GPT 4 is the latest version of OpenAI’s language models, released on March 14, 2023. It’s an upgrade to GPT-3 and offers a variety of benefits.
While still prone to limitations like hallucinating facts and making reasoning errors, GPT-4 performs better than its predecessors. It also improves “steerability,” which allows users to control its behavior based on their preferences. Below are 4 things which we think you should know about the GPT-4, so let’s get started.
1. Natural Language Understanding
Natural language understanding can help businesses improve customer support by providing accurate and personalized responses to queries. It can also be used to create content that is engaging and informative.
One of the best examples of this is GPT-4, which can understand images as well as text. In the video below, it is asked to respond to a series of pictures, including a VGA adaptor plugged into a phone, a Lightning adaptor, and a closer look at the VGA adaptor.
Its ability to process both images and text could have a wide range of applications, including conversational AI and translation. In addition, it can be used to create more effective user interfaces for apps and websites.
Large language models, like GPT-3, require a huge amount of training data and massive computing resources to be efficient. These resources tend to be cost-prohibitive for many companies, especially if they are trying to deploy them in the real world.
2. Automated Tasks
GPT 4 is a natural language processing engine that can process inputs in the form of text and generate responses. It has been trained on a large data set and can more accurately perform language processing tasks than its predecessor, GPT 3.
As a result, it is an excellent tool for automating repetitive tasks, such as writing emails and social media captions. This can reduce the workload for content creators and increase efficiency, freeing up time to focus on more critical tasks.
This technology can also be used to improve accessibility by generating text and speech that is easier to read or hear for people with disabilities. This could be particularly beneficial for users with dyslexia or hearing impairments.
Another way that GPT 4 can help to improve accessibility is by analyzing large amounts of text to identify patterns and trends. This can help researchers to identify new hypotheses and breakthroughs in a variety of fields.
3. High-ROI Tasks
High-ROI tasks are those that require more than a basic understanding of natural language and machine learning. They may include text generation, speech recognition, summarization, and more.
GPT 4 can also be used to automate repetitive tasks, such as data analysis and sales, freeing up your team’s time to focus on more value-added activities. In turn, this can lead to higher productivity and efficiency, which will boost your ROI.
The model has a lot of flexibility, lending itself to a variety of use cases. However, it’s important to be aware of some of its limitations.
For example, while it works well for language generation, it doesn’t always produce output that is consistent with human expectations or desirable values. This is due to the fact that a large language model (LM) is trained on a massive amount of text data, which includes real-world examples that can be inconsistent with each other. This is why fine-tuning your model is crucial.
4. Generating Personalized Content
The newest version of OpenAI’s ChatGPT takes content generation to the next level, delivering highly personalized experiences to users. GPT 4 can generate blog posts, articles, product descriptions, and social media posts that mimic the way human writers use language.
The GPT-4 model is 100 times better than the previous iteration, GPT-3, which was trained on a much larger text dataset. It can handle more input types, including images.
During his demo, Brockman showed how the newer model can specifically output what the user wants by telling it to follow specific requirements. In this case, he asked the assistant to summarize an article into a sentence that begins with the letter “G”.
The GPT-4 model was evaluated against benchmarks ranging from multiple-choice questions in 57 subjects, to commonsense reasoning around everyday events, grade-school multiple-choice science questions, and more. It outperformed the English-language performance of GPT-3 and other large language models.