GPT-4: The New Holy Grail of AI Language Models?
Fabian Mahnke9/22/2023
The next generation of the OpenAI system is here and it promises to further push the boundaries of AI. More on this in this article.
Table of contents
- What exactly is a GPT language model?
- What new features does GPT-4 bring?
- How can GPT-4 be applied?
- How you can currently use GPT-4
- What are the pros and cons of GPT-4?
- What do users of GPT-4 need to be aware of?
- Risks associated with GPT-4
- Cost of GPT-4
- What tools can be integrated into the use of GPT-4?
- What are the alternatives to GPT-4?
- Conclusion
It's finally here! The next generation of the OpenAI system is here and it promises to push the boundaries of AI and NLP (Neural Language Processing) even further. GPT-4 was developed by OpenAI to usher in a new era of machine learning and take AI text generators to a new level. As one of the most anticipated tools for NLP, Machine Learning, and data analysis, GPT-4 has OpenAI ChatGPT already attracted the attention of scientists, developers, and businesses all over the world. With an incredible capacity of 10 trillion parameters and new features like multilingual support, improved language translation, and enhanced text generation, GPT-4 is indeed a ground-breaking system. But what exactly does GPT-4 really have to offer? And what do all these features and jargon really mean for you as a user? In this blog post, you will learn all about GPT-4 and what it holds for the future of AI. So buckle up, as we take a glimpse into the future of machine intelligence!
What exactly is a GPT language model?
A GPT (Generative Pretrained Transformer) language model is an artificial intelligence algorithm specialized in generating human-like text. It was developed by OpenAI and is based on the concept of machine learning.
The model is pretrained on a huge amount of text data to learn the structure and pattern of human language. It captures the relationships between words, sentences, and ideas and can use this knowledge to generate new, coherent text.
A key element of the GPT model is that it is "transformer-based", which means that it takes into account the context of words in a sentence to make accurate and relevant predictions. It can not only complete existing sentences, but also generate complete articles or essays from a single sentence or prompt.
There are several versions of the GPT model, including GPT-1, GPT-2, GPT-3, GPT-3.5, and now GPT-4, with each new version incorporating improvements and extensions over the previous ones. GPT-3, the previous version, had 175 billion machine learning parameters, while GPT-4 is speculated to have up to 1.8 trillion parameters. This makes it the largest and most powerful model of its kind at the time of writing the article.
The training of GPT-4 indeed marks a gigantic milestone, with an impressive volume of 13 trillion tokens deriving from both text- and code-based data. This volume of information includes sources like CommonCrawl and RefinedWeb, and there are even speculations about the involvement of additional data sources like Twitter, Reddit, YouTube, as well as a wide range of textbooks.
For comparison, GPT-3, its predecessor, was trained with only 300 billion tokens. This means that the volume of training data for GPT-4 is more than 40 times larger. To refine the model, additional millions of lines of instructions were used from ScaleAI and internal resources. It is no surprise that GPT-4 is setting new standards in the field of AI.
What new features does GPT-4 bring?
GPT-4 stands out as a so-called multimodal model that constantly redefines the boundaries of what is possible. But what exactly does this mean and what new features does GPT-4 bring? In this chapter, we will take a closer look at the innovative features and capabilities of GPT-4 to understand how this model is revolutionizing the field of AI.
- Understanding more complex inputs: GPT-4 can understand more complex and nuanced prompts, allowing it to more accurately respond to user inputs
- Complex problem-solving: Another significant feature is GPT-4's ability to solve more complex problems, including those that involve multiple steps
- Creative and technical writing: GPT-4 can generate, edit, and collaboratively work with users on creative and technical writing tasks, such as composing songs, writing scripts, or learning
- Visual input: One of the most anticipated features in GPT-4 is its ability to interact with images, not just text. This means GPT-4 can analyze the content of an image and link this information with a written question
- Generating more creative and abstract answers: GPT-4 can generate more creative and abstract answers, making interactions with users in technical and creative areas more engaging
How can GPT-4 be applied?
The application of GPT-4 offers a wide range of possibilities. You can use this advanced technology to automate marketing texts or email campaigns for example. You could also improve voice assistants or chatbots by providing customer-specific voice recognition and text processing services. Compared to human writing, GPT-4 is capable of generating texts in a very short time and can produce a large volume of content.
How you can currently use GPT-4
To harness the impressive power of GPT-4, you have several exciting options to choose from.
The first option is to sign up to one of the many AI text generators that have already integrated GPT-4's amazing technology into their platforms. These innovative services enable you to leverage the capabilities of GPT-4 in a simple and user-friendly manner, without needing to dive into the technical details yourself.
Another attractive option is to subscribe to the ChatGPT Plus subscription. With this premium membership, you get direct access to GPT-4 and can thereby use the full range of its functions. This is an excellent opportunity to try out the latest advancements in AI-based text generation and experience how they can revolutionize your text creation.
And finally, there is the possibility of getting on the waiting list for the OpenAI GPT-4 API interface. This is the ideal option for those planning to integrate GPT-4 directly into their own applications or services. In this way, you can fully exploit the incredible power of GPT-4 and tailor it precisely to the needs of your project.
What are the pros and cons of GPT-4?
GPT-4 generally, but also in comparison to GPT-3, has a few potential downsides I would like to cover as well in order to give you a complete picture of GPT-4.
- Biases and cognitive errors: Like previous language models, GPT-4 also shows a tendency towards biases and cognitive errors. This could result in the model reflecting certain biases in the generated texts or creating inaccuracies.
- Extended monitoring of user input: GPT-4 has more restrictions and requires stronger monitoring of user inputs. This could limit the flexibility and user-friendliness of the model.
- No adding new data: Like GPT-3, GPT-4 is a pretrained model. This means that no new data can be added to further train or adapt the model.
- No processing of audio or video data: Like GPT-3, GPT-4 was not trained to process audio or video data. This could limit its applicability in certain areas.
- Cost: The use of GPT-4 can be more expensive, especially for large companies that need to generate a high volume of text.
- Speed: As GPT-4 relies on much more parameters, the speed of the output is slower than, for example, GPT-3 or 3.5.
Overall, however, it can be said that the advantages of GPT-4 over GPT-3 and other language models far outweigh. The many new features and processing capabilities that GPT-4 brings along make it possible to elevate AI-based text generation to a yet higher level. This alone justifies the disadvantages and, in many cases, virtually completely compensates them.
What do users of GPT-4 need to be aware of?
Basically, there is not much or nothing to be aware of. Many AI text generators like neuroflash, Mindverse or Jasper have already seamlessly integrated GPT-4 and users will likely only notice that the generated outputs are now significantly better and longer, and more input characters are available as well as a longer history is available (the length of time the AI can look back to accurately hit the context of the new outputs).
Risks associated with GPT-4
OpenAI, the organization behind the GPT-4 model, controls when and how the models are updated. Major changes (such as the shift from GPT-3.5 to GPT-4) are communicated, but not smaller updates, which however occur again and again. They are not open source, which means that the exact details of their implementation and their training data are not publicly accessible. This makes them sort of a "black box" where users can see the outputs but don't know exactly how these outputs were generated or what specific changes were made in the latest updates.
This might be problematic for some applications, especially in areas that require transparency and traceability. It can also lead to uncertainties, as users might not always know which version of the model they are using or whether recent changes were made that could impact the model's performance or behavior.
However, it is important to note that OpenAI is striving to monitor the impact of their models on society and ensure they are used responsibly. They have also introduced policies to prevent misuse of their technology.
Cost of GPT-4
As already mentioned in the section "How you can currently use GPT-4", there are several ways to use GPT-4 and hence the costs also vary.
The first option to use one of the many AI text generators that have integrated GPT-4 into their platforms is more or less cost efficient (though generally a bit more expensive than the second option listed below) and does not require any technical knowledge. I have already listed good examples of such tools above and they all offer different pricing levels that are tailored to your specific needs, making it an affordable option for many.
The second option is to subscribe to a ChatGPT Plus subscription. While it does require an investment (currently $20 per month), it gives you direct access to the latest advancements of GPT-4. If you plan to use the service regularly and want to benefit from the additional features, this investment could be well worth it.
The third option to get on the waiting list for the OpenAI GPT-4 API interface could initially be free, but using the API usually incurs costs. The exact costs can vary depending on usage. If you plan to integrate GPT-4 extensively into your own applications or services, you should factor these costs into your budget planning.
What tools can be integrated into the use of GPT-4?
Integration of GPT-4 can happen in a variety of tools and applications, depending on the specific requirements and area of application. Here are some examples:
- Content Management Systeme (CMS): GPT-4 can be integrated into CMS platforms like WordPress or Drupal to generate automated content or enhance existing content.
- Social Media Suites: Platforms like Hootsuite or Buffer can use GPT-4 to create engaging social media posts or even generate responses to user comments.
- Email Marketing: GPT-4 can be used to create personalized email content tailored to the specific interests and needs of recipients. This could be integrated into tools like or Brevo (ehemals Sendinblue).
- Development platforms: For developers, GPT-4 can be integrated into IDEs or code editors to help with writing code or documentation.
Numerous other tools and application scenarios are conceivable. ChatGPT offers a plugin store in its Plus Subscription, with numerous plugins available (though they are not specifically tailored for GPT-4 but, like GPT-4, are also only available after the subscription is completed).
What are the alternatives to GPT-4?
If I get asked this question, then we are talking about language models and not specifically tools like ChatGPT or Jasper. There are several impressive language models that can serve as alternatives to GPT-4. Let's take a look at the most important ones:
BERT (Bidirectional Encoder Representations from Transformers) is a language model developed by Google and is the basis for Google's BARD AI. BERT differs from other models in that it considers the context of words in all directions - both from left to right and from right to left. This allows a deeper, more accurate understanding of language, making it a strong alternative to GPT-41.
LLaMa2 is another noteworthy language model developed by Meta (formerly Facebook). It is an open-source language model that deals with a broad spectrum of NLP (Natural Language Processing) tasks. LLaMa2 is known for understanding the context and meaning of text in a way that allows human-like responses and interactions2.
Luminous from the Heidelberg-based Aleph Alphac is an advanced AI language model. It is a transformer-based model similar to OpenAI's GPT-3 and GPT-4. Luminous is designed to generate human-like texts and perform a wide range of natural language processing tasks.
There are also other alternatives to GPT-4 worth mentioning. PaLM 2 by Google, for example, has proved to be more successful than GPT-4 in certain tests3. Another interesting model is StableLM, introduced by Stability AI, and is considered a strong alternative to GPT-44.
However, it should be noted that each of these models has its own strengths and weaknesses, and the choice of the right model depends on the specific requirements of your application. Even though GPT-4 has drawn lots of attention due to its impressive capabilities in text generation, there are a variety of other advanced language models that are also very powerful and can be employed in various use cases.
Recommend AI-Text-Generators
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Conclusion
GPT-4 is undoubtedly considered the new holy grail of AI language models. It offers a broad range of powerful and limitless applications in the areas of programming, machine learning, creative portfolios as well as customer service and sales experiences, to name a few. It appears that GPT-4 will have a significant impact on our lives in the near future. Like any advanced technology, however, it also poses risks that need to be considered before full utilization. Another challenge could be the costs, as high performance comes with a price. In addition, users must consider what other useful tools can be integrated into the use of GPT-4. Even though GPT-4 represents a massive opportunity for further advancing the technology of natural language processing, there are also alternatives that are no less exciting, but they come with their own pros and cons.
All in all, GPT-4, when used in the right context and with the right incentives, could become an invaluable tool for many tasks that require AI-based solutions and natural language processing.
Author
Fabian Mahnke
Fabian Mahnke ist Informatiker und Online Marketer und beschäftigt sich bereits seit 2016 mit künstlicher Intelligenz und wie sie im Marketing genutzt werden kann. So kam er bereits sehr früh mit der KI-basierten Texterstellung in Kontakt. Sein klares Ziel: Schreiben mithilfe von KI im DACH-Raum salonfähig zu machen. Er ist zweifacher Autor und bietet mit seinem Programm “SmarterSchreiben” Coachings an.
