There are several neural networks that are widely used for text generation. I’ll describe some of the best.
Main AI models used to create texts
GPT-4
This version was developed by OpenAI. With 600 billion parameters and was trained on a huge corpus of texts, it is considered one of the best neural networks for generation at the moment. The model allows you to generate coherent, informative and structured texts with a high level of quality.
GPT-3
Generative Pre-trained Transformer 3: Developed by OpenAI and was a previous version of the pre-GPT-4 model. The GPT-3 model had 175 billion parameters. It is capable of generating high-quality and coherent texts in various styles and topics.
GPT-2
Generative Pre-trained Transformer 2: It is also developed by OpenAI and is the predecessor of GPT-3. Despite its lower dimensionality compared to GPT-3, this model is still capable of generating high-quality texts and has been used in many research papers and commercial projects.
BERT
Bidirectional Encoder Representations from Transformers: This is a model developed by Google researchers. It was aimed at natural language processing tasks, including text generation. BERT is trained on a huge volume of texts and has the ability to understand the context and semantics of sentences, making it effective at writing natural and grammatically correct texts.
Popular AI tools for writing texts
Claude AI
An AI assistant that is trained on its own data set, different from the one on which GPT learned. This AI assistant was made by Anthropic, a company that employs former OpenAI employees (the creator of ChatGPT).
What Claude 2 can do:
- summarize articles by links, PDF files with text;
- write clear texts on a particular topic;
- create code.
Handles Russian well. Free. You can register using your email or Google account.
Yandex GPT2
Russian neural network based on GPT. Available as a skill in the Yandex voice assistant, Alice – the skill is called “Let’s figure it out.”
GigaChat
This is another domestic neural network, free and accessible without a VPN. It is made by SBER, the language model is ruGPT3.
Notion AI
This neural network is right inside Notion, a service for creating Kanban boards, managing tasks, projects and planning – both personal and work. It is convenient to use a neural network if you are already using this service – if you are just starting out, the interface may seem complicated.
To generate, you just need to start writing and then select “Write with AI.”
Notion itself is free, more precisely, it costs from $10 per month, but there is a lot of free functionality. 40 calls to the neural network per month are included in the free version.
Writesonic
This is a unique service that works on different versions of GPT (the lower the version, the more text you can generate for free).
The main feature of the service is the ability to choose a text template. That is, there is no need to write requests. Just choose a template, it offers a topic statement, structure, then the text itself.
Can do:
- blog articles;
- posts for social networks;
- names and descriptions of products;
- texts for advertising on Google;
- content for landing pages;
- titles and descriptions of YouTube videos;
- competent rewriting of any texts.
10,000 words available for free. These are somewhat average sized articles. Then you need to register a new account or pay – Russian cards are not accepted. You can log in using your email or Google account.
Convenient AI copywriters
What other options are there if the ones described are not enough:
- Rytr is an AI copywriting service. You can generate 10,000 characters per month for free, as well as 5 images. Works in different Tone of Voice. There is a built-in plagiarism checking service. Paid tariffs start at $9 per month, but, of course, you won’t be able to pay with Russian cards.
- CopyMonkey – the service is also positioned as an AI copywriter for creating texts.
- Gerwin AI – works roughly like Writesonic: it has templates for different tasks, you can generate both texts and images.
It is important to note that choosing the best neural network for a particular task depends on the requirements, available data and computing resources. All of the models listed have their own unique characteristics and applications, and can be customized and modified for specific purposes.
