By this time, you should have experienced the generative AI first-hand. Last few years AI technology improved a lot and imbibed into everyone’s life. For example, from tools like Grammarly to social media like Facebook – every other company uses artificial intelligence to improve productivity, and accuracy to the next level.
But the Open AI ChatGPT release almost shook the AI community at large & also left the common audience speechless, but did you notice that there are other competitors out there? which turns the AI battle to the next level.
Today, we’re going to look at the top 3 ChatGPT competitors in the market. Let’s dive in!
Hugging Face:
Hugging Face is a popular open-source platform and company that focuses on natural language processing (NLP) technologies and provides a range of tools and resources for building and deploying NLP models. It was founded in 2016 by Clément Delangue, Julien Chaumond, and Thomas Wolf.
The company released its first product, the Hugging Face Transformers library, in 2018. This library has become one of the most widely used frameworks for working with pre-trained NLP models. It allows developers to leverage state-of-the-art models such as BERT, GPT, and many others for various NLP tasks like text classification, named entity recognition, language translation, and more.
Hugging Face gained significant attention and popularity with the release of the “Transformers” library and the associated online community. The platform enables researchers and developers to share, collaborate, and fine-tune models on a large scale. It offers a model hub where users can access a wide range of pre-trained models, as well as a suite of tools for model training, evaluation, and deployment.
Hugging Face has attracted notable investors who recognize the value of its technology and community. Some of the key investors behind Hugging Face include Lux Capital, Thirty-five Ventures and Sequoia Capital, etc.
The platform and tools provided by Hugging Face have the potential to benefit various industries. Some of the industries that can leverage NLP models and tools for their applications include:
Customer Service:
NLP models can be used to build chatbots and virtual assistants that can handle customer inquiries and support requests, improving efficiency and enhancing the customer experience.
Healthcare:
NLP models can aid in medical research, diagnosis, and patient care by analyzing medical literature, extracting information from patient records, and providing insights for personalized treatment plans.
Finance:
NLP models can help in analyzing financial news, reports, and social media data to predict market trends, perform sentiment analysis, and support investment decision-making.
E-commerce:
NLP models can improve product search and recommendation systems, enabling personalized shopping experiences for customers.
Content Creation:
NLP models can assist in generating written content, including news articles, blog posts, and marketing copy, saving time and resources for content creators.
Legal:
NLP models can assist in legal research, contract analysis, and document summarization, helping legal professionals streamline their workflows and enhance accuracy.
These are just a few examples, and the potential applications of NLP across industries are extensive. Hugging Face’s tools and resources contribute to the accessibility and advancement of NLP technology, making it easier for developers and researchers to utilize and benefit from these models.
Google Bard:
Google Bard is a large language model (LLM) chatbot developed by Google AI. It is based on the LaMDA family of LLMs and was first released on March 21, 2023. Bard is trained on a massive dataset of text and code and can generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. It is still under development, but it has learned to perform many kinds of tasks, including.
- Follow your instructions and complete your requests thoughtfully.
- Use Google Knowledge to answer your questions in a comprehensive and informative way, even if they are open-ended, challenging, or strange.
- Generate different creative text formats of text content, like poems, code, scripts, musical pieces, emails, letters, etc. I will try my best to fulfill all your requirements.
Bard is available in English, Japanese, and Korean. It is still under development, and Google is working to improve its accuracy and reliability.
The AI model that Bard is using is called LaMDA, which stands for “Language Model for Dialogue Applications.” LaMDA is a generative pre-trained transformer model, which means that it is trained on a massive dataset of text and code. This allows Bard to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way.
Bard has the potential to benefit a wide range of industries, including:
- Education: Bard can be used to help students learn new concepts and improve their writing skills.
- Healthcare: Bard can be used to help doctors diagnose diseases and provide patients with personalized care.
- Customer service: Bard can be used to answer customer questions and resolve issues.
- Marketing: Bard can be used to create personalized marketing campaigns and generate creative content.
- Research: Bard can be used to help researchers find information and collaborate on projects.
- It’s a very powerful tool with lot many use cases, we may experience many of its features introduced into other Google tools moving forward.
Bard is a powerful tool that has the potential to revolutionize the way we interact with computers. It is still under development, but it has already learned to perform many kinds of tasks. As Bard continues to improve, it is likely to have a major impact on a wide range of industries.
It is not grabbed headlines as ChatGPT, but Amazon Web Services working on this tool for years & announced it on June 2022.
It is specially designed to improve developer productivity by generating code on developers’ comments. Due to its customizability to different environments. The downside is that it’s not as user-friendly as some of its competitors, which can be a hurdle for beginners.
Conclusion:
We might see more & more new entrants to this space moving forward, but things might turn more interesting when Meta [Facebook] releases its version of the AI tool which they are working on for years.