Google Bard Vs ChatGpt Which is Better Ai
Google Bard vs ChatGPT are both large language models (LLMs) that are trained on massive datasets of text and code. They can both generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. However, there are some key differences between the two models.
What Is Google bard
Bard is a large language model (LLM) chatbot developed by Google AI. It is still under development, but it has learned to perform many kinds of tasks, including
I will try my best to follow your instructions and complete your requests thoughtfully.
I will use my knowledge to answer your questions in a comprehensive and informative way, even if they are open ended, challenging, or strange.
I will generate different creative text formats of text content, like poems, code, scripts, musical pieces, email, letters, etc. I will try my best to fulfill all your requirements.
Bard is trained on a massive dataset of text and code, and it is able to communicate and generate human-like text in response to a wide range of prompts and questions. For example, Bard can provide summaries of factual topics or create stories.
Bard is still under development, but it has the potential to be a powerful tool for communication, creativity, and learning.
What Is Chatgpt
ChatGPT is a language model developed by OpenAI. It is based on the GPT (Generative Pre-trained Transformer) architecture, specifically GPT-3.5. As a language model, ChatGPT is designed to generate human-like responses to text prompts. It has been trained on a vast amount of diverse text data to learn patterns and relationships between words, allowing it to generate coherent and contextually relevant responses.
ChatGPT uses a transformer neural network architecture, which enables it to process and understand text in a hierarchical manner, capturing both local and global dependencies. It consists of multiple layers of self-attention mechanisms, allowing the model to attend to different parts of the input text when generating responses.
The model can be fine-tuned on specific tasks or domains by exposing it to supervised training data. However, ChatGPT is primarily trained in an unsupervised manner, using a method known as “pre-training.” During pre-training, the model learns to predict the next word in a sentence based on the surrounding context, thereby acquiring a general understanding of grammar, semantics, and world knowledge.
Once the pre-training is completed, ChatGPT can be fine-tuned on specific prompts or tasks using supervised training, where human reviewers provide feedback and rate model-generated responses for quality. This iterative feedback loop helps improve the model’s responses over time.
|Data sources||Books, articles, code, and other text from the internet||Books, articles, code, and other text from the internet, as well as real-time data from the internet|
|Data size||1.56T words||1.56T words + real-time data|
|Data update frequency||Once a year||Constantly|
Overall, Bard has a larger and more up-to-date data set than ChatGPT. This means that Bard is able to generate more accurate and relevant responses.
Here are some additional details about the data sources of ChatGPT and Bard:
- ChatGPT is trained on a dataset of text and code that was collected from the internet in 2021. This means that ChatGPT is limited to information that was available before 2021.
- Bard is trained on a dataset of text and code that is constantly being updated. This means that Bard has access to the latest information, including real-time data from the internet.
- The data quality of ChatGPT is good. However, the data quality of Bard is excellent. This is because Bard’s data set is larger and more up-to-date than ChatGPT’s data set.
Overall, Bard has a better data set than ChatGPT. This means that Bard is able to generate more accurate and relevant responses
Overall, Bard is the more affordable and powerful option. However, ChatGPT is a good option if you are on a tight budget.
|Free tier||10,000 tokens per month||100 tokens per month|
|Paid tiers||$0.01 per 100 tokens||$0.005 per 100 tokens|
|Max tokens per month||10 million||100 million|
|Data sources||Pre-defined set of data||Constantly growing dataset|