Chat GPT Impact, Releases, Pricing

Chat GPT is a family of natural language processing models that can generate coherent and fluent text from a given prompt or context. Chat GPT has had a significant impact on the AI/ML industry, especially for startups, in several ways. Some of the impacts are:

• Chat GPT has enabled startups to create conversational agents that can interact with users in various domains and scenarios, such as customer service, education, entertainment, health, etc. Chat GPT models can be fine-tuned or adapted to specific tasks or domains using relatively small amounts of data, which reduces the cost and time of development.
• Chat GPT has also opened up new possibilities for content creation and generation, such as writing articles, summaries, reviews, captions, headlines, slogans, etc. Chat GPT models can produce high-quality and diverse texts that can be used for various purposes, such as marketing, SEO, social media, etc. Chat GPT models can also help users with their own writing tasks, such as rewriting, improving, or optimizing their texts.
• Chat GPT has also advanced the research and innovation in the field of natural language processing and understanding. Chat GPT models have demonstrated impressive capabilities of generating texts that are not only grammatical and coherent, but also informative, logical, and engaging. Chat GPT models have also challenged the existing methods of evaluating and measuring the quality and performance of natural language generation systems, such as using metrics like BLEU or ROUGE. Chat GPT models have also inspired new research directions and applications, such as controllable text generation, text style transfer, text summarization, text simplification, etc.

Some new startups gaining traction that use ChatGPT or other large language models are:

• Cohere, a platform that allows developers to build natural language applications using state-of-the-art models like ChatGPT and Falcon.
• Bloom, an open-source, multilingual LLM that supports 276 languages and can generate text, summaries, translations, and more.
• Chatsonic, a reliable AI chatbot supported by Google that can handle complex queries and tasks across multiple domains and languages.
• GitaGPT, an AI chatbot created by a Google India software developer that can answer questions about Hindu scriptures and philosophy.
• LLaMA-13B, a new LLM by Meta that can run on a single GPU and outperform ChatGPT in several benchmarks.

Chat-GPT Release Overview

The main releases of chat GPT are chat GPT-2, chat GPT-3, and chat GPT-4. Each release has different capabilities and limitations, as well as different applications and use cases.

Chat GPT-2 was the first release of chat GPT, and it was based on the original GPT-2 model that was trained on a large corpus of web text. Chat GPT-2 can generate text in multiple languages, but it is not very fluent or consistent across different domains and topics. Chat GPT-2 is also prone to generating factual errors, repetitions, and nonsensical sentences. Chat GPT-2 is mainly used for research and experimentation, as well as for generating low-quality content such as spam or fake news.

Chat GPT-3 was the second release of chat GPT, and it was based on the improved GPT-3 model that was trained on a much larger and more diverse corpus of web text. Chat GPT-3 can generate text in multiple languages with high fluency and coherence, and it can adapt to different domains and topics with minimal prompting. Chat GPT-3 can also generate factual and relevant information, as well as creative and entertaining content such as stories, jokes, or poems. Chat GPT-3 is mainly used for commercial and educational purposes, as well as for generating high-quality content such as articles, summaries, or reviews.

Chat GPT-4 was the third and latest release of chat GPT, and it was based on the advanced GPT-4 model that was trained on a massive and comprehensive corpus of web text, as well as other sources of data such as images, audio, video, and structured data. Chat GPT-4 can generate text in multiple languages with unprecedented fluency and coherence, and it can handle complex and diverse domains and topics with ease. Chat GPT-4 can also generate accurate and reliable information, as well as original and captivating content such as essays, songs, or code. Chat GPT-4 is mainly used for cutting-edge and innovative purposes, as well as for generating novel and valuable content such as insights, solutions, or inventions.

Chat-GPT Pricing: OpenAI, Hugging Face, and Microsoft

The cost of using Chat GPT depends on several factors, such as the number of tokens, the number of requests, the model size, and the API provider. A token is a unit of text that represents a word or a part of a word. A request is a single call to the API that generates a response. The model size is the number of parameters that the GPT model has, which affects its quality and speed. The API provider is the service that offers access to the GPT model, such as OpenAI, Hugging Face, or Microsoft.

According to OpenAI, their pricing for Chat GPT is based on tokens and requests. They charge $0.06 per 1,000 tokens and $0.0008 per request. For example, if you generate a response of 100 tokens with one request, you will pay $0.006 + $0.0008 = $0.0068. If you generate 10 responses of 100 tokens each with 10 requests, you will pay $0.06 + $0.008 = $0.068.

Hugging Face offers a different pricing scheme for Chat GPT, based on model size and requests. They charge $0.01 per request for small models (124M parameters), $0.02 per request for medium models (355M parameters), and $0.04 per request for large models (774M parameters). For example, if you generate a response with a small model with one request, you will pay $0.01. If you generate 10 responses with a large model with 10 requests, you will pay $0.4.

Microsoft also has its own pricing plan for Chat GPT, based on model size and requests. They charge $1 per hour for small models (117M parameters), $3 per hour for medium models (345M parameters), and $12 per hour for large models (1.5B parameters). For example, if you generate a response with a small model in one minute with one request, you will pay $0.0167. If you generate 10 responses with a large model in 10 minutes with 10 requests, you will pay $2.

As you can see, the cost of using Chat GPT varies depending on your needs and preferences. You should consider the trade-offs between quality, speed, and price when choosing a Chat GPT provider and model.