Understanding GPT-4: ChatGPT's Successor With Advanced Reasoning
March 20, 2023
Are you ready for the next big thing in AI? OpenAI has just released its latest and greatest creation: GPT-4, a large-scale, multimodal successor to the groundbreaking GPT series. With ChatGPT setting the record for the fastest-growing user base and the introduction of Google Bard, large language models (LLMs) have recently gained much popularity and changed how we interact with AI technology.
From chatbots to article summarization, these models can handle a wide variety of tasks with incredible speed and accuracy. LLMs are not only used to teach AIs human languages but also have various applications, such as improving the ability to understand and generate natural language text in complex and nuanced scenarios, understanding proteins, and writing software code.
Here, we will discuss OpenAI's latest milestone in scaling up deep learning, GPT-4. Let's take a deep dive.
History of the GPT Series
OpenAI's Generative Pre-trained Transformer (GPT) models have caused a sensation in the natural language processing (NLP) community by introducing highly powerful language models since 2018. The GPT series started with GPT-1 in June 2018, a breakthrough in natural language processing.
GPT-2, released in February 2019, was 10x larger and more powerful than its predecessor. However, its full version was withheld initially due to concerns about misuse. In June 2020, OpenAI released GPT-3, built with 175 billion parameters and an extensive dataset.
GPT-3 was finetuned until the release of GPT-3.5, released in 2022. Finally, GPT-4, released on March 14, 2023, is the latest addition to the GPT series. It has even more parameters than its predecessor, enabling it to perform more complex natural language processing tasks.
What is OpenAI’s GPT-4?
GPT-4, the Generative Pretrained Transformer model, is a large-scale language model trained on a massive amount of data using unsupervised learning techniques. It is a multimodal model capable of accepting both text and image inputs and generating human-like text outputs.
GPT-4 exhibits human-level performance on various professional and academic benchmarks, making it a highly advanced tool for natural language processing and related tasks.
Furthermore, GPT-4 will be available to ChatGPT Plus subscribers through the chat.openai.com platform. To ensure that all subscribers have a fair and equal opportunity to use this powerful tool, OpenAI will implement a usage cap that may be adjusted depending on demand and system performance.
GPT-4's base model was trained to predict the next word in a document using publicly available and licensed data. This includes a web-scale corpus of diverse data, such as correct and incorrect solutions to math problems, weak and strong reasoning, and contradictory and consistent statements. However, the base model's responses to user prompts may not align with their intent.
OpenAI used reinforcement learning with human feedback (RLHF) to fine-tune the model's behavior to improve alignment. Note that while RLHF does not improve the model's capabilities, it is crucial in steering the model's responses to answer user questions.
GPT-4 project prioritizes building a deep learning stack that scales predictably. OpenAI developed infrastructure and optimizations that exhibit consistent behavior across multiple scales. This was verified by predicting GPT-4's final loss on the internal codebase through extrapolation from smaller-scale models.
Capabilities of GPT-4
GPT-4's capabilities surpass GPT-3.5 in terms of accuracy, creativity, and ability to handle nuanced instructions.
Let's explore them below.
When evaluated on traditional benchmarks for machine learning models, GPT-4 demonstrated superior accuracy compared to existing large language models and most state-of-the-art (SOTA) models. For example, GPT-4 gives 86.4% (5-shot) accurate results on the MMLU benchmark, while 95.3% (10-shot) on HellaSwag.
To evaluate GPT-4's accuracy in languages other than English, the MMLU benchmark, consisting of 14,000 multiple-choice problems spanning 57 subjects, was translated into various languages using Azure Translate. GPT-4 outperformed GPT-3.5 and other LLMs in 24 out of 26 tested languages.
Furthermore, GPT-4 reduces the probability of responding to requests for disallowed content by 82% compared to its predecessor GPT-3.5. Additionally, it shows a 40% increase in generating factual responses when evaluated on OpenAI's internal adversarial factuality evaluations.
GPT-4 represents a significant leap forward in the realm of creativity for AI language models. Not only can it generate and edit text, but it also can collaborate with users on a wide range of creative and technical writing tasks. For instance, it can help users compose songs, write screenplays, or even learn a user's writing style.
During a demonstration, GPT-4 was prompted to explain the humor behind an image featuring a squirrel holding a camera. It replied, "we don’t expect them to use a camera or act like a human.” In another instance, Brockman presented a hand-drawn and simple website design to GPT-4, which then generated a functional website based on the sketch.
3. Visual Input
GPT-4 can handle mixed text and image inputs and generate natural language, code, or other outputs. It performs similarly well on mixed input types as it does on text-only inputs across a range of domains that include text, photographs, diagrams, or screenshots.
GPT-4 outperformed many SOTA models when evaluated against a narrow suite of standard academic vision benchmarks. For example, GPT-4 gives 78.0% accurate results for the TextVQA benchmark, while 75.1% for TVQA, as shown in the illustration below.
4. Longer Context
GPT-4 can handle more than 25,000 words of text, making it suitable for tasks such as creating long-form content, engaging in extended conversations, and analyzing and searching documents. GPT-4's capacity for longer context enables it to have improved memory, coherence, and consistency when processing larger inputs.
5. Performance on Tests
GPT-4 outperforms ChatGPT by scoring in higher approximate percentiles among test-takers.
GPT-4's capability was tested on simulating exams designed for humans, where it performed better than its predecessor, GPT-3.5. For example, GPT-4 scored 163 (88th percentile) on the LSAT exam, while GPT-3.5 scored 149 (40th percentile).
Furthermore, GPT-4 scored 710/800 in SAT Evidence-Based Reading & Writing Exam and 75% in Medical Knowledge Self-Assessment Program. While GPT-3.5 scored 670/800 and 53% in the respective exams.
What are the Limitations of GPT-4?
Despite GPT-4’s advanced reasoning and capabilities, it demonstrates similar limitations as previous GPT models. Some of them are given below.
GPT-4 tends to hallucinate due to its lack of real-world expertise and inability to understand the context of the text, like earlier GPT models. It may produce incomprehensible or unrealistic information. As models become increasingly accurate, hallucinations can become more harmful if users grow accustomed to the model's accuracy in areas with which they are already familiar.
2. Harmful Content
Language models may be programmed to produce many types of destructive content, and GPT-4 could produce offensive content, including propaganda, violent or graphic imagery, and hate speech. It could be challenging to filter out such stuff adequately.
- Suggestions or encouragement for self-destructive behavior
- Harassing, degrading, and hostile materials
- Graphic material such as erotica or violent content
- Content used for plotting assaults or violence
- Guidelines for locating illicit content
3. Social Biases
GPT-4-early and GPT-4-launch continue reinforcing societal biases and worldviews, just like earlier GPT models and other standard language models. GPT-4 can reinforce societal prejudices and stereotypes found in the learning algorithms used to create them. This could lead to the continuation of discrimination and injustice.
4. Disinformation and Influence Operations
Language models such as GPT-4 can be used to mass produce and spread propaganda and misinformation, which could cause political or social upheaval. GPT-4 may produce targeted material like emails, tweets, chats, and reasonably realistic news stories.
5. Economic Impacts
The widespread use of cutting-edge language models like GPT-4 may cause essential changes in the labor market, displacing some workers or altering the skills needed for particular professions. The employees may be displaced as a result, and even jobs that have historically needed years of training and education, like legal services, we anticipate that GPT-4 will eventually influence.
Applications of GPT-4
Language model GPT-4 can potentially transform several sectors, including e-commerce, accessibility, and education. Let’s explore real-world use cases of GPT-4.
Khan Academy is a non-profit educational initiative, and with the integration of GPT-4, the platform's educational experience has improved. By giving students more precise and individualized assessments, grading essays and tasks, and creating more exciting and interactive educational materials, GPT-4 makes learning more fun and logical for kids.
A well-known platform for learning languages, Duolingo employs gamification strategies to make the process more entertaining and engaging. Duolingo improves its AI-powered products like Role Play, an AI conversation companion, and Explain my Answer, which clarifies the rules when a user makes a mistake, using GPT-4. The user experience is further enhanced by GPT-4's excellent natural language processing capabilities, allowing for more precise and human-like interactions with these AI-powered features.
Be My Eyes
Be My Eyes is a free app that establishes live video calls between blind and low-vision users, sighted volunteers, and company representatives to provide visual assistance. Be My Eyes recognizes and explains more complex visual data with the help of GPT-4, giving visually impaired users greater in-depth support. Also, GPT-4 has improved the app's voice command capability, facilitating more effective communication between users and volunteers.
GPT-4 can also be used in the e-commerce sector, as demonstrated by Stripe, a provider of payment processing services. Stripe creates more precise and effective fraud detection algorithms with GPT-4's sophisticated language processing skills, enhancing the security of online transactions and lowering the risk of financial loss for businesses and consumers.
Operationalize Your GPT-4-Based Products with Unleashing AI
With the development of GPT-4, the potential for natural language generation has only increased. GPT-4's advanced reasoning capabilities open up even more possibilities for organizations looking to utilize artificial intelligence to generate high-quality text for a range of applications.
Partnering with a skilled development team like Unleashing AI can provide organizations with access to the full potential of GPT-4. With our expertise in GPT-4 development, we can create custom solutions that harness the power of this AI model to generate high-quality text and enhance business operations.
Schedule a call to learn more about how GPT-4 can transform the way you create and consume text-based content. Get started with GPT-4 development today!