published in the United States, China, Germany and Finland. Programs intended for the general public usually consist of short and easy to understand online study units. Programs intended for children are usually project-based. Programs for students at colleges and universities often address the specific professional needs of the student, depending on their field of study. Beyond the education system, AI literacy can also be developed in the community, for example in museums. === Schools === Schools use diverse pedagogies to promote AI literacy. These include: Performing a Turing test with an intelligent agent Creating chatbots Building apps using Blockly-based programming Project-based learning Building robots Data visualization Training AI models Artificial intelligence curricula can improve students' understanding of topics such as machine learning, neural networks, and deep learning. === Higher education === Before the second decade of the 21st century, artificial intelligence was studied mainly in STEM courses. Later, projects emerged to increase artificial intelligence education, specifically to promote AI literacy. Most courses start with one or more study units that deal with basic questions such as what artificial intelligence is, where it comes from, what it can do and what it can't do. Most courses also refer to machine learning and deep learning. Some of the courses deal with moral issues in artificial intelligence. In Ireland, the Higher Education Authority published Generative AI in Higher Education Teaching & Learning: Policy Framework in December 2025, which encouraged higher education institutions to embed AI literacy across programmes as a core graduate attribute. ==== Disciplinary policy ==== As a response to the increase of generative AI use in education, several disciplines formed committees or task forces to examine context-specific approaches toward AI literacy. In spring 2025, the Modern Language Association and Conference on College Composition and Communication Joint Task Force finished development of three working papers, a guide on AI literacy for students, and a collection of resources addressing AI use in writing. The task force emphasized the need for "a culture of critical AI literacy" and included guidelines not only for students but also educators and institutions, highlighting the need for modeling ethical AI use in planning processes. Similarly, a committee formed by the American Historical Association Council published "Guiding Principles for Artificial Intelligence in History Education" which encouraged "clear and transparent engagement with generative AI." The guidelines demonstrate the value of criticality when working with generative AI in thinking and research.

    Read more →
  • Video game

    Video game

    A video game, computer game, or simply game is an electronic game that involves interaction with a user interface or input device (such as a joystick, controller, keyboard, or motion sensing device) to generate visual feedback from a display device, most commonly shown in a video format on a television set, computer monitor, flat-panel display or touchscreen on handheld devices, or a virtual reality headset. Most modern video games are audiovisual, with audio complement delivered through speakers or headphones, and sometimes also with other types of sensory feedback (e.g., haptic technology that provides tactile sensations). Some video games also allow microphone and webcam inputs for in-game chatting and livestreaming. Video games are typically categorized according to their hardware platform, which traditionally includes arcade video games, console games, and computer games (which includes LAN games, online games, and browser games). More recently, the video game industry has expanded onto mobile gaming through mobile devices (such as smartphones and tablet computers), virtual and augmented reality systems, and remote cloud gaming. Video games are also classified into a wide range of genres based on their style of gameplay and target audience. The first video game prototypes in the 1950s and 1960s were simple extensions of electronic games using video-like output from large, room-sized mainframe computers. The first consumer video game was the arcade video game Computer Space in 1971, which took inspiration from the earlier 1962 computer game Spacewar!. In 1972 came the now-iconic video game Pong and the first home console, the Magnavox Odyssey. The industry grew quickly during the "golden age" of arcade video games from the late 1970s to early 1980s but suffered from the crash of the North American video game market in 1983 due to loss of publishing control and saturation of the market. Following the crash, the industry matured, was dominated by Japanese companies such as Nintendo, Sega, and Sony, and established practices and methods around the development and distribution of video games to prevent a similar crash in the future, many of which continue to be followed. In the 2000s, the core industry centered on "AAA" games, leaving little room for riskier experimental games. Coupled with the availability of the Internet and digital distribution, this gave room for independent video game development (or "indie games") to gain prominence into the 2010s. Since then, the commercial importance of the video game industry has been increasing. The emerging Asian markets and proliferation of smartphone games in particular are altering player demographics towards casual and cozy gaming, and increasing monetization by incorporating games as a service. Today, video game development requires numerous skills, vision, teamwork, and liaisons between different parties, including developers, publishers, distributors, retailers, hardware manufacturers, and other marketers, to successfully bring a game to its consumers. As of 2020, the global video game market had estimated annual revenues of US$159 billion across hardware, software, and services, which is three times the size of the global music industry and four times that of the film industry in 2019, making it a formidable heavyweight across the modern entertainment industry. The video game market is also a major influence behind the electronics industry, where personal computer component, console, and peripheral sales, as well as consumer demands for better game performance, have been powerful driving factors for hardware design and innovation. == Origins == Early video games used interactive electronic devices with various display formats. The earliest example dates to 1947—a "cathode-ray tube amusement device" was filed for a patent on 25 January 1947, by Thomas T. Goldsmith Jr. and Estle Ray Mann, and issued on 14 December 1948, as U.S. Patent 2455992. Inspired by radar display technology, it consisted of an analog device allowing a user to control the parabolic arc of a dot on the screen to simulate a missile being fired at targets, which were paper drawings fixed to the screen. Other early examples include the Nimrod computer at the 1951 Festival of Britain; Christopher Strachey's Checkers, possibly the first game to display visuals on an electronic screen in 1952; OXO, a tic-tac-toe computer game by Alexander S. Douglas for the EDSAC in 1952; Tennis for Two, an electronic interactive game engineered by William Higinbotham in 1958; and Spacewar!, written by Massachusetts Institute of Technology students Martin Graetz, Steve Russell, and Wayne Wiitanen's on a DEC PDP-1 computer in 1962. Each game had different means of display: NIMROD had a panel of lights to play the game of Nim, OXO had a graphical display to play tic-tac-toe, Tennis for Two had an oscilloscope to display a side view of a tennis court, and Spacewar! had the DEC PDP-1's vector display to have two spaceships battle each other. These inventions laid the foundation for modern video games. In 1966, while working at Sanders Associates, Ralph H. Baer devised a system to play a basic table tennis game on a television screen. With the company's approval, Baer created the prototype known as the "Brown Box". Sanders patented Baer's innovations and licensed them to Magnavox, which commercialized the technology as the first home video game console, the Magnavox Odyssey, released in 1972. Separately, Nolan Bushnell and Ted Dabney, inspired by seeing Spacewar! running at Stanford University, devised a similar version running in a smaller coin-operated arcade cabinet using a less expensive computer. This was released as Computer Space, the first arcade video game, in 1971. Bushnell and Dabney went on to form Atari, Inc., and with Allan Alcorn, created their second arcade game in 1972, the hit ping pong-style Pong, which was directly inspired by the table tennis game on the Odyssey. Atari made a home version of Pong, which was released by Christmas 1975. The success of the Odyssey and Pong, both as an arcade game and home machine, launched the video game industry. Both Baer and Bushnell have been titled "Father of Video Games" for their contributions. == Terminology == The term "video game" was developed to describe electronic games played on a video display rather than on a teletype printer, audio speaker, or similar device. This also distinguished from handheld electronic games such as Merlin, which commonly used LED lights for indicators not in combination for imaging purposes. "Computer game" may also be used as a descriptor, as all these types of games essentially require the use of a computer processor; in some cases, it is used interchangeably with "video game". Particularly in the United Kingdom and Western Europe, this is common due to the historic relevance of domestically produced microcomputers. Other terms used include digital game, for example, by the Australian Bureau of Statistics. The term "computer game" can also refer to PC games, which are played primarily on personal computers or other flexible hardware systems, to distinguish them from console games, arcade games, or mobile games. Other terms, such as "television game", "telegame", or "TV game", had been used in the 1970s and early 1980s, particularly for home gaming consoles that rely on connection to a television set. However, these terms were also used interchangeably with "video game" in the 1970s, primarily due to "video" and "television" being synonymous. In Japan, where consoles like the Odyssey were first imported and then made within the country by the large television manufacturers such as Toshiba and Sharp Corporation, such games are known as "TV games", "TV geemu", or "terebi geemu". The term "TV game" is still commonly used into the 21st century. "Electronic game" may also be used to refer to video games, but this also incorporates devices like early handheld electronic games that lack any video output. The first appearance of the term "video game" emerged around 1973. The Oxford English Dictionary cited a 10 November 1973 BusinessWeek article as the first printed use of the term. Though Bushnell believed the term came from a vending magazine review of Computer Space in 1971, a review of the major vending magazines Vending Times and Cashbox showed that the term may have come even earlier, appearing first in a letter dated July 10, 1972. In the letter, Bushnell uses the term "video game" twice. Per video game historian Keith Smith, the sudden appearance suggested that the term had been proposed and readily adopted by those in the field. Around March 1973, Ed Adlum, who ran Cashbox's coin-operated section until 1972 and then later founded RePlay Magazine, covering the coin-op amusement field, in 1975, used the term in an article in March 1973. In a September 1982 issue of RePlay, Adlum is credited with first naming these games as "video games": "RePlay

    Read more →
  • Honeywell JetWave

    Honeywell JetWave

    Honeywell's JetWave is a piece of satellite communications hardware produced by Honeywell that enables global in-flight internet connectivity. Its connectivity is provided using Inmarsat’s GX Aviation network. The JetWave platform is used in business and general aviation, as well as defense and commercial airline users. == History == In 2012, Honeywell announced it would provide Inmarsat with the hardware for its GX Ka-band in-flight connectivity network. The Ka-band (pronounced either "kay-ay band" or "ka band") is a portion of the microwave part of the electromagnetic spectrum defined as frequencies in the range 27.5 to 31 gigahertz (GHz). In satellite communications, the Ka-band allows higher bandwidth communication. In 2017, after five years and more than 180 flight hours and testing, JetWave was launched as part of GX Aviation with Lufthansa Group. Honeywell’s JetWave was the exclusive terminal hardware option for the Inmarsat GX Aviation network; however, the exclusivity clause in that contract has expired. In July 2019, the United States Air Force selected Honeywell’s JetWave satcom system for 70 of its C-17 Globemaster III cargo planes. In December 2019, it was reported that six AirAsia aircraft had been fitted with Inmarsat’s GX Aviation Ka-band connectivity system and is slated to be implemented fleetwide across AirAsia’s Airbus A320 and A330 models in 2020, requiring installation of JetWave atop AirAsia’s fuselages. Today, Honeywell’s JetWave hardware is installed on over 1,000 aircraft worldwide. In August 2021, the Civil Aviation Administration of China approved a validation of Honeywell’s MCS-8420 JetWave satellite connectivity system for Airbus 320 aircraft. In December 2021, Honeywell, SES, and Hughes Network Systems demonstrated multi-orbit high-speed airborne connectivity for military customers using Honeywell’s JetWave MCX terminal with a Hughes HM-series modem, and SES satellites in both medium Earth orbit (MEO) and geostationary orbit (GEO). The tests achieved full duplex data rates of more than 40 megabits per second via a number of SES' (GEO) satellites including GovSat-1, and the high-throughput, low-latency O3b MEO satellite constellation, with connections moving between GEO/MEO links in under 30 sec. == Uses == === Commercial aviation === Honeywell’s JetWave enables air transport and regional aircraft to connect to Inmarsat’s GX Aviation network. The multichannel satellite (MSC) JetWave terminals share the same antenna controller, modem and router hardware with the business market, but have an MCS-8200 fuselage-mounted antenna. === Business aviation === Honeywell’s JetWave hardware allows users to connect to Inmarsat’s Jet ConneX, a business aviation broadband connectivity offering to provide Wi-Fi for connected devices. JetWave offers a tail-mount antenna for business jets. === Defense === Honeywell’s JetWave satellite communications system for defense allows users to connect to the Inmarsat GX network, offering global coverage for military airborne operators, including over water, over nontraditional flight paths and in remote areas. JetWave and the Inmarsat GX network enable mission-critical applications like real-time weather; videoconferencing; large file transfers; encryption capabilities; in-flight briefings; intelligence, surveillance, and reconnaissance video; and secure communications. JetWave is configurable for a variety of military platforms and offers antennas for large and small airframes.

    Read more →
  • Web testing

    Web testing

    Web testing is software testing that focuses on web applications. Complete testing of a web-based system before going live can help address issues before the system is revealed to the public. Issues may include the security of the web application, the basic functionality of the site, its accessibility to disabled and fully able users, its ability to adapt to the multitude of desktops, devices, and operating systems, as well as readiness for expected traffic and number of users and the ability to survive a massive spike in user traffic, both of which are related to load testing. == Web application performance tool == A web application performance tool (WAPT) is used to test web applications and web related interfaces. These tools are used for performance, load and stress testing of web applications, web sites, web API, web servers and other web interfaces. WAPT tends to simulate virtual users which will repeat either recorded URLs or specified URL and allows the users to specify number of times or iterations that the virtual users will have to repeat the recorded URLs. By doing so, the tool is useful to check for bottleneck and performance leakage in the website or web application being tested. A WAPT faces various challenges during testing and should be able to conduct tests for: Browser compatibility Operating System compatibility Windows application compatibility where required WAPT allows a user to specify how virtual users are involved in the testing environment.ie either increasing users or constant users or periodic users load. Increasing user load, step by step is called RAMP where virtual users are increased from 0 to hundreds. Constant user load maintains specified user load at all time. Periodic user load tends to increase and decrease the user load from time to time. == Web security testing == Web security testing tells us whether Web-based applications requirements are met when they are subjected to malicious input data. There is a web application security testing plug-in collection for Fire Fox == Web API testing == An application programming interface API exposes services to other software components, which can query the API. The API implementation is in charge of computing the service and returning the result to the component that send the query. A part of web testing focuses on testing these web API implementations. GraphQL is a specific query and API language. It is the focus of tailored testing techniques. Search-based test generation yields good results to generate test cases for GraphQL APIs.

    Read more →
  • Meta AI

    Meta AI

    Meta AI is a research division of Meta (formerly Facebook) that develops artificial intelligence and augmented reality technologies. == History == Meta AI was founded in 2013 as Facebook Artificial Intelligence Research (FAIR). It has workspaces in Menlo Park, London, New York City, Paris, Seattle, Pittsburgh, Tel Aviv, and Montreal as of 2025. In 2016, FAIR partnered with Google, Amazon, IBM, and Microsoft in creating the Partnership on Artificial Intelligence to Benefit People and Society. Meta AI was directed by Yann LeCun until 2018, when Jérôme Pesenti succeeded the role. Pesenti is formerly the CTO of IBM's big data group. FAIR's research includes self-supervised learning, generative adversarial networks, document classification and translation, and computer vision. FAIR released Torch deep-learning modules as well as PyTorch in 2017, an open-source machine learning framework, which was subsequently used in several deep learning technologies, such as Tesla's autopilot and Uber's Pyro. That same year, a pair of chatbots were falsely rumored to be discontinued for developing a language that was unintelligible to humans. FAIR clarified that the research had been shut down because they had accomplished their initial goal to understand how languages are generated by their models, rather than out of fear. FAIR was renamed Meta AI following the rebranding that changed Facebook, Inc. to Meta Platforms Inc. On October 1, 2025, Facebook announced "We will soon use your interactions with AI at Meta to personalize the content and ads you see". == Virtual assistant == Meta AI is also the name of the virtual assistant developed by the team, now integrated as a chatbot into Meta's social networking products. It is also available as a subscription-based stand-alone app. The virtual assistant was pre-installed on the second generation of Ray-Ban Meta smartglasses, and can incorporate inputs from the glasses' cameras after an update. It is also available on Quest 2 and newer HMDs. Since May 2024, the chatbot has summarized news from various outlets without linking directly to original articles, including in Canada, where news links are banned on its platforms. This use of news content without compensation and attribution has raised ethical and legal concerns, especially as Meta continues to reduce news visibility on its platforms. == Current research == === Natural language processing and chatbot === Natural language processing is the ability for machines to understand and generate natural language. The team is also researching unsupervised machine translation and multilingual chatbots. ==== Galactica ==== Galactica is a large language model (LLM) designed for generating scientific text. It was available for three days from 15 November 2022, before being withdrawn for generating racist and inaccurate content. ==== Llama ==== Llama is an LLM released in February 2023. As of January 2026, the most recent release is the Llama 4. === Hardware === Meta used CPUs and in-house custom chips before 2022; they switched to Nvidia GPUs since then. MTIA v1, one of their early chips, is designed for the company's content recommendation algorithms. It was fabricated on TSMC's 7 nm process technology and consumed 25W, capable of 51.2 TFlops FP16. == Controversy == The French media outlet Mediapart reports that in 2022, Facebook's parent company illegally used works accumulated by the pirate site LibGen to train its artificial intelligence.

    Read more →
  • Electronic kit

    Electronic kit

    An electronic kit is a package of electrical components used to build an electronic device. Generally, kits are composed of electronic components, a circuit diagram (schematic), assembly instructions, and often a printed circuit board (PCB) or another type of prototyping board. There are two types of kits. Some build a single device or system. Other types used for education demonstrate a range of circuits. These will include a solderless construction board of some type, such as: Components mounted in plastic blocks with side contacts, that are held together in a base, e.g. Denshi blocks Springs on a card board, the springs trap wire leads, or component leads, such as Philips EE electronic experiment kits. These are a cheap and flexible option Professional type prototyping boards, (breadboards) into which component leads are inserted, following documentation of the "kit". The first type of kit for constructing a single device normally uses a PCB on which components are soldered. They normally come with extended documentation describing which component goes where into the PCB. For advanced hobby projects, sometimes the kit may only consist of a printed circuit board and assembly instructions, and the purchaser may have to source all the parts independently; or, the vendor may provide hard-to-get or pre-programmed parts while expecting the purchaser to obtain the rest of the components. People primarily purchase electronic kits to have fun and learn how things work. They were once popular as a means to reduce the cost of buying goods, but there is usually no cost saving in buying a kit today. Some electronic kits were assembled to make complete complex devices such as color television sets, oscilloscopes, high-end audio amplifiers, amateur radio equipment, electric organs, and even computers such as the Heathkit H-8, and the LNW-80. Many of the early microprocessor computers were sold as either electronic kits or assembled and tested. Heathkit sold millions of electronic kits during its 45-year history. Home assembly of common consumer electronics items no longer provides a cost advantage over commercially manufactured and distributed devices. People still build kits for custom devices and special-purpose electronics for professional and educational use and as a hobby. Also emerging is a trend to simplify the complexity by providing preprogrammed or modular kits often provided by many suppliers online. The fun and thrill of making your own electronics have shifted, in many cases, from easy-to-comprehend applications and analog devices to more sophisticated digital devices. == Examples == The Altair 8800 (the first home computer) was also sold as a kit, as were the MK14, Sinclair ZX80, Sinclair ZX81 and Acorn Atom computers. Many S-100 bus system cards were sold only as kits. Building a Robot kit, most often with a micro controller inside, is now in fashion.

    Read more →
  • HTTP cookie

    HTTP cookie

    An HTTP cookie (also called web cookie, Internet cookie, browser cookie, or simply cookie) is a small block of data created by a web server while a user is browsing a website and placed on the user's computer or other device by the user's web browser. Cookies are placed on the device used to access a website, and more than one cookie may be placed on a user's device during a session. Cookies serve useful and sometimes essential functions on the web. They enable web servers to store stateful information (such as items added in the shopping cart in an online store) on the user's device or to track the user's browsing activity (including clicking particular buttons, logging in, or recording which pages were visited in the past). They can also be used to save information that the user previously entered into form fields, such as names, addresses, passwords, and payment card numbers for subsequent use. Authentication cookies are commonly used by web servers to authenticate that a user is logged in, and with which account they are logged in. Without the cookie, users would need to authenticate themselves by logging in on each page containing sensitive information that they wish to access. The security of an authentication cookie generally depends on the security of the issuing website and the user's web browser, and on whether the cookie data is encrypted. Security vulnerabilities may allow a cookie's data to be read by an attacker, used to gain access to user data, or used to gain access (with the user's credentials) to the website to which the cookie belongs (see cross-site scripting and cross-site request forgery for examples). Tracking cookies, and especially third-party tracking cookies, are commonly used as ways to compile long-term records of individuals' browsing histories — a potential privacy concern that prompted European and U.S. lawmakers to take action in 2011. European law requires that all websites targeting European Union member states gain "informed consent" from users before storing non-essential cookies on their device. == Background == === Origin of the name === The term cookie was coined by web-browser programmer Lou Montulli. It was derived from the term magic cookie, which is a packet of data a program receives and sends back unchanged, used by Unix programmers. === History === Magic cookies were already used in computing when computer programmer Lou Montulli had the idea of using them in web communications in June 1994. At the time, he was an employee of Netscape Communications, which was developing an e-commerce application for MCI. Vint Cerf and John Klensin represented MCI in technical discussions with Netscape Communications. MCI did not want its servers to have to retain partial transaction states, which led them to ask Netscape to find a way to store that state in each user's computer instead. Cookies provided a solution to the problem of reliably implementing a virtual shopping cart. Together with John Giannandrea, Montulli wrote the initial Netscape cookie specification the same year. Version 0.9beta of Mosaic Netscape, released on 13 October 1994, supported cookies. The first use of cookies (out of the labs) was checking whether visitors to the Netscape website had already visited the site. Montulli applied for a patent for the cookie technology in 1995, which was granted in 1998. Support for cookies was integrated with Internet Explorer in version 2, released in October 1995. The introduction of cookies was not widely known to the public at the time. In particular, cookies were accepted by default, and users were not notified of their presence. The public learned about cookies after the Financial Times published an article about them on 12 February 1996. In the same year, cookies received a lot of media attention, especially because of potential privacy implications. Cookies were discussed in two U.S. Federal Trade Commission hearings in 1996 and 1997. The development of the formal cookie specifications was already ongoing. In particular, the first discussions about a formal specification started in April 1995 on the www-talk mailing list. A special working group within the Internet Engineering Task Force (IETF) was formed. Two alternative proposals for introducing state in HTTP transactions had been proposed by Brian Behlendorf and David Kristol respectively. But the group, headed by Kristol himself and Lou Montulli, soon decided to use the Netscape specification as a starting point. In February 1996, the working group identified third-party cookies as a considerable privacy threat. The specification produced by the group was eventually published as RFC 2109 in February 1997. It specifies that third-party cookies were either not allowed at all, or at least not enabled by default. At this time, advertising companies were already using third-party cookies. The recommendation about third-party cookies of RFC 2109 was not followed by Netscape and Internet Explorer. RFC 2109 was superseded by RFC 2965 in October 2000. RFC 2965 added a Set-Cookie2 header field, which informally came to be called "RFC 2965-style cookies" as opposed to the original Set-Cookie header field which was called "Netscape-style cookies". Set-Cookie2 was seldom used, however, and was deprecated in RFC 6265 in April 2011 which was written as a definitive specification for cookies as used in the real world. No modern browser recognizes the Set-Cookie2 header field. == Terminology == === Session cookie === A session cookie (also known as an in-memory cookie, transient cookie or non-persistent cookie) exists only in temporary memory while the user navigates a website. Session cookies expire or are deleted when the user closes the web browser. Session cookies are identified by the browser by the absence of an expiration date assigned to them. === Persistent cookie === A persistent cookie expires at a specific date or after a specific length of time. For the persistent cookie's lifespan set by its creator, its information will be transmitted to the server every time the user visits the website that it belongs to, or every time the user views a resource belonging to that website from another website (such as an advertisement). For this reason, persistent cookies are sometimes referred to as tracking cookies because they can be used by advertisers to record information about a user's web browsing habits over an extended period of time. Persistent cookies are also used for reasons such as keeping users logged into their accounts on websites, to avoid re-entering login credentials at every visit. (See § Uses, below.) === Secure cookie === A secure cookie can only be transmitted over an encrypted connection (i.e. HTTPS). They cannot be transmitted over unencrypted connections (i.e. HTTP). This makes the cookie less likely to be exposed to cookie theft via eavesdropping. A cookie is made secure by adding the Secure flag to the cookie. === Http-only cookie === An http-only cookie cannot be accessed by client-side APIs, such as JavaScript. This restriction eliminates the threat of cookie theft via cross-site scripting (XSS). However, the cookie remains vulnerable to cross-site tracing (XST) and cross-site request forgery (CSRF) attacks. A cookie is given this characteristic by adding the HttpOnly flag to the cookie. === Same-site cookie === In 2016 Google Chrome version 51 introduced a new kind of cookie with attribute SameSite with possible values of Strict, Lax or None. With attribute SameSite=Strict, the browsers would only send cookies to a target domain that is the same as the origin domain. This would effectively mitigate cross-site request forgery (CSRF) attacks. With SameSite=Lax, browsers would send cookies with requests to a target domain even it is different from the origin domain, but only for safe requests such as GET (POST is unsafe) and not third-party cookies (inside iframe). Attribute SameSite=None would allow third-party (cross-site) cookies, however, most browsers require secure attribute on SameSite=None cookies. The Same-site cookie is incorporated into a new RFC draft for "Cookies: HTTP State Management Mechanism" to update RFC 6265 (if approved). Chrome, Firefox, and Edge started to support Same-site cookies. The key of rollout is the treatment of existing cookies without the SameSite attribute defined, Chrome has been treating those existing cookies as if SameSite=None, this would let all website/applications run as before. Google intended to change that default to SameSite=Lax in Chrome 80 planned to be released in February 2020, but due to potential for breakage of those applications/websites that rely on third-party/cross-site cookies and COVID-19 circumstances, Google postponed this change to Chrome 84. === Supercookie === A supercookie is a cookie with an origin of a top-level domain (such as .com) or a public suffix (such as .co.uk). Ordinary cookies, by contrast, have an origin of a specific domain name, such as ex

    Read more →
  • Friending and following

    Friending and following

    Friending is the act of adding someone to a list of "friends" on a social networking service. The notion does not necessarily involve the concept of friendship. It is also distinct from the idea of a "fan"—as employed on the WWW sites of businesses, bands, artists, and others—since it is more than a one-way relationship. A "fan" only receives things. A "friend" can communicate back to the person friending. The act of "friending" someone usually grants that person special privileges (on the service) with respect to oneself. On Facebook, for example, one's "friends" have the privilege of viewing and posting to one's "timeline". Following is a similar concept on other social network services, such as Twitter and Instagram, where a person (follower) chooses to add content from a person or page to their newsfeed. Unlike friending, following is not necessarily mutual, and a person can unfollow (stop following) or block another user at any time without affecting that user's following status. The first scholarly definition and examination of friending and defriending (the act of removing someone from one's friend list, also called unfriending) was David Fono and Kate Raynes-Goldie's "Hyperfriendship and beyond: Friends and Social Norms on LiveJournal" from 2005, which identified the use of the term as both a noun and a verb by users of early social network site and blogging platform LiveJournal, which was originally launched in 1999. == Friend/follower count, friend collecting, and multiple accounts == The addition of people to a friend list without regard to whether one actually is their friend is sometimes known as friend whoring. Matt Jones of Dopplr went so far as to coin the expression "friending considered harmful" to describe the problem of focusing upon the friending of more and more people at the expense of actually making any use of a social network. Friend collecting is the adding of hundreds or thousands of friends/followers, a not uncommon order of magnitude on some social sites. As a result, many teen users feel pressured to heavily curate their posts, posting only carefully posed and edited photographs with well-thought-out captions. Some Instagram users will create a second account, known as a Finsta (short for "Fake Instagram"). A Finsta is typically private, and the owner only allows close friends to follow it. Since the follower count is kept down, the posts can be more candid and silly in nature. Users may also create multiple accounts based on their interests. Someone with a personal social media account might be a photographer and maintain a separate account for that. There is risk associated with following large numbers of people: scholars say that social anxiety could be an effect of managing a large social media network, as users can feel jealous and have a "fear of missing out". == Unfriending and unfollowing == Unfriending is the act of removing someone from a friends list. On Facebook, this means the action is unilateral, meaning, the friendship is terminated on both sides. The act of unfriending is often used when one user was flirting and made the other uncomfortable. Unfollowing is a little different. When a user unfollows someone on Instagram or Twitter, it continues a one-sided relationship. Often, the unfollowed user doesn't realize they were unfollowed, so they continue the following. == Social network friending and friendship == There are distinct groups of "friends" that one can friend on a social networking service. The notion of a social network friend does not necessarily embody the concept of friendship. Although terminology has not yet evolved to distinguish the different types of social networking friends, they can be broken into the following three categories. friends who are actually known These are people that may be one's friends or family in real life, with whom one has regular interaction either on-line or off-line. organizational friends These are companies and other organizations who maintain a "friending" relationship as a contacts list. complete strangers These are social networking "friends" with whom one has no relationship at all. Within these categories "friends" can be made up of strong ties, weak existing ties, weak latent ties, and parasocial ties. Strong ties can be made up of close family members and friends where self-disclosure, intimacy and frequent content occur. Weak existing ties can be made up of acquaintances, co-workers and distance relatives with whom the user has inconsistent contact. Weak latent ties can be made up of people within a similar geographical location or profession that can be used as a potential future bridge to other connections. Parasocial ties can be made up of celebrities, public figures and media personas. Human nature is to reciprocate a friending, marking someone as a friend who has marked oneself as a friend. This is a social norm for social networking services. However, this leads to mixing up who is an actual friend, and who is a contact. Tagging someone as a "contact" who has marked one as a "friend" can be perceived as impolite. Other concerns about this issue are treated in Sherry Turkle's Alone Together which analyses many behavioral dynamics in social media friendships. Turkle defines herself as "cautiously optimistic", but expresses concern that distance communications may undermine genuine face-to-face spoken discourses, lessening people's expectations of one another. One social networking service, FriendFeed, allows one to friend someone as a "fake" friend. The person "fake" friended receives the usual notifications for friending, but that person's updates are not received. Gavin Bell, author of Building Social Web Applications, describes this mechanism as "ludicrous". Results from a 2007 survey the Center for the Digital Future stated that only 23% of internet users have at least one virtual friend whom they have only met online. Ideally the number of virtual friends is directly proportional to the use of the Internet, but the same survey showed 20% of heavy-users (more than 3 hours/day) who claimed an average of 8.7% online friends, reported at least one relationship that started virtually and migrated to in-person contact. This results and other concerning issues are included in the book Networked: The New Social Operating System co-written by Lee Rainie and Barry Wellman in 2012. == Ethical considerations == The act of "friending" someone on a social networking service has particular ethical implications for judges in the United States. Judicial codes of conducts in the various states generally incorporate some form of provision that judges should avoid even the appearance of impropriety. Whether this regulates and even prohibits judges "friending" attorneys that appear before them, and law enforcement personnel, has been the subject of some analysis by the judicial ethics panels of the various states. They haven't all agreed on the guidance that they have given to judges: The New York state Judicial Ethics committee in 2009 simply advised judges to employ caution, noting that the issue of "friending" someone on a social networking service is a publicly observable act that has little difference from other public behavior concerns judges already face. The Florida Judicial Ethics Advisory committee in 2009 noted that, judges being normal human beings, it was unavoidable for judges to form friendships without the responsibilities of their job. It prohibited judges from friending any attorneys that appeared before them, whilst allowing friending of those who do not, on the grounds that it may give the appearance to the general public (even if the substance is otherwise) that those attorneys who are friended hold special sway with the judge. A minority opinion of the committee asserted that there is a substantive difference between "friending" on a social networking service and actual friendship, and that the general public, being aware of the norms of social networking services, was capable of drawing this distinction and would not reasonably conclude either a special degree of influence or a violation of the code of judicial conduct. This minority opinion was outnumbered twice in 2009, both in the Judicial Ethics Advisory and in the Florida Supreme Court Judicial Ethics Advisory committee. The South Carolina judicial conduct committee in 2009 permitted judges to friend attorneys and law enforcement personnel, with the proviso that no judicial business should be conducted upon nor discussed via the social networking service. "... a judge should not become isolated from the community in which the judge lives.", the committee stated. The Kentucky Judicial Ethics committee in 2010 took the same position as the minority opinion in Florida. It urged judges to exercise caution, but recognized that the act of friending "does not, in and of itself, indicate the degree or intensity of a judge's relationship with the person who is the 'friend'

    Read more →
  • Error level analysis

    Error level analysis

    Error level analysis (ELA) is the analysis of compression artifacts in digital data with lossy compression such as JPEG. == Principles == When used, lossy compression is normally applied uniformly to a set of data, such as an image, resulting in a uniform level of compression artifacts. Alternatively, the data may consist of parts with different levels of compression artifacts. This difference may arise from the different parts having been repeatedly subjected to the same lossy compression a different number of times, or the different parts having been subjected to different kinds of lossy compression. A difference in the level of compression artifacts in different parts of the data may therefore indicate that the data has been edited. In the case of JPEG, even a composite with parts subjected to matching compressions will have a difference in the compression artifacts. In order to make the typically faint compression artifacts more readily visible, the data to be analyzed is subjected to an additional round of lossy compression, this time at a known, uniform level, and the result is subtracted from the original data under investigation. The resulting difference image is then inspected manually for any variation in the level of compression artifacts. In 2007, N. Krawetz denoted this method "error level analysis". Additionally, digital data formats such as JPEG sometimes include metadata describing the specific lossy compression used. If in such data the observed compression artifacts differ from those expected from the given metadata description, then the metadata may not describe the actual compressed data, and thus indicate that the data have been edited. == Limitations == By its nature, data without lossy compression, such as a PNG image, cannot be subjected to error level analysis. Consequently, since editing could have been performed on data without lossy compression with lossy compression applied uniformly to the edited, composite data, the presence of a uniform level of compression artifacts does not rule out editing of the data. Additionally, any non-uniform compression artifacts in a composite may be removed by subjecting the composite to repeated, uniform lossy compression. Also, if the image color space is reduced to 256 colors or less, for example, by conversion to GIF, then error level analysis will generate useless results. More significant, the actual interpretation of the level of compression artifacts in a given segment of the data is subjective, and the determination of whether editing has occurred is therefore not robust. == Controversy == In May 2013, Dr Neal Krawetz used error level analysis on the 2012 World Press Photo of the Year and concluded on his Hacker Factor blog that it was "a composite" with modifications that "fail to adhere to the acceptable journalism standards used by Reuters, Associated Press, Getty Images, National Press Photographer's Association, and other media outlets". The World Press Photo organizers responded by letting two independent experts analyze the image files of the winning photographer and subsequently confirmed the integrity of the files. One of the experts, Hany Farid, said about error level analysis that "It incorrectly labels altered images as original and incorrectly labels original images as altered with the same likelihood". Krawetz responded by clarifying that "It is up to the user to interpret the results. Any errors in identification rest solely on the viewer". In May 2015, the citizen journalism team Bellingcat wrote that error level analysis revealed that the Russian Ministry of Defense had edited satellite images related to the Malaysia Airlines Flight 17 disaster. In a reaction to this, image forensics expert Jens Kriese said about error level analysis: "The method is subjective and not based entirely on science", and that it is "a method used by hobbyists". On his Hacker Factor Blog, the inventor of error level analysis Neal Krawetz criticized both Bellingcat's use of error level analysis as "misinterpreting the results" but also on several points Jens Kriese's "ignorance" regarding error level analysis.

    Read more →
  • Hardware trojan

    Hardware trojan

    A hardware trojan (HT) is a malicious modification of the circuitry of an integrated circuit. A hardware trojan is completely characterized by its physical representation and its behavior. The payload of an HT is the entire activity that the Trojan executes when it is triggered. In general, trojans try to bypass or disable the security fence of a system: for example, leaking confidential information by radio emission. HTs also could disable, damage or destroy the entire chip or components of it. Hardware trojans may be introduced as hidden front-doors that are inserted while designing a computer chip, by using a pre-made application-specific integrated circuit (ASIC) semiconductor intellectual property core (IP core) that have been purchased from a non-reputable source, or inserted internally by a rogue employee, either acting on their own, or on behalf of rogue special interest groups, or state sponsored spying and espionage. One paper published by IEEE in 2015 explains how a hardware design containing a trojan could leak a cryptographic key leaked over an antenna or network connection, provided that the correct "easter egg" trigger is applied to activate the data leak. In high security governmental IT departments, hardware trojans are a well known problem when buying hardware such as: a KVM switch, keyboards, mice, network cards, or other network equipment. This is especially the case when purchasing such equipment from non-reputable sources that could have placed hardware trojans to leak keyboard passwords, or provide remote unauthorized entry. == Background == In a diverse global economy, outsourcing of production tasks is a common way to lower a product's cost. Embedded hardware devices are not always produced by the firms that design and/or sell them, nor in the same country where they will be used. Outsourced manufacturing can raise doubt about the evidence for the integrity of the manufactured product (i.e., one's certainty that the end-product has no design modifications compared to its original design). Anyone with access to the manufacturing process could, in theory, introduce some change to the final product. For complex products, small changes with large effects can be difficult to detect. The threat of a serious, malicious, design alteration can be especially relevant to government agencies. Resolving doubt about hardware integrity is one way to reduce technology vulnerabilities in the military, finance, energy and political sectors of an economy. Since fabrication of integrated circuits in untrustworthy factories is common, advanced detection techniques have emerged to discover when an adversary has hidden additional components in, or otherwise sabotaged, the circuit's function. == Characterization of hardware trojans == An HT can be characterized by several methods such as by its physical representation, activation phase and its action phase. Alternative methods characterize the HT by trigger, payload and stealth. === Physical characteristics === One of this physical trojan characteristics is the type. The type of a trojan can be either functional or parametric. A trojan is functional if the adversary adds or deletes any transistors or gates to the original chip design. The other kind of trojan, the parametric trojan, modifies the original circuitry, e.g. thinning of wires, weakening of flip-flops or transistors, subjecting the chip to radiation, or using focused ion-beams (FIB) to reduce the reliability of a chip. The size of a trojan is its physical extension or the number of components it is made of. Because a trojan can consist of many components, the designer can distribute the parts of a malicious logic on the chip. The additional logic can occupy the chip wherever it is needed to modify, add, or remove a function. Malicious components can be scattered, called loose distribution, or consist of only few components, called tight distribution, so the area is small where the malicious logic occupies the layout of the chip. In some cases, high-effort adversaries in may regenerate the layout so that the placement of the components of the IC is altered. In rare cases the chip dimension is altered. These changes are structural alterations. === Activation characteristics === The typical trojan is condition-based: It is triggered by sensors, internal logic states, a particular input pattern or an internal counter value. Condition-based trojans are detectable with power traces to some degree when inactive. That is due to the leakage currents generated by the trigger or counter circuit activating the trojan. Hardware trojans can be triggered in different ways. A trojan can be internally activated, which means it monitors one or more signals inside the IC. The malicious circuitry could wait for a count down logic an attacker added to the chip, so that the trojan awakes after a specific time-span. The opposite is externally activated. There can be malicious logic inside a chip, that uses an antenna or other sensors the adversary can reach from outside the chip. For example, a trojan could be inside the control system of a cruising missile. The owner of the missile does not know, that the enemy will be able to switch off the rockets by radio. A trojan which is always-on can be a reduced wire. A chip that is modified in this way produces errors or fails every time the wire is used intensely. Always-on circuits are hard to detect with power trace. In this context combinational trojans and sequential trojans are distinguished. A combinational trojan monitors internal signals until a specific condition happens. A sequential trojan is also an internally activated condition-based circuit, but it monitors the internal signals and searches for sequences not for a specific state or condition like the combinational trojans do. ==== Cryptographic key extraction ==== Extraction of secret keys by means of a hardware trojan without detecting the trojan requires that the trojan uses a random signal or some cryptographic implementation itself. To avoid storing a cryptographic key in the trojan itself and reduction, a physical unclonable function can be used. Physical unclonable functions are small in size and can have an identical layout while the cryptographic properties are different. === Action characteristics === A HT could modify the chip's function or could change the chip's parametric properties (e.g. provokes a process delay). Confidential information can also be transmitted to the adversary (transmission of key information). === Peripheral device hardware trojans === A relatively new threat vector to networks and network endpoints is a HT appearing as a physical peripheral device that is designed to interact with the network endpoint using the approved peripheral device's communication protocol. For example, a USB keyboard that hides all malicious processing cycles from the target network endpoint to which it is attached by communicating with the target network endpoint using unintended USB channels. Once sensitive data is ex-filtrated from the target network endpoint to the HT, the HT can process the data and decide what to do with the data: store the data to memory for later physical retrieval of the HT or possibly ex-filtrate the data to the internet using wireless or using the compromised network endpoint as a pivot. == Potential of threat == A common trojan is passive most of the time-span an altered device is in use. If a trojan is activated the device functionality can be changed, the device can be destroyed or disabled, the device can leak confidential information or the HT may tear down the security and safety of the device. Trojans are stealthy, to avoid detection of the trojan the precondition for activation is a very rare event. Traditional testing techniques are not sufficient. A manufacturing fault happens at a random position while malicious changes are well placed to avoid detection. == Detection == === Physical inspection === First, the molding coat is cut to reveal the circuitry. Then, the engineer repeatedly scans the surface while grinding the layers of the chip. There are several operations to scan the circuitry. Typical visual inspection methods are: scanning optical microscopy (SOM), scanning electron microscopy (SEM), pico-second imaging circuit analysis (PICA), voltage contrast imaging (VCI), light induced voltage alteration (LIVA) or charge induced voltage alteration (CIVA). To compare the floor plan of the chip has to be compared with the image of the actual chip. This is still quite challenging to do. To detect Trojan hardware which include (crypto) keys which are different, an image diff can be taken to reveal the different structure on the chip. The only known hardware Trojan using unique crypto keys but having the same structure is. This property enhances the undetectability of the trojan. === Functional testing === This detection method stimulates the input ports of a chip and monitors the output

    Read more →
  • Media Block

    Media Block

    A Media Block or Integrated Media Block (IMB) is a component in a digital cinema projection system. Its purpose is to convert the Digital Cinema Package (DCP) content into data that ultimately produces picture and sound in a theater in compliance with DCI anti-piracy encryption requirements. == Terminology == DCI specification allows for two different security system architectures. In the first the Media Block is outside of the projector. This design is simply referred to as a "Media Block" and is typically a device attached directly to the motherboard of a Digital Cinema server. The media block is usually connected to the projector by dual-link SDI cables. Such media block is limited to processing 2K output, downscaling 4K DCPs if necessary. The second architecture describes an "Integrated Media Block". This refers to a device attached and integrated directly into the projector, which receives image data from the server, usually via a cat6 Ethernet connection. They can process 2K and 4K output. Some hardware implementations integrate the entire server on a single board and are able to work both as a MB as well as an IMB. == Security features == All security functions are contained within a Secure Processing Block (SPB), a tamper-proof physical device. Upon ingestion into a DCP server, Key Delivery Messages (KDM) are stored on flash memory in the media block or IMB. A KDM is written to enable the playback of a specific DCP during a specific time window and on a specific media block or IMB, identified by its serial number during the authoring process. Media blocks and IMBs also contain a secure clock that is set in the factory cannot be altered by the end user, which the DCP servers to which they are attached use to determine showtimes. The secure clock prevents theaters from showing encrypted movies outside the times authorized by the KDM (e.g. after it has expired) by simply changing the date and time in the server's BIOS. Media blocks and IMBs also typically include anti-tamper devices, designed to self-destruct the unit if unauthorized modification of its hardware, software or secure clock is attempted.

    Read more →