AIXI

AIXI

AIXI is a theoretical mathematical formalism for artificial general intelligence. It combines Solomonoff induction with sequential decision theory. AIXI was first proposed by Marcus Hutter in 2000 and several results regarding AIXI are proved in Hutter's 2005 book Universal Artificial Intelligence. AIXI is a reinforcement learning (RL) agent. It maximizes the expected total rewards received from the environment. Intuitively, it simultaneously considers every computable hypothesis (or environment). In each time step, it looks at every possible program and evaluates how many rewards that program generates depending on the next action taken. The promised rewards are then weighted by the subjective belief that this program constitutes the true environment. This belief is computed from the length of the program: longer programs are considered less likely, in line with Occam's razor. AIXI then selects the action that has the highest expected total reward in the weighted sum of all these programs. == Etymology == According to Hutter, the word "AIXI" can have several interpretations. AIXI can stand for AI based on Solomonoff's distribution, denoted by ξ {\displaystyle \xi } (which is the Greek letter xi), or e.g. it can stand for AI "crossed" (X) with induction (I). There are other interpretations. == Definition == AIXI is a reinforcement learning agent that interacts with some stochastic and unknown but computable environment μ {\displaystyle \mu } . The interaction proceeds in time steps, from t = 1 {\displaystyle t=1} to t = m {\displaystyle t=m} , where m ∈ N {\displaystyle m\in \mathbb {N} } is the lifespan of the AIXI agent. At time step t, the agent chooses an action a t ∈ A {\displaystyle a_{t}\in {\mathcal {A}}} (e.g. a limb movement) and executes it in the environment, and the environment responds with a "percept" e t ∈ E = O × R {\displaystyle e_{t}\in {\mathcal {E}}={\mathcal {O}}\times \mathbb {R} } , which consists of an "observation" o t ∈ O {\displaystyle o_{t}\in {\mathcal {O}}} (e.g., a camera image) and a reward r t ∈ R {\displaystyle r_{t}\in \mathbb {R} } , distributed according to the conditional probability μ ( o t r t | a 1 o 1 r 1 . . . a t − 1 o t − 1 r t − 1 a t ) {\displaystyle \mu (o_{t}r_{t}|a_{1}o_{1}r_{1}...a_{t-1}o_{t-1}r_{t-1}a_{t})} , where a 1 o 1 r 1 . . . a t − 1 o t − 1 r t − 1 a t {\displaystyle a_{1}o_{1}r_{1}...a_{t-1}o_{t-1}r_{t-1}a_{t}} is the "history" of actions, observations and rewards. The environment μ {\displaystyle \mu } is thus mathematically represented as a probability distribution over "percepts" (observations and rewards) which depend on the full history, so there is no Markov assumption (as opposed to other RL algorithms). Note again that this probability distribution is unknown to the AIXI agent. Furthermore, note again that μ {\displaystyle \mu } is computable, that is, the observations and rewards received by the agent from the environment μ {\displaystyle \mu } can be computed by some program (which runs on a Turing machine), given the past actions of the AIXI agent. The only goal of the AIXI agent is to maximize ∑ t = 1 m r t {\displaystyle \sum _{t=1}^{m}r_{t}} , that is, the sum of rewards from time step 1 to m. The AIXI agent is associated with a stochastic policy π : ( A × E ) ∗ → A {\displaystyle \pi :({\mathcal {A}}\times {\mathcal {E}})^{}\rightarrow {\mathcal {A}}} , which is the function it uses to choose actions at every time step, where A {\displaystyle {\mathcal {A}}} is the space of all possible actions that AIXI can take and E {\displaystyle {\mathcal {E}}} is the space of all possible "percepts" that can be produced by the environment. The environment (or probability distribution) μ {\displaystyle \mu } can also be thought of as a stochastic policy (which is a function): μ : ( A × E ) ∗ × A → E {\displaystyle \mu :({\mathcal {A}}\times {\mathcal {E}})^{}\times {\mathcal {A}}\rightarrow {\mathcal {E}}} , where the ∗ {\displaystyle } is the Kleene star operation. In general, at time step t {\displaystyle t} (which ranges from 1 to m), AIXI, having previously executed actions a 1 … a t − 1 {\displaystyle a_{1}\dots a_{t-1}} (which is often abbreviated in the literature as a < t {\displaystyle a_{

Summify

Summify was a social news aggregator founded by Mircea Paşoi and Cristian Strat, two former Google and Microsoft interns from Romania. The service emailed its users a periodic summary of news articles shared from their social networks based on their relevance and importance. The platform supported Twitter, Facebook, and Google Reader accounts. == History == In 2009, Paşoi and Strat created ReadFu, a plugin that provided a contextual summary and statistics of the target page of a hyperlink. In January 2010, ReadFu was accepted into the Vancouver-based start-up incubator Bootup Labs. On March 20, 2010 the service was renamed to Summify and a private beta began. On August 11, 2010 Paşoi and Strat announced a new direction for the service. It would become a real-time social news reader that aggregates incoming news from social networks and displays articles by importance using social reactions. After some feedback that the users preferred article digests by email more than the real-time news reader version, Summify discontinued the news reader version. In March 2011, Summify completed a Seed round, with investors including Rob Glaser, Accel Partners, and Stewart Butterfield. Summify received coverage from various news and media outlets such as TechCrunch. It was also featured in various news platforms, such as Time, The Globe and Mail, Mashable, VentureBeat, Gizmodo, Lifehacker, and The Next Web. Summify released a free app on the Apple App Store on July 8, 2011. The app allowed users to read their web summaries from iOS mobile devices. Summify was acquired by Twitter on January 19, 2012. The service shut down soon after, on June 22, 2012.

Computer-assisted legal research

Computer-assisted legal research (CALR) or computer-based legal research is a mode of legal research that uses databases of court opinions, statutes, court documents, and secondary material. Electronic databases make large bodies of case law easily available. Databases also have additional benefits, such as Boolean searches, evaluating case authority, organizing cases by topic, and providing links to cited material. Databases are available through paid subscription or for free. Subscription-based services include Westlaw, LexisNexis, JustCite, HeinOnline, Bloomberg Law, Lex Intell, VLex and LexEur. As of 2015, the commercial market grossed $8 billion. Free services include OpenJurist, Google Scholar, AltLaw, Ravel Law, WIPO Lex, Law Delta and the databases of the Free Access to Law Movement. == Purposes == Computer-assisted legal research is undertaken by a variety of actors. It is taught as a topic in many law degrees and is used extensively by undergraduate and postgraduate law students in meeting the work requirements of their degree courses. Professors of Law rely on the digitization of primary and secondary sources of law when conducting their research and writing the material that they submit for publication. Professional lawyers rely on computer-assisted legal research in order to properly understand the status of the law and so to act effectively in the best interest of their client. They may also consult the text of case judgements and statutes specifically, as well as wider academic comment, in order to form the basis of (or response to) an appeal. The availability of legal information online differs by type, jurisdiction and subject matter. The types of information available include: Texts of statutes, statutory instruments, civil codes, etc. Explanatory notes and government publications relating to statutes and their operation Texts of governing documents such as constitutions and treaties Case judgements Journals on legal matters or legal theory Dictionaries and legal encyclopedia Legal texts and materials in the form of e-books Current affairs and market information Educational information on the law and its operation == Before the Internet == Prior to the advent and popularization of the World Wide Web, access to digital legal information was largely through the use of CD-ROMs, designed and sold by commercial organizations. Dial-up services were also available from the 1970s. As the use of the Internet spread in the early 1990s, companies such as LexisNexis and Westlaw incorporated Internet connectivity into their software packages. Browser-based legal information started to be published by Legal Information Institutes from 1992. == Publicly available information == The first effort to provide free computer access to legal information was made by two academics, Peter Martin and Tom Bruce, in 1992. Today, the Legal Information Institute freely publishes such resources as the text of the United States Constitution, judgements of the United States Supreme Court, and the text of the United States Code. The Australasian Legal Information Institute (AusLII) was established soon after in 1995. Other legal information institutes, such as those of Great Britain and Ireland (BAILII), Canada (CII) and South Africa (SAfLI) soon followed. LIIs were partially formalized in 2002 following the signing of the Declaration of Free Access to the Law, which has been signed by 54 countries. At the time of writing, the World Legal Information Institute contains in excess of 1800 databases from 123 jurisdictions. Many governments also publish legal information online. For example, UK legislation and statutory instruments have been publicly available online since 2010. Depending on the jurisdiction in question, the decisions of higher appellate courts may also be published online, either by the Legal Information Institute or by the court service directly. Sources of European Union Law are published for free by EUR-Lex in 23 languages, including judgments of the European Courts. Similarly, judgements of the European Court of Human Rights are published on its website.

Take Us to Your Chief: and Other Stories

Take Us to Your Chief: and Other Stories is a collection of nine short stories by Canadian author, playwright, and journalist Drew Hayden Taylor published in 2016 by Douglas & McIntyre. Taylor, who is part Caucasian, part Ojibwe, explains in the acknowledgments section of the book that the origin of the project lies in several failed attempts "to compile an anthology of Native sci-fi from Canada’s best First Nations writers." The stories explore contemporary First Nations social issues through employing a number of 1950s-era science fiction tropes and themes in these stories, including time travel, alien contact, and superpowers. Many reviews of the books have noted Taylor's use of humor to examine dark subject matter, such as the heritage of Canadian Indian residential schools, First Nations suicide rates, or the water quality crisis on Canadian reserves. == The Stories == "Andrei nas" "I Am...Am I" "Lost in Space" "Dreams of Doom" "Mr. Gizmo" "Petropaths" "Stars" "Superdisappointed" "Take Us to Your Chief" == Story summaries == === Foreword === In his foreword, Taylor describes the genesis of Take Us to Your Chief: and Other Stories and invites readers into, in his term, a “new terra nullius.” He begins by describing his biracial upbringing and heritage. He points out that First Nations people are rarely associated with technology or science fiction, in part because Indigenous peoples were often at a technological disadvantage against European colonizers. He references the few examples that he can think of from popular culture, such as the Star Trek episode called “The Paradise Syndrome,” in which First Nations people are portrayed as stereotypical Indians in hippie clothing. He also elaborates on his fascination with the world of sci-fi, which first started in comic books. He enjoyed the literary work of H.G. Wells, such as The Time Machine and The Invisible Man. Since sci-fi is a world of endless opportunities, he intends that these short stories help people explore science fiction through Native peoples’ minds, something that needs to be explored more thoroughly. === "A Culturally Inappropriate Armageddon" === “A Culturally Inappropriate Armageddon” is set on a Haudenosaunee reserve, towards the end of the Oka Crisis, with a handful of people that work at its first ever radio station, C-RES, which opens in 1991. Part 1, titled “C-Res Is on the Air,” depicts Emily, Aaron, and Tracey on their first days at the station. Within the group, there is a constant debate between broadcasting popular programming, including science fiction and film reviews, and culturally-relevant programming meant to aid in cultural revitalization efforts. One night, Aaron is late to work but once he shows up he can't stop talking about radio transmissions broadcasting into deep space, an event that has been occurring since the initial discovery of the radio waves by Heinrich Hertz. The story then skips ahead seven years to 1998, when Emily is struggling to find better content for her station until Tracey stumbles upon an old anthropological record named “The Calling Song” that they decide to broadcast to their audience. The story then jumps to the year 2018 where they are all huddled around a television watching a news station reporting that extraterrestrial life is heading towards them. The discussion of what is going to happen comes into the picture and they all decide it would either be like Contact or The Day the Earth Stood Still. A year later in 2019, the aliens have invaded the planet and destroyed everything. As the three former radio station employees suffer from radioactive fallout, they realize that the aliens received the broadcast of “The Calling Song” and took it as a message to come to Earth. They thus realize that the Haudenosaunee people were inadvertently responsible for the destruction of the Earth. Part 2, titled “Old Men and Old Sayings,” tells us of an elderly man that is watching the news and listening to the radio about a spaceship coming to earth. He knows that he and everyone will die, but the people around him are excited. He finds a book on his night stand and flips to a page where he underlined a sentence a long time ago about the European colonization of the Americas. That sentence reads “those who cannot remember the past are condemned to repeat it” (23). He closes the book and Taylor concludes the story by writing, “he hated it when white people were right." === "I Am...Am I" === “I Am...Am I” chronicles the accidental creation and unexpected ending of artificial intelligence. Professor Mark King has a plethora of degrees and works for a research firm called FUTUREVISION. One night as Professor King searches the lab for his car keys—a common occurrence for him—he notices something unusual in the Matrix room. He reads on a computer the phrase “I am.” First believing it to be a prank, King later comes to the realization that his Matrix project has evolved into a responsive Artificial Intelligence. After this realization, Professor King calls his peer Dr. Gayle Chambers to further investigate this miraculous event. After receiving approval from their superiors, Professor King and Dr. Chambers move forward in feeding the AI information, with Chambers serving as the lead communicator. With more information, it becomes increasingly concerned with its own existence and the concept of whether it has a soul. After several days of conversation with the AI, Chambers and King begin to feel uneasy about the AI's responses, which show signs of neuroses. Despite this behavior, Chambers decides to feed the AI information about the culture and history of the human race. Upon receiving this information, the AI becomes obsessed with Indigenous spirituality prior to the colonization of the Americas, and it requests more information on First Nations people. Dr. Chambers is hesitant at first, but gives in and continues to feed the AI the information with the intention to return to it in the morning. This leads to the AI finding out about colonization and genocide of Indigenous peoples. Upon her arrival the next day, Chambers discovers that the code for the AI has been completely wiped from the hard drive and a single message is left on the screen—"I was”—that signifies the AI's suicide. === "Lost in Space" === "Lost in Space" is told from the perspective of Mitchell, an Anishinabe astrosurveyor who is aboard a space shuttle on a two-year tour collecting rocks from an asteroid belt. He is accompanied by an Artificial general intelligence named Mac, short for “machine.” Mac is aboard this tour in order to accompany Mitchell and keep him sane; however, his company is a burden because for Mitchell, “true space exploration consists largely of boredom.” In the midst of Mitchell seeking a way to occupy his downtime, Mac interrupts with news about his grandfather, Papa Peter, dying. Papa Peter was Mitchell's only real tie to his Indigenous identity. After receiving the news Mitchell begins to reminisce on all of the things Papa Peter had taught him throughout his life. He constantly posed questions concerning the world above (Father Sky) and how it is more important than the land they live on (Mother Earth), which eventually led Mitchell to the selection of his career. During his state of mourning, Mitchell begins to go through all the videos his grandfather had sent him throughout his space tours. Papa Peter had sent Mitchell videos from Otter Lake, a First Nations reserve; these videos are about controversial topics regarding being both native and an astronaut. In the midst of Mitchell's grieving, Mac tries to relieve the situation by finding an online video of Mitchell's grandfather participating in a drum ceremony at Ottawa’s National Aboriginal Day festival. He reconnects to his roots and his grandfather’s spirit as he listens to the Indigenous music by feeling the drum beat and humming along. Mac’s small act of kindness leads Mitchell to gain a new-found appreciation for his presence. Mitchell feels responsible to moving forward in his life in memory of Papa Peter. === "Dreams of Doom" === "Dreams of Doom" is narrated by an Ojibway reporter named Pamela Wanishin who works for an aboriginal newspaper called the West Wind. One day she receives a mysterious package with a broken dreamcatcher and a flash drive containing highly classified files. As she reads the files, she keeps seeing the term “Project Nightlight,” and out of curiosity, she Googles it. Once she Googles this, she is contacted by a nameless agent from Indigenous and Northern Affairs Canada and told that she must be relocated because the knowledge she now possesses must never be released to the public. She quickly flees the area to a cabin at Otter Lake, owned by a family member, to lie low for a few days. Eventually, the government organization tracks her down using drones, which forces her to fight back and flee once again. Pamela then runs to her friend and coworker Sally's hous

Artificial intelligence in customer experience

Artificial intelligence in customer experience is the use and development of artificial intelligence (AI) to aid and improve customer experience (sometimes abbreviated to CX AI). Chatbots are often seen as the first step in the development of AI within the industry, but more tailored offerings are slowly becoming available. The use of artificial intelligence in the space has since become more diverse than simply chatbots, with AI underpinning entire CX cloud platforms now used at major corporations. Contact center as a service (CCaaS) has become a core solution of the CX (customer experience) industry, with the CCaaS market size expected to reach $17.19 Billion by 2030 in the United States alone. == History == As with many AI applications, CX AI early implementation case studies have demonstrated that AI can increase the quality of customer interactions and therefore the overall experience that organizations can provide. This in turn has suggested a higher return on investment and/or revenue as a result. The beginning of the revolution of customer experience and the use of machine learning was with chatbots. The use of this type of AI can be traced back to Alan Turing in 1950, when the Church–Turing thesis suggested that computers could use "formal reasoning" to reach conclusions. In 2017, Meta produced one of the first breakthroughs for everyday use of AI for customer experience when it allowed Facebook users to create their own messaging bots for free on its Facebook messenger platform. The main focus of this was to both automate and improve customer experience and interaction. In 2023, CCaaS vendors began announcing the integration of ChatGPT’s generative AI into their CX solutions. Generative AI adds a layer of semantics into AI outputs. This was a major breakthrough for conversational AI. Using natural language processing and conversational AI, chatbots could enhance the level of service they could provide, speaking to customers in an easy-to-understand and conversational tone. == Applications == Currently the main location for the application of CX AI in the sector is in contact centers. Historically, contact centers were simply known as call centers, but in recent years differentiation developed between the two terms. Call centers provide phone support, while contact centers also provide support via digital channels in addition to analogue phone systems. Contact centers are therefore seen as a complete customer service solution, where as call centers simply cover one aspect of customer interactions. As a part of improving CX, AI is also improving the employee experience. AI is able to automate tasks to free up time for contact center agents to focus on higher priority tasks. For example, AI can be used for auto summarization. This means that instead of human agents having to summarize customer interactions now AI can do it, saving organizations time and money.

CodeSandbox

CodeSandbox is a cloud-based online integrated development environment (IDE) focused on web application development. It supports popular web technologies such as JavaScript, TypeScript, React, Vue.js, and Node.js. CodeSandbox allows users to create, edit, and deploy web applications directly from the browser with zero setup. CodeSandbox is widely used for front-end development, rapid prototyping, sharing code snippets, and real-time collaborative coding. It provides GitHub integration, templates for common frameworks, and a cloud-based development container for full-stack projects. == Templates == == Limitations == Slower performance for larger tasks compared to native IDEs Some features require a paid subscription Performance and storage limits for free-tier users Limited offline capabilities

We Appreciate Power

"We Appreciate Power" is a song by Canadian musician Grimes, featuring American musician Hana. It was released on November 29, 2018, billed as the lead single from her fifth studio album Miss Anthropocene, however it is only available on the Japanese and deluxe releases. The song was written and produced by Grimes, Poppy (originally), Hana and Chris Greatti. == Background and release == The song was supposed to be one of two collaborations between Grimes and American singer Poppy, for the latter's second studio album Am I a Girl?. In an interview, Poppy mentioned that she wrote two songs with Grimes; one about "destroying things" and another about "power". The other song, "Play Destroy", was featured on the album. Grimes shared a lyric of the song with a photo of her with Poppy on Twitter in May 2018. Following feuds between the two singers, the song was released by Grimes featuring singer Hana instead. On November 26, Grimes announced she would be releasing new music on November 29. Two days later, she revealed that the single is titled "We Appreciate Power" and features Hana, and shared the artwork. The release of the song was accompanied by a lyric video directed by Grimes and her brother Mac Boucher. == Music and lyrics == "We Appreciate Power" is an industrial rock, nu metal, and techno-industrial song. The track is regarded as a further step into Grimes's experimentation with guitars that started on 2015's Art Angels. The track was compared to the works of Nine Inch Nails; Jillian Mapes of Pitchfork described the song as "an immediate onslaught of mutilated noise—distorted metal guitar chug, bloody screams, a guitar loop that conjures fear and demands worship. Flashes of Nine Inch Nails' Pretty Hate Machine reverberate through the drum programming and synths." Brendan Klinkenberg of Rolling Stone placed the song "somewhere between power pop and straightforward industrial (with an extended bridge reminiscent of the most sweeping moments in a Final Fantasy score)" and "a distinctly 2018 take on Nine Inch Nails-esque hard-edged rock." A press release stated that the song was inspired by the North Korean band Moranbong and was written "from the perspective of a Pro-A.I. Girl Group Propaganda machine who use song, dance, sex and fashion to spread goodwill towards Artificial Intelligence." In addition Grimes stated that by simply listening to the song you will be reducing your risk of ending up on any future AI overlord's hit list when it reigns supreme, mirroring the Roko's basilisk theory. Lyrically, the song touches on transhumanist ideas such as the betterment and future of the human race, the possibilities of merging consciousness with machines to extend life indefinitely through mind uploading, and the idea that reality may be simulated. The song's chorus generated a spike in interest in the word "capitulate". == Critical reception == Pitchfork critic Jillian Mapes wrote: "If "Freak on a Leash" isn't a dealbreaker, then the supervillain allure of "We Appreciate Power" might pull you in (it legitimately slaps), but it just as well may leave you weighed down by Grimes' commitment to the absolute darkest timeline." Billboard's Gil Kaufman described the song as "a dystopian, aggressive dive into a more rock-leaning sound." Similarly, Brendan Klinkenberg of Rolling Stone called it "the most aggressive single Grimes has released to date" Noisey called the song "an absolute motherfucker of a single" and opined it sounds "like a K-pop band covering nu-metal". Justin Kamp of Paste described the track as a "glitchy empowerment anthem that chugs along on screeching synths and Grimes' repeated exultations of power." == Personnel == Credits adapted from Tidal. Grimes – vocals, guitar, production, engineering Hana – vocals, guitar, additional production Chris Greatti – guitar, keyboards, production, engineering Zakk Cervini – mixing == Track listing == == Charts ==