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Announced in 2016, Gym is an open-source Python library developed to facilitate the development of support knowing algorithms. It aimed to standardize how environments are specified in AI research study, making published research more quickly reproducible [24] [144] while supplying users with a basic interface for engaging with these environments. In 2022, brand-new developments of Gym have been transferred to the library Gymnasium. [145] [146]
Gym Retro
Released in 2018, Gym Retro is a platform for reinforcement learning (RL) research study on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research study focused mainly on enhancing agents to solve single tasks. Gym Retro offers the capability to generalize between games with comparable ideas but different looks.
RoboSumo
Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot representatives initially lack knowledge of how to even walk, however are provided the goals of discovering to move and to push the opposing agent out of the ring. [148] Through this adversarial learning procedure, the representatives learn how to adapt to changing conditions. When a representative is then removed 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 balance in a generalized method. [148] [149] OpenAI's Igor Mordatch argued that competitors in between representatives could create an intelligence "arms race" that might increase a representative's ability to operate even outside the context of the competitors. [148]
OpenAI 5
OpenAI Five is a team of five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that find out to play against human players at a high skill level entirely through trial-and-error wiki.vst.hs-furtwangen.de algorithms. Before ending up being a group of 5, the first public demonstration happened at The International 2017, the annual premiere 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 learned by playing against itself for 2 weeks of real time, which the knowing software application was a step in the direction of developing software that can deal with complicated tasks like a surgeon. [152] [153] The system uses a kind of reinforcement knowing, as the bots find out over time by playing against themselves numerous times a day for months, and are rewarded for actions such as killing an opponent and taking map goals. [154] [155] [156]
By June 2018, the capability of the bots expanded to play together as a full group of 5, and they were able to beat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibit matches against expert gamers, however ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champions of the game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' last public appearance came later on that month, where they played in 42,729 overall video games in a four-day open online competition, winning 99.4% of those video games. [165]
OpenAI 5's mechanisms in Dota 2's bot player shows the challenges of AI systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has demonstrated making use of deep support learning (DRL) agents to skills in Dota 2 matches. [166]
Dactyl
Developed in 2018, Dactyl uses device learning to train a Shadow Hand, a human-like robotic hand, to control physical items. [167] It discovers totally in simulation utilizing the exact same RL algorithms and training code as OpenAI Five. OpenAI tackled the things orientation issue by utilizing domain randomization, a simulation method which exposes the learner to a variety of experiences rather than attempting to fit to reality. The set-up for Dactyl, aside from having motion tracking cameras, also has RGB cameras to allow the robotic to manipulate 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]
In 2019, OpenAI showed that Dactyl could resolve a Rubik's Cube. The robot had the ability to fix the puzzle 60% of the time. Objects like the Rubik's Cube present intricate physics that is harder to model. OpenAI did this by improving the effectiveness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of generating gradually harder environments. ADR varies from manual domain randomization by not requiring a human to define randomization varieties. [169]
API
In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing brand-new AI designs established by OpenAI" to let designers get in touch with it for "any English language AI job". [170] [171]
Text generation
The company has popularized generative pretrained transformers (GPT). [172]
OpenAI's original GPT model ("GPT-1")
The original paper on generative pre-training of a transformer-based language model was composed by Alec Radford and his colleagues, and released in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative design of language could obtain world understanding and process long-range dependences by pre-training on a diverse corpus with long stretches of adjoining text.
GPT-2
Generative Pre-trained Transformer 2 ("GPT-2") is a without supervision transformer language model and the follower to OpenAI's initial GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just restricted demonstrative variations at first released to the public. The full variation of GPT-2 was not right away released due to concern about prospective misuse, consisting of applications for composing phony news. [174] Some experts revealed uncertainty that GPT-2 positioned a considerable risk.
In reaction to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to spot "neural phony news". [175] Other researchers, such as Jeremy Howard, warned of "the innovation to completely 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 total variation of the GPT-2 language model. [177] Several sites host interactive presentations of different circumstances of GPT-2 and other transformer designs. [178] [179] [180]
GPT-2's authors argue without supervision language designs to be general-purpose learners, shown by GPT-2 attaining state-of-the-art precision and perplexity on 7 of 8 zero-shot tasks (i.e. the model was not additional trained on any task-specific input-output examples).
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 issues encoding vocabulary with word tokens by using byte pair encoding. This allows representing any string of characters by encoding both private characters and multiple-character tokens. [181]
GPT-3
First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is a without supervision transformer language model and the follower to GPT-2. [182] [183] [184] OpenAI stated that the full version of GPT-3 contained 175 billion specifications, [184] two orders of magnitude larger than the 1.5 billion [185] in the full variation of GPT-2 (although GPT-3 models with as few as 125 million criteria were also trained). [186]
OpenAI stated that GPT-3 was successful at certain "meta-learning" jobs and might generalize the purpose of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer learning in between English and Romanian, and between English and German. [184]
GPT-3 considerably enhanced benchmark outcomes over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or experiencing the essential capability constraints of predictive language models. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of calculate, compared to tens of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not immediately released to the public for concerns of possible abuse, although OpenAI planned to permit gain access to through a paid cloud API after a two-month free private beta that began in June 2020. [170] [189]
On September 23, 2020, GPT-3 was certified solely to Microsoft. [190] [191]
Codex
Announced in mid-2021, Codex is a descendant of GPT-3 that has in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the AI powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the design can produce working code in over a lots programming languages, many efficiently in Python. [192]
Several concerns with glitches, style flaws and security vulnerabilities were pointed out. [195] [196]
GitHub Copilot has been implicated of discharging copyrighted code, without any author attribution or license. [197]
OpenAI revealed that they would stop assistance for Codex API on March 23, 2023. [198]
GPT-4
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 examination with a score around the leading 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 as much as 25,000 words of text, and compose code in all significant programming languages. [200]
Observers reported that the model of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based iteration, 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 declined to expose different technical details and data about GPT-4, such as the accurate size of the model. [203]
GPT-4o
On May 13, 2024, OpenAI revealed and released GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained advanced lead to 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]
On July 18, 2024, OpenAI released GPT-4o mini, a smaller variation of GPT-4o replacing GPT-3.5 Turbo on the ChatGPT user 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 especially useful for business, start-ups and designers seeking to automate services with AI agents. [208]
o1
On September 12, 2024, OpenAI released the o1-preview and o1-mini designs, which have been created to take more time to consider their responses, causing greater accuracy. These models are especially effective in science, coding, and thinking jobs, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was replaced by o1. [211]
o3
On December 20, 2024, OpenAI revealed o3, the follower of the o1 reasoning model. OpenAI likewise revealed o3-mini, a lighter and quicker variation of OpenAI o3. Since December 21, 2024, this model is not available for public usage. According to OpenAI, they are evaluating o3 and o3-mini. [212] [213] Until January 10, 2025, security and security researchers had the chance to obtain early access to these designs. [214] The design is called o3 instead of o2 to prevent confusion with telecoms services provider O2. [215]
Deep research study
Deep research is an agent established by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 design to perform comprehensive web browsing, information analysis, and synthesis, providing detailed reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools allowed, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120]
Image classification
CLIP
Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a design that is trained to examine the semantic similarity between text and images. It can significantly be used for image classification. [217]
Text-to-image
DALL-E
Revealed in 2021, DALL-E is a Transformer model that produces images from textual descriptions. [218] DALL-E uses a 12-billion-parameter variation of GPT-3 to translate natural language inputs (such as "a green leather bag formed like a pentagon" or "an isometric view of an unfortunate capybara") and produce corresponding images. It can produce pictures of sensible objects ("a stained-glass window with an image of a blue strawberry") in addition to objects that do not exist in truth ("a cube with the texture of a porcupine"). Since March 2021, no API or code is available.
DALL-E 2
In April 2022, OpenAI announced DALL-E 2, an upgraded version of the model with more practical outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a new rudimentary system for transforming a text description into a 3-dimensional model. [220]
DALL-E 3
In September 2023, OpenAI announced DALL-E 3, a more effective model much better able to generate images from complicated descriptions without manual timely engineering and render complex details like hands and text. [221] It was launched to the general public as a ChatGPT Plus function in October. [222]
Text-to-video
Sora
Sora is a text-to-video model that can produce videos based on short detailed prompts [223] as well as extend existing videos forwards or backwards in time. [224] It can generate videos with resolution as much as 1920x1080 or 1080x1920. The optimum length of created videos is unknown.
Sora's advancement group called it after the Japanese word for "sky", to represent its "unlimited innovative potential". [223] Sora's innovation is an adjustment of the technology behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos in addition to copyrighted videos accredited for that purpose, but did not expose the number or the specific sources of the videos. [223]
OpenAI showed some Sora-created high-definition videos to the general public on February 15, 2024, mentioning that it could generate videos approximately one minute long. It also shared a technical report highlighting the approaches utilized to train the design, and the model's abilities. [225] It acknowledged some of its drawbacks, consisting of battles replicating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "impressive", however kept in mind that they must have been cherry-picked and might not represent Sora's typical output. [225]
Despite uncertainty from some scholastic leaders following Sora's public demo, noteworthy entertainment-industry figures have actually revealed substantial interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry expressed his awe at the innovation's ability to produce realistic video from text descriptions, mentioning its possible to change storytelling and content creation. He said that his excitement about Sora's possibilities was so strong that he had actually decided to stop briefly plans for broadening his Atlanta-based film studio. [227]
Speech-to-text
Whisper
Released in 2022, Whisper is a general-purpose speech recognition design. [228] It is trained on a large dataset of varied audio and is also a multi-task design that can perform multilingual speech recognition in addition to speech translation and language recognition. [229]
Music generation
MuseNet
Released in 2019, MuseNet is a deep neural net trained to anticipate subsequent musical notes in MIDI music files. It can produce songs with 10 instruments in 15 designs. According to The Verge, a tune generated by MuseNet tends to begin fairly however then fall into turmoil the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were utilized as early as 2020 for the web mental thriller Ben Drowned to create music for the titular character. [232] [233]
Jukebox
Released in 2020, Jukebox is an open-sourced algorithm to generate music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a bit of lyrics and outputs tune samples. OpenAI specified the songs "show local musical coherence [and] follow conventional chord patterns" but acknowledged that the tunes lack "familiar bigger musical structures such as choruses that repeat" which "there is a substantial space" between Jukebox and human-generated music. The Verge stated "It's technologically excellent, even if the outcomes seem like mushy versions of tunes that may feel familiar", while Business Insider stated "remarkably, some of the resulting tunes are catchy and sound legitimate". [234] [235] [236]
User interfaces
Debate Game
In 2018, OpenAI launched the Debate Game, which teaches makers to debate toy issues in front of a human judge. The function is to research whether such a technique may help in auditing AI choices and in developing explainable AI. [237] [238]
Microscope
Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and neuron of 8 neural network designs which are frequently studied in interpretability. [240] Microscope was produced to examine the functions that form inside these neural networks quickly. The models consisted of are AlexNet, VGG-19, various versions of Inception, and various variations of CLIP Resnet. [241]
ChatGPT
Launched in November 2022, ChatGPT is an artificial intelligence tool constructed on top of GPT-3 that supplies a conversational user interface that permits users to ask questions in natural language. The system then responds with a response within seconds.
這將刪除頁面 "The Verge Stated It's Technologically Impressive"
。請三思而後行。