AI Chat You

AI Chat You — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

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  Distributed concurrency control

  Distributed concurrency control is the concurrency control of a system distributed over a computer network (Bernstein et al. 1987, Weikum and Vossen 2001). In database systems and transaction processing (transaction management) distributed concurrency control refers primarily to the concurrency control of a distributed database. It also refers to the concurrency control in a multidatabase (and other multi-transactional object) environment (e.g., federated database, grid computing, and cloud computing environments. A major goal for distributed concurrency control is distributed serializability (or global serializability for multidatabase systems). Distributed concurrency control poses special challenges beyond centralized one, primarily due to communication and computer latency. It often requires special techniques, like distributed lock manager over fast computer networks with low latency, like switched fabric (e.g., InfiniBand). The most common distributed concurrency control technique is strong strict two-phase locking (SS2PL, also named rigorousness), which is also a common centralized concurrency control technique. SS2PL provides both the serializability and strictness. Strictness, a special case of recoverability, is utilized for effective recovery from failure. For large-scale distribution and complex transactions, distributed locking's typical heavy performance penalty (due to delays, latency) can be saved by using the atomic commitment protocol, which is needed in a distributed database for (distributed) transactions' atomicity.

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  Radio network

  A radio network is a system that distributes radio signals to multiple receivers or enables two-way communication between stations and mobile units. Worldwide, radio networks include broadcast networks, such as BBC Radio in the United Kingdom and NPR in the United States, which transmit one-to-many signals for news, entertainment, and public information; two-way radio networks, used by police, fire services, taxicabs, and delivery fleets for operational communication; and cellular networks, such as Verizon, Vodafone, and China Mobile, which provide mobile telephony and data services using frequency or time division duplexing. While all rely on radio-frequency technology like transmitters, receivers, and antennas, their network architectures, protocols, and regulatory frameworks differ substantially across applications and regions. The two-way type of radio network shares many of the same technologies and components as the broadcast-type radio network but is generally set up with fixed broadcast points (transmitters) with co-located receivers and mobile receivers/transmitters or transceivers. In this way both the fixed and mobile radio units can communicate with each other over broad geographic regions ranging in size from small single cities to entire states/provinces or countries. There are many ways in which multiple fixed transmit/receive sites can be interconnected to achieve the range of coverage required by the jurisdiction or authority implementing the system: conventional wireless links in numerous frequency bands, fibre-optic links, or microwave links. In all of these cases the signals are typically backhauled to a central switch of some type where the radio message is processed and resent (repeated) to all transmitter sites where it is required to be heard. In contemporary two-way radio systems, a concept called trunking is commonly used to achieve better efficiency of radio spectrum use. It provides a very wide range of coverage, with no switching of channels required by the mobile radio user as it roams throughout the system coverage. Trunking of two-way radio is identical to the concept used for cellular phone systems where each fixed and mobile radio is specifically identified to the system controller and its operation is switched by the controller. == Broadcasting networks == The broadcast type of radio network is a network system which distributes radio programming to multiple stations simultaneously, or slightly delayed, for the purpose of extending total coverage beyond the limits of a single broadcast signal. The resulting expanded audience for radio programming or information essentially applies the benefits of mass-production to the broadcasting enterprise. A radio network has two sales departments, one to package and sell programs to radio stations, and one to sell the audience of those programs to advertisers. Most radio networks also produce much of their programming. Originally, radio networks owned some or all of the stations that broadcast the network's radio format programming. Presently however, there are many networks that do not own any stations and only produce and/or distribute programming. Similarly station ownership does not always indicate network affiliation. A company might own stations in several different markets and purchase programming from a variety of networks. Radio networks rose rapidly with the growth of regular broadcasting of radio to home listeners in the 1920s. This growth took various paths in different places. In Britain the BBC was developed with public funding, in the form of a broadcast receiver license, and a broadcasting monopoly in its early decades. In contrast, in the United States various competing commercial broadcasting networks arose funded by advertising revenue. In that instance, the same corporation that owned or operated the network often manufactured and marketed the listener's radio. Major technical challenges to be overcome when distributing programs over long distances are maintaining signal quality and managing the number of switching/relay points in the signal chain. Early on, programs were sent to remote stations (either owned or affiliated) by various methods, including leased telephone lines, pre-recorded gramophone records and audio tape. The world's first all-radio, non-wireline network was claimed to be the Rural Radio Network, a group of six upstate New York FM stations that began operation in June 1948. Terrestrial microwave relay, a technology later introduced to link stations, has been largely supplanted by coaxial cable, fiber, and satellite, which usually offer superior cost-benefit ratios. Many early radio networks evolved into television networks.

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  Greedy embedding

  In distributed computing and geometric graph theory, greedy embedding is a process of assigning coordinates to the nodes of a telecommunications network in order to allow greedy geographic routing to be used to route messages within the network. Although greedy embedding has been proposed for use in wireless sensor networks, in which the nodes already have positions in physical space, these existing positions may differ from the positions given to them by greedy embedding, which may in some cases be points in a virtual space of a higher dimension, or in a non-Euclidean geometry. In this sense, greedy embedding may be viewed as a form of graph drawing, in which an abstract graph (the communications network) is embedded into a geometric space. The idea of performing geographic routing using coordinates in a virtual space, instead of using physical coordinates, is due to Rao et al. Subsequent developments have shown that every network has a greedy embedding with succinct vertex coordinates in the hyperbolic plane, that certain graphs including the polyhedral graphs have greedy embeddings in the Euclidean plane, and that unit disk graphs have greedy embeddings in Euclidean spaces of moderate dimensions with low stretch factors. == Definitions == In greedy routing, a message from a source node s to a destination node t travels to its destination by a sequence of steps through intermediate nodes, each of which passes the message on to a neighboring node that is closer to t. If the message reaches an intermediate node x that does not have a neighbor closer to t, then it cannot make progress and the greedy routing process fails. A greedy embedding is an embedding of the given graph with the property that a failure of this type is impossible. Thus, it can be characterized as an embedding of the graph with the property that for every two nodes x and t, there exists a neighbor y of x such that d(x,t) > d(y,t), where d denotes the distance in the embedded space. == Graphs with no greedy embedding == Not every graph has a greedy embedding into the Euclidean plane; a simple counterexample is given by the star K1,6, a tree with one internal node and six leaves. Whenever this graph is embedded into the plane, some two of its leaves must form an angle of 60 degrees or less, from which it follows that at least one of these two leaves does not have a neighbor that is closer to the other leaf. In Euclidean spaces of higher dimensions, more graphs may have greedy embeddings; for instance, K1,6 has a greedy embedding into three-dimensional Euclidean space, in which the internal node of the star is at the origin and the leaves are a unit distance away along each coordinate axis. However, for every Euclidean space of fixed dimension, there are graphs that cannot be embedded greedily: whenever the number n is greater than the kissing number of the space, the graph K1,n has no greedy embedding. == Hyperbolic and succinct embeddings == Unlike the case for the Euclidean plane, every network has a greedy embedding into the hyperbolic plane. The original proof of this result, by Robert Kleinberg, required the node positions to be specified with high precision, but subsequently it was shown that, by using a heavy path decomposition of a spanning tree of the network, it is possible to represent each node succinctly, using only a logarithmic number of bits per point. In contrast, there exist graphs that have greedy embeddings in the Euclidean plane, but for which any such embedding requires a polynomial number of bits for the Cartesian coordinates of each point. == Special classes of graphs == === Trees === The class of trees that admit greedy embeddings into the Euclidean plane has been completely characterized, and a greedy embedding of a tree can be found in linear time when it exists. For more general graphs, some greedy embedding algorithms such as the one by Kleinberg start by finding a spanning tree of the given graph, and then construct a greedy embedding of the spanning tree. The result is necessarily also a greedy embedding of the whole graph. However, there exist graphs that have a greedy embedding in the Euclidean plane but for which no spanning tree has a greedy embedding. === Planar graphs === Papadimitriou & Ratajczak (2005) conjectured that every polyhedral graph (a 3-vertex-connected planar graph, or equivalently by Steinitz's theorem the graph of a convex polyhedron) has a greedy embedding into the Euclidean plane. By exploiting the properties of cactus graphs, Leighton & Moitra (2010) proved the conjecture; the greedy embeddings of these graphs can be defined succinctly, with logarithmically many bits per coordinate. However, the greedy embeddings constructed according to this proof are not necessarily planar embeddings, as they may include crossings between pairs of edges. For maximal planar graphs, in which every face is a triangle, a greedy planar embedding can be found by applying the Knaster–Kuratowski–Mazurkiewicz lemma to a weighted version of a straight-line embedding algorithm of Schnyder. The strong Papadimitriou–Ratajczak conjecture, that every polyhedral graph has a planar greedy embedding in which all faces are convex, remains unproven. === Unit disk graphs === The wireless sensor networks that are the target of greedy embedding algorithms are frequently modeled as unit disk graphs, graphs in which each node is represented as a unit disk and each edge corresponds to a pair of disks with nonempty intersection. For this special class of graphs, it is possible to find succinct greedy embeddings into a Euclidean space of polylogarithmic dimension, with the additional property that distances in the graph are accurately approximated by distances in the embedding, so that the paths followed by greedy routing are short.

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  Photonically Optimized Embedded Microprocessors

  The Photonically Optimized Embedded Microprocessors (POEM) is DARPA program. It should demonstrate photonic technologies that can be integrated within embedded microprocessors and enable energy-efficient high-capacity communications between the microprocessor and DRAM. For realizing POEM technology CMOS and DRAM-compatible photonic links should operate at high bit-rates with very low power dissipation. == Current research == Currently research in this field is at University of Colorado, Berkley University, and Nanophotonic Systems Laboratory ( Ultra-Efficient CMOS-Compatible Grating Coupler Design).

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  The AI Con

  The AI Con: How to Fight Big Tech's Hype and Create the Future We Want is a 2025 non-fiction book by linguist Emily M. Bender and sociologist Alex Hanna. It argues that much of what is labeled "artificial intelligence" is a misleading term that obscures ordinary automation while concentrating power in a small number of technology firms. The book was published in May 2025 by Harper in the United States and Bodley Head in the United Kingdom. It was developed alongside the authors' long-running podcast Mystery AI Hype Theater 3000, which critiques exaggerated claims about AI. == Synopsis == The authors present AI as a marketing umbrella that encourages audiences to infer understanding and agency where none exist. They argue readers should treat such language skeptically and to separate specific automated tasks from broad claims of intelligence. The book describes a recurring hype cycle in which corporate narratives justify data and labor extraction, the replacement of human services with cheaper substitutes, and the diversion of attention from present harms to speculative futures. While acknowledging limited uses such as pattern recognition, the authors argue that contemporary systems are best understood as text and media generators shaped by training data and human labor, not as thinking or reasoning entities. A central theme is the social and environmental cost of scaling these systems, including increased energy and water use, the appropriation of creative work for training, and the outsourcing of ghost work to low-paid data workers worldwide. These costs are linked to workplace effects, with the authors arguing that automation rarely eliminates jobs outright and more often degrades them through surveillance, work intensification, and unpaid oversight. As alternatives to passive adoption, the authors propose concrete responses: asking precise questions about what is being automated and why, demanding transparency about data and evaluation, and practicing what they call strategic refusal when deployment conflicts with evidence or values. The book also develops a vocabulary for public debate, rejecting both boosterish and doomerish narratives as grounded in the same assumption that AI is a singular, autonomous force. The authors recommend reading strategies such as favoring trusted human sources over automated summaries and using humor to deflate inflated claims. They describe a link between language to policy and power, arguing that precise terminology can help policymakers and the public resist austerity-driven automation and demand accountability for errors and harms. == Reception == The Guardian praised the book's myth-busting approach and its analysis of how hype erodes cultural and civic life by normalizing synthetic media as a substitute for human judgment. Kirkus Reviews described it as a contrarian account that catalogs concrete risks while cutting through speculative predictions. An interview in Business Insider highlighted the authors' accessible frameworks, including their proposal to describe chatbots as conversation simulators and to evaluate systems in terms of values, labor, and evidence. Coverage in GeekWire emphasized the book's call for resistance through collective bargaining, stronger data rights, and a norm of rejecting deployments that fail basic standards of necessity and evaluation. Some reviews were more critical. A review in LLRX argued that the book's tone could be overly polemical and that it gave limited attention to potential benefits claimed for generative systems. Coverage in the Financial Times, focused on Bender's broader public scholarship, situated the book within her long-standing critique of anthropomorphic narratives about large language models and her advocacy for more democratic oversight of automated systems.

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  Grid network

  A grid network is a computer network consisting of a number of computer systems connected in a grid topology. In a regular grid topology, each node in the network is connected with two neighbors along one or more dimensions. If the network is one-dimensional, and the chain of nodes is connected to form a circular loop, the resulting topology is known as a ring. Network systems such as FDDI use two counter-rotating token-passing rings to achieve high reliability and performance. In general, when an n-dimensional grid network is connected circularly in more than one dimension, the resulting network topology is a torus, and the network is called "toroidal". When the number of nodes along each dimension of a toroidal network is 2, the resulting network is called a hypercube. A parallel computing cluster or multi-core processor is often connected in regular interconnection network such as a de Bruijn graph, a hypercube graph, a hypertree network, a fat tree network, a torus, or cube-connected cycles. A grid network is not the same as a grid computer or a computational grid, although the nodes in a grid network are usually computers, and grid computing requires some kind of computer network or "universal coding" to interconnect the computers.

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  Web science

  Web science is an emerging interdisciplinary field concerned with the study of large-scale socio-technical systems, particularly the World Wide Web. It considers the relationship between people and technology, the ways that society and technology co-constitute one another and the impact of this co-constitution on broader society. Web Science combines research from disciplines as diverse as sociology, computer science, economics, and mathematics. The Web Science Institute, founded at the University of Southampton by director Wendy Hall and colleagues, describes Web Science as focusing "the analytical power of researchers from disciplines as diverse as mathematics, sociology, economics, psychology, law and computer science to understand and explain the Web. It is necessarily interdisciplinary – as much about social and organizational behaviour as about the underpinning technology." A central pillar of Web science development is Artificial Intelligence or "AI". The current artificial intelligence that in development at the moment is Human-Centered, with goals to further professional development courses as well as influencing public policy. Artificial intelligence developers are focused on the most impactful uses of this technology, while also hoping to expedite the growth and development of the human race. An early definition was given by American computer scientist Ben Shneiderman: "Web Science" is processing the information available on the web in similar terms to those applied to natural environment. == Areas of activity == === Emergent properties === Philip Tetlow, an IBM-based scientist influential in the emergence of web science as an independent discipline, argued for the concept of web life, which considers the Web not as a connected network of computers, as in common interpretations of the Internet, but rather as a sociotechnical machine capable of fusing together individuals and organisations into larger coordinated groups. It argues that unlike the technologies that have come before it, the Web is different in that its phenomenal growth and complexity are starting to outstrip our capability to control it directly, making it impossible for us to grasp its completeness in one go. Tetlow made use of Fritjof Capra's concept of the 'web of life' as a metaphor. == Research groups == There are numerous academic research groups engaged in Web Science research, many of which are members of WSTNet, the Web Science Trust Network of research labs. Health Web Science emerged as a sub-discipline of Web Science that studies the role of the Web's impact on human's health outcomes and how to further utilize the Web to improve health outcomes. These groups focus on the developmental possibilities, provided through Web Science, in areas such as health care and social welfare. Discussion of web science has been widely adopted as a method in which the internet can have a real world impact in the field of medicine, currently coined Medicine 2.0. The World Wide Web acts as a medium for the spread and circulation of knowledge, though these various research groups consider themselves responsible for maintaining verifiable and testable knowledge. Using their knowledge of the healthcare system as well as web science, researchers are focused on formatting and structuring their knowledge in a way that is easily accessible throughout the internet. The World Wide Web is quickly evolving meaning that the information we provide and its formatting must also. Recognizing the overlap between both aspects, the spread of knowledge and development of the internet, allows us to properly display our knowledge in a manner that evolves as quickly as the internet and everyday medical research. The accessibility of the internet and quick development of knowledge must be companied with efficient formatting to allocate successful dissemination of information, as described by these various researcher groups. == Related major conferences == Association for Computing Machinery (ACM), Hypertext Conference (HT) sponsored by SIGWEB ACM SIGCHI Conference on Human Factors in Computing Systems (CHI) International AAAI Conference on Weblogs and Social Media (ICWSM) The Web Conference (WWW) Association for Computing Machinery (ACM) Web Science Conference (WebSci)

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  Creepiness

  Creepiness is the state of being creepy, or causing an unpleasant feeling of fear or unease to someone and/or something. Certain traits or hobbies may make people seem creepy to others; interest in horror or the macabre might come across as 'creepy', and often people who are perverted or exhibit predatory behavior are called 'creeps'. The internet, especially some functions of social media, has been described as increasingly creepy. Adam Kotsko has compared the modern conception of creepiness to the Freudian concept of unheimlich. The term has also been used to describe paranormal or supernatural phenomena. Some people have phobias which are irrational fears, which can make them perceive something as creepy. == History and studies == "Creepiness" is subjective: for example some dolls have been described as creepy, while what makes something "creepy" or "strange" to someone might seem normal to someone else. The adjective "creepy", referring to a feeling of creeping in the flesh, was first used in 1831, but it was Charles Dickens who coined and popularized the term "the creeps" in his 1849 novel David Copperfield. In the 20th century, association was made between involuntary celibacy and creepiness. The concept of creepiness has only recently been formally addressed in social media marketing. The sensation of creepiness has only recently been the subject of psychological research, despite the widespread colloquial use of the word throughout the years. Francis T. McAndrew of Knox College is the first psychologist to do an empirical study on creepiness. == Causes == The state of creepiness has been associated with "feeling scared, nervous, anxious or worried", "awkward or uncomfortable", "vulnerable or violated" in a study conducted by Watt et al. This state arises in the presence of a creepy element, which can be an individual or, as recently observed, new technologies. === Individuals === Creepiness can be caused by the appearance of an individual. Another study investigated the characteristics that make people creepy. Creepy people were thought to be more often male than female by an overwhelming majority of participants (around 95% of both male and female participants). Another study conducted by Watt et al. also found that participants associated the ectomorphic body type (more linear) with creepiness, more than the other two body types (51% vs mesomorphic, 24% and endomorphic, 23%). Other cues of creepiness included low hygiene, especially according to female participants, and a disheveled appearance. Participants also identified the face as an area with potentially creepy features: in particular the eyes and the teeth. Both of those physical features were deemed creepy not only for their unpleasant appearance (ex. squinty eyes or crooked teeth) but also for the movements and expressions they engaged it (ex. darting eye movements and odd smiles). In fact, appearance does not seem to be the only factor making an individual creepy: behaviors provide cues as well. Behaviors such as "being unusually quiet and staring (34%), following or lurking (15%), behaving abnormally (21%), or in a socially awkward, "sketchy" or suspicious way (20%)" are all contributing to a feeling of creepiness, as described by Watt et al.'s study. === Technology === In addition to other individuals, new technologies, such as marketing's targeted ads and AI, have been qualified as creepy. A study by Moore et al. described what aspect of marketing participants considered creepy. The main three reasons are the following: using invasive tactics, causing discomfort and violating of norms. Invasive tactics are practiced by marketers that know so much about the consumer that the ads are "creepily" personalized. Secondly, some ads create discomfort by making the consumer question "the motives of the company advertising the product". Finally, some ads violate social norms by having inappropriate content, for example by unnecessarily sexualizing it. It is marketing's extensive knowledge used in an improper way, together with a certain loss of control over our data, that creates a feeling of creepiness. Another creepy aspect of technology is human-looking AI: this phenomenon is called the uncanny valley. Humans find robots creepy when they start closely resembling humans. It has been hypothesized that the reason why they are viewed as creepy is because they violate our notion of how a robot should look. A study focusing on children's responses to this phenomenon found evidence to support the hypothesis. == Evolutionary explanation == Several studies have hypothesized that creepiness is an evolutionary response to potentially dangerous situations. It could be linked to a mechanism called agent detection which makes individuals expect malignant agents to be responsible for small changes in the environment. McAndrew et al. illustrates the idea with the example of a person hearing some noises while walking in a dark alley. That person would go in high alert, fearing that some dangerous individual was there. If that was not the case the loss would be small. If, on the other hand, a dangerous individual was actually in the alley and the person had not been alerted by this creepy feeling, the loss could have been significant. Creepiness would therefore serve the purpose of alerting us in situations in which the danger is not outright obvious but rather ambiguous. In this case, ambiguity both refers to the possible presence of a threat and to its nature, sexual or physical for example. Creepiness "may reside in between the unknowing and the fear" in the sense that individuals experiencing it are unsure if there truly is something to fear or not. Creepy characteristics are not simply caused by threat potential: in fact, ectomorphic body types are not the most powerful bodies and facial expressions are not a proxy of physical strength either. Therefore, creepiness is not only related to how threatening a characteristic is, in the sense of how dangerous and strong the individual can be. There are more facets to consider. Another characteristic of creepiness is unpredictable behavior. Unpredictability links back to this idea of ambiguity. When an individual is unpredictable it is not possible to tell when their behavior will turn violent: this adds to the ambiguity of a potentially dangerous situation. This theory is endorsed by studies. Not only is unpredictability directly listed as a creepy characteristic, but other behaviors, such as norm-breaking behaviors are indirectly linked with unpredictability. Such behaviors show that the individual does not conform to some social standards others would expect in a given situation. For example, the aforementioned staring at strangers or lack of hygiene—behaviors that make us uneasy or creeped out because they do not fit the norm and therefore are not expected. More generally, participants tended to define creepiness as "different" in the sense of not behaving, or looking, socially acceptable. Such differences point towards a "social mismatch". Humans have a natural system of detection of such mismatch: a physical feeling of coldness. When an individual is creeped out, they report feeling those "cold chills". This phenomenon has been studied by Leander et al, with relation to nonverbal mimicry in social interactions, meaning the unintentional copying of another's behavior. Inappropriate mimicry may leave a person feeling like something is off about the other. Absence of non-verbal mimicry in a friendly interaction, or the presence of it in a professional setting, raises suspicion as it does not follow the relevant social norms. Individuals are left wondering what other unusual behavior the other might engage in.

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  Gödel machine

  A Gödel machine is a hypothetical self-improving computer program that solves problems in an optimal way. It uses a recursive self-improvement protocol in which it rewrites its own code when it can prove the new code provides a better strategy. The machine was invented by Jürgen Schmidhuber (first proposed in 2003), but is named after Kurt Gödel who inspired the mathematical theories. The Gödel machine is often discussed when dealing with issues of meta-learning, also known as "learning to learn." Applications include automating human design decisions and transfer of knowledge between multiple related tasks, and may lead to design of more robust and general learning architectures. Though theoretically possible, no full implementation has been created. The Gödel machine is often compared with Marcus Hutter's AIXI, another formal specification for an artificial general intelligence. Schmidhuber points out that the Gödel machine could start out by implementing AIXItl as its initial sub-program, and self-modify after it finds proof that another algorithm for its search code will be better. == Limitations == Traditional problems solved by a computer only require one input and provide some output. Computers of this sort had their initial algorithm hardwired. This does not take into account the dynamic natural environment, and thus was a goal for the Gödel machine to overcome. The Gödel machine has limitations of its own, however. According to Gödel's First Incompleteness Theorem, any formal system that encompasses arithmetic is either flawed or allows for statements that cannot be proved in the system. Hence even a Gödel machine with unlimited computational resources must ignore those self-improvements whose effectiveness it cannot prove. == Variables of interest == There are three variables that are particularly useful in the run time of the Gödel machine. At some time t {\displaystyle t} , the variable time {\displaystyle {\text{time}}} will have the binary equivalent of t {\displaystyle t} . This is incremented steadily throughout the run time of the machine. Any input meant for the Gödel machine from the natural environment is stored in variable x {\displaystyle x} . It is likely the case that x {\displaystyle x} will hold different values for different values of variable time {\displaystyle {\text{time}}} . The outputs of the Gödel machine are stored in variable y {\displaystyle y} , where y ( t ) {\displaystyle y(t)} would be the output bit-string at some time t {\displaystyle t} . At any given time t {\displaystyle t} , where ( 1 ≤ t ≤ T ) {\displaystyle (1\leq t\leq T)} , the goal is to maximize future success or utility. A typical utility function follows the pattern u ( s , E n v ) : S × E → R {\displaystyle u(s,\mathrm {Env} ):S\times E\rightarrow \mathbb {R} } : u ( s , E n v ) = E μ [ ∑ τ = time T r ( τ ) ∣ s , E n v ] {\displaystyle u(s,\mathrm {Env} )=E_{\mu }{\Bigg [}\sum _{\tau ={\text{time}}}^{T}r(\tau )\mid s,\mathrm {Env} {\Bigg ]}} where r ( t ) {\displaystyle r(t)} is a real-valued reward input (encoded within s ( t ) {\displaystyle s(t)} ) at time t {\displaystyle t} , E μ [ ⋅ ∣ ⋅ ] {\displaystyle E_{\mu }[\cdot \mid \cdot ]} denotes the conditional expectation operator with respect to some possibly unknown distribution μ {\displaystyle \mu } from a set M {\displaystyle M} of possible distributions ( M {\displaystyle M} reflects whatever is known about the possibly probabilistic reactions of the environment), and the above-mentioned time = time ⁡ ( s ) {\displaystyle {\text{time}}=\operatorname {time} (s)} is a function of state s {\displaystyle s} which uniquely identifies the current cycle. Note that we take into account the possibility of extending the expected lifespan through appropriate actions. == Instructions used by proof techniques == The nature of the six proof-modifying instructions below makes it impossible to insert an incorrect theorem into proof, thus trivializing proof verification. === get-axiom(n) === Appends the n-th axiom as a theorem to the current theorem sequence. Below is the initial axiom scheme: Hardware Axioms formally specify how components of the machine could change from one cycle to the next. Reward Axioms define the computational cost of hardware instruction and the physical cost of output actions. Related Axioms also define the lifetime of the Gödel machine as scalar quantities representing all rewards/costs. Environment Axioms restrict the way new inputs x are produced from the environment, based on previous sequences of inputs y. Uncertainty Axioms/String Manipulation Axioms are standard axioms for arithmetic, calculus, probability theory, and string manipulation that allow for the construction of proofs related to future variable values within the Gödel machine. Initial State Axioms contain information about how to reconstruct parts or all of the initial state. Utility Axioms describe the overall goal in the form of utility function u. === apply-rule(k, m, n) === Takes in the index k of an inference rule (such as Modus tollens, Modus ponens), and attempts to apply it to the two previously proved theorems m and n. The resulting theorem is then added to the proof. === delete-theorem(m) === Deletes the theorem stored at index m in the current proof. This helps to mitigate storage constraints caused by redundant and unnecessary theorems. Deleted theorems can no longer be referenced by the above apply-rule function. === set-switchprog(m, n) === Replaces switchprog S pm:n, provided it is a non-empty substring of S p. === check() === Verifies whether the goal of the proof search has been reached. A target theorem states that given the current axiomatized utility function u (Item 1f), the utility of a switch from p to the current switchprog would be higher than the utility of continuing the execution of p (which would keep searching for alternative switchprogs). === state2theorem(m, n) === Takes in two arguments, m and n, and attempts to convert the contents of Sm:n into a theorem. == Example applications == === Time-limited NP-hard optimization === The initial input to the Gödel machine is the representation of a connected graph with a large number of nodes linked by edges of various lengths. Within given time T it should find a cyclic path connecting all nodes. The only real-valued reward will occur at time T. It equals 1 divided by the length of the best path found so far (0 if none was found). There are no other inputs. The by-product of maximizing expected reward is to find the shortest path findable within the limited time, given the initial bias. === Fast theorem proving === Prove or disprove as quickly as possible that all even integers > 2 are the sum of two primes (Goldbach’s conjecture). The reward is 1/t, where t is the time required to produce and verify the first such proof. === Maximizing expected reward with bounded resources === A cognitive robot that needs at least 1 liter of gasoline per hour interacts with a partially unknown environment, trying to find hidden, limited gasoline depots to occasionally refuel its tank. It is rewarded in proportion to its lifetime, and dies after at most 100 years or as soon as its tank is empty or it falls off a cliff, and so on. The probabilistic environmental reactions are initially unknown but assumed to be sampled from the axiomatized Speed Prior, according to which hard-to-compute environmental reactions are unlikely. This permits a computable strategy for making near-optimal predictions. One by-product of maximizing expected reward is to maximize expected lifetime.

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  Creative work

  A creative work is a manifestation of creative effort in the world through a creative process involving one or more individuals. The term includes fine artwork (sculpture, paintings, drawing, sketching, performance art), dance, writing (literature), filmmaking, and musical composition. The term is frequently used in the context of copyright. It is an important concept in both philosophy and law. Creative works require a creative mindset and are not typically rendered in an arbitrary fashion, although works may demonstrate (i.e., have in common) a degree of arbitrariness, such that it is improbable that two people would independently create the same work. At its base, creative work involves two main steps – having an idea, and then turning that idea into a substantive form or process. Typically, the creative process results in work that has some aesthetic value, identified as a creative expression. Naturally, this expression generally invokes external stimuli (e.g., influences and experiences) which a person draws on because they view the source as creative or inspirational; the degree to which this is reflected may be used in determinations of the derivativeness of the created work. Alternatively, the creator may draw on imagination, and their references may be clouded even to them, for the nature of imagination is as yet not fully understood philosophically, and the level of necessary self-examination of an artist's internal processing is a challenge for even those most self-aware of their minds and mental processes. == Legal definition == === United Kingdom === For the purpose of section 221(2)(c) of the Income Tax (Trading and Other Income) Act 2005, the expression "creative works" means: (a) literary, dramatic, musical or artistic works, or (b) designs,created by the taxpayer personally or, if the qualifying trade, profession or vocation is carried on in partnership, by one or more of the partners personally.

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  Randomized benchmarking

  Randomized benchmarking is an experimental method for measuring the average error rates of quantum computing hardware platforms. The protocol estimates the average error rates by implementing long sequences of randomly sampled quantum gate operations. Randomized benchmarking is the industry-standard protocol used by quantum hardware developers such as IBM and Google to test the performance of the quantum operations. The original theory of randomized benchmarking, proposed by Joseph Emerson and collaborators, considered the implementation of sequences of Haar-random operations, but this had several practical limitations. The now-standard protocol for randomized benchmarking (RB) relies on uniformly random Clifford operations, as proposed in 2006 by Dankert et al. as an application of the theory of unitary t-designs. In current usage randomized benchmarking sometimes refers to the broader family of generalizations of the 2005 protocol involving different random gate sets that can identify various features of the strength and type of errors affecting the elementary quantum gate operations. Randomized benchmarking protocols are an important means of verifying and validating quantum operations and are also routinely used for the optimization of quantum control procedures. == Overview == Randomized benchmarking offers several key advantages over alternative approaches to error characterization. For example, the number of experimental procedures required for full characterization of errors (called tomography) grows exponentially with the number of quantum bits (called qubits). This makes tomographic methods impractical for even small systems of just 3 or 4 qubits. In contrast, randomized benchmarking protocols are the only known approaches to error characterization that scale efficiently as number of qubits in the system increases. Thus RB can be applied in practice to characterize errors in arbitrarily large quantum processors. Additionally, in experimental quantum computing, procedures for state preparation and measurement (SPAM) are also error-prone, and thus quantum process tomography is unable to distinguish errors associated with gate operations from errors associated with SPAM. In contrast, RB protocols are robust to state-preparation and measurement errors Randomized benchmarking protocols estimate key features of the errors that affect a set of quantum operations by examining how the observed fidelity of the final quantum state decreases as the length of the random sequence increases. If the set of operations satisfies certain mathematical properties, such as comprising a sequence of twirls with unitary two-designs, then the measured decay can be shown to be an invariant exponential with a rate fixed uniquely by features of the error model. == History == Randomized benchmarking was proposed in Scalable noise estimation with random unitary operators, where it was shown that long sequences of quantum gates sampled uniformly at random from the Haar measure on the group SU(d) would lead to an exponential decay at a rate that was uniquely fixed by the error model. Emerson, Alicki and Zyczkowski also showed, under the assumption of gate-independent errors, that the measured decay rate is directly related to an important figure of merit, the average gate fidelity and independent of the choice of initial state and any errors in the initial state, as well as the specific random sequences of quantum gates. This protocol applied for arbitrary dimension d and an arbitrary number n of qubits, where d=2n. The SU(d) RB protocol had two important limitations that were overcome in a modified protocol proposed by Dankert et al., who proposed sampling the gate operations uniformly at random from any unitary two-design, such as the Clifford group. They proved that this would produce the same exponential decay rate as the random SU(d) version of the protocol proposed in Emerson et al.. This follows from the observation that a random sequence of gates is equivalent to an independent sequence of twirls under that group, as conjectured in and later proven in. This Clifford-group approach to Randomized Benchmarking is the now standard method for assessing error rates in quantum computers. A variation of this protocol was proposed by NIST in 2008 for the first experimental implementation of an RB-type for single qubit gates. However, the sampling of random gates in the NIST protocol was later proven not to reproduce any unitary two-design. The NIST RB protocol was later shown to also produce an exponential fidelity decay, albeit with a rate that depends on non-invariant features of the error model In recent years a rigorous theoretical framework has been developed for Clifford-group RB protocols to show that they work reliably under very broad experimental conditions. In 2011 and 2012, Magesan et al. proved that the exponential decay rate is fully robust to arbitrary state preparation and measurement errors (SPAM). They also proved a connection between the average gate fidelity and diamond norm metric of error that is relevant to the fault-tolerant threshold. They also provided evidence that the observed decay was exponential and related to the average gate fidelity even if the error model varied across the gate operations, so-called gate-dependent errors, which is the experimentally realistic situation. In 2018, Wallman and Dugas et al., showed that, despite concerns raised in, even under very strong gate-dependence errors the standard RB protocols produces an exponential decay at a rate that precisely measures the average gate-fidelity of the experimentally relevant errors. The results of Wallman. in particular proved that the RB error rate is so robust to gate-dependent errors models that it provides an extremely sensitive tool for detecting non-Markovian errors. This follows because under a standard RB experiment only non-Markovian errors (including time-dependent Markovian errors) can produce a statistically significant deviation from an exponential decay The standard RB protocol was first implemented for single qubit gate operations in 2012 at Yale on a superconducting qubit. A variation of this standard protocol that is only defined for single qubit operations was implemented by NIST in 2008 on a trapped ion. The first implementation of the standard RB protocol for two-qubit gates was performed in 2012 at NIST for a system of two trapped ions

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  Outline of web design and web development

  The following outline is provided as an overview of and topical guide to web design and web development, two very related fields: Web design – field that encompasses many different skills and disciplines in the production and maintenance of websites. The different areas of web design include web graphic design; interface design; authoring, including standardized code and proprietary software; user experience design; and search engine optimization. Often many individuals will work in teams covering different aspects of the design process, although some designers will cover them all. The term web design is normally used to describe the design process relating to the front-end (client side) design of a website including writing markup. Web design partially overlaps web engineering in the broader scope of web development. Web designers are expected to have an awareness of usability and if their role involves creating markup then they are also expected to be up to date with web accessibility guidelines. Web development – work involved in developing a web site for the Internet (World Wide Web) or an intranet (a private network). Web development can range from developing a simple single static page of plain text to complex web-based internet applications (web apps), electronic businesses, and social network services. A more comprehensive list of tasks to which web development commonly refers, may include web engineering, web design, web content development, client liaison, client-side/server-side scripting, web server and network security configuration, and e-commerce development. Among web professionals, "web development" usually refers to the main non-design aspects of building web sites: writing markup and coding. Web development may use content management systems (CMS) to make content changes easier and available with basic technical skills. For larger organizations and businesses, web development teams can consist of hundreds of people (web developers) and follow standard methods like Agile methodologies while developing websites. Smaller organizations may only require a single permanent or contracting developer, or secondary assignment to related job positions such as a graphic designer or information systems technician. Web development may be a collaborative effort between departments rather than the domain of a designated department. There are three kinds of web developer specialization: front-end developer, back-end developer, and full-stack developer. Front-end developers are responsible for behaviour and visuals that run in the user browser, back-end developers deal with the servers and full-stack developers are responsible for both. Currently, the demand for React and Node.JS developers are very high all over the world. == Web design == Graphic design Typography Page layout User experience design (UX design) User interface design (UI design) Web Design techniques Responsive web design (RWD) Adaptive web design (AWD) Progressive enhancement Tableless web design Software Adobe Photoshop Adobe Illustrator Adobe XD Figma Sketch (software) Affinity Designer Inkscape == Web development == Front-end web development – the practice of converting data to a graphical interface, through the use of HTML, CSS, and JavaScript, so that users can view and interact with that data. HyperText Markup Language (HTML) (.html) Cascading Style Sheets (CSS) (.css) CSS framework JavaScript (.js) Package managers for JavaScript npm (originally short for Node Package Manager) Server-side scripting (also known as "Server-side (web) development" or "Back-end (web) development") ASP (.asp) ASP.NET Web Forms (.aspx) ASP.NET Web Pages (.cshtml, .vbhtml) ColdFusion Markup Language (.cfm) Go (.go) Google Apps Script (.gs) Hack (.php) Haskell (.hs) (example: Yesod) Java (.jsp) via JavaServer Pages JavaScript or TypeScript using Server-side JavaScript (.ssjs, .js, .ts) (example: Node.js) Lasso (.lasso) Lua (.lp .op .lua) Node.js (.node) Parser (.p) Perl via the CGI.pm module (.cgi, .ipl, .pl) PHP (.php, .php3, .php4, .phtml) Progress WebSpeed (.r,.w) Python (.py) (examples: Pyramid, Flask, Django) R (.rhtml) – (example: rApache) React (.jsx, .tsx) Ruby (.rb, .rbw) (example: Ruby on Rails) SMX (.smx) Tcl (.tcl) Full stack web development – involves both front-end and back-end (server-side) development Web framework Types of framework architectures Model–view–controller Three-tier architecture Software Atom IntelliJ IDEA Sublime Text Visual Studio Code

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  Tandem (app)

  Tandem is a mobile language exchange and language learning app. == History == Tandem was founded in Hannover, Germany in 2014 by Arnd Aschentrup, Tobias Dickmeis, and Matthias Kleimann. Prior to founding Tandem, the trio had launched Vive, a members-only mobile video chat platform. Tandem has been criticised for not accepting members into the community immediately, as opposed to competitors including HelloTalk, Speaky or Cafehub. In some countries, there is a waiting list and applicants can wait up to seven days for their application to be processed by human moderators. In 2015, Tandem completed its first funding round (seed funding) of €600,000. Participating investors included business angels such as Atlantic Labs (Christophe Maire), Hannover Beteiligungsfonds, Marcus Englert (Chairman of the Supervisory Board of Rocket Internet SE ), Catagonia, Ludwig zu Salm, Florian Langenscheidt, Heiko Hubertz, Martin Sinner, and Zehden Enterprises. In 2016, the company received a further €2 million from new investors Rubylight and Faber Ventures, as well as from existing investors Hannover Beteiligungsfonds, Atlantic Labs, and Zehden Enterprises. Since 2018, the premium membership Tandem Pro has been available, which offers members unlimited access to all language learning features of the app as well as the removal of advertising for a monthly fee.

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  Mashup (web application hybrid)

  A mashup (computer industry jargon), in web development, is a web page or web application that uses content from more than one source to create a single new service displayed in a single graphical interface. For example, a user could combine the addresses and photographs of their library branches with a Google map to create a map mashup. The term implies easy, fast integration, frequently using open application programming interfaces (open API) and data sources to produce enriched results that were not necessarily the original reason for producing the raw source data. The term mashup originally comes from creating something by combining elements from two or more sources. The main characteristics of a mashup are combination, visualization, and aggregation. It is important to make existing data more useful, for personal and professional use. To be able to permanently access the data of other services, mashups are generally client applications or hosted online. In the past years, more and more Web applications have published APIs that enable software developers to easily integrate data and functions the SOA way, instead of building them by themselves. Mashups can be considered to have an active role in the evolution of social software and Web 2.0. Mashup composition tools are usually simple enough to be used by end-users. They generally do not require programming skills and rather support visual wiring of GUI widgets, services and components together. Therefore, these tools contribute to a new vision of the Web, where users are able to contribute. The term "mashup" is not formally defined by any standard-setting body. == History == The broader context of the history of the Web provides a background for the development of mashups. Under the Web 1.0 model, organizations stored consumer data on portals and updated them regularly. They controlled all the consumer data, and the consumer had to use their products and services to get the information. The advent of Web 2.0 introduced Web standards that were commonly and widely adopted across traditional competitors and which unlocked the consumer data. At the same time, mashups emerged, allowing mixing and matching competitors' APIs to develop new services. The first mashups used mapping services or photo services to combine these services with data of any kind and therefore to produce visualizations of data. In the beginning, most mashups were consumer-based, but recently the mashup is to be seen as an interesting concept useful also to enterprises. Business mashups can combine existing internal data with external services to generate new views on the data. There was also the free Yahoo! Pipes to build mashups for free using the Yahoo! Query Language. == Types of mashup == There are many types of mashup, such as business mashups, consumer mashups, and data mashups. The most common type of mashup is the consumer mashup, aimed at the general public. Business (or enterprise) mashups define applications that combine their own resources, application and data, with other external Web services. They focus data into a single presentation and allow for collaborative action among businesses and developers. This works well for an agile development project, which requires collaboration between the developers and customer (or customer proxy, typically a product manager) for defining and implementing the business requirements. Enterprise mashups are secure, visually rich Web applications that expose actionable information from diverse internal and external information sources. Consumer mashups combine data from multiple public sources in the browser and organize it through a simple browser user interface. (e.g.: Wikipediavision combines Google Map and a Wikipedia API) Data mashups, opposite to the consumer mashups, combine similar types of media and information from multiple sources into a single representation. The combination of all these resources create a new and distinct Web service that was not originally provided by either source. === By API type === Mashups can also be categorized by the basic API type they use but any of these can be combined with each other or embedded into other applications. ==== Data types ==== Indexed data (documents, weblogs, images, videos, shopping articles, jobs ...) used by metasearch engines Cartographic and geographic data: geolocation software, geovisualization Feeds, podcasts: news aggregators ==== Functions ==== Data converters: language translators, speech processing, URL shorteners... Communication: email, instant messaging, notification... Visual data rendering: information visualization, diagrams Security related: electronic payment systems, ID identification... Editors == Mashup enabler == In technology, a mashup enabler is a tool for transforming incompatible IT resources into a form that allows them to be easily combined, in order to create a mashup. Mashup enablers allow powerful techniques and tools (such as mashup platforms) for combining data and services to be applied to new kinds of resources. An example of a mashup enabler is a tool for creating an RSS feed from a spreadsheet (which cannot easily be used to create a mashup). Many mashup editors include mashup enablers, for example, Presto Mashup Connectors, Convertigo Web Integrator or Caspio Bridge. Mashup enablers have also been described as "the service and tool providers, [sic] that make mashups possible". === History === Early mashups were developed manually by enthusiastic programmers. However, as mashups became more popular, companies began creating platforms for building mashups, which allow designers to visually construct mashups by connecting together mashup components. Mashup editors have greatly simplified the creation of mashups, significantly increasing the productivity of mashup developers and even opening mashup development to end-users and non-IT experts. Standard components and connectors enable designers to combine mashup resources in all sorts of complex ways with ease. Mashup platforms, however, have done little to broaden the scope of resources accessible by mashups and have not freed mashups from their reliance on well-structured data and open libraries (RSS feeds and public APIs). Mashup enablers evolved to address this problem, providing the ability to convert other kinds of data and services into mashable resources. === Web resources === Of course, not all valuable data is located within organizations. In fact, the most valuable information for business intelligence and decision support is often external to the organization. With the emergence of rich web applications and online Web portals, a wide range of business-critical processes (such as ordering) are becoming available online. Unfortunately, very few of these data sources syndicate content in RSS format and very few of these services provide publicly accessible APIs. Mashup editors therefore solve this problem by providing enablers or connectors. == Mashups versus portals == Mashups and portals are both content aggregation technologies. Portals are an older technology designed as an extension to traditional dynamic Web applications, in which the process of converting data content into marked-up Web pages is split into two phases: generation of markup "fragments" and aggregation of the fragments into pages. Each markup fragment is generated by a "portlet", and the portal combines them into a single Web page. Portlets may be hosted locally on the portal server or remotely on a separate server. Portal technology defines a complete event model covering reads and updates. A request for an aggregate page on a portal is translated into individual read operations on all the portlets that form the page ("render" operations on local, JSR 168 portlets or "getMarkup" operations on remote, WSRP portlets). If a submit button is pressed on any portlet on a portal page, it is translated into an update operation on that portlet alone (processAction on a local portlet or performBlockingInteraction on a remote, WSRP portlet). The update is then immediately followed by a read on all portlets on the page. Portal technology is about server-side, presentation-tier aggregation. It cannot be used to drive more robust forms of application integration such as two-phase commit. Mashups differ from portals in the following respects: The portal model has been around longer and has had greater investment and product research. Portal technology is therefore more standardized and mature. Over time, increasing maturity and standardization of mashup technology will likely make it more popular than portal technology because it is more closely associated with Web 2.0 and lately Service-oriented Architectures (SOA). New versions of portal products are expected to eventually add mashup support while still supporting legacy portlet applications. Mashup technologies, in contrast, are not expected to provide support for portal standards. == Business mashups

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  Webby Awards

  The Webby Awards (colloquially referred to as the Webbys) are awards for excellence on the Internet presented annually by the International Academy of Digital Arts and Sciences, a judging body composed of over three thousand industry experts and technology innovators. Categories include websites, advertising and media, online film and video, mobile sites and apps, and social. Two winners are selected in each category, one by members of The International Academy of Digital Arts and Sciences, and one by the public who cast their votes during Webby People's Voice voting. Each winner presents a five-word acceptance speech, a trademark of the annual awards show. In its early years, the award was hailed as the "Internet's highest honor" and was associated with the phrase "The Oscars of the Internet." == History == In its early years, the organization was one of several vying to be the premiere internet awards show. Both shows would compare themselves to the Oscars, as did media outlets such as The New York Times to Canada's Globe & Mail. The winners of the First Annual Webby Awards in 1995 were presented by John Brancato and Michael Ferris, writers for Columbia Pictures. It was held at the Hollywood Roosevelt Hotel. The televised Webby Awards were sponsored by the Academy of Web Design and Cool Site of the Day. The first Webby Awards were produced by Kay Dangaard at the Hollywood Roosevelt Hotel as a nod to the first site of the Academy of Motion Picture Arts and Sciences (Oscars). That first year, they were called "Webbie" Awards. The first "Site of the Year" winner was the pioneer webisodic serial The Spot. The modern Webby Awards were co-founded by Tiffany Shlain, a filmmaker, when she was hired by The Web Magazine to re-establish them, and were first held in San Francisco in 1997. They quickly became known for its requirement that winners give their acceptance speeches in five words. After this, the awards became more successful than the magazine and IDG closed the publication. Shlain and co-founder Maya Draisin Farrah continued to run The Webby Awards until 2004. The International Academy of Digital Arts and Sciences, which selects the winners of The Webby Awards, was established in 1998 by co-founders Tiffany Shlain, Spencer Ante and Maya Draisin. Members of the Academy include Kevin Spacey, Grimes, Questlove, Internet inventor Vint Cerf, Instagram's Head of Fashion Partnerships Eva Chen, comedian Jimmy Kimmel, Twitter founder Biz Stone, Vice Media co-founder and CEO Shane Smith, Tumblr's David Karp, Director of Harvard's Berkman Klein Center for Internet & Society Susan P. Crawford, Refinery29's Executive Creative Director Piera Gelardi, and CEO and co-founder of Gimlet Media Alex Blumberg. The Webby Awards is owned and operated by the Webby Media Group, a division of Recognition Media, which also owns and produces the Lovie Awards in Europe and Netted by the Webbys, a daily email publication launched in 2009. David-Michel Davies, CEO of Webby Media Group, current Executive Director of the Webby Awards and co-founder of Internet Week New York, was named Executive Director of the Webby Awards in 2005. In 2009, the 13th Annual Webby Awards received nearly 10,000 entries from all 50 US states and over 60 countries. That same year, more than 500,000 votes were cast in The Webby People's Voice Awards. In 2012, the 16th Annual Webby awards received 1.5 million votes from more than 200 countries for the People's Voice awards. In 2015, the 19th Annual Webby Awards received nearly 13,000 entries from all 50 U.S. states and over 60 countries worldwide. == Nomination process == The 2000 awards began the transition to nominee submissions. Previously, nominees had been selected by an internal committee. As early as 2017, organizations wanting to nominate themselves were charged $395 for a single entry. An "ad campaign entry" would cost $595. By 2024, those fees had risen to $495 and $675, respectively. Executive Academy Members with category-specific expertise evaluate the shortlisted entries based on the appropriate Website, Advertising & Media, Online Film & Video, Mobile Sites & Apps, and Social category criteria, and cast ballots to determine Webby Honorees, Nominees and Webby Winners. Deloitte provides vote tabulation consulting for the Webby Awards. In addition to the award given in each category by the International Academy of Digital Arts and Sciences, another winner is selected in each category as determined by the general public during People's Voice voting. Winners of both the Academy-selected and People's Voice-selected awards are invited to the Webbys. == Awards granted == The Webby Awards are presented in over a hundred categories among all four types of entries. A website can be entered in multiple categories and receive multiple awards. In each category, two awards are handed out: a Webby Award selected by The International Academy of Digital Arts and Sciences, and a People's Voice Award selected by the general public. == Ceremony == Between 2005 and 2019, the Webby Awards were presented in New York City. Many of the ceremony hosts are comedians and comedic actors. Comedian Rob Corddry hosted the ceremony from 2005 to 2007. Seth Meyers of Saturday Night Live hosted in 2008 and 2009, B.J. Novak of the sitcom The Office in 2010, and Lisa Kudrow in 2011. Comedian, actor, and writer Patton Oswalt hosted from 2012 to 2014. Comedian Hannibal Buress hosted in 2015. The Webbys are famous for limiting recipients to five-word speeches, which are often humorous, although some exceed the limit. In 2005 when accepting his Lifetime Achievement Award, former Vice President Al Gore's speech was "Please don't recount this vote." He was introduced by Vint Cerf who used the same format to state, "We all invented the Internet." In 2013, the creator of the Graphics Interchange Format (GIF), Steve Wilhite, accepted his Webby and delivered his now famous five-word speech, "It's pronounced 'Jif' not 'Gif'." == Criticism == The Webbys have been criticized for their pay-to-enter and pay-to-attend policy (winners and nominees also have to pay to attend the award ceremony), and thus for not taking most websites into consideration before distributing their awards. Gawker, its Valleywag column, and others, have called the awards a scam, with Valleywag saying, "...somewhere along the way, the organizers figured out that this goofy charade could be milked for profit." In response, Webby Awards executive director David-Michel Davies told the Wall Street Journal that entry fees "provide the best and most sustainable model for ensuring that our judging process remains consistent and rigorous and is not dependent on things like sponsorships that can fluctuate from year to year." == Anthem Awards == In 2021, the Webby organization started a new line of awards, the Anthem Awards, to honor the purpose and mission-driven work of people, companies and organizations worldwide. The finalists and winners are selected by the International Academy of Digital Arts and Sciences.

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