Executive Order 14110, titled Executive Order on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (sometimes referred to as "Executive Order on Artificial Intelligence") was the 126th executive order signed by former U.S. President Joe Biden. Signed on October 30, 2023, the order defines the administration's policy goals regarding artificial intelligence (AI), and orders executive agencies to take actions pursuant to these goals. The order is considered to be the most comprehensive piece of governance by the United States regarding AI. It was rescinded by U.S. President Donald Trump within hours of his assuming office on January 20, 2025. Policy goals outlined in the executive order pertain to promoting competition in the AI industry, preventing AI-enabled threats to civil liberties and national security, and ensuring U.S. global competitiveness in the AI field. The executive order required a number of major federal agencies to create dedicated "chief artificial intelligence officer" positions within their organizations. == Background == The drafting of the order was motivated by the rapid pace of development in generative AI models in the 2020s, including the release of large language model ChatGPT. Executive Order 14110 is the third executive order dealing explicitly with AI, with two AI-related executive orders being signed by then-President Donald Trump. The development of AI models without policy safeguards has raised a variety of concerns among experts and commentators. These range from future existential risk from advanced AI models to immediate concerns surrounding current technologies' ability to disseminate misinformation, enable discrimination, and undermine national security. In August 2023, Arati Prabhakar, the director of the Office of Science and Technology Policy, indicated that the White House was expediting its work on executive action on AI. A week prior to the executive order's unveiling, Prabhakar indicated that Office of Management and Budget (OMB) guidance on the order would be released "soon" after. == Policy goals and provisions == The order has been characterized as an effort for the United States to capture potential benefits from AI while mitigating risks associated with AI technologies. Upon signing the order, Biden stated that AI technologies were being developed at "warp speed", and argued that to "realize the promise of AI and avoid the risk, we need to govern this technology". Policy goals outlined by the order include the following: Promoting competition and innovation in the AI industry Upholding civil and labor rights and protecting consumers and their privacy from AI-enabled harms Specifying federal policies governing procurement and use of AI Developing watermarking systems for AI-generated content and warding off intellectual property theft stemming from the use of generative models Maintaining the nation's place as a global leader in AI == Impact on agencies == === Creation of chief AI officer positions === The executive order required a number of large federal agencies to appoint a chief artificial intelligence officer, with a number of departments having already appointed a relevant officer prior to the order. In the days following the order, news publication FedScoop confirmed that the General Services Administration (GSA) and the United States Department of Education appointed relevant chief AI officers. The National Science Foundation (NSF) also confirmed it had elevated an official to serve as its chief AI officer. === Department responsibilities === Under the executive order, the Department of Homeland Security (DHS) was responsible for developing AI-related security guidelines, including cybersecurity-related matters. The DHS will also work with private sector firms in sectors including the energy industry and other "critical infrastructure" to coordinate responses to AI-enabled security threats. Executive Order 14110 mandated the Department of Veterans Affairs to launch an AI technology competition aimed at reducing occupational burnout among healthcare workers through AI-assisted tools for routine tasks. The order also mandated the Department of Commerce's National Institute of Standards and Technology (NIST) to develop a generative artificial intelligence-focused resource to supplement the existing AI Risk Management Framework. == Analysis == The executive order has been described as the most comprehensive piece of governance by the United States government pertaining to AI. Earlier in 2023 prior to the signing of the order, the Biden administration had announced a Blueprint for an AI Bill of Rights, and had secured non-binding AI safety commitments from major tech companies. The issuing of the executive order comes at a time in which lawmakers including Senate Majority Leader Chuck Schumer have pushed for legislation to regulate AI in the 118th United States Congress. According to Axios, despite the wide scope of the executive order, it notably does not touch upon a number of AI-related policy proposals. This includes proposals for a "licensing regime" to government advanced AI models, which has received support from industry leaders including Sam Altman. Additionally, the executive order does not seek to prohibit 'high-risk' uses of AI technology, and does not aim to mandate that tech companies release information surrounding AI systems' training data and models. == Reception == === Political and media reception === The editorial board of the Houston Chronicle described the order as a "first step toward protecting humanity". The issuing of the order received praise from Democratic members of Congress, including Senator Richard Blumenthal (D-CT) and Representative Ted Lieu (D-CA). Representative Don Beyer (D-VA), who leads the House AI Caucus, praised the order as a "comprehensive strategy for responsible innovation", while arguing that Congress must take initiative to pass legislation on AI. The draft of the order received criticism from Republican Senator Ted Cruz (R-TX), who described it as creating "barriers to innovation disguised as safety measures". === Public reception === Polling from the AI Policy Institute showed that 69% of all voters support the executive order, while 15% oppose it. Breaking it down by party, support was at 78% for Democrats, 65% for independents, and 64% for Republicans. === Industry reception === The executive order received strong criticism from the Chamber of Commerce as well as tech industry groups including NetChoice and the Software and Information Industry Association, all of which count "Big Tech" companies Amazon, Meta, and Google as members. Representatives from the organizations argued that the executive order threatens to hinder private sector innovation. === Civil society reception === According to CNBC, a number of leaders advocacy organizations praised the executive order for its provisions on "AI fairness", while simultaneously urging congressional action to strengthen regulation. Maya Wiley, president and CEO of the Leadership Conference on Civil and Human Rights, praised the order while urging Congress to take initiative to "ensure that innovation makes us more fair, just, and prosperous, rather than surveilled, silenced, and stereotyped". A representative from the American Civil Liberties Union (ACLU) praised provisions of the order centered on combating AI-enabled discrimination, while also voiced concern over sections of the order focused on law enforcement and national security. === Second Trump administration === Hours after his inauguration as the 47th president of the United States, Donald Trump rescinded the order, labeling it, among several other of Biden's executive orders and actions, as "unpopular, inflationary, illegal, and radical practices".
Teamwork (project management)
Teamwork.com is an Irish, privately owned, web-based software company headquartered in Cork, Ireland. Teamwork creates task management and team collaboration software. Founded in 2007, as of 2016 the company stated that its software was in use by over 370,000 organisations worldwide (including Disney, Spotify and HP), and that it had over 2.4m users. == History == Peter Coppinger and Dan Mackey founded a company, Digital Crew, in 2007. This company built websites, intranets and custom web-based solutions for clients in Cork, Ireland. Frustrated by whiteboards and software management tools, Coppinger wanted a software system that would help manage client projects and which would be easy to use and generic enough to be used by different types of companies. Originally 37signals Basecamp users themselves, Coppinger and Mackey were frustrated by the limited feature set, and by Basecamp's apparent inaction on their feedback. In October 2007, Coppinger and Mackey launched Teamwork Project Manager, nicknamed TeamworkPM. In March 2015, this was renamed as Teamwork Projects. In 2014, after two years of negotiations, TeamworkPM bought the domain name 'Teamwork.com' for US$675,000 (€500,000). At the time this was one of the most expensive domain name purchases by an Irish company, and involved the transfer of a domain name which had been dormant since it was first acquired by the original owner in 1999. In 2015, Teamwork.com was named by Gartner to be one of their "Cool Vendors" in the Program and Portfolio Management Category. This was followed by the launch of a new real-time messaging product, Teamwork Chat, in January 2015. In June 2015, the company announced a drive to recruit for 40 positions by the end of the year. This was followed by the announcement that the company was investing more than €1 million in a new office, and had leased office space in Park House, Blackpool. In June 2016, Teamwork.com undertook a further recruitment drive to entice developers to Cork. In July 2021, the company announced that it had raised an investment of $70 million (€59.1 million) from venture capital firm Bregal Milestone to fund further growth. == Products == Teamwork markets a number of cloud-based applications, including Teamwork, Teamwork Desk, Teamwork Spaces, Teamwork CRM and Teamwork Chat. Teamwork was launched on 4 October 2007, at which time it had time management, milestone management, file sharing, time tracking, and messaging features. Teamwork's platform reportedly integrates with martech software like HubSpot, as well as other productivity tools like Slack, G Suite, MS Teams, Zapier, Dropbox and QuickBooks. == Awards == In 2016, Teamwork was awarded Cork's Best SME in the Cork Chamber of Commerce "Company of the Year" awards. In 2016, Teamwork was named number 7 in Deloitte's Fast 50 tech companies hit €1.6bn turnover. In 2015, Teamwork was identified as a Gartner "Cool Vendor" in the Program and Portfolio Management Category.
Digital edition
A digital edition is an online magazine or online newspaper delivered in electronic form which is formatted identically to the print version. Digital editions are often called digital facsimiles to underline the likeness to the print version. Digital editions have the benefit of reduced cost to the publisher and reader by avoiding the time and the expense to print and deliver paper edition. This format is considered more environmentally friendly due to the reduction of paper and energy use. These editions also often feature interactive elements such as hyperlinks both within the publication itself and to other internet resources, search option and bookmarking, and can also incorporate multimedia such as video or animation to enhance articles themselves or for advertisement purposes. Some delivery methods also include animation and sound effects that replicate turning of the page to further enhance the experience of their print counterparts. Magazine publishers have traditionally relied on two revenue sources: selling ads and selling magazines. Additionally some publishers are using other electronic publication methods such as RSS to reach out to readers and inform them when new digital editions are available. Current technologies are generally either reader-based, requiring a download of an application and subsequent download of each edition, or browser-based, often using Macromedia Flash, requiring no application download (such as Adobe Acrobat). Some application-based readers allow users to access editions while not connected to internet. Dedicated hardware such as the Amazon Kindle and the iPad is also available for reading digital editions of select books, popular national magazines such as Time, The Atlantic, and Forbes and popular national newspapers such as the New York Times, Wall Street Journal, and Washington Post. Archives of print newspapers, in some cases dating hundreds of years back, are being digitized and made available online. Google is indexing existing digital archives produced by the newspapers themselves or by third parties. Newspaper and magazine archival began with microform film formats solving the problem of efficiently storing and preserving. This format, however, lacked accessibility. Many libraries, especially state libraries in the United States are archiving their collections digitally and converting existing microfilm to digital format. The Library of Congress provides project planning assistance and the National Endowment for the Humanities procures funding through grants from its National Digital Newspaper Program. Digital magazines, ezines, e-editions and emags are sometimes referred to as digital editions, however some of these formats are published only in digital format unlike digital editions which replicate a printed edition as well. == Digital magazines == Digital-replica magazines number in thousands—consumer and business publications, house magazines for associations, institutions and corporations – and conversion from print to digital was still increasing as of 2009. A 2008 report funded by digital-replica technology providers and auditing agencies counted 1,786 digital-replica editions having more than 7 million circulation among business-to-business publications, of which 230 editions were audited The same report counted 1,470 digital-replica editions of consumer magazines having 5.5 million digital circulation, of which 240 editions were audited. These authors estimated that by year end of 2009 there would be 8,000 digital magazines, having a combined distribution of more than 30 million people. Surveys have shown that, while not all subscribers prefer a digital edition, some do because of the environmental benefit and also because digital magazines are searchable and may easily be passed along or linked to. One such survey funded by a digital publisher reported on inputs from more than 30,000 subscribers to business, consumer and other digital magazines. == Digital magazine business models == === Reduced printing and distribution costs === The publishers' choice to save by moving some or all subscribers from print to digital is widely accepted. Oracle magazine, which has 176,000 of its 516,000 subscribers receiving digital according to its June 2009 BPA circulation statement, is said to be the most widely circulated digital edition of a business-to-business publication. Publishers who do this need to choose whether to make some issues all-digital, move some subscribers to digital edition, add some digital-only subscribers, or send all subscribers the digital edition. === Paid subscription revenue === In 2009, a major consumer magazine, PC Magazine, went all-digital, charging an annual subscription fee for its digital-replica edition. Many consumer magazines and newspapers are already available in eReader formats that are sold through booksellers. === Sponsorship and advertising revenue === Digital editions often carry special "front cover" advertising, or advertising on the email message alerting the subscriber of the digital edition. Publishers also produce special digital-only inserts and rich-media ads or advertorials. === Designed-for-digital issues === Another approach is to fully replace printed issues with digital ones, or to use digital editions for extra issues that would otherwise have to be printed.
CodePen
CodePen is an online community for testing and showcasing user-created HTML, CSS and JavaScript code snippets. It functions as an online code editor and open-source learning environment, where developers can create code snippets, called "pens," and test them. It was founded in 2012 by full-stack developers Alex Vazquez and Tim Sabat and front-end designer Chris Coyier. Its employees work remotely, rarely all meeting together in person. CodePen is a large community for web designers and developers to showcase their coding skills, with an estimated 330,000 registered users and 14.16 million monthly visitors.
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.
Sherwood Applied Business Security Architecture
SABSA (Sherwood Applied Business Security Architecture) is a model and methodology for developing a risk-driven enterprise information security architecture and service management, to support critical business processes. It was developed independently from the Zachman Framework, but has a similar structure. The primary characteristic of the SABSA model is that everything must be derived from an analysis of the business requirements for security, especially those in which security has an enabling function through which new business opportunities can be developed and exploited. The process analyzes the business requirements at the outset, and creates a chain of traceability through the strategy and concept, design, implementation, and ongoing ‘manage and measure’ phases of the lifecycle to ensure that the business mandate is preserved. Framework tools created from practical experience further support the whole methodology. The model is layered, with the top layer being the business requirements definition stage. At each lower layer a new level of abstraction and detail is developed, going through the definition of the conceptual architecture, logical services architecture, physical infrastructure architecture and finally at the lowest layer, the selection of technologies and products (component architecture). The SABSA model itself is generic and can be the starting point for any organization, but by going through the process of analysis and decision-making implied by its structure, it becomes specific to the enterprise, and is finally highly customized to a unique business model. It becomes in reality the enterprise security architecture, and it is central to the success of a strategic program of information security management within the organization. SABSA is a particular example of a methodology that can be used both for IT (information technology) and OT (operational technology) environments. == SABSA matrix == Note: The above is the original SABSA Matrix, which is still valid today, but it has been expanded by a comprehensive service management matrix and updated in some detail and terminology areas. In the words of David Lynas, SABSA author, "The SABSA Matrix and the SABSA Service Management Matrix have not been updated since the late 90s. We have redesigned them to deliver the improvements your feedback has requested over the years. We have not fundamentally changed the structure or principles of the matrices (very few elements have changed position) but have focused on terminology update and consistency." The new versions can be downloaded (along with the 2009 revision of the SABSA White Paper and other important documents like the SABSA Certification Roadmap) at the SABSA Members' Web Site.
Digital intermediate
Digital intermediate (DI) is a motion picture finishing process which classically involves digitizing a motion picture and manipulating the color and other image characteristics. == Definition and overview == A digital intermediate often replaces or augments the photochemical timing process and is usually the final creative adjustment to a movie before distribution in theaters. It is distinguished from the telecine process in which film is scanned and color is manipulated early in the process to facilitate editing. However the lines between telecine and DI are continually blurred and are often executed on the same hardware by colorists of the same background. These two steps are typically part of the overall color management process in a motion picture at different points in time. A digital intermediate is also customarily done at higher resolution and with greater color fidelity than telecine transfers. Although originally used to describe a process that started with film scanning and ended with film recording, digital intermediate is also used to describe color correction and color grading and even final mastering when a digital camera is used as the image source and/or when the final movie is not output to film. This is due to recent advances in digital cinematography and digital projection technologies that strive to match film origination and film projection. In traditional photochemical film finishing, an intermediate is produced by exposing film to the original camera negative. The intermediate is then used to mass-produce the films that get distributed to theaters. Color grading is done by varying the amount of red, green, and blue light used to expose the intermediate. The digital intermediate process uses digital tools to color grade, which allows for much finer control of individual colors and areas of the image, and allows for the adjustment of image structure (grain, sharpness, etc.). The intermediate for film reproduction can then be produced by means of a film recorder. The physical intermediate film that is a result of the recording process is sometimes also called a digital intermediate, and is usually recorded to internegative (IN) stock, which is inherently finer-grain than original camera negative (OCN). One of the key technical achievements that made the transition to DI possible was the use of 3D look-up tables, which could be used to mimic how the digital image would look once it was printed onto release print stock. This removed a large amount of guesswork from the film-making process, and allowed greater freedom in the colour grading process while reducing risk. The digital master is often used as a source for a DCI-compliant distribution of the motion picture for digital projection. For archival purposes, the digital master created during the digital intermediate process can be recorded to very stable high dynamic range yellow-cyan-magenta (YCM) separations on black-and-white film with an expected 100-year or longer life. While still subject to the natural degradation of any analog chemical master, this archival format, long used in the industry prior to the invention of DI, was considered valuable for providing an archival medium that is independent of changes in digital data recording technologies and file formats that might otherwise render digitally archived material unreadable in the long term. A "film intermediate" is an analog variation of a digital intermediate, where a project shot on digital video is printed onto film stock and transferred back to digital video to emulate film. The term was coined after it was used on the Oscar-winning 2012 short film "Curfew". The process was also used on the films Dune (2021) and The Batman (2022). == History == Telecine tools to electronically capture film images are nearly as old as broadcast television, but the resulting images were widely considered unsuitable for exposing back onto film for theatrical distribution. Film scanners and recorders with quality sufficient to produce images that could be inter-cut with regular film began appearing in the 1970s, with significant improvements in the late 1980s and early 1990s. During this time, digitally processing an entire feature-length film was impractical because the scanners and recorders were extremely slow and the image files were too large compared to computing power available. Instead, individual shots or short sequences were processed for visual effects. In 1992, Visual Effects Supervisor/Producer Chris F. Woods broke through several "techno-barriers" in creating a digital studio to produce the visual effects for the 1993 release Super Mario Bros. It was the first feature film project to digitally scan a large number of VFX plates (over 700) at 2K resolution. It was also the first film scanned and recorded at Kodak's just launched Cinesite facility in Hollywood. This project based studio was the first feature film to use Discreet Logic's (now Autodesk) Flame and Inferno systems, which enjoyed early dominance as high resolution / high performance digital compositing systems. Digital film compositing for visual effects was immediately embraced, while optical printer use for VFX declined just as quickly. Chris Watts further revolutionized the process on the 1998 feature film Pleasantville, becoming the first visual effects supervisor for New Line Cinema to scan, process, and record the majority of a feature-length, live-action, Hollywood film digitally. The first Hollywood film to utilize a digital intermediate process from beginning to end was O Brother, Where Art Thou? in 2000 and in Europe it was Chicken Run released that same year. The process rapidly caught on in the mid-2000s. Around 50% of Hollywood films went through a digital intermediate in 2005, increasing to around 70% by mid-2007. This is due not only to the extra creative options the process affords film makers but also the need for high-quality scanning and color adjustments to produce movies for digital cinema. == Milestones == 1990: The Rescuers Down Under – First feature-length film to be entirely recorded to film from digital files; in this case animation assembled on computers using Walt Disney Feature Animation and Pixar's CAPS system. 1992: Visual effects supervisor and producer Chris F. Woods creates a VFX studio to produce the visual effects for the 1993 film Super Mario Bros. It was the first 35mm feature film to digitally scan a large number of VFX plates (over 700) at 2K resolution, as well as to output the finished VFX to 35mm negative at 2K. 1993: Snow White and the Seven Dwarfs – First film to be entirely scanned to digital files, manipulated, and recorded back to film at 4K resolution. The restoration project was done entirely at 4K resolution and 10-bit color depth using the Cineon system to digitally remove dirt and scratches and restore faded colors. 1998: Pleasantville – The first time the majority of a new feature film was scanned, processed, and recorded digitally. The black-and-white meets color world portrayed in the movie was filmed entirely in color and selectively desaturated and contrast adjusted digitally. The work was done in Los Angeles by Cinesite utilizing a Spirit DataCine for scanning at 2K resolution and a MegaDef color correction system from UK Company Pandora International 1998: Zingo - The first feature film to use digital color correction via digital intermediate in its entirety. The work was performed at the Digital Film Lab in Copenhagen, using a Spirit Datacine to transfer the entire film to digital files at 2K resolution. The digital intermediate process was also used to perform a digital blowup of the film's original Super 16 source format to a 35mm output. 1999: Pacific Ocean Post Film, a team led by John McCunn and Greg Kimble used Kodak film scanners & laser film printer, Cineon software as well as proprietary tools to rebuild and repair the first two reels of the 1968 Beatles' film Yellow Submarine for re-release. 1999: Star Wars: Episode I – The Phantom Menace - Industrial Light & Magic (ILM) scanned the entirety of the visual effects-laden film for the purposes of digital enhancement and the integration of thousands of separately filmed elements with computer generated characters and environments. Outside of the approximately 2000 effects shots that were digitally manipulated, the remaining 170 non-effects shots were also scanned for continuity. However, after the digital shots were manipulated at ILM, they were filmed out individually and sent to Deluxe Labs where they were processed and color timed photochemically. 2000: Sorted - The first feature-length, color 35mm motion picture to fully utilize the digital intermediate process in its entirety from inception to completion. The film was produced at Wave Pictures' digital intermediate film facility in London, England. It was scanned at 2K resolution with 8 bits color depth per color / per pixel using a pin registered, liquid gate Oxberry