AI For Business Research

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

• 

  Zero-knowledge service

  In cloud computing, the term zero-knowledge (or occasionally no-knowledge or zero-access) is a commonly used term for online services that store, transfer or manipulate data with a high level of confidentiality, where the data is only accessible to the data's owner (the client), and not to the service provider. However, unlike "end-to-end encryption", the term "zero-knowledge" does not imply any specific threat model or security notion, and its use is commonly frowned-upon by the security community. The term "zero-knowledge" was popularized by backup service SpiderOak, which later switched to using the term "no knowledge", acknowledging that the previous terminology was not technically accurate. == Disadvantages == Most cloud storage services keep a copy of the client's password on their servers, allowing clients who have lost their passwords to retrieve and decrypt their data using alternative means of authentication; but since zero-knowledge services do not store copies of clients' passwords, if a client loses their password then their data cannot be decrypted, making it practically unrecoverable. Most of the most used cloud storage services, such as Google Drive, Dropbox, OneDrive or iCloud, are also able to furnish access requests from law enforcement agencies for similar reasons; zero-knowledge services, however, are unable to do so, since their systems are designed to make clients' data inaccessible without the client's explicit cooperation.

  Read more →
• 

  Question (short story)

  "Question" is a science fiction short story by American writer Isaac Asimov. The story first appeared in the March 1955 issue of Computers and Automation (thought to be the first computer magazine), and was reprinted in the April 30, 1957, issue of Science World. It is the first of a loosely connected series of stories concerning a fictional supercomputer called Multivac. The story concerns two technicians who are servicing Multivac, and their argument over whether or not the machine is truly intelligent and able to think. Multivac, however, supplies the answer on its own. After the reprint, another author, Robert Sherman Townes, noticed the climax in the last sentence was very similar to one of his own stories, "Problem for Emmy" (Startling Stories, June 1952), and wrote to Asimov about it. After searching in his library, Asimov did find the original story and, although he did not recall having read it, admitted that the endings were pretty similar. He then replied to Townes, apologizing and promising the story would never again be published, and it never was. Asimov mentioned "Question" in an editorial called "Plagiarism" which appeared in the August 1985 issue of Asimov's Science Fiction (although he did not mention Townes' name or the title of either story). "Plagiarism" was reprinted in Asimov's collection Gold (1995).

  Read more →
• 

  International Conference on Autonomous Agents and Multiagent Systems

  The International Conference on Autonomous Agents and Multiagent Systems or AAMAS is the leading scientific conference for research in the areas of artificial intelligence, autonomous agents, and multiagent systems. It is annually organized by a non-profit organization called the International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). == History == The International Conference on Autonomous Agents and Multiagent Systems (AAMAS) is a highly respected joint conference that provides a quality forum for discussing research in intelligent computational agents and their interactions. It is a merger of three major international conferences/workshops, namely the International Conference on Autonomous Agents (AGENTS), International Conference on Multi-Agent Systems (ICMAS), and International Workshop on Agent Theories, Architectures, and Languages (ATAL). ICMAS is itself a merger of three formative workshops, each with an attendance of fewer than 50 researchers. At a meeting during IJCAI-93 held in Chambery, France in August 1993, the leaders of the European Workshops on Modelling Autonomous Agents in a Multi-Agent World, the Asian MAAC Workshops, and the North American Distributed Artificial Intelligence Workshops (Victor Lesser, Michael N. Huhns, Les Gasser, Barbara Grosz, Nicholas Jennings, Michael Wooldridge, Gerhard Weiss, Mario Tokoro, and Toru Ishida) began the planning for a combined conference, which resulted in the first ICMAS in San Francisco, CA, USA in 1995, attended by more than 500 researchers. The AAMAS Conference is under the guidance and management of the International Foundation for Autonomous Agents and Multiagent Systems, which is incorporated as a 501(c)(3) non-profit organization in South Carolina, USA. == Current and previous conferences == 2024: Auckland, New Zealand (May 6-10) 2023: London, United Kingdom (May 29-June 1) 2022: Auckland, New Zealand (May 9–13) 2021: London, United Kingdom (May 3-May 7) 2020: Auckland, New Zealand (May 9–13) 2019: Montreal, Canada (May 13–17) 2018: Stockholm, Sweden (July 10–15) 2017: São Paulo, Brazil 2016: Singapore City, Singapore 2015: Istanbul, Turkey 2014: Paris, France 2013: Saint Paul, USA 2012: Valencia, Spain 2011: Taipei, Taiwan 2010: Toronto, Canada 2009: Budapest, Hungary 2008: Estoril, Portugal 2007: Honolulu, USA 2006: Hakodate, Japan 2005: Utrecht, The Netherlands 2004: New York, USA 2003: Melbourne, Australia 2002: Bologna, Italy == Activities == Besides the main program that consists of a main track, an industry and applications track, and a couple of special area tracks, AAMAS also hosts over 20 workshops (e.g., AOSE, COIN, DALT, ProMAS, to mention a few) and many tutorials. There is also a demonstration session and a doctoral symposium. Finally, each year AAMAS features a bunch of awards, most notably the IFAAMAS Influential Paper Award. It publishes proceedings which are available online.

  Read more →
• 

  Fuzzy differential equation

  Fuzzy differential equation are general concept of ordinary differential equation in mathematics defined as differential inclusion for non-uniform upper hemicontinuity convex set with compactness in fuzzy set. d x ( t ) / d t = F ( t , x ( t ) , α ) , {\displaystyle dx(t)/dt=F(t,x(t),\alpha ),} for all α ∈ [ 0 , 1 ] {\displaystyle \alpha \in [0,1]} . == First order fuzzy differential equation == A first order fuzzy differential equation with real constant or variable coefficients x ′ ( t ) + p ( t ) x ( t ) = f ( t ) {\displaystyle x'(t)+p(t)x(t)=f(t)} where p ( t ) {\displaystyle p(t)} is a real continuous function and f ( t ) : [ t 0 , ∞ ) → R F {\displaystyle f(t)\colon [t_{0},\infty )\rightarrow R_{F}} is a fuzzy continuous function y ( t 0 ) = y 0 {\displaystyle y(t_{0})=y_{0}} such that y 0 ∈ R F {\displaystyle y_{0}\in R_{F}} . == Linear systems of fuzzy differential equations == A system of equations of the form x ( t ) n ′ = a n 1 ( t ) x 1 ( t ) + . . . . . . + a n n ( t ) x n ( t ) + f n ( t ) {\displaystyle x(t)'_{n}=a_{n}1(t)x_{1}(t)+......+a_{n}n(t)x_{n}(t)+f_{n}(t)} where a i j {\displaystyle a_{i}j} are real functions and f i {\displaystyle f_{i}} are fuzzy functions x n ′ ( t ) = ∑ i = 0 1 a i j x i . {\displaystyle x'_{n}(t)=\sum _{i=0}^{1}a_{ij}x_{i}.} == Fuzzy partial differential equations == A fuzzy differential equation with partial differential operator is ∇ x ( t ) = F ( t , x ( t ) , α ) , {\displaystyle \nabla x(t)=F(t,x(t),\alpha ),} for all α ∈ [ 0 , 1 ] {\displaystyle \alpha \in [0,1]} . == Fuzzy fractional differential equation == A fuzzy differential equation with fractional differential operator is d n x ( t ) d t n = F ( t , x ( t ) , α ) , {\displaystyle {\frac {d^{n}x(t)}{dt^{n}}}=F(t,x(t),\alpha ),} for all α ∈ [ 0 , 1 ] {\displaystyle \alpha \in [0,1]} where n {\displaystyle n} is a rational number.

  Read more →
• 

  Eager learning

  In artificial intelligence, eager learning is a learning method in which the system tries to construct a general, input-independent target function during training of the system, as opposed to lazy learning, where generalization beyond the training data is delayed until a query is made to the system. The main advantage gained in employing an eager learning method, such as an artificial neural network, is that the target function will be approximated globally during training, thus requiring much less space than using a lazy learning system. Eager learning systems also deal much better with noise in the training data. Eager learning is an example of offline learning, in which post-training queries to the system have no effect on the system itself, and thus the same query to the system will always produce the same result. The main disadvantage with eager learning is that it is generally unable to provide good local approximations in the target function.

  Read more →
• 

  Your AI Slop Bores Me

  Your AI Slop Bores Me (stylized in all lowercase) is a website and social experiment created by programmer Mihir Maroju. Serving as a parody of large language models (LLMs) like ChatGPT and Claude, all questions and image prompts posed by users are answered by other, randomly-selected human users of the site. As of March 2026, the site has reached 50 million hits and sits at 16,000 concurrent users. == Background == In an interview with Fast Company, Maroju said he was inspired to create the site by his frustration with AI proliferating the internet with AI generated content, saying the site came from "a frustration for AI art and its proliferation, making artists' lives worse and also just filling the internet with low-effort generic slop". == Overview == The site has a credit system, in which a first-time user will be given 1 credit for free. Every 10 minutes, if a user has 0 credits, they will receive 2 credits. Once the credits are used up, the user can no longer do prompts unless the user earns them. The user can earn credits by responding to other user's prompts by "larping as AI" while given a 75-second time limit. Prompts can either be for a written response, or a drawing for the other user to fulfill the prompt. The maximum amount of credits a user can have is 6 credits, and cannot exceed the maximum limit. If the prompting user activates "thinking mode", the countdown is extended to 150 seconds for the cost of 2 credits. == Reception == The site has garnered attention and praise from X users, and across many online communities. The Daily Dot's Rachel Kiley wrote that "the best part about the game is that there's really no right or wrong way to do it. Humans aren't LLMs trained on copyrighted material and the whole of the free internet, but we do retain a certain amount of the information we've learned from those things over the course of our lives, while also being capable of creativity". Chris Taylor of Mashable called the site "amateurish and charming". Aftermath's Nicole Carpenter wrote that the site reminded her of "the human touch of chaos".

  Read more →
• 

  Ghost in the Shell

  Ghost in the Shell is a Japanese cyberpunk military science fiction media franchise that began with the eponymous manga series, written and illustrated by Masamune Shirow. The manga, first serialized from 1989 to 1991, is set in the mid-21st-century and follows the fictional counter-cyberterrorist organization Public Security Section 9, led by protagonist Major Motoko Kusanagi. Animation studio Production I.G has produced several anime adaptations of the series. These include the 1995 film of the same name and its 2004 sequel, Ghost in the Shell 2: Innocence; the 2002 television series Ghost in the Shell: Stand Alone Complex and its 2020 follow-up, Ghost in the Shell: SAC_2045; and the Ghost in the Shell: Arise original video animation series. In addition, an American-produced live-action film was released in March 2017. == Overview == === Title === The original editor Koichi Yuri says: At first, Ghost in the Shell came from Shirow, but when Yuri asked for "something more flashy", Shirow came up with "攻殻機動隊 Koukaku Kidou Tai (Shell Squad)" for Yuri. But Shirow was attached to including "Ghost in the Shell" as well even if in smaller type. === Setting === Primarily set in the mid-twenty-first century in the fictional Japanese city of Niihama, Niihama Prefecture (新浜県新浜市, Niihama-ken Niihama-shi), otherwise known as New Port City (ニューポートシティ, Nyū Pōto Shiti), the manga and the many anime adaptations follow the members of Public Security Section 9, a task-force consisting of various professionals skilled at solving and preventing crime, mostly with some sort of police background. Political intrigue and counter-terrorism operations are standard fare for Section 9, but the various actions of corrupt officials, companies, and cyber-criminals in each scenario are unique and require the diverse skills of Section 9's staff to prevent a series of incidents from escalating. In this post-cyberpunk iteration of a possible future, computer technology has advanced to the point that many members of the public possess cyberbrains, technology that allows them to interface their biological brain with various networks. The level of cyberization varies from simple minimal interfaces to almost complete replacement of the brain with cybernetic parts, in cases of severe trauma. This can also be combined with various levels of prostheses, with a fully prosthetic body enabling a person to become a cyborg. The main character of Ghost in the Shell, Major Motoko Kusanagi, is such a cyborg, having had a terrible accident befall her as a child that ultimately required her to use a full-body prosthesis to house her cyberbrain. This high level of cyberization, however, opens the brain up to attacks from highly skilled hackers, with the most dangerous being those who will hack a person to bend to their whims. == Media == === Literature === ==== Original manga ==== The original Ghost in the Shell manga ran in Japan from April 1989 to November 1990 in Kodansha's manga anthology Young Magazine, and was released in a tankōbon volume on October 2, 1991. Ghost in the Shell 2: Man-Machine Interface followed in 1997 for nine issues in Young Magazine, and was collected in the Ghost in the Shell: Solid Box on December 1, 2000. Then a standard version with modifications and new pages was published on June 26, 2001. Four stories from Man-Machine Interface that were not released in tankobon format from previous releases were later collected in Ghost in the Shell 1.5: Human-Error Processor, and published by Kodansha on July 17, 2003. Several art books have also been published for the manga. === Films === ==== Animated films ==== Two animated films based on the original manga have been released, both directed by Mamoru Oshii and animated by Production I.G. Ghost in the Shell was released in 1995 and follows the "Puppet Master" storyline from the manga. It was re-released in 2008 as Ghost in the Shell 2.0 with new audio and updated 3D computer graphics in certain scenes. Innocence, otherwise known as Ghost in the Shell 2: Innocence, was released in 2004, with its story based on a chapter from the first manga. ==== Live-action film ==== In 2008, DreamWorks and producer Steven Spielberg acquired the rights to a live-action film adaptation of the original Ghost in the Shell manga. On January 24, 2014, Rupert Sanders was announced as director, with a screenplay by William Wheeler. In April 2016, the full cast was announced, which included Juliette Binoche, Chin Han, Lasarus Ratuere and Kaori Momoi, and Scarlett Johansson in the lead role; the casting of Johansson drew accusations of whitewashing. Principal photography on the film began on location in Wellington, New Zealand, on February 1, 2016. Filming wrapped in June 2016. Ghost in the Shell premiered in Tokyo on March 16, 2017, and was released in the United States on March 31, 2017, in 2D, 3D and IMAX 3D. It received mixed reviews, with praise for its visuals and Johansson's performance but criticism for its script. === Television === ==== Stand Alone Complex TV series, film and ONA ==== In 2002, Ghost in the Shell: Stand Alone Complex premiered on Animax, presenting a new telling of Ghost in the Shell independent from the original manga, focusing on Section 9's investigation of the Laughing Man hacker. It was followed in 2004 by a second season titled Ghost in the Shell: S.A.C. 2nd GIG, which focused on the Individual Eleven terrorist group. The primary storylines of both seasons were compressed into OVAs broadcast as Ghost in the Shell: Stand Alone Complex The Laughing Man in 2005 and Ghost in the Shell: Stand Alone Complex Individual Eleven in 2006. Also in 2006, Ghost in the Shell: Stand Alone Complex - Solid State Society, featuring Section 9's confrontation with a hacker known as the Puppeteer, was broadcast, serving as a finale to the anime series. The extensive score for the series and its films was composed by Yoko Kanno. On April 7, 2017, Kodansha and Production I.G announced that Kenji Kamiyama and Shinji Aramaki would be co-directing a new Kōkaku Kidōtai anime production. On December 7, 2018, it was reported by Netflix that they had acquired the worldwide streaming rights to the original net animation (ONA) anime series, titled Ghost in the Shell: SAC_2045, and that it would premiere on April 23, 2020. The series is in 3DCG and Sola Digital Arts collaborated with Production I.G on the project. Ilya Kuvshinov handled character designs. The series had two seasons of 12 episodes each. In addition to the anime, a series of published books, two separate manga adaptations, and several video games for consoles and mobile phones have been released for Stand Alone Complex. ==== Arise OVA, TV series and film ==== In 2013, a new iteration of the series titled Ghost in the Shell: Arise premiered, taking an original look at the Ghost in the Shell world, set before the original manga. It was released as a series of four original video animation (OVA) episodes (with limited theatrical releases) from 2013 to 2014, then recompiled as a 10-episode television series under the title of Kōkaku Kidōtai: Arise - Alternative Architecture. An additional fifth OVA titled Pyrophoric Cult, originally premiering in the Alternative Architecture broadcast as two original episodes, was released on August 26, 2015. Kazuchika Kise served as the chief director of the series, with Tow Ubukata as head writer. Cornelius was brought onto the project to compose the score for the series, with the Major's new voice actress Maaya Sakamoto also providing vocals for certain tracks. Ghost in the Shell: The New Movie, also known as Ghost in the Shell: Arise − The Movie or New Ghost in the Shell, is a 2015 film directed by Kazuya Nomura that serves as a finale to the Ghost in the Shell: Arise story arc. The film is a continuation to the plot of the Pyrophoric Cult episode of Arise, and ties up loose ends from that arc. A manga adaptation was serialized in Kodansha's Young Magazine, which started on March 13 and ended on August 26, 2013. ==== 2026 anime ==== On May 25, 2024, it was announced that a new anime television series adaptation will be produced by Science Saru for a July 2026 premiere. Saru will be in a production committee with Bandai Namco Filmworks, Kodansha and Production I.G. The series will be directed by Monkochan, with a script by EnJoe Toh. === Video games === Ghost in the Shell was developed by Exact and released for the PlayStation on July 17, 1997, in Japan by Sony Computer Entertainment. It is a third-person shooter featuring an original storyline where the character plays a rookie member of Section 9. The video game's soundtrack Megatech Body features various techno artists, such as Takkyu Ishino, Scan X and Mijk Van Dijk. Several video games were also developed to tie into the Stand Alone Complex television series, in addition to a first-person shooter by Nexon and Neople titled Ghost in the Shell: Stand Alone Complex - First Assault Online,

  Read more →
• 

  A.I. Insight forums

  The Artificial Intelligence Insight forums, also known as the A.I. Insight forums, are a series of forums to build consensus on how the United States Congress should craft A.I. legislation. Organized by Senate Majority Leader Charles "Chuck" Schumer, the first of nine closed-door forums convened on September 13, 2023. == Background == Amid a surge in the popularity and advancement of artificial intelligence, senator Chuck Schumer launched an effort to establish a framework for the regulation of A.I. in April 2023. By the end of June, a preliminary framework – dubbed the "SAFE Innovation Framework" – was established and presented to Congress. Schumer also announced a series of forums wherein tech leaders who were well-acquainted with A.I. would help to "educate" Congress on the risks and problems that A.I. poses. Many tech leaders including Sam Altman, Elon Musk, and Sundar Pichai were set to attend the meetings. Many U.S. lawmakers and senators such as Mike Rounds and Todd Young were also set to attend. == September 13 forum == The overarching consensus following the conclusion of the September 13 forum was that there "should be" regulations regarding the use and advancement of A.I., but it should not be made "too fast". Many tech executives who attended the forum also warned senators of the risks and threats that A.I. could pose. Musk, who attended the forum, stated afterwards that there was "overwhelming consensus" on the regulation of A.I. === Invitees === This is a list of people who were invited to attend the September 13 forum. Elon Musk (Tesla, SpaceX, X Corp.) Sam Altman (OpenAI) Bill Gates (ex–Microsoft) Jensen Huang (Nvidia) Alex Karp (Palantir) Satya Nadella (Microsoft) Arvind Krishna (IBM) Sundar Pichai (Alphabet Inc., Google) Eric Schmidt (ex–Google) Mark Zuckerberg (Meta) Charles Rivkin (Motion Picture Association) Liz Shuler (AFL-CIO) Meredith Stiehm (Writers Guild of America) Randi Weingarten (American Federation of Teachers) Maya Wiley (LCCHR) == October 24 forum == The second of nine forums was hosted on October 24, 2023, as federal A.I. regulation drew nearer. According to Schumer's office, the forum was centered mainly on how A.I. could "enable innovation", and the innovation that is needed for the safe progression of A.I. At the forum, Senators Brian Schatz and John Kennedy introduced the "Schatz-Kennedy A.I. Labeling Act", a new piece of A.I. legislation that would provide "more transparency on A.I.-generated content". Following the forum, Senator Rounds stated that in order to fuel the development of A.I., a total estimated $56 billion would be needed for the next three years. Rounds, alongside Senator Young and Schumer, also highlighted the need to outcompete China and workforce initiatives. === Invitees === 21 people were invited to attend the forum, and were composed largely of venture capitalists, academics, civil rights campaigners, and industry figures. Some key figures included venture capitalists Marc Andreessen and John Doerr. == Future == Over the course of fall 2023, there is slated to be a total of nine forums on the topic of A.I., with the first hosted on September 13.

  Read more →
• 

  PerfKitBenchmarker

  PerfKit Benchmarker is an open source benchmarking tool used to measure and compare cloud offerings. PerfKit Benchmarker is licensed under the Apache 2 license terms. PerfKit Benchmarker is a community effort involving over 500 participants including researchers, academic institutions and companies together with the originator, Google. == General == PerfKit Benchmarker (PKB) is a community effort to deliver a repeatable, consistent, and open way of measuring Cloud Performance. It supports a growing list of cloud providers including: Alibaba Cloud, Amazon Web Services, CloudStack, DigitalOcean, Google Cloud Platform, Kubernetes, Microsoft Azure, OpenStack, Rackspace, IBM Bluemix (Softlayer). In addition to Cloud Providers to supports container orchestration including Kubernetes [1] and Mesos [2] and local "static" workstations and clusters of computers [3]. The goal is to create an open source living benchmark [framework] that represents how Cloud developers are building applications, evaluating Cloud alternatives, learning how to architect applications for each cloud. Living because it will change and morph quickly as developers change. PerfKit Benchmarker measures the end to end time to provision resources in the cloud, in addition to reporting on the most standard metrics of peak performance, e.g.: latency, throughput, time-to-complete, IOPS. PerfKit Benchmarker reduces the complexity in running benchmarks on supported cloud providers by unified and simple commands. It's designed to operate via vendor provided command line tools. PerfKit Benchmarker contains a canonical set of public benchmarks. All benchmarks are running with default/initial state and configuration (Not tuned to in favor of any providers). This provides a way to benchmark across cloud platforms, while getting a transparent view of application throughput, latency, variance, and overhead. == History == PerfKit Benchmarker (PKB) was started by Anthony F. Voellm, Alain Hamel, and Eric Hankland at Google in 2014. Once an initial "alpha" was in place Anthony F. Voellm and Ivan Santa Maria Filho built a community including ARM, Broadcom, Canonical, CenturyLink, Cisco, CloudHarmony, CloudSpectator, EcoCloud@EPFL, Intel, Mellanox, Microsoft, Qualcomm Technologies, Inc., Rackspace, Red Hat, Tradeworx Inc., and Thesys Technologies LLC. This community worked together behind the scenes in a private GitHub project to create an open way to measure cloud performance. This community released the first public "beta" was released on February 11, 2015, and announced in a blog post at which point the GitHub project was open to everyone. After almost a year and with large adaption (600+ participants on GitHub) the V1.0.0 was released along with a detailed architectural design on December 10, 2015. == Benchmarks == A list of available benchmarks from PerfKitBenchmarker: (The latest set of benchmarks can be found at GitHub readme file.) == Industry participants == Since Google open sourced the PerfKitBenchmarker, it became a community effort from over 30 leading researchers, academic schools and industry companies. Those organizations include: ARM, Broadcom, Canonical, CenturyLink, Cisco, CloudHarmony, Cloud Spectator, EcoCloud@EPFL, Intel, Mellanox, Microsoft, Qualcomm Technologies, Rackspace, Red Hat, and Thesys Technologies. In addition, Stanford and MIT are leading quarterly discussions on default benchmarks and settings proposed by the community. EcoCloud@EPFL is integrating CloudSuite into PerfKit Benchmarker. == Example runs == On Google Cloud Platform On AWS On Azure On Rackspace On a local machine

  Read more →
• 

  IJCAI Award for Research Excellence

  The IJCAI Award for Research Excellence is a biannual award before given at the IJCAI conference to researcher in artificial intelligence as a recognition of excellence of their career. Beginning in 2016, the conference is held annually and so is the award. == Laureates == The recipients of this award have been: John McCarthy (1985) Allen Newell (1989) Marvin Minsky (1991) Raymond Reiter (1993) Herbert A. Simon (1995) Aravind Joshi (1997) Judea Pearl (1999) Donald Michie (2001) Nils Nilsson (2003) Geoffrey E. Hinton (2005) Alan Bundy (2007) Victor R. Lesser (2009) Robert Kowalski (2011) Hector Levesque (2013) Barbara Grosz (2015) for her pioneering research in Natural Language Processing and in theories and applications of Multiagent Collaboration. Michael I. Jordan (2016) for his groundbreaking and impactful research in both the theory and application of statistical machine learning. Andrew Barto (2017) for his pioneering work in the theory of reinforcement learning. Jitendra Malik (2018) Yoav Shoham (2019) Eugene Freuder (2020) Richard S. Sutton (2021) Stuart J. Russell (2022) Sarit Kraus (2023) for her pioneering work of the study of interactions among self-interested agents, creating the field of automated negotiation, and developing methods for coalition formation and teamwork, both as formal models and real-world implementations. == Winners of also Turing Award == John McCarthy (1971) Allen Newell (1975) Marvin Minsky (1969) Herbert A. Simon (1975) Judea Pearl (2011) Geoffrey Hinton (2018) Andrew Barto (2024) Richard S. Sutton (2024)

  Read more →
• 

  Death of Elaine Herzberg

  The death of Elaine Herzberg (August 2, 1968 – March 18, 2018) was the first recorded case of a pedestrian fatality involving a self-driving car, after a collision that occurred late in the evening of March 18, 2018. Herzberg was pushing a bicycle across a four-lane road in Tempe, Arizona, United States, when she was struck by an Uber test vehicle, which was operating in self-drive mode with a human safety backup driver sitting in the driving seat. Herzberg was taken to the local hospital where she died of her injuries. Following the fatal incident, the National Transportation Safety Board (NTSB) issued a series of recommendations and sharply criticized Uber. The company suspended testing of self-driving vehicles in Arizona, where such testing had been approved since August 2016. Uber chose not to renew its permit for testing self-driving vehicles in California when it expired at the end of March 2018. Uber resumed testing in December 2018, starting in Pittsburgh, Pennsylvania. In March 2019, Arizona prosecutors ruled that Uber was not criminally responsible for the crash. The back-up driver of the vehicle was charged with negligent homicide, pled guilty to endangerment, and was sentenced to three years' probation. While Herzberg was the first pedestrian killed by a self-driving car, driver Gao Yaning died in a Tesla semi-autonomous car two years earlier. A reporter for The Washington Post compared Herzberg's fate with that of Bridget Driscoll who, in the United Kingdom in 1896, was the first pedestrian to be killed by an automobile. The Arizona incident has magnified the importance of collision avoidance systems for self-driving vehicles. == Collision summary == Herzberg was crossing Mill Avenue (North) from west to east, approximately 360 feet (110 m) south of the intersection with Curry Road, outside the designated pedestrian crosswalk, close to the Red Mountain Freeway. She was pushing a bicycle laden with shopping bags, and had crossed at least two lanes of traffic when she was struck at approximately 9:58 pm MST (UTC−07:00) by a prototype Uber self-driving car based on a Volvo XC90, which was traveling north on Mill. The vehicle had been operating in autonomous mode since 9:39 pm, nineteen minutes before it struck and killed Herzberg. The car's human safety backup driver, Rafaela Vasquez, did not intervene in time to prevent the collision. Vehicle telemetry obtained after the crash showed that the human operator responded by moving the steering wheel less than a second before impact, and she engaged the brakes less than a second after impact. == Cause investigation == The county district attorney's office recused itself from the investigation, due to a prior joint partnership with Uber promoting their services as an alternative to driving under the influence of alcohol. Accounts differ on the speed limit at the place of the incident. According to Tempe police the car was traveling in a 35 mph (56 km/h) zone, but this is contradicted by a posted speed limit of 45 mph (72 km/h). The National Transportation Safety Board (NTSB) sent a team of federal investigators to gather data from vehicle instruments, and to examine vehicle condition along with the actions taken by the safety driver. Their preliminary findings were substantiated by multiple event data recorders and proved the vehicle was traveling 43 miles per hour (69 km/h) when Herzberg was first detected 6 seconds (378 feet (115 m)) before impact; during 4.7 seconds the self driving system did not infer that emergency braking was needed. A vehicle traveling 43 mph (69 km/h) can generally stop within 89 feet (27 m) once the brakes are applied. The machine needed to be 1.3 seconds (82 feet (25 m)) away prior to discerning that emergency braking was required, whereas at least that much distance was required to stop. The system failed to behave properly. A total stopping distance of 76 feet itself would imply a safe speed under 25 mph (40 km/h). Human intervention was still legally required. Computer perception–reaction time would have been a speed limiting factor had the technology been superior to humans in ambiguous situations; however, the nascent computerized braking technology was disabled the day of the crash, and the machine's apparent 4.7-second perception–reaction (alarm) time allowed the car to travel 250 feet (76 m). Video released by the police on March 21 showed the safety driver was not watching the road moments before the vehicle struck Herzberg. === Environment === In widely disseminated remarks that would shape the narrative about the crash, which were later seen as prejudicial and subsequently contradicted by her own department, Tempe Police Chief Sylvia Moir was quoted stating that the collision was "unavoidable" based on the initial police investigation, which included a review of the video captured by an onboard camera. Moir faulted Herzberg for crossing the road in an unsafe manner: "It is dangerous to cross roadways in the evening hour when well-illuminated, managed crosswalks are available." According to Uber, safety drivers were trained to keep their hands very close to the wheel all the time while driving the vehicle so they were ready to quickly take control if necessary. The driver said it was like a flash, the person walked out in front of them. His [sic] first alert to the collision was the sound of the collision. [...] it's very clear it would have been difficult to avoid this collision in any kind of mode (autonomous or human-driven) based on how she came from the shadows right into the roadway. Tempe police released video on March 21, 2018, showing footage recorded by two onboard cameras: one forward-looking, and one capturing the safety driver's actions. The forward-facing video shows that the self-driving car was traveling in the far right lane when it struck Herzberg. The driver-facing video shows the safety driver was looking down prior to the collision. The Uber operator is responsible for intervening and taking manual control when necessary as well as for monitoring diagnostic messages, which are displayed on a screen in the center console. In an interview conducted after the crash with NTSB, the driver stated she was monitoring the center stack at the time of the collision. After the Uber video was released, journalist Carolyn Said noted the police explanation of Herzberg's path meant she had already crossed two lanes of traffic before she was struck by the autonomous vehicle. The Marquee Theatre and Tempe Town Lake are west of Mill Avenue, and pedestrians commonly cross mid-street without detouring north to the crosswalk at Curry. According to reporting by the Phoenix New Times, Mill Avenue contains what appears to be a brick-paved path in the median between the northbound and southbound lanes; however, posted signs prohibit pedestrians from crossing in that location. When the second of the Mill Avenue bridges over the town lake was added in 1994 for northbound traffic, the X-shaped crossover in the median was installed to accommodate the potential closing of one of the two road bridges. The purpose of this brick-paved structure is purely to divert cars from one side to the other if a bridge is closed to traffic, and although it may look like a crosswalk for pedestrians, it is in fact a temporary roadway with vertical curbs and warning signs. === Software issues === Michael Ramsey, a self-driving car expert with Gartner, characterized the video as showing "a complete failure of the system to recognize an obviously seen person who is visible for quite some distance in the frame. Uber has some serious explaining to do about why this person wasn't seen and why the system didn't engage." The NTSB preliminary report, however, noted that the software did order the car to brake 1.3 seconds before the collision. A video shot from the vehicle's dashboard camera showed the safety driver looking down, away from the road. It also appeared that the driver's hands were not hovering above the steering wheel, which is what drivers are instructed to do so they can quickly retake control of the car. Uber had moved from two employees in every car to one. The paired employees had been splitting duties: one ready to take over if the autonomous system failed, and another to keep an eye on what the computers were detecting. The second person was responsible for keeping track of system performance as well as labeling data on a laptop computer. Mr. Kallman, the Uber spokesman, said the second person was in the car for purely data related tasks, not safety. When Uber moved to a single operator, some employees expressed safety concerns to managers, according to the two people familiar with Uber's operations. They were worried that going solo would make it harder to remain alert during hours of monotonous driving. The recorded telemetry showed the system had detected Herzberg six seconds before the crash, and classified her first as an unknown object, then as a

  Read more →
• 

  The Sword in the Stoned

  "The Sword in the Stoned" is the fifth episode of the second season of the American fantasy comedy television series Ted. Written by Julius Sharpe, and directed by Seth MacFarlane, it premiered on the American streaming service Peacock, along with the rest of season two, on March 5, 2026. The series acts as a precursor to the Ted film franchise, showcasing the childhood lives of the protagonists. The series, set in 1994, focuses on John Bennett (Max Burkholder), the series' primary protagonist, an awkward high-school aged boy; along with Ted (MacFarlane), the series' titular anthropomorphic teddy bear. The two live with John's family, Susan (Alanna Ubach), his mild mannered mother, and Matty (Scott Grimes), his conservative father. Also residing with the family is Blaire (Giorgia Whigham), his radically liberal cousin whom often clashes with Matty. In the episode, Ted and John join the school play so they can have more extracurricular activities for their college applications, but the latter grows a connection with the school's popular teenager, Erin (Francesca Xuereb). Concurrently, Susan and Matty get a job at Dunkin' Donuts to help with their financial troubles, and Matty is given an opportunity to tell off Bill Clinton. Burkholder wore prop armor during the episode's play scenes. Bill Clinton’s appearance in the episode was portrayed by MacFarlane. After conventional makeup and visual techniques failed to convincingly resemble Clinton, the production used artificial intelligence to digitally replace MacFarlane's face with Clinton's likeness. Upon release, the episode received generally positive reviews from critics, though the use of AI in the Clinton scene was polarizing among audiences and reviewers. == Plot == John tells Ted that he is the last single guy left at their school, to which Ted points out the popular, single cheerleader, Erin, but John dismisses this. At home, Blaire tells John that he needs extracurricular activities to get into college, while Susan and Matty discuss their financial troubles, especially regarding John's college tuition. Looking over their options, they decide to audition for a school production of the play Camelot. Matty takes a job at Dunkin' Donuts, despite being told that nobody will give him a tip, and having to wear an incorrect name tag. Waiting for their auditions, John and Ted watch several poor auditions for the play before seeing Erin's, who delivers a flawless performance; John and Ted do less serious auditions, getting cast as knights, while Erin gets the role of Guinevere. Matty complains about his low salary, and Susan decides to get a job at Dunkin' Donuts beside him to help earn more income. Erin clashes with Lancelot's actor while rehearsing, and John compliments her performance, which she ignores, but, seeing Ted and John give good performances in a repetition exercise, she becomes interested in him, particularly since he treats her better than her stage-partner. Matty and Susan watch an employee training video, explaining how they should treat customers politely, not affecting Matty's nihilistic attitude. The manager announces that Bill Clinton is visiting their Dunkin' Donuts for publicity, and Matty sees this as a chance to tell Bill off. John and Erin practice lines, as she reveals the show is being taped so it can be sent to Emerson College in hopes of her getting in; Erin asks John to go out with her after the show. At dinner, Matty enthusiastically reveals what he plans to tell Bill, as John becomes stressed about the play when Susan tells there will be a large audience. Bill comes to the Dunkin' Donuts, and, seeing Matty is nervously insulting him, stages a private meeting with him, where Bill yells at Matty, calling him a loser before posing for a picture with Matty and subsequently throwing the cold coffee onto him. To ease the pressure, Ted and John take edibles from Blaire, but learn at the show that they contained mushrooms, causing them to stress further. On stage, Ted and John yell nervously that they're on drugs as the latter urinates in his costume, causing Erin to angrily storm off. == Production == "The Sword in the Stoned" was directed by series creator and lead Seth MacFarlane, and written by Julius Sharpe in his third and final writing credit for the series. When Ted and John are doing repetition exercises, they tackle each other to the ground, which required a stuntman named Ashton to play the role of Ted, according to Max Burkholder, who portrays John. Burkholder also recalled that, when Ted was choking John in the scene, he kept making a noise during the choking, which made Bill, the cameraman, laugh, despite being a "stone face" that never laughs, noting that seeing him be amused by the noise he was making assured Burkholder that what he was doing was "hilarious". Burkholder found the filming of the play scenes "weird", as he was put in fake armor with a hose inside his suit—which was filled with water mixed with yellow food coloring—that was made to create the urine stream that comes out of John's armor in the episode; he also noted that it took around 45 minutes to put on and take off the armor. He revealed that he himself had to urinate during the filming, as doing a scene about a character having to do so "really [broke] my brain", with the fact that it took 45 minutes to get the suit off adding to the frustration. Jennifer Ashley Connell, who worked for wardrobe, had to repeatedly go to Burkholder quickly between takes to dry off his pants with two hair dryers to make it look like the fake urine hadn't already streamed down his pants, so they could get as many shots of it as possible. Francesca Xuereb guest stars in the episode as Erin, the cheerleader who stars in the play. Incumbent president Bill Clinton was portrayed by MacFarlane, with artificial intelligence (AI) being used to digitally make MacFarlane's face look like Clinton's during post-production. Before settling on AI, the crew tried to use traditional computer-generated imagery and prosthetics, which made him look "terrifying", resulting in them deciding that AI would give them a more accurate look. One of the original technologies considered was one where, after scanning MacFarlane, a mesh of his head was created, and they had to use computer graphics to replace MacFarlane's face with Clinton's. An issue was faced, however, when they found the archival footage used as reference from the Clinton Library—an official Presidential Library containing information related to Clinton—to be extremely low-quality, making it hard to properly emulate his face, since only still images were of acceptable quality, and there weren't references of his moving face to work off of. A forensic artist was hired to help with this, and they created a 3D model of Clinton's head in ZBrush, based off of his presidential portrait. The model head worked for still frames, but movement was still difficult to do realistically, due to it being made for a "single-point perspective", which made details like the cheekbones or other minor issues more noticeable when using it for the scene. Since this did not work, AI was ultimately chosen through the studio Deep Voodoo, which used large language models to teach the tool how to correctly replicate Clinton's appearance. Defending the episode's use of AI, MacFarlane noted that the crew did not want people to focus on the tool being used, trying to utilize it in a way that wouldn't distract from the humor and narrative. Like the rest of the series, the episode was shot using ViewScreen; MacFarlane was able to act live with the cast as Ted due to ViewScreen, a technology that allows the production crew to visualize what Ted will look like in each scene in real time. == Release and reception == "The Sword in the Stoned" was first released on March 5, 2026, on the American streaming service Peacock, along with the rest of the second season. Nate Richards of Collider highlighted the Dunkin' Donuts subplot as an example of Scott Grimes delivering a "lot of laughs" through his performance as Matty. Dustin Rowles of Pajiba called "The Sword in the Stoned" one of the season's many episodes he'd recommend, particularly for the scenes of Ted and John being high on mushrooms during the play. Oppositely, Nick Valdez of ComicBook.com ranked the episode as the worst of the second season, criticizing it for not having a "huge impact" on the Bennett family dynamic like other episodes of the season do, and Susan and Matty's side story as the main reason he felt it was "[kept] from being great". Valdez noted the episode for likely being an advertisement for Dunkin' Donuts, calling the plot's ending scene involving Clinton the reason "it just all sticks out like a sore thumb". === Response to AI usage === The episode's use of AI for MacFarlane's portrayal of Clinton proved controversial, mainly on social media, where audiences asserted that the crew should have gotten an actor that resembl

  Read more →
• 

  Wavelet noise

  Wavelet noise is an alternative to Perlin noise which reduces the problems of aliasing and detail loss that are encountered when Perlin noise is summed into a fractal. == Algorithm detail == The basic algorithm for 2-dimensional wavelet noise is as follows: Create an image, R {\displaystyle R} , filled with uniform white noise. Downsample R {\displaystyle R} to half-size to create R ↓ {\displaystyle R^{\downarrow }} , then upsample it back up to full size to create R ↓↑ {\displaystyle R^{\downarrow \uparrow }} . Subtract R ↓↑ {\displaystyle R^{\downarrow \uparrow }} from R {\displaystyle R} to create the end result, N {\displaystyle N} . This results in an image that contains all the information that cannot be represented at half-scale. From here, N {\displaystyle N} can be used similarly to Perlin noise to create fractal patterns.

  Read more →
• 

  Mobile Fortify

  Mobile Fortify is a mobile app used by United States Immigration and Customs Enforcement (ICE) on their government-issued phones. The app allows agents to take a photo in order to gather biometrics, including contactless fingerprints and faceprints, for the purpose of identifying an individual and their potential immigration status. The app was created by NEC. == History == In June 2025, use of Mobile Fortify by ICE was uncovered through leaked emails and the user manual, reported by 404 Media. The app is internally developed, and details of the parent company and developer were initially unknown. In January 2026, the DHS's 2025 AI Use Case Inventory revealed the vendor as NEC Corporation, an international conglomerate with subsidiaries in Argentina, Australia, China, India and Malaysia. Later that month, several senators demanded transparency around the app and its origins, and that ICE stop using it. A second letter was sent again in November, after hearing no response to the previous letter from ICE. == Technology == Unlike other facial recognition software, Fortify uses federally linked databases. By contrast, Clearview AI uses public social media databases for biometric scanning. Federal databases include DHS's automated biometric identification system (IDENT), containing more than 270 million biometric records, and Customs and Border Protection's Traveler Verification Service. The State Department's visa and passport photo database, the FBI's National Crime Information Center, National Law Enforcement Telecommunications Systems, and CBP's TECS and Seized Assets and Case Tracing System (SEACATS). == Oversight == Several senators urged ICE to stop using the app for fear of infringing on fourth amendment and first amendment rights, and requested details on who developed the app, when it was deployed, whether the app was tested for accuracy, and policies and practices governing its use. In June 2025, they sent an open letter to Todd Lyons, ICE acting director, signed by senators Cory Booker, Chris Van Hollen, Ed Markey, Bernie Sanders, Adam Schiff, Tina Smith, Elizabeth Warren, and Ron Wyden. On November 3, a second letter was sent to the ICE by senators, after not receiving answers to questions from the previous letter deadlined for October 2. == Criticism == Mobile Fortify, and ICE's use of similar biometric identification technologies (such as Mobile Identify, an app similar to Mobile Fortify to be used by local or regional law enforcement to assist in immigration enforcement ) has faced scrutiny from a variety of digital rights organizations, politicians, and news outlets. The criticism is already considered to potentially be a reason why the similar Mobile Identify app was pulled from the Google Play Store. Facial recognition technologies are known to produce false-positives and generally unreliable results, especially on those with darker skin tones. ICE has already previously mistakenly arrested a U.S. citizen under the belief he was illegally in the country, and later stated that he "could be deported based on biometric confirmation of his identity" prior to his release. U.S. representative Bennie Thompson, ranking member of the House Homeland Security Committee has previously commented that "ICE officials have told us that an apparent biometric match by Mobile Fortify is a ‘definitive’ determination of a person's status and that an ICE officer may ignore evidence of American citizenship—including a birth certificate—if the app says the person is an alien," and that "Mobile Fortify is a dangerous tool in the hands of ICE, and it puts American citizens at risk of detention and even deportation," On January 19, 2026, 404 Media reported on a case where a woman, identified in court documents as "MJMA", was scanned by Mobile Fortify twice in the same interaction, and two entirely different names were provided by the app. According to the Innovation Law Lab, whose attorneys are representing MJMA, both of the names were incorrect. ICE has stated that they will not allow people to decline to be scanned by Mobile Fortify, and that photos taken, even those of U.S. citizens, will be stored for 15 years, something that has been criticized primarily because ICE has not performed a Privacy Impact Assessment (PIA) for Mobile Fortify, the right to decline other forms of biometric verification to the U.S. government is often available under other circumstances, and the 15 year window is viewed as unnecessarily large.

  Read more →
• 

  Vagueness

  In linguistics and philosophy, a vague predicate is one which gives rise to borderline cases. For example, the English adjective "tall" is vague since it is not clearly true or false for someone of middling height. By contrast, the word "prime" is not vague since every number is definitively either prime or not. Vagueness is commonly diagnosed by a predicate's ability to give rise to the sorites paradox. Vagueness is separate from ambiguity, in which an expression has multiple denotations. For instance the word "bank" is ambiguous since it can refer either to a river bank or to a financial institution, but there are no borderline cases between both interpretations. Vagueness is a major topic of research in philosophical logic, where it serves as a potential challenge to classical logic. Work in formal semantics has sought to provide a compositional semantics for vague expressions in natural language. Work in philosophy of language has addressed implications of vagueness for the theory of meaning, while metaphysicists have considered whether reality itself is vague. == Importance == The concept of vagueness has philosophical importance. Suppose one wants to come up with a definition of "right" in the moral sense. One wants a definition to cover actions that are clearly right and exclude actions that are clearly wrong, but what does one do with the borderline cases? Surely, there are such cases. Some philosophers say that one should try to come up with a definition that is itself unclear on just those cases. Others say that one has an interest in making his or her definitions more precise than ordinary language, or his or her ordinary concepts, themselves allow; they recommend one advances precising definitions. === In law === Vagueness is also a problem which arises in law, and in some cases, judges have to arbitrate regarding whether a borderline case does, or does not, satisfy a given vague concept. Examples include disability (how much loss of vision is required before one is legally blind?), human life (at what point from conception to birth is one a legal human being, protected for instance by laws against murder?), adulthood (most familiarly reflected in legal ages for driving, drinking, voting, consensual sex, etc.), race (how to classify someone of mixed racial heritage), etc. Even such apparently unambiguous concepts such as biological sex can be subject to vagueness problems, not just from transsexuals' gender transitions but also from certain genetic conditions which can give an individual mixed male and female biological traits (see intersex). In the common law system, vagueness is a possible legal defence against by-laws and other regulations. The legal principle is that delegated power cannot be used more broadly than the delegator intended. Therefore, a regulation may not be so vague as to regulate areas beyond what the law allows. Any such regulation would be "void for vagueness" and unenforceable. This principle is sometimes used to strike down municipal by-laws that forbid "explicit" or "objectionable" contents from being sold in a certain city; courts often find such expressions to be too vague, giving municipal inspectors discretion beyond what the law allows. In the US this is known as the vagueness doctrine and in Europe as the principle of legal certainty. === In science === Many scientific concepts are of necessity vague, for instance species in biology cannot be precisely defined, owing to unclear cases such as ring species. Nonetheless, the concept of species can be clearly applied in the vast majority of cases. As this example illustrates, to say that a definition is "vague" is not necessarily a criticism. Consider those animals in Alaska that are the result of breeding huskies and wolves: are they dogs? It is not clear: they are borderline cases of dogs. This means one's ordinary concept of doghood is not clear enough to let us rule conclusively in this case. == Approaches == The philosophical question of what the best theoretical treatment of vagueness is—which is closely related to the problem of the paradox of the heap, a.k.a. sorites paradox—has been the subject of much philosophical debate. === Fuzzy logic === One theoretical approach is that of fuzzy logic, developed by American mathematician Lotfi Zadeh. Fuzzy logic proposes a gradual transition between "perfect falsity", for example, the statement "Bill Clinton is bald", to "perfect truth", for, say, "Patrick Stewart is bald". In ordinary logics, there are only two truth-values: "true" and "false". The fuzzy perspective differs by introducing an infinite number of truth-values along a spectrum between perfect truth and perfect falsity. Perfect truth may be represented by "1", and perfect falsity by "0". Borderline cases are thought of as having a "truth-value" anywhere between 0 and 1 (for example, 0.6). Advocates of the fuzzy logic approach have included K. F. Machina (1976) and Dorothy Edgington (1993). === Supervaluationism === Another theoretical approach is known as "supervaluationism". This approach has been defended by Kit Fine and Rosanna Keefe. Fine argues that borderline applications of vague predicates are neither true nor false, but rather are instances of "truth value gaps". He defends an interesting and sophisticated system of vague semantics, based on the notion that a vague predicate might be "made precise" in many alternative ways. This system has the consequence that borderline cases of vague terms yield statements that are neither true, nor false. Given a supervaluationist semantics, one can define the predicate "supertrue" as meaning "true on all precisifications". This predicate will not change the semantics of atomic statements (e.g. "Frank is bald", where Frank is a borderline case of baldness), but does have consequences for logically complex statements. In particular, the tautologies of sentential logic, such as "Frank is bald or Frank is not bald", will turn out to be supertrue, since on any precisification of baldness, either "Frank is bald" or "Frank is not bald" will be true. Since the presence of borderline cases seems to threaten principles like this one (excluded middle), the fact that supervaluationism can "rescue" them is seen as a virtue. === Subvaluationism === Subvaluationism is the logical dual of supervaluationism, and has been defended by Dominic Hyde (2008) and Pablo Cobreros (2011). Whereas the supervaluationist characterises truth as 'supertruth', the subvaluationist characterises truth as 'subtruth', or "true on at least some precisifications". Subvaluationism proposes that borderline applications of vague terms are both true and false. It thus has "truth-value gluts". According to this theory, a vague statement is true if it is true on at least one precisification and false if it is false under at least one precisification. If a vague statement comes out true under one precisification and false under another, it is both true and false. Subvaluationism ultimately amounts to the claim that vagueness is a truly contradictory phenomenon. Of a borderline case of "bald man" it would be both true and false to say that he is bald, and both true and false to say that he is not bald. === Epistemicist view === A fourth approach, known as "the epistemicist view", has been defended by Timothy Williamson (1994), R. A. Sorensen (1988) and (2001), and Nicholas Rescher (2009). They maintain that vague predicates do, in fact, draw sharp boundaries, but that one cannot know where these boundaries lie. One's confusion about whether some vague word does or does not apply in a borderline case is due to one's ignorance. For example, in the epistemicist view, there is a fact of the matter, for every person, about whether that person is old or not old; some people are ignorant of this fact. === As a property of objects === One possibility is that one's words and concepts are perfectly precise, but that objects themselves are vague. Consider Peter Unger's example of a cloud (from his famous 1980 paper, "The Problem of the Many"): it is not clear where the boundary of a cloud lies; for any given bit of water vapor, one can ask whether it is part of the cloud or not, and for many such bits, one will not know how to answer. Hence, perhaps such a term as 'cloud' is not itself vague, but rather precisely denotes a vague object. This strategy has occasionally been poorly received; most notably, in Gareth Evans' short paper "Can There Be Vague Objects?" (1978), wherein an argument is examined which appears to show that vague identity-statements are impossible (i.e., result in logical incoherence). David Lewis explains that the reader is intended to conclude, with Evans, that—since there clearly are, in fact, meaningful vague identities—any purported proof to the contrary cannot be right; and as the proof relies upon the premise that vague terms precisely denote vague objects, but fails under the view that vague terms reflect a merel

  Read more →