Announced in 2016, Gym is an open-source Python library developed to assist in the advancement of reinforcement learning algorithms. It aimed to standardize how environments are defined in AI research, making published research study more quickly reproducible [24] [144] while providing users with a basic user interface for connecting with these environments. In 2022, new developments of Gym have actually been relocated to the library Gymnasium. [145] [146]
Gym Retro

Released in 2018, is a platform for reinforcement learning (RL) research on video games [147] utilizing RL algorithms and research study generalization. Prior RL research focused mainly on enhancing agents to fix single tasks. Gym Retro gives the ability to generalize in between video games with comparable concepts but different appearances.

RoboSumo

Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic agents at first do not have understanding of how to even walk, however are offered the goals of learning to move and to press the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the representatives find out how to adapt to altering conditions. When an agent is then eliminated from this virtual environment and placed in a new virtual environment with high winds, the representative braces to remain upright, recommending it had actually found out how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition in between representatives might develop an intelligence "arms race" that could increase an agent's ability to function even outside the context of the competitors. [148]
OpenAI 5

OpenAI Five is a group of five OpenAI-curated bots utilized in the competitive five-on-five computer game Dota 2, that find out to play against human gamers at a high ability level entirely through experimental algorithms. Before ending up being a group of 5, the very first public demonstration occurred at The International 2017, the yearly best champion competition for the video game, where Dendi, a professional Ukrainian player, 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 2 weeks of actual time, which the learning software was a step in the direction of creating software that can manage complicated tasks like a surgeon. [152] [153] The system utilizes a kind of support knowing, as the bots learn in time by playing against themselves numerous times a day for months, and are rewarded for actions such as killing an enemy and taking map objectives. [154] [155] [156]
By June 2018, the capability of the bots broadened 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 gamers, however wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the ruling world champs 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 total video games in a four-day open online competitors, winning 99.4% of those games. [165]
OpenAI 5's systems in Dota 2's bot player shows the difficulties of AI systems in multiplayer online fight arena (MOBA) games and how OpenAI Five has actually demonstrated making use of deep support knowing (DRL) agents to attain superhuman proficiency in Dota 2 matches. [166]
Dactyl

Developed in 2018, Dactyl uses machine learning to train a Shadow Hand, a human-like robotic hand, to manipulate physical things. [167] It discovers totally in simulation using the exact same RL algorithms and training code as OpenAI Five. OpenAI took on the object orientation issue by using domain randomization, a simulation technique which exposes the student to a variety of experiences rather than trying to fit to reality. The set-up for Dactyl, aside from having movement tracking cameras, wiki.snooze-hotelsoftware.de likewise has RGB cams to permit the robotic to control an approximate item 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 demonstrated that Dactyl could solve a Rubik's Cube. The robot had the ability to resolve the puzzle 60% of the time. Objects like the Rubik's Cube present complicated physics that is harder to model. OpenAI did this by enhancing the toughness of Dactyl to perturbations by using Automatic Domain Randomization (ADR), a simulation approach of creating gradually harder environments. ADR varies from manual domain randomization by not requiring a human to define randomization ranges. [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 task". [170] [171]
Text generation

The business has popularized generative pretrained transformers (GPT). [172]
OpenAI's original GPT model ("GPT-1")

The initial paper on generative pre-training of a transformer-based language model was written by Alec Radford and his associates, and released in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative model of language could obtain world understanding and process long-range dependences by pre-training on a varied corpus with long stretches of contiguous text.

GPT-2

Generative Pre-trained Transformer 2 ("GPT-2") is an unsupervised transformer language model and the successor to OpenAI's original GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with just limited demonstrative versions at first launched to the public. The complete version of GPT-2 was not right away released due to issue about potential abuse, consisting of applications for composing phony news. [174] Some professionals expressed uncertainty that GPT-2 positioned a significant threat.

In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to spot "neural fake news". [175] Other scientists, such as Jeremy Howard, warned of "the technology to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be difficult to filter". [176] In November 2019, OpenAI launched the total version of the GPT-2 language model. [177] Several websites host interactive demonstrations of different instances of GPT-2 and other transformer models. [178] [179] [180]
GPT-2's authors argue without supervision language models to be general-purpose learners, illustrated by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the design was not additional trained on any task-specific input-output examples).

The corpus it was trained on, called WebText, contains somewhat 40 gigabytes 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 permits representing any string of characters by encoding both specific characters and multiple-character tokens. [181]
GPT-3

First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is a not being watched transformer language design and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the full variation of GPT-3 contained 175 billion parameters, [184] 2 orders of magnitude bigger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 designs with as couple of as 125 million specifications were also trained). [186]
OpenAI mentioned that GPT-3 succeeded at certain "meta-learning" jobs and wiki.snooze-hotelsoftware.de might generalize the function 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 between English and raovatonline.org German. [184]
GPT-3 drastically improved benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or experiencing the fundamental ability constraints of predictive language designs. [187] Pre-training GPT-3 required several thousand petaflop/s-days [b] of calculate, 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 instantly released to the general public for concerns of possible abuse, although OpenAI planned to permit gain access to through a paid cloud API after a two-month free personal beta that began in June 2020. [170] [189]
On September 23, 2020, GPT-3 was certified exclusively to Microsoft. [190] [191]
Codex

Announced in mid-2021, Codex is a descendant of GPT-3 that has actually 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 released in personal beta. [194] According to OpenAI, the model can produce working code in over a dozen programming languages, a lot of effectively in Python. [192]
Several issues with problems, style flaws and security vulnerabilities were pointed out. [195] [196]
GitHub Copilot has been accused of producing copyrighted code, with no author attribution or license. [197]
OpenAI revealed that they would terminate 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), efficient in accepting text or image inputs. [199] They announced that the updated innovation passed a simulated law school bar test with a rating around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also read, analyze or create up to 25,000 words of text, and compose code in all significant shows languages. [200]
Observers reported that the model of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based model, with the caveat 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 decreased to reveal numerous technical details and statistics about GPT-4, such as the exact size of the design. [203]
GPT-4o

On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and generate text, images and audio. [204] GPT-4o attained advanced outcomes in voice, multilingual, and vision criteria, setting new records in audio speech acknowledgment 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 launched GPT-4o mini, a smaller sized variation of GPT-4o changing 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 expects it to be especially useful for business, startups and developers seeking to automate services with AI representatives. [208]
o1

On September 12, 2024, pediascape.science OpenAI launched the o1-preview and o1-mini models, which have actually been designed to take more time to consider their actions, leading to higher accuracy. These models are especially effective in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and setiathome.berkeley.edu Staff member. [209] [210] In December 2024, o1-preview was changed by o1. [211]
o3

On December 20, 2024, OpenAI revealed o3, the successor of the o1 reasoning design. OpenAI also unveiled o3-mini, a lighter and quicker version of OpenAI o3. As of 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, safety and security scientists had the opportunity to obtain early access to these models. [214] The model is called o3 rather than o2 to avoid confusion with telecoms providers O2. [215]
Deep research study

Deep research is a representative established by OpenAI, unveiled on February 2, 2025. It leverages the abilities of OpenAI's o3 design to perform extensive web surfing, data analysis, setiathome.berkeley.edu and synthesis, delivering detailed reports within a timeframe of 5 to 30 minutes. [216] With browsing and Python tools made it possible for, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120]
Image category

CLIP

Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to evaluate the semantic resemblance in between text and images. It can notably be utilized for image classification. [217]
Text-to-image

DALL-E

Revealed in 2021, DALL-E is a Transformer design that creates images from textual descriptions. [218] DALL-E uses a 12-billion-parameter version of GPT-3 to analyze natural language inputs (such as "a green leather bag shaped like a pentagon" or "an isometric view of a sad capybara") and generate matching images. It can create images of reasonable items ("a stained-glass window with a picture of a blue strawberry") as well as things that do not exist in truth ("a cube with the texture of a porcupine"). As of March 2021, no API or code is available.

DALL-E 2

In April 2022, OpenAI revealed DALL-E 2, an upgraded variation of the model with more practical outcomes. [219] In December 2022, OpenAI published on GitHub software application for Point-E, a brand-new basic system for transforming a text description into a 3-dimensional design. [220]
DALL-E 3

In September 2023, OpenAI revealed DALL-E 3, a more powerful design better able to create images from complex descriptions without manual timely engineering and render intricate details like hands and text. [221] It was released to the general public as a ChatGPT Plus feature in October. [222]
Text-to-video

Sora

Sora is a text-to-video design that can produce videos based upon brief detailed prompts [223] along with extend existing videos forwards or in reverse in time. [224] It can create videos with resolution as much as 1920x1080 or 1080x1920. The maximal length of produced videos is unknown.

Sora's advancement group called it after the Japanese word for "sky", to symbolize its "limitless creative potential". [223] Sora's technology is an adaptation of the innovation behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system utilizing publicly-available videos along with copyrighted videos accredited for that purpose, however did not reveal the number or the exact sources of the videos. [223]
OpenAI demonstrated some Sora-created high-definition videos to the general public on February 15, 2024, stating that it might produce videos approximately one minute long. It also shared a technical report highlighting the approaches used to train the model, and the model's abilities. [225] It acknowledged a few of its drawbacks, consisting of battles imitating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "outstanding", however noted that they need to have been cherry-picked and may not represent Sora's common output. [225]
Despite uncertainty from some academic leaders following Sora's public demo, significant entertainment-industry figures have actually revealed substantial interest in the technology's potential. In an interview, actor/filmmaker Tyler Perry revealed his awe at the innovation's capability to generate reasonable video from text descriptions, mentioning its possible to revolutionize storytelling and material production. He said that his excitement about Sora's possibilities was so strong that he had decided to stop briefly strategies for expanding his Atlanta-based motion picture 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 likewise a multi-task design that can carry out multilingual speech acknowledgment along with 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 generate songs with 10 instruments in 15 designs. According to The Verge, pipewiki.org a tune generated by MuseNet tends to begin fairly but then fall under chaos the longer it plays. [230] [231] In popular culture, preliminary applications of this tool were used as early as 2020 for the internet 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 category, artist, and a snippet of lyrics and outputs tune samples. OpenAI specified the tunes "reveal regional musical coherence [and] follow conventional chord patterns" however acknowledged that the tunes lack "familiar larger musical structures such as choruses that duplicate" and that "there is a significant gap" between Jukebox and human-generated music. The Verge stated "It's technically impressive, even if the outcomes sound like mushy variations of tunes that may feel familiar", while Business Insider stated "remarkably, some of the resulting songs are appealing and sound genuine". [234] [235] [236]
Interface

Debate Game

In 2018, OpenAI introduced the Debate Game, which teaches devices to dispute toy problems in front of a human judge. The function is to research whether such an approach may assist in auditing AI choices and in establishing explainable AI. [237] [238]
Microscope

Released in 2020, Microscope [239] is a collection of visualizations of every substantial layer and neuron of eight neural network designs which are frequently studied in interpretability. [240] Microscope was created to examine the features that form inside these neural networks easily. The models included are AlexNet, VGG-19, different variations of Inception, and various versions of CLIP Resnet. [241]
ChatGPT

Launched in November 2022, ChatGPT is an expert system tool constructed on top of GPT-3 that offers a conversational user interface that enables users to ask concerns in natural language. The system then responds with an answer within seconds.