smarthr

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

Released in 2018, Gym Retro is a platform for reinforcement knowing (RL) research on video games [147] using RL algorithms and research study generalization. Prior RL research focused mainly on optimizing representatives to resolve single tasks. Gym Retro gives the ability to generalize between games with comparable concepts however various appearances.

RoboSumo

Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents at first do not have understanding of how to even stroll, but are given the objectives of finding out to move and to push the opposing representative out of the ring. [148] Through this adversarial knowing procedure, the representatives discover how to adjust to altering conditions. When an agent is then eliminated from this virtual environment and positioned in a brand-new virtual environment with high winds, the agent braces to remain upright, recommending it had found out how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives could produce an intelligence "arms race" that might increase an agent's capability to operate even outside the context of the competition. [148]
OpenAI 5

OpenAI Five is a group of five OpenAI-curated bots used in the competitive five-on-five video game Dota 2, that find out to play against human gamers at a high ability level entirely through trial-and-error algorithms. Before becoming a group of 5, the first public demonstration occurred at The International 2017, the yearly premiere championship tournament for the video game, where Dendi, a professional 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 discovered by playing against itself for 2 weeks of actual time, and that the learning software was a step in the instructions of creating software that can manage complex tasks like a cosmetic surgeon. [152] [153] The system uses a type of reinforcement knowing, as the bots discover over time by playing against themselves numerous times a day for months, and are rewarded for kousokuwiki.org actions such as killing an enemy and taking map goals. [154] [155] [156]
By June 2018, the ability of the bots broadened to play together as a complete group of 5, and they had the ability to beat teams of amateur and semi-professional gamers. [157] [154] [158] [159] At The International 2018, OpenAI Five played in 2 exhibition matches against expert gamers, but ended up losing both video games. [160] [161] [162] In April 2019, OpenAI Five beat OG, the reigning world champs of the video game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' last public appearance came later that month, where they played in 42,729 overall games in a four-day open online competitors, winning 99.4% of those games. [165]
OpenAI 5's mechanisms in Dota 2's bot gamer shows the challenges of AI systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has demonstrated the usage of deep reinforcement learning (DRL) agents to attain superhuman skills in Dota 2 matches. [166]
Dactyl

Developed in 2018, Dactyl uses machine learning to train a Shadow Hand, a human-like robot hand, to manipulate physical items. [167] It discovers totally in simulation using the very same RL algorithms and training code as OpenAI Five. OpenAI took on the object orientation problem by utilizing domain randomization, a simulation approach which exposes the learner to a range of experiences rather than trying to fit to reality. The set-up for Dactyl, aside from having motion tracking video cameras, also has RGB cameras to allow the robotic to control an arbitrary item by seeing it. In 2018, OpenAI revealed that the system had the ability to control a cube and an octagonal prism. [168]
In 2019, hb9lc.org OpenAI showed that Dactyl might solve a Rubik's Cube. The robotic had the ability to resolve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex physics that is harder to design. OpenAI did this by improving the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation method of creating progressively more tough environments. ADR differs from manual domain randomization by not requiring a human to specify randomization ranges. [169]
API

In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new AI models established by OpenAI" to let designers contact it for "any English language AI job". [170] [171]
Text generation

The company has promoted generative pretrained transformers (GPT). [172]
OpenAI's original GPT design ("GPT-1")

The original paper on generative pre-training of a transformer-based language design 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 design of language could obtain world knowledge 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 an unsupervised transformer language design and the successor to OpenAI's initial GPT design ("GPT-1"). GPT-2 was announced in February 2019, with only limited demonstrative variations initially released to the public. The complete variation of GPT-2 was not instantly released due to issue about possible misuse, consisting of applications for composing phony news. [174] Some professionals revealed uncertainty that GPT-2 presented a significant threat.

In response to GPT-2, the Allen Institute for Artificial Intelligence reacted with a tool to identify "neural fake news". [175] Other researchers, such as Jeremy Howard, cautioned of "the technology to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be impossible to filter". [176] In November 2019, OpenAI released the complete version of the GPT-2 language design. [177] Several sites host interactive presentations of various instances of GPT-2 and other transformer models. [178] [179] [180]
GPT-2's authors argue without supervision language models to be general-purpose students, shown by GPT-2 attaining state-of-the-art 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).

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 avoids certain issues 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 an unsupervised transformer and the successor to GPT-2. [182] [183] [184] OpenAI stated that the complete variation of GPT-3 contained 175 billion specifications, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 models with as couple of as 125 million specifications were also trained). [186]
OpenAI mentioned that GPT-3 prospered at certain "meta-learning" tasks and could generalize the function of a single input-output pair. The GPT-3 release paper offered examples of translation and cross-linguistic transfer knowing in between English and Romanian, and in between English and German. [184]
GPT-3 dramatically improved benchmark results over GPT-2. OpenAI warned that such scaling-up of language designs might be approaching or experiencing the essential ability constraints of predictive language models. [187] Pre-training GPT-3 needed a number of 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 right away launched to the 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]
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 additionally 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 private beta. [194] According to OpenAI, the design can produce working code in over a dozen shows languages, the majority of effectively in Python. [192]
Several issues with glitches, style defects and security vulnerabilities were pointed out. [195] [196]
GitHub Copilot has actually been accused of emitting copyrighted code, without any author attribution or license. [197]
OpenAI announced that they would discontinue 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 revealed that the upgraded technology passed a simulated law school bar examination 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 might also check out, analyze or generate as much as 25,000 words of text, and write code in all major shows languages. [200]
Observers reported that the iteration of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 retained a few of the issues with earlier revisions. [201] GPT-4 is also efficient in taking images as input on ChatGPT. [202] OpenAI has actually decreased to reveal different technical details and data about GPT-4, such as the accurate size of the model. [203]
GPT-4o

On May 13, 2024, OpenAI announced and released GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained modern 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) benchmark compared to 86.5% by GPT-4. [207]
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 it to be particularly helpful for enterprises, start-ups and developers looking for to automate services with AI representatives. [208]
o1

On September 12, wiki.lafabriquedelalogistique.fr 2024, OpenAI launched the o1-preview and trademarketclassifieds.com o1-mini designs, which have been designed to take more time to think about their actions, leading to greater precision. These models are especially effective 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]
o3

On December 20, 2024, OpenAI unveiled o3, the successor of the o1 reasoning model. OpenAI likewise revealed o3-mini, a lighter and faster variation of OpenAI o3. Since December 21, 2024, this model is not available for public use. According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, safety and security scientists had the chance to obtain early access to these models. [214] The model is called o3 instead of o2 to avoid confusion with telecommunications companies O2. [215]
Deep research

Deep research study is a representative established by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out comprehensive web browsing, information analysis, and synthesis, providing 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) benchmark. [120]
Image category

CLIP

Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to analyze the semantic similarity between text and images. It can notably be used 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 utilizes a 12-billion-parameter version of GPT-3 to interpret natural language inputs (such as "a green leather handbag shaped like a pentagon" or "an isometric view of a sad capybara") and produce corresponding images. It can develop images of sensible items ("a stained-glass window with an image of a blue strawberry") in addition to items 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 updated variation of the design with more reasonable results. [219] In December 2022, OpenAI published on GitHub software for Point-E, a brand-new primary system for transforming a text description into a 3-dimensional model. [220]
DALL-E 3

In September 2023, OpenAI revealed DALL-E 3, a more effective design much better able to produce images from intricate 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 function in October. [222]
Text-to-video

Sora

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

Sora's development team called it after the Japanese word for "sky", to symbolize its "endless creative potential". [223] Sora's innovation is an adjustment of the innovation behind the DALL · E 3 text-to-image design. [225] OpenAI trained the system using publicly-available videos as well as copyrighted videos licensed for that purpose, however did not expose the number or the specific sources of the videos. [223]
OpenAI demonstrated some Sora-created high-definition videos to the public on February 15, trademarketclassifieds.com 2024, mentioning that it might create videos approximately one minute long. It also shared a technical report highlighting the techniques utilized to train the model, and the design's capabilities. [225] It acknowledged a few of its drawbacks, including battles imitating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "excellent", 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 demonstration, significant entertainment-industry figures have revealed substantial interest in the innovation's potential. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the technology's capability to generate reasonable video from text descriptions, citing its potential to change storytelling and content creation. He said that his excitement about Sora's possibilities was so strong that he had actually decided to pause strategies for expanding his Atlanta-based film studio. [227]
Speech-to-text

Whisper

Released in 2022, Whisper is a general-purpose speech acknowledgment design. [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]
Music generation

MuseNet

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 designs. According to The Verge, a tune generated by MuseNet tends to start fairly however then fall under chaos the longer it plays. [230] [231] In pop culture, initial applications of this tool were utilized as early as 2020 for the internet psychological thriller Ben Drowned to produce music for the titular character. [232] [233]
Jukebox

Released in 2020, Jukebox is an open-sourced algorithm to produce 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 stated the songs "show local musical coherence [and] follow standard chord patterns" but acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that repeat" and that "there is a considerable space" between Jukebox and human-generated music. The Verge mentioned "It's highly excellent, even if the results seem like mushy variations of songs that may feel familiar", while Business Insider mentioned "remarkably, some of the resulting songs are appealing and sound genuine". [234] [235] [236]
User interfaces

Debate Game

In 2018, OpenAI launched the Debate Game, which teaches machines to discuss toy problems in front of a human judge. The purpose is to research whether such a method may help in auditing AI decisions 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 often studied in interpretability. [240] Microscope was produced to analyze the features that form inside these neural networks quickly. The models included are AlexNet, VGG-19, different versions of Inception, yewiki.org and different versions of CLIP Resnet. [241]
ChatGPT

Launched in November 2022, ChatGPT is an expert system tool developed on top of GPT-3 that provides a conversational interface that allows users to ask questions in natural language. The system then reacts with an answer within seconds.