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<br>Announced in 2016, Gym is an open-source Python library designed to facilitate the advancement of reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](https://storymaps.nhmc.uoc.gr) research study, making released research more easily reproducible [24] [144] while providing users with an easy user interface for interacting with these environments. In 2022, brand-new advancements of Gym have actually been moved to the library Gymnasium. [145] [146] |
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<br>Gym Retro<br> |
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<br>Released in 2018, Gym Retro is a platform for [reinforcement learning](https://truejob.co) (RL) research study on computer game [147] utilizing RL algorithms and study generalization. Prior RL research focused mainly on optimizing representatives to resolve single jobs. [Gym Retro](https://117.50.190.293000) offers the [ability](https://47.98.175.161) to generalize in between video games with similar concepts but various looks.<br> |
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<br>RoboSumo<br> |
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<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents at first lack knowledge of how to even walk, but are provided the objectives of discovering to move and to push the opposing agent out of the ring. [148] Through this adversarial learning procedure, the representatives find out how to adapt to altering conditions. When a representative is then gotten rid of from this virtual environment and put in a brand-new virtual environment with high winds, the agent braces to remain upright, suggesting it had actually discovered how to stabilize in a generalized way. [148] [149] [OpenAI's Igor](https://codes.tools.asitavsen.com) Mordatch argued that competition in between agents might create an intelligence "arms race" that might increase a representative's capability to operate even outside the context of the competition. [148] |
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<br>OpenAI 5<br> |
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<br>OpenAI Five is a group of five OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that discover to play against human players at a high [skill level](https://supremecarelink.com) entirely through experimental algorithms. Before becoming a team of 5, the first public demonstration happened at The International 2017, the yearly premiere champion competition for the game, where Dendi, an expert Ukrainian player, lost against a bot in a live one-on-one match. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually found out by playing against itself for 2 weeks of actual time, and that the learning software application was an action in the direction of creating software application that can deal with intricate jobs like a surgeon. [152] [153] The system uses a kind of support knowing, as the bots discover over time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as eliminating an opponent and taking [map goals](http://fujino-mori.com). [154] [155] [156] |
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<br>By June 2018, the ability of the bots expanded to play together as a complete group of 5, and they had the ability to beat groups of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against expert gamers, but wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champs of the game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' final public look came later on that month, where they played in 42,729 total video games in a four-day open online competition, winning 99.4% of those video games. [165] |
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<br>OpenAI 5's systems in Dota 2's bot gamer reveals the obstacles of [AI](https://younghopestaffing.com) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has shown using deep reinforcement [knowing](http://47.108.105.483000) (DRL) agents to attain superhuman [competence](http://missima.co.kr) in Dota 2 matches. [166] |
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<br>Dactyl<br> |
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<br>Developed in 2018, Dactyl uses maker finding out to train a Shadow Hand, a human-like robotic hand, to manipulate physical items. [167] It learns totally in simulation using the very same RL algorithms and training code as OpenAI Five. OpenAI took on the object orientation issue by utilizing domain randomization, a simulation method which exposes the learner to a variety of experiences rather than attempting to fit to truth. The set-up for Dactyl, aside from having movement tracking cams, likewise has RGB cameras to enable the robotic to manipulate an approximate things by seeing it. In 2018, OpenAI revealed that the system was able to control a cube and an octagonal prism. [168] |
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<br>In 2019, [garagesale.es](https://www.garagesale.es/author/lashaylaroc/) OpenAI demonstrated that Dactyl might solve a Rubik's Cube. The robot was able to fix the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex physics that is harder to design. OpenAI did this by enhancing the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), [systemcheck-wiki.de](https://systemcheck-wiki.de/index.php?title=Benutzer:MattieGuinn) a simulation approach of producing gradually harder environments. ADR differs from manual domain randomization by not needing a human to specify [randomization varieties](https://crossdark.net). [169] |
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<br>API<br> |
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<br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing brand-new [AI](http://git.sdkj001.cn) designs developed by OpenAI" to let designers contact it for "any English language [AI](https://brightworks.com.sg) job". [170] [171] |
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<br>Text generation<br> |
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<br>The company has promoted generative pretrained transformers (GPT). [172] |
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<br>OpenAI's original GPT design ("GPT-1")<br> |
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<br>The original paper on generative pre-training of a transformer-based language design was written by Alec Radford and his associates, and published in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative design of language could obtain world knowledge and process long-range dependencies by pre-training on a diverse corpus with long of [adjoining](https://storage.sukazyo.cc) text.<br> |
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<br>GPT-2<br> |
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<br>Generative Pre-trained Transformer 2 ("GPT-2") is an unsupervised transformer language design and the follower to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with only [restricted demonstrative](https://tribetok.com) versions at first released to the general public. The complete variation of GPT-2 was not instantly released due to issue about potential abuse, consisting of applications for writing phony news. [174] Some specialists expressed uncertainty that GPT-2 positioned a considerable hazard.<br> |
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<br>In response to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to identify "neural fake news". [175] Other scientists, such as Jeremy Howard, alerted of "the innovation to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would muffle all other speech and be impossible to filter". [176] In November 2019, OpenAI released the complete variation of the GPT-2 language model. [177] Several websites host interactive demonstrations of different circumstances of GPT-2 and other transformer models. [178] [179] [180] |
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<br>GPT-2's authors argue not being watched language models to be general-purpose students, highlighted by GPT-2 attaining cutting edge accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not further trained on any task-specific input-output examples).<br> |
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<br>The corpus it was [trained](http://git.baobaot.com) on, called WebText, contains a little 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It prevents certain [issues encoding](https://jktechnohub.com) vocabulary with word tokens by [utilizing byte](https://www.dailynaukri.pk) pair encoding. This permits representing any string of characters by encoding both specific characters and [multiple-character tokens](https://www.p3r.app). [181] |
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<br>GPT-3<br> |
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<br>First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI stated that the complete version of GPT-3 contained 175 billion parameters, [184] two orders of magnitude bigger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 designs with as few as 125 million criteria were likewise trained). [186] |
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<br>OpenAI specified that GPT-3 prospered at certain "meta-learning" jobs and might generalize the purpose of a single input-output pair. The GPT-3 release paper provided examples of translation and cross-linguistic transfer learning in between English and Romanian, and in between [English](https://sunrise.hireyo.com) and German. [184] |
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<br>GPT-3 dramatically improved [benchmark](https://divsourcestaffing.com) results over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or experiencing the fundamental capability constraints of predictive language designs. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of compute, compared to 10s of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not instantly launched to the general public for issues of possible abuse, although OpenAI planned to enable gain access to through a paid cloud API after a two-month totally free private beta that started in June 2020. [170] [189] |
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<br>On September 23, 2020, GPT-3 was certified exclusively to [Microsoft](http://47.108.182.667777). [190] [191] |
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<br>Codex<br> |
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<br>Announced in mid-2021, Codex is a descendant of GPT-3 that has in addition been [trained](https://nailrada.com) on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://iamtube.jp) powering the code autocompletion tool [GitHub Copilot](https://theindietube.com). [193] In August 2021, an API was released in private beta. [194] According to OpenAI, the model can develop working code in over a dozen programming languages, a lot of effectively in Python. [192] |
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<br>Several concerns with problems, style flaws and security vulnerabilities were mentioned. [195] [196] |
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<br>GitHub Copilot has been implicated of producing copyrighted code, without any author attribution or license. [197] |
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<br>OpenAI announced that they would terminate support for Codex API on March 23, 2023. [198] |
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<br>GPT-4<br> |
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<br>On March 14, 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. [199] They announced that the upgraded technology passed a simulated law school bar test with a rating around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also check out, analyze or [generate](http://115.236.37.10530011) up to 25,000 words of text, and write code in all significant shows languages. [200] |
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<br>Observers reported that the model of ChatGPT utilizing GPT-4 was an improvement on the previous GPT-3.5-based model, with the caution that GPT-4 retained a few of the problems with earlier modifications. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has actually decreased to reveal various technical details and stats about GPT-4, such as the exact size of the model. [203] |
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<br>GPT-4o<br> |
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<br>On May 13, 2024, [OpenAI revealed](http://47.109.153.573000) and [released](https://dlya-nas.com) GPT-4o, which can process and produce text, images and audio. [204] GPT-4o attained modern outcomes in voice, multilingual, and vision benchmarks, setting new records in audio speech acknowledgment and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207] |
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<br>On July 18, 2024, OpenAI released GPT-4o mini, a smaller sized variation of GPT-4o [changing](http://124.70.149.1810880) GPT-3.5 Turbo on the ChatGPT interface. Its API costs $0.15 per million input tokens and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI anticipates it to be particularly useful for enterprises, start-ups and developers seeking to automate services with [AI](http://113.177.27.200:2033) agents. [208] |
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<br>o1<br> |
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<br>On September 12, [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:LeiaBuckley2869) 2024, OpenAI released the o1-preview and o1-mini models, which have been created to take more time to think of their reactions, leading to higher accuracy. These designs are especially reliable in science, coding, and thinking tasks, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1-preview was changed by o1. [211] |
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<br>o3<br> |
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<br>On December 20, 2024, OpenAI unveiled o3, the follower of the o1 thinking design. OpenAI also unveiled o3-mini, a lighter and much faster version of OpenAI o3. Since December 21, 2024, this model is not available for public use. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, security and security researchers had the [opportunity](https://blazblue.wiki) to obtain early access to these models. [214] The model is called o3 instead of o2 to prevent confusion with telecommunications [services company](http://121.37.138.2) O2. [215] |
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<br>Deep research study<br> |
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<br>Deep research is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the abilities of OpenAI's o3 model to perform substantial web surfing, data analysis, and synthesis, delivering detailed reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120] |
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<br>Image classification<br> |
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<br>CLIP<br> |
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<br>Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to examine the semantic similarity between text and images. It can notably be used for [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:IsiahMoreira6) image [category](https://gogs.greta.wywiwyg.net). [217] |
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<br>Text-to-image<br> |
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<br>DALL-E<br> |
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<br>[Revealed](https://sttimothysignal.org) in 2021, DALL-E is a Transformer design that creates images from [textual descriptions](https://myafritube.com). [218] DALL-E uses a 12-billion-parameter version of GPT-3 to analyze natural language inputs (such as "a green leather purse formed like a pentagon" or "an isometric view of an unfortunate capybara") and create corresponding images. It can produce pictures of realistic items ("a stained-glass window with an image of a blue strawberry") in addition to items that do not exist in reality ("a cube with the texture of a porcupine"). Since March 2021, no API or code is available.<br> |
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<br>DALL-E 2<br> |
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<br>In April 2022, OpenAI announced DALL-E 2, an updated variation of the model with more realistic results. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a brand-new simple system for transforming a text description into a 3-dimensional model. [220] |
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<br>DALL-E 3<br> |
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<br>In September 2023, OpenAI revealed DALL-E 3, a more effective design better able to produce images from complicated descriptions without manual timely engineering and render intricate details like hands and text. [221] It was released to the general public as a [ChatGPT](https://git.olivierboeren.nl) Plus function in October. [222] |
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<br>Text-to-video<br> |
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<br>Sora<br> |
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<br>Sora is a text-to-video model that can create videos based on short detailed triggers [223] along with extend existing videos forwards or in reverse in time. [224] It can produce videos with resolution approximately 1920x1080 or 1080x1920. The maximal length of generated videos is unknown.<br> |
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<br>Sora's advancement team named it after the Japanese word for "sky", to signify its "limitless innovative potential". [223] Sora's technology is an adaptation of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos licensed for that function, however did not reveal the number or [wiki.asexuality.org](https://wiki.asexuality.org/w/index.php?title=User_talk:NoellaKeldie49) the precise sources of the videos. [223] |
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<br>OpenAI demonstrated some [Sora-created high-definition](https://rami-vcard.site) videos to the public on February 15, 2024, mentioning that it could generate videos up to one minute long. It likewise shared a technical report highlighting the techniques utilized to train the design, and the model's abilities. [225] It acknowledged a few of its shortcomings, including struggles simulating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "excellent", however noted that they need to have been cherry-picked and might not represent Sora's typical output. [225] |
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<br>Despite uncertainty from some academic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have revealed significant interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the technology's ability to produce realistic video from text descriptions, citing its potential to revolutionize storytelling and content development. He said that his enjoyment about Sora's possibilities was so strong that he had actually decided to stop briefly prepare for broadening his Atlanta-based motion picture studio. [227] |
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<br>Speech-to-text<br> |
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<br>Whisper<br> |
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<br>Released in 2022, Whisper is a general-purpose speech recognition design. [228] It is trained on a big dataset of varied audio and is also a multi-task model that can carry out multilingual speech recognition in addition to speech translation and language identification. [229] |
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<br>Music generation<br> |
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<br>MuseNet<br> |
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<br>Released in 2019, MuseNet is a deep neural net trained to [forecast subsequent](https://thebigme.cc3000) musical notes in MIDI music files. It can [generate tunes](https://kibistudio.com57183) with 10 [instruments](https://tagreba.org) in 15 styles. According to The Verge, a tune generated by MuseNet tends to start fairly however then fall into chaos the longer it plays. [230] [231] In pop culture, [initial applications](https://coolroomchannel.com) of this tool were used as early as 2020 for the internet mental thriller Ben Drowned to develop music for the titular character. [232] [233] |
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<br>Jukebox<br> |
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<br>Released in 2020, Jukebox is an open-sourced algorithm to [generate music](https://croart.net) with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a bit of lyrics and outputs song samples. OpenAI stated the songs "reveal local musical coherence [and] follow conventional chord patterns" however acknowledged that the tunes do not have "familiar larger musical structures such as choruses that repeat" which "there is a considerable space" in between Jukebox and human-generated music. The Verge stated "It's highly outstanding, even if the outcomes seem like mushy variations of songs that may feel familiar", while Business Insider mentioned "remarkably, a few of the resulting tunes are appealing and sound genuine". [234] [235] [236] |
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<br>Interface<br> |
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<br>Debate Game<br> |
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<br>In 2018, OpenAI introduced the Debate Game, which teaches machines to dispute toy issues in front of a human judge. The purpose is to research whether such a technique might assist in auditing [AI](https://git.privateger.me) choices and in developing explainable [AI](https://git.thewebally.com). [237] [238] |
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<br>Microscope<br> |
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<br>Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of 8 neural network models which are often studied in interpretability. [240] Microscope was developed to examine the features that form inside these neural networks quickly. The designs consisted of are AlexNet, VGG-19, different versions of Inception, and different variations of CLIP Resnet. [241] |
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<br>ChatGPT<br> |
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<br>Launched in November 2022, [ChatGPT](https://notitia.tv) is an expert system tool built on top of GPT-3 that offers a [conversational interface](https://geniusactionblueprint.com) that allows users to ask concerns in natural language. The system then reacts with an answer within seconds.<br> |
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