OpenAI has released GPT-4, the latest version of its ChatGPT AI system, which is more creative, less likely to make up facts, and less biased than its predecessor. It is a "multimodal" model that can accept images as well as text as inputs, can handle massive text inputs, and can remember and act on more than 20,000 words at once.
Let's with Fordeer learn more about this latest version of the groundbreaking AI system.
What are Generative Pre-trained Transformers?
Generative Pre-trained Transformers (GPT) are a type of deep learning model used to generate human-like text. Typical uses include:
- answering inquiries
- text summarization text translation into foreign languages
- writing code to create dialogues, tales, blog entries, and other sorts of content.
GPT models have countless uses, and you can even fine-tune them using particular data to produce even better outcomes. You can cut expenditures on computing, time, and other resources by employing transformers.
The history of GPT
Transformer models were only able to enable the current AI revolution for natural language, beginning with Google's BERT in 2017. Prior to this, deep learning models like recursive neural networks (RNNs) and long short-term memory neural networks (LSTMs) were used to generate text. They were effective at producing single words or brief sentences but were unable to produce realistically long content.
As BERT's transformer approach is not supervised learning-based, it represents a significant advancement. In other words, it did not need to be trained on an expensive annotated dataset. Although BERT was utilized by Google to analyze natural language searches, it is unable to produce text in response to a prompt.
Using their GPT-1 language model, OpenAI published a paper in 2018 titled "Improving Language Understanding by Generative Pre-Training" that discussed the use of natural language understanding. This proof-of-concept model was not made available to the general public.
A second study regarding OpenAI's most recent model, GPT-2, entitled "Language Models are Unsupervised Multitask Learners," was published the following year. This time, the machine learning community was given access to the model, which was used for several text production jobs. GPT-2 might frequently produce a few phrases before faltering. In 2019, this was cutting-edge technology.
Another study regarding their GPT-3 model, titled "Language Models are Few-Shot Learners," was released by OpenAI in 2020. The model performed better since it had 100 times more parameters than GPT-2 and was trained on an even bigger text dataset. After numerous versions, collectively referred to as the GPT-3.5 series, the model kept getting better, including the ChatGPT, which is conversation-focused.
This version shocked everyone by producing pages of human-like text, which caused it to become viral. As ChatGPT reached 100 million users in just two months, it became the web application with the highest growth rate ever.
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What’s new in GPT-4?
GPT-4 has been developed to improve the model's "alignment", or ability to follow user intentions while also being more truthful and generating less offensive or dangerous output.
As one may anticipate, GPT-4 models outperform GPT-3.5 models in terms of the veracity of the responses. With GPT-4 scoring 40% higher than GPT-3.5 on OpenAI's internal factual performance benchmark, the percentage of "hallucinations," when the model commits factual or reasoning errors, is reduced.
Also, it enhances "steerability," or the capacity to modify behavior in response to user demands. You may instruct it to write, for instance, in a different tone, style, or voice. Attempt prompts that begin, "You are a garrulous data expert," or "You are a terse data expert," and have it walk you through a data science idea. Further information on creating effective prompts for GPT models may be found here.
Using visual inputs in GPT-4
The ability to input text and images into GPT-4 is a significant development (research preview only; not yet available to the public). Users can enter any language or vision task by sprinkling text and images throughout the text.
In the examples, complicated images like charts, memes, and screenshots from academic publications are successfully interpreted by GPT-4.
These are some illustrations of the visual input.
GPT-4 performance benchmarks
OpenAI assessed GPT-4 by simulating tests designed for humans, such as the SAT for college admission and the Uniform Bar Examination for lawyers. On established criteria, including multiple-choice questions in 57 disciplines, commonsense thinking about everyday events, grade-school multiple-choice science questions, and more, it fared better than existing large language models and the majority of cutting-edge models. Also, it fared better than GPT-3.5's and other large language models' English performances. These findings show that OpenAI's efforts to create AI models with ever-improving capabilities have made tremendous progress.
GPT-4 - the ChatGPT successor
Being released by OpenAI, GPT-4 is a new model that can respond to images and write captions and descriptions. It can also process up to 25,000 words, about eight times as many as ChatGPT, which has been used by millions of people since it launched in November 2022. It is a type of generative artificial intelligence (GAN) that uses algorithms and predictive text to create new content based on prompts. However, it is still not fully reliable and may "hallucinate," a phenomenon where AI invents facts or makes reasoning errors. It will initially be available to ChatGPT Plus subscribers, who pay $20 per month for premium access to the service. OpenAI also announced new partnerships with language learning app Duolingo and Be My Eyes, an application for the visually impaired, to create AI Chatbots that can assist their users using natural language.
How to gain access to GPT-4
Via ChatGPT, OpenAI is making a text input for GPT-4 available. For the time being, ChatGPT+ subscribers can access it. There is a waitlist for the GPT-4 API.
The ability to input images has not yet been made publicly available.
OpenAI has open-sourced OpenAI Evals, a framework for automated evaluation of AI model performance, to enable anybody to report shortcomings in their models and drive future improvements.