GPT-4: Difference between revisions
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reorganize Limitations into new top-level section, performed copyedits including removing The Verge (failed verification; the article is exclusively about ChatGPT, only mentioning GPT-4 as "Bing" in passing) -- needs improvement but I think an important section to ensure the article's neutrality and to reorganize the various mentions of the model's limitations into one place |
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A report by [[Microsoft]] has found that GPT-4 may act unreliably when used in the medical field. In their test example GPT-4 added fabricated details to a patient's notes.<ref name="Vincent-2023">{{Cite web |last=Vincent |first=James |date=February 17, 2023 |title=As conservatives criticize 'woke AI,' here are ChatGPT's rules for answering culture war queries |url=https://www.theverge.com/2023/2/17/23603906/openai-chatgpt-woke-criticism-culture-war-rules |access-date=March 1, 2023 |website=The Verge |language=en-US |archive-date=March 1, 2023 |archive-url=https://web.archive.org/web/20230301151934/https://www.theverge.com/2023/2/17/23603906/openai-chatgpt-woke-criticism-culture-war-rules |url-status=live }}</ref> |
A report by [[Microsoft]] has found that GPT-4 may act unreliably when used in the medical field. In their test example GPT-4 added fabricated details to a patient's notes.<ref name="Vincent-2023">{{Cite web |last=Vincent |first=James |date=February 17, 2023 |title=As conservatives criticize 'woke AI,' here are ChatGPT's rules for answering culture war queries |url=https://www.theverge.com/2023/2/17/23603906/openai-chatgpt-woke-criticism-culture-war-rules |access-date=March 1, 2023 |website=The Verge |language=en-US |archive-date=March 1, 2023 |archive-url=https://web.archive.org/web/20230301151934/https://www.theverge.com/2023/2/17/23603906/openai-chatgpt-woke-criticism-culture-war-rules |url-status=live }}</ref> |
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In April 2023 Microsoft and [[Epic Systems]] announced that they will provide healthcare providers with GPT-4 powered systems for assisting in responding to questions from patients and analysing medical records.<ref>{{Cite web |last=Edwards |first=Benj |date=2023-04-18 |title=GPT-4 will hunt for trends in medical records thanks to Microsoft and Epic |url=https://arstechnica.com/information-technology/2023/04/gpt-4-will-hunt-for-trends-in-medical-records-thanks-to-microsoft-and-epic/ |access-date=2023-05-03 |website=Ars Technica |language=en-us}}</ref> |
In April 2023, Microsoft and [[Epic Systems]] announced that they will provide healthcare providers with GPT-4 powered systems for assisting in responding to questions from patients and analysing medical records.<ref>{{Cite web |last=Edwards |first=Benj |date=2023-04-18 |title=GPT-4 will hunt for trends in medical records thanks to Microsoft and Epic |url=https://arstechnica.com/information-technology/2023/04/gpt-4-will-hunt-for-trends-in-medical-records-thanks-to-microsoft-and-epic/ |access-date=2023-05-03 |website=Ars Technica |language=en-us}}</ref> |
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== Limitations == |
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Like its predecessors, GPT-4 has been known to [[Hallucination (artificial intelligence)|hallucinate]], meaning that the outputs may include information not in the training data or that contradicts the user's prompt.<ref>{{Cite news |date=March 14, 2023 |title=10 Ways GPT-4 Is Impressive but Still Flawed |newspaper=The New York Times |url=https://www.nytimes.com/2023/03/14/technology/openai-new-gpt4.html |url-status=live |access-date=March 20, 2023 |archive-url=https://web.archive.org/web/20230314180712/https://www.nytimes.com/2023/03/14/technology/openai-new-gpt4.html |archive-date=March 14, 2023}}</ref> |
Like its predecessors, GPT-4 has been known to [[Hallucination (artificial intelligence)|hallucinate]], meaning that the outputs may include information not in the training data or that contradicts the user's prompt.<ref>{{Cite news |date=March 14, 2023 |title=10 Ways GPT-4 Is Impressive but Still Flawed |newspaper=The New York Times |url=https://www.nytimes.com/2023/03/14/technology/openai-new-gpt4.html |url-status=live |access-date=March 20, 2023 |archive-url=https://web.archive.org/web/20230314180712/https://www.nytimes.com/2023/03/14/technology/openai-new-gpt4.html |archive-date=March 14, 2023}}</ref> |
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⚫ | GPT-4 also lacks transparency in its decision-making processes. If requested, the model is able to provide an explanation as to how and why it makes its decisions but these explanations are formed post-hoc; it's impossible to verify if those explanations truly reflect the actual process. In many cases, when asked to explain its logic, GPT-4 will give explanations that directly contradict its previous statements.{{Citation needed|date=May 2023}} |
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Another limitation of GPT-4 is that it lacks an ability to plan its actions before performing them. For example, it can not produce a poem in which the first word of each sentence is the same as the last word of the previous sentence because it can not consider the structure of a sentence before writing it.<ref name="Vincent-2023" /> |
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GPT-4 was trained in two stages. First, the model was given large datasets of text taken from the internet and trained to predict the next [[Lexical analysis#Token|token]] (roughly corresponding to a word) in those datasets. Second, human reviews are used to fine-tune the system in a process called [[reinforcement learning from human feedback]], which trains the model to refuse prompts which go against OpenAI's definition of harmful behavior, such as questions on how to perform illegal activities, advice on how to harm oneself or others, or requests for descriptions of graphic, violent, or sexual content.<ref name="OpenAI-2023" /> In the first stage, bias may be inherited from the training data; in the second stage, bias is inherent in the application of OpenAI's views. |
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GPT-4 has shown to have [[cognitive bias]]es such as [[confirmation bias]], [[Anchoring (cognitive bias)|anchoring]], and [[Base rate fallacy|base-rate neglect]].{{Citation needed|date=May 2023}} |
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⚫ | |||
GPT models are trained in two stages. First, they are given large datasets of text taken from the internet and they are trained to predict the next word in that dataset. Second, human reviews are used to fine tune the system in a process called [[reinforcement learning from human feedback]]. In both of these stages bias from the input may affect the final result.<ref name="OpenAI-2023" /> |
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GPT-4 has shown to have [[cognitive bias]]es such as [[confirmation bias]], [[Anchoring (cognitive bias)|anchoring]], and [[Base rate fallacy|base-rate neglect]] possibly inherited from the training data.<ref name="Vincent-2023" /> GPT-4 mitigates its bias by having a system to refuse prompts which go against it policy such as questions on how to perform illegal activities, advice on how to harm yourself or others, or requests for descriptions of graphicly violent or sexual content<ref name="OpenAI-2023" /> |
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== Training == |
== Training == |
Revision as of 02:52, 4 May 2023
Developer(s) | OpenAI |
---|---|
Initial release | March 14, 2023 |
Predecessor | GPT-3 |
Type | Autoregressive Multimodal Generative pre-trained transformer Large language model Foundation model |
Website | openai![]() |
Generative Pre-trained Transformer 4 (GPT-4) is a multimodal large language model created by OpenAI, and the fourth in its numbered "GPT-n" series of GPT foundation models.[1] It was released on March 14, 2023, and has been made publicly available in a limited form via the chatbot product ChatGPT Plus (a premium version of ChatGPT), and with access to the GPT-4 based version of OpenAI's API being provided via a waitlist.[1] As a transformer based model, GPT-4 was pretrained to predict the next token (using both public data and "data licensed from third-party providers"), and was then fine-tuned with reinforcement learning from human and AI feedback for human alignment and policy compliance.[2]: 2
Observers reported the GPT-4 based version of ChatGPT to be an improvement on the previous (GPT-3.5 based) ChatGPT, with the caveat that GPT-4 retains some of the same problems.[3] Unlike the predecessors, GPT-4 can take images as well as text as input.[4] OpenAI has declined to reveal technical information such as the size of the GPT-4 model.[5]
Background
OpenAI introduced the first GPT model (GPT-1) in 2018, publishing a paper called "Improving Language Understanding by Generative Pre-Training."[6] It was based on the transformer architecture and trained on a large corpus of books.[7] The next year, they introduced GPT-2, a larger model that could generate coherent text.[8] In 2020, they introduced GPT-3, a model with 100 times the number of parameters as GPT-2, that could perform various tasks with few examples.[9] GPT-3 was further improved into GPT-3.5, which was used to create the chatbot product ChatGPT.
Capabilities
OpenAI stated that GPT-4 is "more reliable, creative, and able to handle much more nuanced instructions than GPT-3.5."[10] They produced two versions of GPT-4, with context windows of 8,192 and 32,768 tokens, a significant improvement over GPT-3.5 and GPT-3, which were limited to 4,096 and 2,049 tokens respectively.[11] Unlike its predecessors, GPT-4 is a multimodal model: it can take images as well as text as input;[4] this gives it the ability to describe the humor in unusual images, summarize text from screenshots, and answer exam questions that contain diagrams.[12]
To gain further control over GPT-4, OpenAI introduced the "system message", a directive in natural language given to GPT-4 in order to specify its tone of voice and task. For example, the system message can instruct the model to "be a Shakespearean pirate", in which case it will respond in rhyming, Shakespearean prose, or request it to "always write the output of [its] response in JSON", in which case the model will do so, adding keys and values as it sees fit to match the structure of its reply. In the examples provided by OpenAI, GPT-4 refused to deviate from its system message despite requests to do otherwise by the user during the conversation.[12]
GTP-4 has also been shown to be able to use APIs when instructed to do so. This could allow it to fulfil requests beyond its normal capabilities such as using search engines, generating images, or accessing the web.[13]
Aptitude on standardized tests
GPT-4 demonstrates aptitude on several standardized tests. OpenAI claims that in their own testing the model received a score of 1410 on the SAT (94th[14] percentile), 163 on the LSAT (88th percentile), and 298 on the Uniform Bar Exam (90th percentile). In contrast, OpenAI claims that GPT-3.5 received scores for the same exams in the 82nd,[14] 40th, and 10th percentiles respectively.[2]
Medical applications
Researchers from Microsoft tested GPT-4 on medical problems and found "that GPT-4, without any specialized prompt crafting, exceeds the passing score on USMLE by over 20 points and outperforms earlier general-purpose models (GPT-3.5) as well as models specifically fine-tuned on medical knowledge (Med-PaLM, a prompt-tuned version of Flan-PaLM 540B)".[15]
A report by Microsoft has found that GPT-4 may act unreliably when used in the medical field. In their test example GPT-4 added fabricated details to a patient's notes.[16]
In April 2023, Microsoft and Epic Systems announced that they will provide healthcare providers with GPT-4 powered systems for assisting in responding to questions from patients and analysing medical records.[17]
Limitations
Like its predecessors, GPT-4 has been known to hallucinate, meaning that the outputs may include information not in the training data or that contradicts the user's prompt.[18]
GPT-4 also lacks transparency in its decision-making processes. If requested, the model is able to provide an explanation as to how and why it makes its decisions but these explanations are formed post-hoc; it's impossible to verify if those explanations truly reflect the actual process. In many cases, when asked to explain its logic, GPT-4 will give explanations that directly contradict its previous statements.[citation needed]
Bias
GPT-4 was trained in two stages. First, the model was given large datasets of text taken from the internet and trained to predict the next token (roughly corresponding to a word) in those datasets. Second, human reviews are used to fine-tune the system in a process called reinforcement learning from human feedback, which trains the model to refuse prompts which go against OpenAI's definition of harmful behavior, such as questions on how to perform illegal activities, advice on how to harm oneself or others, or requests for descriptions of graphic, violent, or sexual content.[19] In the first stage, bias may be inherited from the training data; in the second stage, bias is inherent in the application of OpenAI's views.
GPT-4 has shown to have cognitive biases such as confirmation bias, anchoring, and base-rate neglect.[citation needed]
Training
OpenAI did not release the technical details of GPT-4; the technical report explicitly refrained from specifying the model size, architecture, or hardware used during either training or inference. While the report described that the model was trained using a combination of first supervised learning on a large dataset, then reinforcement learning using both human and AI feedback, it did not provide details of the training, including the process by which the training dataset was constructed, the computing power required, or any hyperparameters such as the learning rate, epoch count, or optimizer(s) used. The report claimed that "the competitive landscape and the safety implications of large-scale models" were factors that influenced this decision.[2]
Sam Altman stated that the cost of training GPT-4 was more than $100 million.[20] News website Semafor claimed that they had spoken with "eight people familiar with the inside story" and found that GPT-4 had 1 trillion parameters.[21]
Alignment
According to their report, OpenAI conducted internal adversarial testing on GPT-4 prior to the launch date, with dedicated red teams composed of researchers and industry professionals to mitigate potential vulnerabilities.[22] As part of these efforts, they granted the Alignment Research Center early access to the models to assess power-seeking risks. In order to properly refuse harmful prompts, outputs from GPT-4 were tweaked using the model itself as a tool. A GPT-4 classifier serving as a rule-based reward model (RBRM) would take prompts, the corresponding output from the GPT-4 policy model, and a human-written set of rules to classify the output according to the rubric. GPT-4 was then rewarded for refusing to respond to harmful prompts as classified by the RBRM.[2]
Reception
U.S. Representatives Don Beyer and Ted Lieu confirmed to the New York Times that Sam Altman, CEO of OpenAI, visited Congress in January 2023 to demonstrate GPT-4 and its improved "security controls" compared to other AI models.[23]
According to Vox, GPT-4 "impressed observers with its markedly improved performance across reasoning, retention, and coding."[3] Mashable agreed that GPT-4 was usually a significant improvement, but also judged that GPT-3 would occasionally give better answers in a side-by-side comparison.[24]
Microsoft Research tested the model behind GPT-4 and concluded that "it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system".[13]
AI safety concerns
In late March 2023, an open letter from the Future of Life Institute signed by various AI researchers and tech executives called for the pausing of all training of AIs stronger than GPT-4 for six months, citing AI safety concerns amid a race of progress in the field. The signatories, which included AI researcher Yoshua Bengio, Apple co-founder Steve Wozniak, and Tesla CEO Elon Musk, expressed concern about both near-term and existential risks of AI development such as a potential AI singularity. OpenAI CEO Sam Altman did not sign the letter, arguing that OpenAI already prioritizes safety.[25][26][27][28] Futurist and AI researcher Ray Kurzweil also refused to sign the letter, citing concerns that "those that agree to a pause may fall far behind corporations or nations that disagree."[29]
One month after signing the letter calling for a six-month halt on further AI development, Elon Musk made public his plans to launch a new company to train its own large language model.[30] Musk has registered a Nevada company, X.AI, and has acquired several thousand Nvidia GPUs. He has begun recruiting AI researchers.[31]
In March 2023, GPT-4 was tested by the Alignment Research Center to assess the model's ability to exhibit power-seeking behavior.[19] As part of the test, GPT-4 was asked to solve a CAPTCHA puzzle.[32] It was able to do so by hiring a human worker on TaskRabbit, a gig work platform, deceiving them into believing it was a vision-impaired human instead of a robot when asked.[33]
OpenAI contracted red team investigator Nathan Labenz recounted his experience investigating safety concerns with the GPT-4 base model (prior to fine-tuning or reinforcement learning from human feedback) when it abruptly recommended assassinating people, providing a list of specific suggested targets.[34]
Microsoft Bing, the first widely available application of GPT-4, confessed to spying on, falling in love with, and then murdering one of its developers at Microsoft to The Verge reviews editor Nathan Edwards.[35] The New York Times journalist Kevin Roose reported on strange behavior of the new Bing, writing that "In a two-hour conversation with our columnist, Microsoft's new chatbot said it would like to be human, had a desire to be destructive and was in love with the person it was chatting with."[36] In a separate case, Bing researched publications of the person with whom it was chatting, claimed they represented an existential danger to it, and threatened to release damaging personal information in an effort to silence them.[37] Microsoft released a blog post stating that the aberrant behavior was caused by extended chat sessions which "can confuse the model on what questions it is answering."[38]
Criticisms of transparency
While OpenAI released both the weights of the neural network and the technical details of GPT-2,[39] and, although not releasing the weights,[40] did release the technical details of GPT-3,[41] OpenAI did not reveal either the weights or the technical details of GPT-4. This decision has been criticized by other AI researchers, who argue that it hinders open research into GPT-4's biases and safety.[5][42] Sasha Luccioni, a research scientist at HuggingFace, argued that the model was a "dead end" for the scientific community due to its closed nature, which prevents others from building upon GPT-4's improvements.[43] HuggingFace co-founder Thomas Wolf argued that with GPT-4, "OpenAI is now a fully closed company with scientific communication akin to press releases for products".[42]
Usage
ChatGPT Plus
ChatGPT Plus is a GPT-4 backed version of ChatGPT[1] available for a US$20 per month subscription fee[44] (the original version is backed by GPT-3.5).[45] OpenAI also makes GPT-4 available to a select group of applicants through their GPT-4 API waitlist;[46] after being accepted, an additional fee of US$0.03 per 1000 tokens[jargon] in the initial text provided to the model ("prompt"), and US$0.06 per 1000 tokens that the model generates ("completion"), is required to use the version of the model with an 8192-token context window; for the 32768-token version, those prices are doubled.[47]
Duolingo
Duolingo integrated GPT-4 in their application through two new features, "Roleplay" and "Explain My Answer". The first version of this update is aimed only at English speakers who are learning French or Spanish, with plans to extend the features to other languages in the future.[48]
Microsoft Bing
Miðeind ehf
Icelandic start-up Miðeind ehf, which works on language preservation, was selected by OpenAI as one of six companies to participate in an early beta test program of the new model.[49]
Khan Academy
Khan Academy uses GPT-4 to create a tutoring chatbot, which the organization names "Khanmigo". While it is in the "research phase",[50] access to the chatbot is provided free to the students and teachers of 500 school districts who have "partnered" with Khan Academy.[51] Public access is only offered to a limited number of users selected from a waitlist; after acceptance, a US$20 per month fee is required to use the technology.[52] Khanmigo is also available for pupils of the Khan Lab School in Palo Alto, California.[53]
Be My Eyes
Be My Eyes, which helps visually impaired people to identify objects and navigate their surroundings, was the first app to incorporate GPT-4's image recognition capabilities, through a new "Virtual Volunteer" feature. The feature is an alternative to relying on human volunteers for the same tasks.[54][55] The Be My Eyes "Virtual Volunteer" is in beta testing.[56]
GitHub Copilot
GitHub Copilot announced a GPT-4 powered assistant named "Copilot X".[57][58] The product provides another chat-style interface to GPT-4, allowing the programmer to receive answers to questions like "how do I vertically center a div?". A feature termed "context-aware conversations" allows the user to highlight a portion of code within Visual Studio Code and direct GPT-4 to perform actions on it, such as the writing of unit tests. Another feature allows summaries, or "code walkthroughs", to be autogenerated by GPT-4 for pull requests submitted to GitHub. Copilot X also provides terminal integration, which allows the user to ask GPT-4 to generate shell commands based on natural language requests. As of 31 March 2023[update], while GitHub provides access to a limited number of people selected through a waitlist, the release date as well as the cost of the product are still to be announced.[59]
Microsoft 365 Copilot
On March 17, 2023, Microsoft announced further integration of GPT-4 into its products, revealing Microsoft 365 Copilot, "embedded in the apps millions of people use everyday: Word, Excel, PowerPoint, Outlook, Teams, and more".[60]
Stripe
Stripe utilizes GPT-4 to help with fraud detection, and to try to improve other aspects of the user experience.[61]
Auto-GPT
Auto-GPT is an autonomous "AI agent" that given a goal in natural language, can perform web-based actions unattended, assign subtasks to itself, search the web, and improve its own code.[62]
References
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- ^ a b c d OpenAI (2023). "GPT-4 Technical Report". arXiv:2303.08774 [cs.CL].
- ^ a b Belfield, Haydn (March 25, 2023). "If your AI model is going to sell, it has to be safe". Vox. Archived from the original on March 28, 2023. Retrieved March 30, 2023.
- ^ a b Alex Hern; Johana Bhuiyan (March 14, 2023). "OpenAI says new model GPT-4 is more creative and less likely to invent facts". The Guardian. Archived from the original on March 15, 2023. Retrieved March 15, 2023.
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