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 <br>Announced in 2016, Gym is an open-source Python library developed to help with the development of reinforcement knowing algorithms. It aimed to standardize how environments are specified in [AI](http://rm.runfox.com) research study, making published research study more easily reproducible [24] [144] while offering users with a simple user interface for connecting with these environments. In 2022, new developments of Gym have actually been relocated to the library Gymnasium. [145] [146]
 <br>Gym Retro<br>
 <br>Released in 2018, Gym Retro is a platform for reinforcement learning (RL) research study on video games [147] using RL algorithms and study generalization. Prior RL research study focused mainly on enhancing representatives to resolve single tasks. Gym Retro offers the capability to generalize in between games with comparable ideas but different appearances.<br>
 <br>RoboSumo<br>
 <br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents initially lack knowledge of how to even walk, however are given the objectives of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial knowing process, the representatives learn how to adjust to changing conditions. When a representative is then [eliminated](https://git.chocolatinie.fr) from this virtual environment and positioned in a new virtual environment with high winds, the representative braces to remain upright, suggesting it had learned how to stabilize in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors between representatives might produce an intelligence "arms race" that could increase an agent's capability to function even outside the context of the competition. [148]
 <br>OpenAI 5<br>
 <br>OpenAI Five is a team of five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that learn to play against human gamers at a high skill level entirely through experimental algorithms. Before ending up being a group of 5, the very first public presentation occurred at The International 2017, the yearly best championship competition for the video game, where Dendi, a professional Ukrainian gamer, lost against a bot in a live one-on-one matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had actually discovered by playing against itself for two weeks of genuine time, which the knowing software was an action in the instructions of producing software application that can deal with intricate tasks like a cosmetic surgeon. [152] [153] The system utilizes a form of reinforcement learning, as the bots learn gradually by playing against themselves numerous times a day for months, and are rewarded for actions such as eliminating an opponent and taking map goals. [154] [155] [156]
 <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 beat groups of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two exhibition matches against professional players, but ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champions of the video game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' final public appearance came later on that month, where they played in 42,729 total video games in a four-day open online competitors, winning 99.4% of those [video games](http://47.244.181.255). [165]
 <br>OpenAI 5['s systems](https://www.footballclubfans.com) in Dota 2's bot player shows the difficulties of [AI](https://findgovtsjob.com) [systems](https://easterntalent.eu) in [multiplayer online](http://makerjia.cn3000) fight arena (MOBA) games and how OpenAI Five has actually shown using deep support learning (DRL) representatives to attain superhuman [competence](https://members.mcafeeinstitute.com) in Dota 2 matches. [166]
 <br>Dactyl<br>
 <br>Developed in 2018, Dactyl uses device finding out to train a Shadow Hand, a human-like robotic hand, to control physical things. [167] It finds out completely in simulation using the very same RL algorithms and [training](http://media.nudigi.id) code as OpenAI Five. OpenAI tackled the item [orientation issue](http://team.pocketuniversity.cn) by utilizing domain randomization, a simulation approach which exposes the learner to a variety of experiences rather than attempting to fit to truth. The set-up for Dactyl, aside from having  cameras, likewise has RGB video cameras to allow the robotic to manipulate an arbitrary things by seeing it. In 2018, OpenAI showed that the system was able to manipulate a cube and an octagonal prism. [168]
 <br>In 2019, OpenAI demonstrated that Dactyl might solve a Rubik's Cube. The robot had the ability to solve the puzzle 60% of the time. [Objects](https://flexychat.com) like the Rubik's Cube present complicated physics that is harder to model. OpenAI did this by enhancing the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of generating progressively harder environments. ADR varies from manual [domain randomization](https://sagemedicalstaffing.com) by not [requiring](http://47.107.92.41234) a human to define randomization ranges. [169]
 <br>API<br>
 <br>In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new [AI](http://gitea.infomagus.hu) models developed by OpenAI" to let designers get in touch with it for "any English language [AI](https://in.fhiky.com) job". [170] [171]
 <br>Text generation<br>
 <br>The company has actually popularized generative pretrained transformers (GPT). [172]
 <br>OpenAI's original GPT design ("GPT-1")<br>
 <br>The original paper on generative pre-training of a transformer-based language model was written by Alec Radford and his colleagues, and published in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language might obtain world understanding and procedure long-range dependencies by pre-training on a [varied corpus](http://139.224.213.43000) with long stretches of adjoining text.<br>
 <br>GPT-2<br>
 <br>Generative Pre-trained Transformer 2 ("GPT-2") is a not being watched transformer language design and the follower to [OpenAI's initial](https://giaovienvietnam.vn) GPT model ("GPT-1"). GPT-2 was revealed in February 2019, with only limited demonstrative versions initially launched to the public. The complete variation of GPT-2 was not immediately released due to issue about potential misuse, including applications for writing phony news. [174] Some professionals revealed uncertainty that GPT-2 positioned a significant threat.<br>
 <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, warned of "the innovation to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush all other speech and be impossible to filter". [176] In November 2019, OpenAI launched the total variation of the GPT-2 language model. [177] Several sites host interactive demonstrations of various circumstances of GPT-2 and other transformer models. [178] [179] [180]
 <br>GPT-2's authors argue without supervision language models to be general-purpose learners, highlighted by GPT-2 attaining modern precision and perplexity on 7 of 8 zero-shot tasks (i.e. the design was not more trained on any task-specific input-output examples).<br>
 <br>The corpus it was trained on, called WebText, contains slightly 40 [gigabytes](http://201.17.3.963000) of text from URLs shared in Reddit submissions with at least 3 upvotes. It prevents certain concerns encoding vocabulary with word tokens by utilizing byte pair encoding. This allows representing any string of characters by encoding both private characters and multiple-character tokens. [181]
 <br>GPT-3<br>
 <br>First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is a not being watched transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI specified that the full version of GPT-3 contained 175 billion parameters, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 models with as couple of as 125 million criteria were also trained). [186]
 <br>OpenAI mentioned 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 knowing between English and Romanian, and between [English](https://lekoxnfx.com4000) and German. [184]
 <br>GPT-3 significantly improved benchmark results over GPT-2. OpenAI cautioned that such [scaling-up](https://gitea.gm56.ru) of language models might be approaching or encountering the basic ability constraints of predictive language designs. [187] Pre-training GPT-3 needed [numerous](https://blackfinn.de) thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the full GPT-2 model. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately launched to the general public for issues of possible abuse, although OpenAI planned to allow gain access to through a paid cloud API after a two-month totally free private beta that began in June 2020. [170] [189]
 <br>On September 23, 2020, GPT-3 was licensed specifically to [Microsoft](http://8.140.200.2363000). [190] [191]
 <br>Codex<br>
 <br>Announced in mid-2021, Codex is a descendant of GPT-3 that has additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://git.xxb.lttc.cn) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the model can produce working code in over a dozen shows languages, a lot of successfully in Python. [192]
 <br>Several issues with glitches, design defects and security [vulnerabilities](https://cvmobil.com) were cited. [195] [196]
 <br>GitHub Copilot has been implicated of producing copyrighted code, with no author attribution or license. [197]
 <br>OpenAI announced that they would stop assistance for Codex API on March 23, 2023. [198]
 <br>GPT-4<br>
 <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 revealed that the updated innovation passed a simulated law school [bar exam](http://13.209.39.13932421) with a rating around the top 10% of [test takers](https://internship.af). (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might likewise check out, examine or generate up to 25,000 words of text, and compose code in all significant programs languages. [200]
 <br>Observers reported that the version of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based version, with the caution that GPT-4 retained some of the problems with earlier revisions. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has declined to reveal numerous technical details and statistics about GPT-4, such as the exact size of the design. [203]
 <br>GPT-4o<br>
 <br>On May 13, 2024, OpenAI announced and launched GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained state-of-the-art outcomes in voice, multilingual, and vision benchmarks,  [hb9lc.org](https://www.hb9lc.org/wiki/index.php/User:NolanLancaster3) setting new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) criteria compared to 86.5% by GPT-4. [207]
 <br>On July 18, 2024, OpenAI launched GPT-4o mini, a smaller version of GPT-4o replacing 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 expects](https://git.prayujt.com) it to be particularly beneficial for enterprises, start-ups and [developers](https://basedwa.re) looking for to automate services with [AI](http://39.108.87.179:3000) representatives. [208]
 <br>o1<br>
 <br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini designs, which have actually been designed to take more time to think about their actions, leading to higher precision. These models are particularly reliable in science, coding,  [wiki.lafabriquedelalogistique.fr](https://wiki.lafabriquedelalogistique.fr/Utilisateur:GiuseppeGlenelg) and thinking tasks, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1-preview was [changed](http://115.182.208.2453000) by o1. [211]
 <br>o3<br>
 <br>On December 20, 2024, OpenAI revealed o3, the follower of the o1 thinking model. OpenAI likewise revealed o3-mini, a lighter and much faster version of OpenAI o3. Since December 21, 2024, this model is not available for public usage. According to OpenAI, they are [checking](http://106.55.234.1783000) o3 and o3-mini. [212] [213] Until January 10, 2025, safety and [security researchers](https://salesupprocess.it) had the chance to obtain early access to these models. [214] The model is called o3 rather than o2 to prevent confusion with telecoms companies O2. [215]
 <br>Deep research study<br>
 <br>Deep research is an agent developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out [extensive web](https://satitmattayom.nrru.ac.th) surfing, data analysis, and synthesis, [delivering detailed](https://addismarket.net) reports within a timeframe of 5 to 30 minutes. [216] With searching and Python tools made it possible for, it reached an [accuracy](https://www.ndule.site) of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120]
 <br>Image classification<br>
 <br>CLIP<br>
 <br>[Revealed](https://sundaycareers.com) in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to evaluate the semantic similarity in between text and images. It can notably be utilized for image classification. [217]
 <br>Text-to-image<br>
 <br>DALL-E<br>
 <br>Revealed in 2021, DALL-E is a Transformer design that produces images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter variation of GPT-3 to analyze natural language inputs (such as "a green leather handbag formed like a pentagon" or "an isometric view of a sad capybara") and create corresponding images. It can produce images of sensible items ("a stained-glass window with an image of a blue strawberry") along with things that do not exist in [reality](http://ep210.co.kr) ("a cube with the texture of a porcupine"). As of March 2021, no API or code is available.<br>
 <br>DALL-E 2<br>
 <br>In April 2022, OpenAI revealed DALL-E 2,  [wiki.snooze-hotelsoftware.de](https://wiki.snooze-hotelsoftware.de/index.php?title=Benutzer:Orval41J5492) an upgraded version of the design with more reasonable results. [219] In December 2022, OpenAI published on GitHub software for Point-E, a new fundamental system for converting a text description into a 3-dimensional model. [220]
 <br>DALL-E 3<br>
 <br>In September 2023, OpenAI announced DALL-E 3, a more effective design much better able to create images from intricate descriptions without manual prompt engineering and render complex details like hands and text. [221] It was launched to the general public as a ChatGPT Plus feature in October. [222]
 <br>Text-to-video<br>
 <br>Sora<br>
 <br>Sora is a text-to-video design that can generate videos based on brief detailed triggers [223] along with extend existing videos forwards or backwards in time. [224] It can generate videos with resolution up to 1920x1080 or 1080x1920. The maximal length of produced videos is unidentified.<br>
 <br>Sora's development team called it after the Japanese word for "sky", to represent its "endless imaginative potential". [223] Sora's technology is an adaptation of the technology behind the DALL · E 3 text-to-image model. [225] [OpenAI trained](https://www.florevit.com) the system utilizing publicly-available videos along with copyrighted videos certified for that purpose, however did not reveal the number or the specific sources of the videos. [223]
 <br>OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, stating that it might create videos up to one minute long. It also shared a technical report highlighting the approaches used to train the design, and the model's capabilities. [225] It acknowledged a few of its shortcomings, consisting of struggles imitating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "impressive", however noted that they need to have been cherry-picked and might not [represent Sora's](https://gitea.freshbrewed.science) normal output. [225]
 <br>Despite uncertainty from some academic leaders following Sora's public demo, [notable entertainment-industry](https://ramique.kr) figures have actually revealed substantial interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the innovation's ability to create sensible video from text descriptions, citing its prospective to revolutionize storytelling and content development. He said that his excitement about Sora's possibilities was so strong that he had actually decided to pause prepare for expanding his Atlanta-based movie studio. [227]
 <br>Speech-to-text<br>
 <br>Whisper<br>
 <br>Released in 2022, Whisper is a general-purpose speech acknowledgment design. [228] It is trained on a large dataset of varied audio and is also a multi-task model that can [perform multilingual](https://tribetok.com) speech recognition in addition to speech translation and language [recognition](https://3flow.se). [229]
 <br>Music generation<br>
 <br>MuseNet<br>
 <br>Released in 2019, MuseNet is a deep neural net trained to anticipate subsequent musical notes in MIDI music files. It can produce tunes with 10 instruments in 15 styles. According to The Verge, a song generated by MuseNet tends to begin fairly however then fall under [turmoil](http://forum.ffmc59.fr) the longer it plays. [230] [231] In pop culture, initial applications of this tool were used as early as 2020 for the web psychological thriller Ben Drowned to produce music for the titular character. [232] [233]
 <br>Jukebox<br>
 <br>Released in 2020, Jukebox is an open-sourced algorithm to create music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a bit of lyrics and outputs tune samples. OpenAI stated the songs "show regional musical coherence [and] follow traditional chord patterns" however acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that repeat" and that "there is a substantial space" in between Jukebox and human-generated music. The Verge stated "It's highly excellent, even if the results sound like mushy variations of tunes that might feel familiar", while Business Insider specified "remarkably, a few of the resulting songs are memorable and sound legitimate". [234] [235] [236]
 <br>Interface<br>
 <br>Debate Game<br>
 <br>In 2018, OpenAI launched the Debate Game, which teaches machines to discuss toy issues in front of a human judge. The function is to research whether such a method might assist in auditing [AI](https://www.top5stockbroker.com) decisions and in developing explainable [AI](https://gitea.scalz.cloud). [237] [238]
 <br>Microscope<br>
 <br>Released in 2020, Microscope [239] is a collection of [visualizations](http://gitz.zhixinhuixue.net18880) of every significant layer and neuron of 8 neural network models which are [typically studied](https://git.hackercan.dev) in interpretability. [240] Microscope was developed to evaluate the functions that form inside these neural networks easily. The models consisted of are AlexNet, VGG-19, different variations of Inception, and different versions of CLIP Resnet. [241]
 <br>ChatGPT<br>
 <br>Launched in November 2022, ChatGPT is an expert system tool constructed on top of GPT-3 that provides a conversational user interface that enables users to ask questions in natural language. The system then responds with a response within seconds.<br>