Add The Verge Stated It's Technologically Impressive
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<br>Announced in 2016, Gym is an open-source Python library designed to assist in the advancement of support learning algorithms. It aimed to standardize how environments are specified in [AI](https://git.logicloop.io) research study, making released research study more quickly reproducible [24] [144] while providing users with a simple interface for communicating with these environments. In 2022, brand-new developments of Gym have been transferred 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 support learning (RL) research on [video games](https://2workinoz.com.au) [147] using RL algorithms and study generalization. Prior RL research focused mainly on enhancing representatives to solve single tasks. Gym Retro provides the ability to generalize in between games with comparable ideas but different appearances.<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 representatives at first lack understanding of how to even stroll, however are provided the objectives of learning to move and to push the opposing representative out of the ring. [148] Through this adversarial learning process, the [representatives discover](https://git.danomer.com) how to adapt to altering conditions. When a representative is then gotten rid of from this virtual environment and put in a new virtual environment with high winds, [raovatonline.org](https://raovatonline.org/author/charissa670/) the agent braces to remain upright, suggesting it had learned how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors in between agents might an intelligence "arms race" that might increase a representative's ability to work even outside the context of the competitors. [148]
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<br>OpenAI 5<br>
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<br>OpenAI Five is a group of five OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that [discover](https://aggeliesellada.gr) to play against human players at a high skill level totally through trial-and-error algorithms. Before ending up being a group of 5, the very first public presentation happened at The International 2017, the yearly best champion tournament for the video game, where Dendi, an expert Ukrainian player, lost against a bot in a live individually match. [150] [151] After the match, CTO Greg Brockman explained that the bot had discovered by playing against itself for 2 weeks of actual time, and that the knowing software application was an action in the direction of [producing software](https://www.facetwig.com) that can manage intricate tasks like a [cosmetic surgeon](https://git.mario-aichinger.com). [152] [153] The system utilizes a form of support learning, as the bots discover with time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as [killing](http://bc.zycoo.com3000) an enemy and taking map goals. [154] [155] [156]
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<br>By June 2018, the capability of the bots expanded to play together as a complete group of 5, and they had the ability to defeat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against expert players, but ended up losing both games. [160] [161] [162] In April 2019, [wiki.vst.hs-furtwangen.de](https://wiki.vst.hs-furtwangen.de/wiki/User:ReubenQid343925) OpenAI Five beat OG, the ruling world champs of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public look came later that month, where they played in 42,729 overall video games in a four-day open online competitors, winning 99.4% of those games. [165]
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<br>OpenAI 5's mechanisms in Dota 2's bot player shows the challenges of [AI](http://47.109.30.194:8888) systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has shown making use of deep reinforcement knowing (DRL) representatives to [attain superhuman](https://dongochan.id.vn) skills in Dota 2 matches. [166]
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<br>Dactyl<br>
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<br>Developed in 2018, Dactyl utilizes [machine learning](https://www.tvcommercialad.com) to train a Shadow Hand, a [human-like robot](https://www.luckysalesinc.com) hand, to control physical objects. [167] It discovers totally in simulation using the exact same RL algorithms and [ratemywifey.com](https://ratemywifey.com/author/ollieholtze/) training code as OpenAI Five. OpenAI dealt with the things orientation problem by utilizing domain randomization, a simulation approach which exposes the student to a range of experiences instead of trying to fit to truth. The set-up for Dactyl, aside from having movement tracking electronic cameras, likewise has RGB video cameras to permit the robot to control an approximate object by seeing it. In 2018, OpenAI revealed that the system had the ability to manipulate a cube and an octagonal prism. [168]
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<br>In 2019, OpenAI showed that Dactyl could solve a Rubik's Cube. The robotic was able to resolve the puzzle 60% of the time. Objects like the Rubik's Cube present complex physics that is harder to model. OpenAI did this by improving the toughness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of generating progressively more tough environments. ADR varies from manual domain randomization by not needing a human to specify randomization ranges. [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 new [AI](https://younetwork.app) designs developed by OpenAI" to let developers contact it for "any English language [AI](https://git.rootfinlay.co.uk) job". [170] [171]
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<br>Text generation<br>
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<br>The company has actually popularized generative pretrained transformers (GPT). [172]
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<br>OpenAI's initial GPT model ("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 colleagues, and released in preprint on OpenAI's website on June 11, 2018. [173] It revealed how a generative model of language could obtain world knowledge and process long-range dependences by pre-training on a diverse corpus with long stretches of adjoining text.<br>
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<br>GPT-2<br>
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<br>Generative Pre-trained Transformer 2 ("GPT-2") is a without supervision transformer language design and the follower to OpenAI's initial GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with just limited demonstrative versions at first released to the public. The complete variation of GPT-2 was not right away launched due to issue about possible abuse, including applications for composing phony news. [174] Some experts expressed uncertainty that GPT-2 positioned a substantial danger.<br>
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<br>In action to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to discover "neural fake news". [175] Other researchers, such as Jeremy Howard, cautioned 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 difficult to filter". [176] In November 2019, OpenAI launched the complete variation of the GPT-2 language design. [177] Several sites host interactive presentations 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 precision and perplexity on 7 of 8 zero-shot jobs (i.e. the model was not more trained on any task-specific input-output examples).<br>
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<br>The corpus it was trained on, called WebText, contains slightly 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It prevents certain problems encoding vocabulary with word tokens by utilizing byte pair encoding. This permits representing any string of characters by encoding both individual characters and multiple-character tokens. [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 a not being watched transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI mentioned that the full version of GPT-3 contained 175 billion criteria, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 models with as few as 125 million criteria were also trained). [186]
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<br>OpenAI stated that GPT-3 was successful at certain "meta-learning" tasks and could generalize the purpose of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer learning between English and Romanian, and between English and German. [184]
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<br>GPT-3 considerably enhanced benchmark results over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or [pipewiki.org](https://pipewiki.org/wiki/index.php/User:IvyCano5125640) coming across the fundamental ability constraints of predictive language designs. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of compute, compared to tens of petaflop/s-days for the complete GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately [launched](https://1millionjobsmw.com) to the public for issues of possible abuse, although OpenAI planned to allow gain access to through a [paid cloud](https://wiki.eqoarevival.com) API after a two-month complimentary personal beta that began in June 2020. [170] [189]
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<br>On September 23, 2020, GPT-3 was certified exclusively to Microsoft. [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 furthermore been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://git.declic3000.com) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in [personal](http://182.92.251.553000) beta. [194] According to OpenAI, the model can develop working code in over a [dozen programs](https://git.spitkov.hu) languages, a lot of successfully in Python. [192]
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<br>Several concerns with problems, design defects and security vulnerabilities were pointed out. [195] [196]
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<br>GitHub Copilot has actually been accused of discharging copyrighted code, without any author attribution or license. [197]
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<br>OpenAI announced that they would discontinue 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](http://git.motr-online.com) 4 (GPT-4), [capable](http://120.77.213.1393389) of accepting text or image inputs. [199] They revealed that the upgraded innovation passed a simulated law school [bar examination](https://kol-jobs.com) with a score around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also read, analyze or generate approximately 25,000 words of text, and [bytes-the-dust.com](https://bytes-the-dust.com/index.php/User:CharleyRudall29) compose code in all significant programming languages. [200]
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<br>Observers reported that the [iteration](https://canworkers.ca) of [ChatGPT utilizing](https://app.deepsoul.es) GPT-4 was an improvement on the previous GPT-3.5-based version, with the caveat that GPT-4 retained some of the issues with earlier revisions. [201] GPT-4 is likewise efficient in taking images as input on [ChatGPT](http://gsend.kr). [202] OpenAI has actually declined to reveal different technical details and statistics about GPT-4, such as the accurate size of the model. [203]
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<br>GPT-4o<br>
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<br>On May 13, 2024, OpenAI announced and launched GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained modern outcomes in voice, multilingual, and vision benchmarks, setting brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) standard compared to 86.5% by GPT-4. [207]
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<br>On July 18, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11857434) 2024, OpenAI released GPT-4o mini, a smaller sized variation of GPT-4o changing 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 beneficial for enterprises, start-ups and designers looking for to automate services with [AI](https://bartists.info) representatives. [208]
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<br>o1<br>
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<br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have been created to take more time to think of their actions, leading to higher precision. These designs are particularly efficient in science, coding, and reasoning jobs, and were made available to ChatGPT Plus and Staff member. [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 revealed o3, the follower of the o1 [thinking design](https://xn--v69atsro52ncsg2uqd74apxb.com). OpenAI also revealed o3-mini, a lighter and faster variation of OpenAI o3. Since December 21, 2024, this model is not available for [public usage](https://kaymack.careers). According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the chance to obtain early access to these designs. [214] The design is called o3 rather than o2 to avoid confusion with telecommunications providers O2. [215]
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<br>Deep research study<br>
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<br>Deep research is a representative developed by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out substantial web browsing, data analysis, [pipewiki.org](https://pipewiki.org/wiki/index.php/User:Shawnee3364) and synthesis, providing detailed [reports](https://cinetaigia.com) within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools enabled, it [reached](http://gogs.oxusmedia.com) an accuracy of 26.6 percent on HLE (Humanity's Last Exam) standard. [120]
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<br>Image category<br>
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<br>CLIP<br>
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<br>Revealed in 2021, CLIP ([Contrastive Language-Image](https://git.rootfinlay.co.uk) Pre-training) is a model that is trained to examine the semantic similarity between text and images. It can notably be utilized for image category. [217]
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<br>Text-to-image<br>
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<br>DALL-E<br>
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<br>Revealed in 2021, DALL-E is a Transformer design that produces images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to interpret natural [language inputs](http://www.evmarket.co.kr) (such as "a green leather bag shaped like a pentagon" or "an isometric view of a sad capybara") and create matching images. It can produce images of sensible objects ("a stained-glass window with a picture of a blue strawberry") as well as items that do not exist in truth ("a cube with the texture of a porcupine"). As of 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 revealed DALL-E 2, an updated variation of the design with more practical results. [219] In December 2022, [OpenAI published](https://www.sc57.wang) on GitHub software application for Point-E, a brand-new simple system for converting a text description into a 3-dimensional design. [220]
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<br>DALL-E 3<br>
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<br>In September 2023, OpenAI announced DALL-E 3, a more powerful design better able to generate images from complex descriptions without manual prompt engineering and render complex [details](https://git.rootfinlay.co.uk) like hands and text. [221] It was released to the public as a ChatGPT Plus feature 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 design that can create videos based upon brief detailed triggers [223] along with extend existing videos forwards or backwards in time. [224] It can create videos with resolution up to 1920x1080 or 1080x1920. The optimum length of generated videos is unidentified.<br>
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<br>Sora's advancement group named it after the Japanese word for "sky", to [represent](https://site4people.com) its "limitless innovative capacity". [223] Sora's innovation is an adaptation of the technology behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos as well as copyrighted videos licensed for that purpose, but did not expose the number or the [exact sources](http://81.71.148.578080) of the videos. [223]
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<br>OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, mentioning that it might produce videos up to one minute long. It likewise shared a technical report highlighting the approaches used to train the design, and the model's abilities. [225] It acknowledged some of its drawbacks, consisting of battles mimicing complex physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "excellent", however kept in mind that they need to have been cherry-picked and might not represent Sora's normal output. [225]
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<br>Despite uncertainty from some academic leaders following Sora's public demo, noteworthy entertainment-industry figures have shown substantial interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the innovation's capability to generate sensible video from text descriptions, citing its prospective to revolutionize storytelling and content development. He said that his enjoyment about [Sora's possibilities](https://tiktack.socialkhaleel.com) was so strong that he had actually decided to pause strategies for expanding his Atlanta-based film 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 model. [228] It is trained on a big dataset of diverse audio and is likewise a multi-task design that can perform multilingual speech recognition in addition to speech translation and language recognition. [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 anticipate subsequent musical notes in MIDI music files. It can create songs with 10 instruments in 15 styles. According to The Verge, a song produced by MuseNet tends to start fairly however then fall into chaos the longer it plays. [230] [231] In pop culture, initial applications of this tool were [utilized](https://skillsvault.co.za) as early as 2020 for the web psychological 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 [produce](https://gitlab.informicus.ru) music with vocals. After [training](http://47.107.126.1073000) on 1.2 million samples, the system accepts a category, artist, and a bit of lyrics and [outputs tune](https://git.pm-gbr.de) samples. OpenAI mentioned the tunes "show regional musical coherence [and] follow traditional chord patterns" but acknowledged that the tunes lack "familiar larger musical structures such as choruses that repeat" and that "there is a substantial gap" between Jukebox and human-generated music. The Verge stated "It's technologically remarkable, even if the results seem like mushy versions of tunes that may feel familiar", while Business Insider specified "surprisingly, a few of the resulting songs are memorable 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 released the Debate Game, which teaches machines to debate toy problems in front of a human judge. The function is to research whether such a technique might assist in auditing [AI](http://211.91.63.144:8088) choices and in establishing explainable [AI](http://www.cl1024.online). [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 substantial layer and nerve cell of 8 neural network models which are typically studied in interpretability. [240] [Microscope](https://pak4job.com) was produced to examine the features that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, various 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 is a synthetic intelligence tool developed on top of GPT-3 that offers a conversational user interface that permits users to ask concerns in natural language. The system then responds with an answer within seconds.<br>
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