AI Face Fixer

AI Face Fixer — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • CrewAI

    CrewAI

    CrewAI is an open-source software framework and platform for building AI agents and multi-agent systems. Written primarily in Python, it is used to define artificial-intelligence agents, assign tasks to them, and coordinate their work through agent teams and workflows. The framework is associated with CrewAI Inc., a startup developing enterprise tools for automating business workflows with large language model-based agents. == History == CrewAI was first released on the Python Package Index in December 2023. The project was created by João Moura and later developed by CrewAI Inc. and open-source contributors. In October 2024, TechCrunch reported that CrewAI had raised $18 million across seed and Series A funding rounds from investors including Boldstart Ventures, Craft Ventures, Earl Grey Capital, and Insight Partners. The report also stated that Andrew Ng and HubSpot co-founder Dharmesh Shah had invested in the company. SiliconANGLE described the company as the developer of an open-source framework for building artificial-intelligence agents and reported that the funding consisted of a seed round led by Boldstart Ventures and a Series A led by Insight Partners. By late 2024, CrewAI had introduced commercial enterprise products built on top of its open-source components. TechCrunch reported that the company's enterprise offering added access controls, analytics, support, and templates for workflow automation. == Features == CrewAI is designed around groups of agents, sometimes called "crews", that can be assigned roles, goals, and tasks. The framework supports agent collaboration, task delegation, tool use, memory, and knowledge sources for retrieval-augmented generation workflows. The project describes two main building blocks: "Crews", which are used for autonomous agent collaboration, and "Flows", which are used for more controlled event-driven workflows. The framework is independent of LangChain and is released under the MIT License. It can be installed as a Python package and is commonly used with external large language model APIs or local models, depending on the developer's configuration. == Business model == CrewAI combines an open-source framework with commercial enterprise products. Its enterprise products are intended for organizations that need to build, monitor, and manage agent-based automations with additional security, observability, and administrative controls.

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  • Krzysztof Wołk

    Krzysztof Wołk

    Krzysztof Wołk (born 16 August 1986) is a Polish IT researcher who specializes in artificial intelligence, machine learning, mobile applications, linguistic engineering, multimedia, NLP and graphic applications. His research works have been cited in more than 70 international research journals, books and research papers. He is member of scientific committee at the Health and Social Care Information Systems and Technologies (HCist), an international conference which brings in new ideas, new technologies, academic scientists, healthcare IT professionals, managers and solution providers from all over the world. His research in statistical machine learning has been recognized as one of the most cited researches in the world. He is the member of Scientific Committee-Reviewers at Research Conference in Technical Disciplines (RCITD), based in Slovakia, which brings together the academic scientists and researchers from all around the world. == Biography == He obtained the doctorate degree in 2016 from the Polish-Japanese Academy of Information and Technology in Warsaw, Poland. He is currently working as researcher and assistant professor at the Polish-Japanese Computer Science Academy (PJATK) in Warsaw, Poland. == Achievements == He has published three books: Biblia Windows Server 2012, Administrator's Guide, Mac OS X Server 10.8, and MAC OS X Server 10.6 and 10.7 Practical Guide has been cited by many researchers in the scholarly books, research journals and articles. His research work on the Polish-English statistical machine translation has been featured in the book New Research in Multimedia and Internet System. Similarly, his works regarding the machine translation system have been featured in the books New Perspective in Information System and Technologies Volume 1, Multimedia and Network Information System, and Recent Advances in Information Systems and Technologies, Volume 1.

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  • Ronald J. Williams

    Ronald J. Williams

    Ronald James Williams (1945 – February 16, 2024) was an American mathematician and computer scientist who spent the majority of his career at Northeastern University. He is considered one of the pioneers of neural networks. In 1986, he co-authored the seminal paper in Nature on the backpropagation algorithm along with David Rumelhart and Geoffrey Hinton, which triggered a boom in neural network research. == Education and career == Williams was born in Southern California. He studied at California Institute of Technology as a undergraduate student and received a B.S. in mathematics there in 1966. He received his M.A. and Ph.D. in mathematics, both at University of California, San Diego (UCSD) in 1972 and 1975, respectively. His Ph.D. thesis was supervised by Donald Werner Anderson. He worked for a defense contractor for some time after graduation. From 1983 to 1986, Williams was a member of the Parallel Distributed Processing research group headed by David Rumelhart at the Institute for Cognitive Science at UCSD. In 1986, Williams accepted a professorship in computer science at Northeastern University in Boston, where he remained afterwards. In addition to the backpropagation paper, Williams made fundamental contributions to the fields of recurrent neural networks, where he, along with David Zipser, invented the teacher forcing algorithm and made important contributions to backpropagation through time. In reinforcement learning, Williams introduced the REINFORCE algorithm in 1992, which became the first policy gradient method. Besides his works on neural networks, Williams, together with Wenxu Tong and Mary Jo Ondrechen, developed Partial Order Optimum Likelihood (POOL), a machine learning method used in the prediction of active amino acids in protein structures. POOL is a maximum likelihood method with a monotonicity constraint and is a general predictor of properties that depend monotonically on the input features.

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  • Semiautomaton

    Semiautomaton

    In mathematics and theoretical computer science, a semiautomaton is a deterministic finite automaton having inputs but no output. It consists of a set Q of states, a set Σ called the input alphabet, and a function T: Q × Σ → Q called the transition function. Associated with any semiautomaton is a monoid called the characteristic monoid, input monoid, transition monoid or transition system of the semiautomaton, which acts on the set of states Q. This may be viewed either as an action of the free monoid of strings in the input alphabet Σ, or as the induced transformation semigroup of Q. In older books like Clifford and Preston (1967) semigroup actions are called "operands". In category theory, semiautomata essentially are functors. == Transformation semigroups and monoid acts == A transformation semigroup or transformation monoid is a pair ( M , Q ) {\displaystyle (M,Q)} consisting of a set Q (often called the "set of states") and a semigroup or monoid M of functions, or "transformations", mapping Q to itself. They are functions in the sense that every element m of M is a map m : Q → Q {\displaystyle m\colon Q\to Q} . If s and t are two functions of the transformation semigroup, their semigroup product is defined as their function composition ( s t ) ( q ) = ( s ∘ t ) ( q ) = s ( t ( q ) ) {\displaystyle (st)(q)=(s\circ t)(q)=s(t(q))} . Some authors regard "semigroup" and "monoid" as synonyms. Here a semigroup need not have an identity element; a monoid is a semigroup with an identity element (also called "unit"). Since the notion of functions acting on a set always includes the notion of an identity function, which when applied to the set does nothing, a transformation semigroup can be made into a monoid by adding the identity function. === M-acts === Let M be a monoid and Q be a non-empty set. If there exists a multiplicative operation μ : Q × M → Q {\displaystyle \mu \colon Q\times M\to Q} ( q , m ) ↦ q m = μ ( q , m ) {\displaystyle (q,m)\mapsto qm=\mu (q,m)} which satisfies the properties q 1 = q {\displaystyle q1=q} for 1 the unit of the monoid, and q ( s t ) = ( q s ) t {\displaystyle q(st)=(qs)t} for all q ∈ Q {\displaystyle q\in Q} and s , t ∈ M {\displaystyle s,t\in M} , then the triple ( Q , M , μ ) {\displaystyle (Q,M,\mu )} is called a right M-act or simply a right act. In long-hand, μ {\displaystyle \mu } is the right multiplication of elements of Q by elements of M. The right act is often written as Q M {\displaystyle Q_{M}} . A left act is defined similarly, with μ : M × Q → Q {\displaystyle \mu \colon M\times Q\to Q} ( m , q ) ↦ m q = μ ( m , q ) {\displaystyle (m,q)\mapsto mq=\mu (m,q)} and is often denoted as M Q {\displaystyle \,_{M}Q} . An M-act is closely related to a transformation monoid. However the elements of M need not be functions per se, they are just elements of some monoid. Therefore, one must demand that the action of μ {\displaystyle \mu } be consistent with multiplication in the monoid (i.e. μ ( q , s t ) = μ ( μ ( q , s ) , t ) {\displaystyle \mu (q,st)=\mu (\mu (q,s),t)} ), as, in general, this might not hold for some arbitrary μ {\displaystyle \mu } , in the way that it does for function composition. Once one makes this demand, it is completely safe to drop all parenthesis, as the monoid product and the action of the monoid on the set are completely associative. In particular, this allows elements of the monoid to be represented as strings of letters, in the computer-science sense of the word "string". This abstraction then allows one to talk about string operations in general, and eventually leads to the concept of formal languages as being composed of strings of letters. Another difference between an M-act and a transformation monoid is that for an M-act Q, two distinct elements of the monoid may determine the same transformation of Q. If we demand that this does not happen, then an M-act is essentially the same as a transformation monoid. === M-homomorphism === For two M-acts Q M {\displaystyle Q_{M}} and B M {\displaystyle B_{M}} sharing the same monoid M {\displaystyle M} , an M-homomorphism f : Q M → B M {\displaystyle f\colon Q_{M}\to B_{M}} is a map f : Q → B {\displaystyle f\colon Q\to B} such that f ( q m ) = f ( q ) m {\displaystyle f(qm)=f(q)m} for all q ∈ Q M {\displaystyle q\in Q_{M}} and m ∈ M {\displaystyle m\in M} . The set of all M-homomorphisms is commonly written as H o m ( Q M , B M ) {\displaystyle \mathrm {Hom} (Q_{M},B_{M})} or H o m M ( Q , B ) {\displaystyle \mathrm {Hom} _{M}(Q,B)} . The M-acts and M-homomorphisms together form a category called M-Act. == Semiautomata == A semiautomaton is a triple ( Q , Σ , T ) {\displaystyle (Q,\Sigma ,T)} where Σ {\displaystyle \Sigma } is a non-empty set, called the input alphabet, Q is a non-empty set, called the set of states, and T is the transition function T : Q × Σ → Q . {\displaystyle T\colon Q\times \Sigma \to Q.} When the set of states Q is a finite set—it need not be—, a semiautomaton may be thought of as a deterministic finite automaton ( Q , Σ , T , q 0 , A ) {\displaystyle (Q,\Sigma ,T,q_{0},A)} , but without the initial state q 0 {\displaystyle q_{0}} or set of accept states A. Alternately, it is a finite-state machine that has no output, and only an input. Any semiautomaton induces an act of a monoid in the following way. Let Σ ∗ {\displaystyle \Sigma ^{}} be the free monoid generated by the alphabet Σ {\displaystyle \Sigma } (so that the superscript is understood to be the Kleene star); it is the set of all finite-length strings composed of the letters in Σ {\displaystyle \Sigma } . For every word w in Σ ∗ {\displaystyle \Sigma ^{}} , let T w : Q → Q {\displaystyle T_{w}\colon Q\to Q} be the function, defined recursively, as follows, for all q in Q: If w = ε {\displaystyle w=\varepsilon } , then T ε ( q ) = q {\displaystyle T_{\varepsilon }(q)=q} , so that the empty word ε {\displaystyle \varepsilon } does not change the state. If w = σ {\displaystyle w=\sigma } is a letter in Σ {\displaystyle \Sigma } , then T σ ( q ) = T ( q , σ ) {\displaystyle T_{\sigma }(q)=T(q,\sigma )} . If w = σ v {\displaystyle w=\sigma v} for σ ∈ Σ {\displaystyle \sigma \in \Sigma } and v ∈ Σ ∗ {\displaystyle v\in \Sigma ^{}} , then T w ( q ) = T v ( T σ ( q ) ) {\displaystyle T_{w}(q)=T_{v}(T_{\sigma }(q))} . Let M ( Q , Σ , T ) {\displaystyle M(Q,\Sigma ,T)} be the set M ( Q , Σ , T ) = { T w | w ∈ Σ ∗ } . {\displaystyle M(Q,\Sigma ,T)=\{T_{w}\vert w\in \Sigma ^{}\}.} The set M ( Q , Σ , T ) {\displaystyle M(Q,\Sigma ,T)} is closed under function composition; that is, for all v , w ∈ Σ ∗ {\displaystyle v,w\in \Sigma ^{}} , one has T w ∘ T v = T v w {\displaystyle T_{w}\circ T_{v}=T_{vw}} . It also contains T ε {\displaystyle T_{\varepsilon }} , which is the identity function on Q. Since function composition is associative, the set M ( Q , Σ , T ) {\displaystyle M(Q,\Sigma ,T)} is a monoid: it is called the input monoid, characteristic monoid, characteristic semigroup or transition monoid of the semiautomaton ( Q , Σ , T ) {\displaystyle (Q,\Sigma ,T)} . == Properties == If the set of states Q is finite, then the transition functions are commonly represented as state transition tables. The structure of all possible transitions driven by strings in the free monoid has a graphical depiction as a de Bruijn graph. The set of states Q need not be finite, or even countable. As an example, semiautomata underpin the concept of quantum finite automata. There, the set of states Q are given by the complex projective space C P n {\displaystyle \mathbb {C} P^{n}} , and individual states are referred to as n-state qubits. State transitions are given by unitary n×n matrices. The input alphabet Σ {\displaystyle \Sigma } remains finite, and other typical concerns of automata theory remain in play. Thus, the quantum semiautomaton may be simply defined as the triple ( C P n , Σ , { U σ 1 , U σ 2 , … , U σ p } ) {\displaystyle (\mathbb {C} P^{n},\Sigma ,\{U_{\sigma _{1}},U_{\sigma _{2}},\dotsc ,U_{\sigma _{p}}\})} when the alphabet Σ {\displaystyle \Sigma } has p letters, so that there is one unitary matrix U σ {\displaystyle U_{\sigma }} for each letter σ ∈ Σ {\displaystyle \sigma \in \Sigma } . Stated in this way, the quantum semiautomaton has many geometrical generalizations. Thus, for example, one may take a Riemannian symmetric space in place of C P n {\displaystyle \mathbb {C} P^{n}} , and selections from its group of isometries as transition functions. The syntactic monoid of a regular language is isomorphic to the transition monoid of the minimal automaton accepting the language. == Literature == A. H. Clifford and G. B. Preston, The Algebraic Theory of Semigroups. American Mathematical Society, volume 2 (1967), ISBN 978-0-8218-0272-4. F. Gecseg and I. Peak, Algebraic Theory of Automata (1972), Akademiai Kiado, Budapest. W. M. L. Holcombe, Algebraic Automata Theory (1982), Cambridge University Press J. M. Howie, Automata and Languages, (1991), Cla

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  • Enterprise resource planning

    Enterprise resource planning

    Enterprise resource planning (ERP) is the integrated management of main business processes, often in real time and mediated by software and technology. ERP is usually referred to as a category of business management software—typically a suite of integrated applications—that an organization can use to collect, store, manage and interpret data from many business activities. The finance module in particular is essential to a suite of applications meeting the definition of an ERP system. The finance module provides the system of record for the organisation; recording the commercial impact of the business operations in the General Ledger. ERP systems can be local-based or cloud-based. Cloud-based applications have grown rapidly since the early 2010s due to the increased efficiencies arising from information being readily available from any location with Internet access. However, ERP differs from integrated business management systems by including planning all resources that are required in the future to meet business objectives. This includes plans for getting suitable staff and manufacturing capabilities for future needs. ERP provides an integrated and continuously updated view of core business processes, typically using a shared database managed by a database management system. ERP systems track business resources—cash, raw materials, production capacity—and the status of business commitments: orders, purchase orders, and payroll. The applications that make up the system share data across various departments (manufacturing, purchasing, sales, accounting, etc.) that provide the data. ERP facilitates information flow between all business functions and manages connections to outside stakeholders. Estimates of the size of the global ERP market range between USD $78 and $81 billion in 2026 . Though early ERP systems focused on large enterprises, smaller enterprises increasingly use ERP systems. The ERP system integrates varied organizational systems and facilitates error-free transactions and production, thereby enhancing the organization's efficiency. However, developing an ERP system differs from traditional system development. ERP systems run on a variety of computer hardware and network configurations, typically using a database as an information repository. == Origin == Business and technology research and advisory firm Gartner is credited for first using the acronym ERP in the 1990s. The term captured a functional extension of two manufacturing-based concepts, material requirements planning (MRP) and manufacturing resource planning (MRP II). Without replacing these terms, ERP came to represent a larger whole that reflected the evolution of application integration beyond manufacturing. Not all ERP packages are developed from a manufacturing core; ERP vendors variously began assembling their packages with finance-and-accounting, maintenance, and human-resource components. By the mid-1990s ERP systems addressed all core enterprise functions. Governments and non–profit organizations also began to use ERP systems. An "ERP system selection methodology" is a formal process for selecting an enterprise resource planning (ERP) system. Existing methodologies include: Kuiper's funnel method, Dobrin's three-dimensional (3D) web-based decision support tool, and the Clarkston Potomac methodology. == Expansion == ERP systems experienced rapid growth in the 1990s. Because of the year 2000 problem many companies took the opportunity to replace their old systems with ERP. ERP systems initially focused on automating back office functions that did not directly affect customers and the public. Front office functions, such as customer relationship management (CRM), dealt directly with customers, or e-business systems such as e-commerce and e-government—or supplier relationship management (SRM) became integrated later, when the internet simplified communicating with external parties. "ERP II" was coined in 2000 in an article by Gartner Publications entitled ERP Is Dead—Long Live ERP II. It describes web–based software that provides real–time access to ERP systems to employees and partners (such as suppliers and customers). The ERP II role expands traditional ERP resource optimization and transaction processing. Rather than just manage buying, selling, etc.—ERP II leverages information in the resources under its management to help the enterprise collaborate with other enterprises. ERP II is more flexible than the first generation ERP. Rather than confine ERP system capabilities within the organization, it goes beyond the corporate walls to interact with other systems. Enterprise application suite is an alternate name for such systems. ERP II systems are typically used to enable collaborative initiatives such as supply chain management (SCM), customer relationship management (CRM) and business intelligence (BI) among business partner organizations through the use of various electronic business technologies. The large proportion of companies are pursuing a strong managerial targets in ERP system instead of acquire an ERP company. Developers now make more effort to integrate mobile devices with the ERP system. ERP vendors are extending ERP to these devices, along with other business applications, so that businesses don't have to rely on third-party applications. As an example, the e-commerce platform Shopify was able to make ERP tools from Microsoft and Oracle available on its app in October 2021. Technical stakes of modern ERP concern integration—hardware, applications, networking, supply chains. ERP now covers more functions and roles—including decision making, stakeholders' relationships, standardization, transparency, globalization, etc. == Functional areas == An ERP system covers the following common functional areas. In many ERP systems, these are called and grouped together as ERP modules: Financial accounting: general ledger, fixed assets, payables including vouchering, matching and payment, receivables and collections, cash management, financial consolidation Management accounting: budgeting, costing, cost management, activity based costing, billing, invoicing (optional) Human resources: recruiting, training, rostering, payroll, benefits, retirement and pension plans, diversity management, retirement, separation Manufacturing: engineering, bill of materials, work orders, scheduling, capacity, workflow management, quality control, manufacturing process, manufacturing projects, manufacturing flow, product life cycle management Order processing: order to cash, order entry, credit checking, pricing, available to promise, inventory, shipping, sales analysis and reporting, sales commissioning Supply chain management: supply chain planning, supplier scheduling, product configurator, order to cash, purchasing, inventory, claim processing, warehousing (receiving, putaway, picking and packing) Project management: project planning, resource planning, project costing, work breakdown structure, billing, time and expense, performance units, activity management Customer relationship management (CRM): sales and marketing, commissions, service, customer contact, call center support – CRM systems are not always considered part of ERP systems but rather business support systems (BSS) Supplier relationship management (SRM): suppliers, orders, payments. Data services: various "self-service" interfaces for customers, suppliers or employees Management of school and educational institutes. Contract management: creating, monitoring, and managing contracts, reducing administrative burdens and minimising legal risks. These modules often feature contract templates, electronic signature capabilities, automated alerts for contract milestones, and advanced search functionality. === GRP – ERP use in government === Government resource planning (GRP) is the equivalent of an ERP for the public sector and an integrated office automation system for government bodies. The software structure, modularization, core algorithms and main interfaces do not differ from other ERPs, and ERP software suppliers manage to adapt their systems to government agencies. Both system implementations, in private and public organizations, are adopted to improve productivity and overall business performance in organizations, but comparisons (private vs. public) of implementations shows that the main factors influencing ERP implementation success in the public sector are cultural. == Best practices == Most ERP systems incorporate best practices. This means the software reflects the vendor's interpretation of the most effective way to perform each business process. Systems vary in how conveniently the customer can modify these practices. Use of best practices eases compliance with requirements such as International Financial Reporting Standards, Sarbanes–Oxley, or Basel II. They can also help comply with de facto industry standards, such as electronic funds transfer. This is because the procedure can be readily

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  • Edward Stabler

    Edward Stabler

    Edward Stabler is a Professor of Linguistics at the University of California, Los Angeles. His primary areas of research are (1) Natural Language Processing (NLP), (2) Parsing and formal language theory, and (3) Philosophy of Logic and Language. He was a member of the faculty at UCLA from 1984 to 2016. His work involves the production of software for minimalist grammars (MGs) and related systems. == Early life and education == Stabler received his Ph.D. from the Department of Linguistics and Philosophy at MIT in 1981. == Recent publications == Edward Stabler (2011) Computational perspectives on minimalism. Revised version in C. Boeckx, ed, Oxford Handbook of Linguistic Minimalism, pp. 617–642. Edward Stabler (2010) A defense of this perspective against the Evans&Levinson critique appears here, with revised version in Lingua 120(12): 2680-2685. Edward Stabler (2010) After GB. Revised version in J. van Benthem & A. ter Meulen, eds, Handbook of Logic and Language, pp. 395–414. Edward Stabler (2010) Recursion in grammar and performance. Presented at the 2009 UMass recursion conference. Edward Stabler (2009) Computational models of language universals. Revised version appears in M. H. Christiansen, C. Collins, and S. Edelman, eds., Language Universals, Oxford: Oxford University Press, pages 200-223. Edward Stabler (2008) Tupled pregroup grammars. Revised version appears in P. Casadio and J. Lambek, eds., Computational Algebraic Approaches to Natural Language, Milan: Polimetrica, pages 23–52. Edward Stabler (2006) Sidewards without copying. Proceedings of the 11th Conference on Formal Grammar, edited by P. Monachesi, G. Penn, G. Satta, and S. Wintner. Stanford: CSLI Publications, 2006, pages 133-146.

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  • SDL plc

    SDL plc

    SDL plc was a British multinational professional services company based in Maidenhead, Berkshire, United Kingdom. SDL specialized in language translation software and services (including interpretation services). It was listed on the London Stock Exchange until it was acquired by RWS Group in November 2020. == Name == SDL is an abbreviation for "Software and Documentation Localization". == History == The company was founded by Mark Lancaster with nine employees in 1992. It opened its first overseas office in France in 1996 and was first listed on the London Stock Exchange in 1999. The company grew organically and via acquisitions. SDL acquired Polylang Multimedia in 1998, International Translation & Publishing (ITP) in 2000, Alpnet in 2001, and the machine translation (MT) assets of Transparent Language in 2001. It bought Trados, a rival translation memory (TM) developer, in 2005. In 2007, the company acquired Tridion, a content management system vendor, and PASS Engineering, developers of the Passolo software. In 2008, it bought Idiom Technologies, a global information system management business. In July 2009 SDL acquired XyEnterprise in an all-cash transaction to add XML Professional Publisher as well as Contenta content management software and LiveContent to manage and deliver XML. This unit combined with Trisoft formerly Infoshare. In December 2009, SDL acquired Fredhopper, a Dutch eCommerce onsite search and navigation, onsite targeting and targeted advertising software vendor. Later that same year, it bought Xopus, another Dutch company and the leader in online XML editing. In May 2011 SDL acquired Dutch-based Media Asset Management company, Calamares, in 2012 the campaign management and social media analytics company, Alterian, and in 2013, bemoko, a supplier of internet software for mobile devices. In January 2016, having undertaken a strategic review, SDL announced the divestment of Fredhopper and Alterian as non-complementary to its new strategy. In August 2020 RWS Group announced a proposed takeover of the company for £809 million. The transaction was completed on 4 November 2020. == Operations == SDL provided software for language translation purposes.

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  • Deterministic acyclic finite state automaton

    Deterministic acyclic finite state automaton

    In computer science, a deterministic acyclic finite state automaton (DAFSA), is a data structure that represents a set of strings, and allows for a query operation that tests whether a given string belongs to the set in time proportional to its length. Algorithms exist to construct and maintain such automata, while keeping them minimal. DAFSA is the rediscovery of a data structure called Directed Acyclic Word Graph (DAWG), although the same name had already been given to a different data structure which is related to suffix automaton. A DAFSA is a special case of a finite state recognizer that takes the form of a directed acyclic graph with a single source vertex (a vertex with no incoming edges), in which each edge of the graph is labeled by a letter or symbol, and in which each vertex has at most one outgoing edge for each possible letter or symbol. The strings represented by the DAFSA are formed by the symbols on paths in the graph from the source vertex to any sink vertex (a vertex with no outgoing edges). In fact, a deterministic finite state automaton is acyclic if and only if it recognizes a finite set of strings. == History == Blumer et al first defined terminology Directed Acyclic Word Graph (DAWG) in 1983. Appel and Jacobsen used the same naming for a different data structure in 1988. Independent of earlier work, Daciuk et al rediscovered the latter data structure in 2000 but called it DAFSA. == Comparison to tries == By allowing the same vertices to be reached by multiple paths, a DAFSA may use significantly fewer vertices than the strongly related trie data structure. Consider, for example, the four English words "tap", "taps", "top", and "tops". A trie for those four words would have 12 vertices, one for each of the strings formed as a prefix of one of these words, or for one of the words followed by the end-of-string marker. However, a DAFSA can represent these same four words using only six vertices vi for 0 ≤ i ≤ 5, and the following edges: an edge from v0 to v1 labeled "t", two edges from v1 to v2 labeled "a" and "o", an edge from v2 to v3 labeled "p", an edge v3 to v4 labeled "s", and edges from v3 and v4 to v5 labeled with the end-of-string marker. There is a tradeoff between memory and functionality, because a standard DAFSA can tell you if a word exists within it, but it cannot point you to auxiliary information about that word, whereas a trie can. The primary difference between DAFSA and trie is the elimination of suffix and infix redundancy in storing strings. The trie eliminates prefix redundancy since all common prefixes are shared between strings, such as between doctors and doctorate the doctor prefix is shared. In a DAFSA common suffixes are also shared, for words that have the same set of possible suffixes as each other. For dictionary sets of common English words, this translates into major memory usage reduction. Because the terminal nodes of a DAFSA can be reached by multiple paths, a DAFSA cannot directly store auxiliary information relating to each path, e.g. a word's frequency in the English language. However, if for each node we store the number of unique paths through that point in the structure, we can use it to retrieve the index of a word, or a word given its index. The auxiliary information can then be stored in an array.

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  • VoxForge

    VoxForge

    VoxForge is a free speech corpus and acoustic model repository for open source speech recognition engines. VoxForge was set up to collect transcribed speech to create a free GPL speech corpus in order to be uses with open source speech recognition engines. The speech audio files will be 'compiled' into acoustic models for use with open source speech recognition engines such as Julius, ISIP, and Sphinx and HTK (note: HTK has distribution restrictions). VoxForge has used LibriVox as a source of audio data since 2007.

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  • Cobham's theorem

    Cobham's theorem

    Cobham's theorem is a theorem in combinatorics on words that has important connections with number theory, notably transcendental numbers, and automata theory. Informally, the theorem gives the condition for the members of a set S of natural numbers written in bases b1 and base b2 to be recognised by finite automata. Specifically, consider bases b1 and b2 such that they are not powers of the same integer. Cobham's theorem states that S written in bases b1 and b2 is recognised by finite automata if and only if S differs by a finite set from a finite union of arithmetic progressions. The theorem was proved by Alan Cobham in 1969 and has since given rise to many extensions and generalisations. == Definitions == Let n > 0 {\displaystyle n>0} be an integer. The representation of a natural number n {\textstyle n} in base b {\textstyle b} is the sequence of digits n 0 n 1 ⋯ n h {\displaystyle n_{0}n_{1}\cdots n_{h}} such that n = n 0 + n 1 b + ⋯ + n h b h {\displaystyle n=n_{0}+n_{1}b+\cdots +n_{h}b^{h}} where 0 ≤ n 0 , n 1 , … , n h < b {\displaystyle 0\leq n_{0},n_{1},\ldots ,n_{h} 0 {\displaystyle n_{h}>0} . The word n 0 n 1 ⋯ n h {\displaystyle n_{0}n_{1}\cdots n_{h}} is often denoted ⟨ n ⟩ b {\displaystyle \langle n\rangle _{b}} , or more simply, n b {\displaystyle n_{b}} . A set of natural numbers S is recognisable in base b {\textstyle b} or more simply b {\textstyle b} -recognisable or b {\textstyle b} -automatic if the set { n b ∣ n ∈ S } {\displaystyle \{n_{b}\mid n\in S\}} of the representations of its elements in base b {\displaystyle b} is a language recognisable by a finite automaton on the alphabet { 0 , 1 , … , b − 1 } {\displaystyle \{0,1,\ldots ,b-1\}} . Two positive integers k {\displaystyle k} and ℓ {\displaystyle \ell } are multiplicatively independent if there are no non-negative integers p {\displaystyle p} and q {\displaystyle q} such that k p = ℓ q {\displaystyle k^{p}=\ell ^{q}} . For example, 2 and 3 are multiplicatively independent, but 8 and 16 are not since 8 4 = 16 3 {\displaystyle 8^{4}=16^{3}} . Two integers are multiplicatively dependent if and only if they are powers of a same third integer. == Problem statements == === Original problem statement === More equivalent statements of the theorem have been given. The original version by Cobham is the following: Another way to state the theorem is by using automatic sequences. Cobham himself calls them "uniform tag sequences." The following form is found in Allouche and Shallit's book:We can show that the characteristic sequence of a set of natural numbers S recognisable by finite automata in base k is a k-automatic sequence and that conversely, for all k-automatic sequences u {\displaystyle u} and all integers 0 ≤ i < k {\displaystyle 0\leq i 1 {\displaystyle \alpha >1} is the dominant eigenvalue of the matrix of morphism f {\displaystyle f} , namely, the matrix M ( f ) = ( m x , y ) x ∈ B , y ∈ A {\displaystyle M(f)=(m_{x,y})_{x\in B,y\in A}} , where m x , y {\displaystyle m_{x,y}} is the number of occurrences of the letter x {\displaystyle x} in the word f ( y ) {\displaystyle f(y)} . A set S of natural numbers is α {\displaystyle \alpha } -recognisable if its characteristic sequence s {\displaystyle s} is α {\displaystyle \alpha } -substitutive. A last definition: a Perron number is an algebraic number z > 1 {\displaystyle z>1} such that all its conjugates belong to the disc { z ′ ∈ C , | z ′ | < z } {\displaystyle \{z'\in \mathbb {C} ,|z'| Read more →

  • How to Choose an AI Avatar Generator

    How to Choose an AI Avatar Generator

    Trying to pick the best AI avatar generator? An AI avatar generator is software that uses machine learning to help you get more done — it scales effortlessly from a single task to thousands. The best picks balance beginner-friendly simplicity with the depth power users need, and they ship updates often. Whether you are a beginner or a pro, the right AI avatar generator slots into your workflow and pays for itself fast. Read on for hands-on impressions, pricing tiers, and the standout features that matter.

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  • The Best Free AI Writing Assistant for Beginners

    The Best Free AI Writing Assistant for Beginners

    Shopping for the best AI writing assistant? An AI writing assistant is software that uses machine learning to help you get more done — it keeps getting smarter as the underlying models improve. Pricing, accuracy, and the size of the model behind the tool are the three factors that most affect daily usefulness. Whether you are a beginner or a pro, the right AI writing assistant slots into your workflow and pays for itself fast. Below we compare features, pricing, and real output so you can choose with confidence.

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  • Software construction

    Software construction

    Software construction is the process of creating working software via coding and integration. The process includes unit and integration testing although does not include higher level testing such as system testing. Construction is an aspect of the software development lifecycle and is integrated in the various software development process models with varying focus on construction as an activity separate from other activities. In the waterfall model, a software development effort consists of sequential phases including requirements analysis, design, and planning which are prerequisites for starting construction. In an iterative model such as scrum, evolutionary prototyping, or extreme programming, construction as an activity that occurs concurrently or overlapping other activities. Construction planning may include defining the order in which components are created and integrated, the software quality management processes, and the allocation of tasks to teams and developers. To facilitate project management, numerous construction aspects can be measured; these include the amount of code developed, modified, reused, and destroyed, code complexity, code inspection statistics, faults-fixed and faults-found rates, and effort expended. These measurements can be useful for aspects such as ensuring quality and improving the process. == Activities == Construction includes many activities. === Coding === The following are a few of the key aspects of the coding activity: Naming Choice of name for each identifier. One study showed that the effort required to debug a program is minimized when variable names are between 10 and 16 characters. Logic Organization into statements and routines Highly cohesive routines proved to be less error prone than routines with lower cohesion. A study of 450 routines found that 50 percent of the highly cohesive routines were fault free compared to only 18 percent of routines with low cohesion. Another study of a different 450 routines found that routines with the highest coupling-to-cohesion ratios had 7 times as many errors as those with the lowest coupling-to-cohesion ratios and were 20 times as costly to fix. Although studies showed inconclusive results regarding the correlation between routine sizes and the rate of errors in them, but one study found that routines with fewer than 143 lines of code were 2.4 times less expensive to fix than larger routines. Another study showed that the code needed to be changed least when routines averaged 100 to 150 lines of code. Another study found that structural complexity and amount of data in a routine were correlated with errors regardless of its size. Interfaces between routines are some of the most error-prone areas of a program. One study showed that 39 percent of all errors were errors in communication between routines. Unused parameters are correlated with an increased error rate. In one study, only 17 to 29 percent of routines with more than one unreferenced variable had no errors, compared to 46 percent in routines with no unused variables. The number of parameters of a routine should be 7 at maximum as research has found that people generally cannot keep track of more than about seven chunks of information at once. One experiment showed that designs which access arrays sequentially, rather than randomly, result in fewer variables and fewer variable references. One experiment found that loops-with-exit are more comprehensible than other kinds of loops. Regarding the level of nesting in loops and conditionals, studies have shown that programmers have difficulty comprehending more than three levels of nesting. Control flow complexity has been shown to correlate with low reliability and frequent errors. Modularity Structuring and refactoring the code into classes, packages and other structures. When considering containment, the maximum number of data members in a class shouldn't exceed 7±2. Research has shown that this number is the number of discrete items a person can remember while performing other tasks. When considering inheritance, the number of levels in the inheritance tree should be limited. Deep inheritance trees have been found to be significantly associated with increased fault rates. When considering the number of routines in a class, it should be kept as small as possible. A study on C++ programs has found an association between the number of routines and the number of faults. A study by NASA showed that the putting the code into well-factored classes can double the code reusability compared to the code developed using functional design. Error handling Encoding logic to handle both planned and unplanned errors and exceptions. Resource management Managing computational resource use via exclusion mechanisms and discipline in accessing serially reusable resources, including threads or database locks. Security Prevention of code-level security breaches such as buffer overrun and array index overflow. Optimization Optimization while avoiding premature optimization. Documentation Both embedded in the code as comments and as external documents. === Integration === Integration is about combining separately constructed parts. Concerns include planning the sequence in which components will be integrated, creating scaffolding to support interim versions of the software, determining the degree of testing and quality work performed on components before they are integrated, and determining points in the project at which interim versions are tested. === Testing === Testing can reduce the time between when faulty logic is inserted in the code and when it is detected. In some cases, testing is performed after code has been written, but in test-first programming, test cases are created before code is written. Construction includes at least two forms of testing, often performed by the developer who wrote the code: unit testing and integration testing. === Reuse === Software reuse entails more than creating and using libraries. It requires formalizing the practice of reuse by integrating reuse processes and activities into the software life cycle. The tasks related to reuse in software construction during coding and testing may include: selection of the reusable code, evaluation of code or test re-usability, reporting reuse metrics. === Quality assurance === Techniques for ensuring quality as software is constructed include: Testing One study found that the average defect detection rates of Unit testing and integration testing are 30% and 35% respectively. Software inspection With respect to software inspection, one study found that the average defect detection rate of formal code inspections is 60%. Regarding the cost of finding defects, a study found that code reading detected 80% more faults per hour than testing. Another study shown that it costs six times more to detect design defects by using testing than by using inspections. A study by IBM showed that only 3.5 hours were needed to find a defect through code inspections versus 15–25 hours through testing. Microsoft has found that it takes 3 hours to find and fix a defect by using code inspections and 12 hours to find and fix a defect by using testing. In a 700 thousand lines program, it was reported that code reviews were several times as cost-effective as testing. Studies found that inspections result in 20% - 30% fewer defects per 1000 lines of code than less formal review practices and that they increase productivity by about 20%. Formal inspections will usually take 10% - 15% of the project budget and will reduce overall project cost. Researchers found that having more than 2 - 3 reviewers on a formal inspection doesn't increase the number of defects found, although the results seem to vary depending on the kind of material being inspected. Technical review With respect to technical review, one study found that the average defect detection rates of informal code reviews and desk checking are 25% and 40% respectively. Walkthroughs were found to have a defect detection rate of 20% - 40%, but were found also to be expensive especially when project pressures increase. Code reading was found by NASA to detect 3.3 defects per hour of effort versus 1.8 defects per hour for testing. It also finds 20% - 60% more errors over the life of the project than different kinds of testing. A study of 13 reviews about review meetings, found that 90% of the defects were found in preparation for the review meeting while only around 10% were found during the meeting. Static analysis With respect to Static analysis (IEEE1028), studies have shown that a combination of these techniques needs to be used to achieve a high defect detection rate. Other studies showed that different people tend to find different defects. One study found that the extreme programming practices of pair programming, desk checking, unit testing, integration testing, and regression testing can achieve a 90% defect detection rate. An experiment involving exper

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  • How to Choose an AI Avatar Generator

    How to Choose an AI Avatar Generator

    Trying to pick the best AI avatar generator? An AI avatar generator is software that uses machine learning to help you get more done — it scales effortlessly from a single task to thousands. The best picks balance beginner-friendly simplicity with the depth power users need, and they ship updates often. Whether you are a beginner or a pro, the right AI avatar generator slots into your workflow and pays for itself fast. Read on for hands-on impressions, pricing tiers, and the standout features that matter.

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  • Project Bergamot

    Project Bergamot

    Project Bergamot is a joint project between several European universities and Mozilla for the development of machine translation software based on artificial neural networks, which is intended for local execution on end-user devices. The software library that was created and the associated language models were made available to the general public as Free Software. Execution requires a x86 CPU with SSE4.1 instruction set extensions. In 2022, Devin Coldewey of TechCrunch judged the translation quality to be "more than adequate", but considered Firefox Translations to be not yet fully mature. == Usage == Mozilla used the Bergamot Translator to expand its web browser Firefox with a feature for translating web pages, which was previously considered an important gap in Firefox' feature set. It is often compared to the much older corresponding feature in Google Chrome, which utilizes a cloud-based background service. In contrast, Firefox Translations does not require any data to leave the user's computer, resulting in advantages in terms of data protection, availability and possibly response times. There is just the installation of a new language model that needs to take place the first time a new language is encountered. Greater independence from large technology companies and their interests is also mentioned as an important advantage. Mozilla thus strengthened its position as an alternative software vendor with a particular focus on data protection and security. Mozilla followed up with the similar feature of speech recognition for spoken user input, based on whisperfile. On the other hand, slow translation times have been observed, especially on older devices. Also, Firefox Translations initially supported far fewer language pairs than other major translation services and is only gradually adding new models. On that matter, the training pipeline is also made available to interested parties to enable the creation of missing language models. TranslateLocally is a Firefox-independent translation software based on the Bergamot Translator. It is also available as an (Electron-based) standalone application or as an extension for Chromium-based web browsers. == History == Mozilla had already tried to get a (cloud-based) web content translation feature into Firefox a few years before Project Bergamot, but had failed because of the financial challenge. Microsoft had already delivered offline capabilities for its translation software in 2018. Google soon followed suit, Apple two years later. The software is based on the free translation framework Marian, which the University of Edinburgh had previously developed in cooperation with Microsoft, and is itself based on the Nematus toolkit that was presented in 2017. Under the leadership of the University of Edinburgh, a development consortium was formed with the Mozilla Corporation and the additional European universities of Prague, Sheffield and Tartu. In 2018, it was able to get 3 million euros of funding from the EU's Horizon 2020 programme. Firefox Translations was initially provided as an add-on. A first functional demonstration prototype was presented in October 2019. Beta version 117 had the feature integrated directly into the browser, the official release was in version 118 from September 2023. Both the add-on module and as part of Firefox, the code and the models are subject to the version 2 of the Mozilla Public License. Since 2022, the EU-funded HPLT project creates new language models. It involves additional partners, including the universities of Helsinki, Turku, Oslo and other partners from Spain, Norway and the Czech Republic.

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