Anthropic is a research company that is working to build safe and beneficial artificial intelligence. In March 2023, they launched their AI chatbot, Claude. Claude is a large language model (LLM) that can generate text, write code, and function as an AI assistant.
Anthropic has recently announced that they have expanded Claude’s context window from 9,000 to 100,000 tokens. This means that Claude can now process and understand much larger amounts of text. This is a significant improvement, and it will allow Claude to perform even more complex tasks.
For example, Claude can now be used to generate summaries of long documents, translate languages, and write different kinds of creative content. It can also be used to answer your questions in an informative way, even if they are open ended, challenging, or strange.
Anthropic’s expansion of Claude’s context window is a major step forward in the development of safe and beneficial AI. It shows that Anthropic is committed to building AI systems that can be used for good.
What Are Tokens?
Tokens are the building blocks of language for LLM AI models. They can be individual characters, words, subwords, or other text segments and are assigned numerical values or identifiers. These tokens are then arranged in sequences or vectors and fed into or outputted from the model.
The significance of the 100k token context window
The increase of the context window from 9,000 to 100,000 tokens is a significant milestone for Anthropic and their AI chatbot, Claude. This allows Claude to process and understand much larger amounts of text, which opens up new possibilities for its use. With this new model, Claude can generate summaries of long documents, translate languages, write creative content, and answer open ended or challenging questions. This development is an important step towards building safe and beneficial AI systems that can be used for positive purposes.
Comparing Claude’s context window to other AI models such as OpenAI’s GPT-4
This table just shows you the drastic difference between the latest Anthropic model.
How much does higher content size matter?
There are trade-offs with huge token models. Large language models (LLMs) are relatively new and have been shown to be very effective in natural language processing tasks. However, they require a lot of computational resources and memory to train and run. The number of parameters is a measure of the size and the complexity of the model. The more parameters a model has, the more data it can process, learn from, and generate1. There was already a research paper on a 1M token model2. We will also have to see how this impacts hallucination. It will also be interesting to see how this will impact vector databases since one of the main reasons that that they’re used is for data retrieval and semantic search.
Here are what others are saying about it:
Use cases for the 100k token model
Here are some potential use cases for Anthropic’s new 100k token model:
- Summarizing long documents and articles Generating translations between languages Writing creative content such as poetry or fiction Answering complex or open-ended questions Providing informative responses to difficult or strange inquiries
- Writing Code: With Anthropic’s new 100k token model, Claude can also write code. This is a particularly exciting development, as it opens up new possibilities for the use of AI in software development. With Claude’s ability to read and understand large amounts of text, it can now assist in programming tasks such as debugging, documentation, and even generating code. This could potentially lead to more efficient and effective software development processes.
These are just a few examples of the many possibilities that this expanded context window enables. With these capabilities, Anthropic’s AI chatbot, Claude, is poised to become an even more powerful tool for researchers, writers, and professionals in a variety of fields.
It will be interesting to see how this stacks up with other forms of data retrieval, such as using LangChain. A lot of this could come down to pricing. The OpenAI Embeddings and 3.5 turbo APIs are very cheap. GPT-4’s 32K context seems still quite expensive so we will have to wait and see if price comes down. Here are some results we are seeing as the Claude 100k model is being rolled out.
From the looks of those that are testing it, it seems that claude-instance-v1.3-100k can accurately do information retrieval over 100k tokens down to the resolution of a single line!
Anthropic’s expansion of Claude’s context window is a major development in the field of safe and beneficial AI. With the new 100k token model, Claude can process and understand larger amounts of text, allowing it to perform more complex tasks such as summarizing long documents, writing creative content, and even assisting in software development. This development opens up new possibilities for the use of AI in a variety of fields and shows Anthropic’s commitment to building AI systems for good. With further advancements, AI chatbots like Claude could become even more powerful tools for researchers and professionals. have you used the 100k model? What are your thoughts?